data mining research papers 2012-2013






Data Mining For Security PurposeIts Solitude Suggestions
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ABSTRACT In this paper we first look at data mining applications in safety measures and their suggestions for privacy. After that we then inspect the idea of privacy and give a synopsis of the developments particularly those on privacy preserving data mining. We then present

Mobility Prediction for Delay Reduction in WLAN using Location Tracking and Data Mining
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ABSTRACT Prediction of mobile path of a mobile node is of great importance since it reduces the handoff delays incurred during the handoff procedure. The proposed system is called Predictive Mobility Management scheme. We track the movement of mobile nodes

COMPLEX EVENT PROCESSING AND DATA MINING FOR SMART CITIES
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Abstract Complex Event Processing (CEP) is emerging as a new paradigm for continuous processing of streaming data in order to detect relevant information and provide support for timely reactions. The main role of a CEP engine is to detect the occurrence of

Data Mining QFD for The Dynamic Forecasting of Life Cycle under Green Supply Chain
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ABSTRACT The satisfaction of customer requirements is critical issue for the computer designers and manufacturers, because computer design is a high risk and value-added technology. When considering green design, designers should incorporate the voices

Review and Analysis of Data Security in Data Mining
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ABSTRACT In new era the information and data communication technologies are highly used in the Business Industry. The data warehouse is used in the significant business value by improving the effectiveness of managerial decision-making. Naturally such a process may

Multimedia Data Mining: A Survey
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ABSTRACT Multimedia data mining (MDM) can be defined as the process of finding interesting patterns from media data such as audio, video, image and text that are not ordinarily accessible by basic queries and associated results. MDM is the mining of knowledge and

Sessionization–A Vital Stage in Data Preprocessing of Web Usage Mining-A Survey
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 Web mining uses many data mining techniques but it is not an application of traditional data mining due to heterogeneity and unstructured nature of the data on Web. Web mining tasks can be categorized into three types: Web Structure Mining,.

Anomaly Detection in Network using Data mining Techniques
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ABSTRACT As the network dramatically extended security considered as major issue in networks. There are many methods to increase the network security at the moment such as encryption, VPN, firewall etc. but all of these are too static to give an effective protection

Data Mining Industrial Applications
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Novel, advanced sensors, dynamic development of information technologies as well as modern high-performance computers applied in different fields of human activity result in large amount of data. Consequently, these data, grouped in the data sets are both large and complex.

Data Mining Techniques to Find Out Heart Diseases: An Overview
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ABSTRACT Heart disease is a major cause of morbidity and mortality in modern society. Medical diagnosis is extremely important but complicated task that should be performed accurately and efficiently. Although significant progress has been made in the diagnosis

An application of data mining to fruit and vegetable sample identification using Gas Chromatography-Mass Spectrometry
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ABSTRACT One of the uses of Gas Chromatography-Mass Spectrometry (GC-MS) is in the detection of pesticide residues in fruit and vegetables. In a high throughput laboratory there is the potential for sample swaps or mislabelling, as once a sample has been pre-

Performance Analysis of Healthy Diet Recommendation System using Web Data Mining
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ABSTRACT Medical study has revealed that people set a bigger possibility of countering free radicals and warding off illness by consumption of healthy foods and by increasing their resistant system. Due to the poor eating habits people suffer from many diseases. In the

On Computing Minimal Generators in Multi-Relational Data Mining with respect to ?-Subsumption
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N Nishio, A Mutoh, N Inuzuka ,ida.felk.cvut.cz ABSTRACT. We study the minimal generators (mingens) in multi-relational data mining. The mingens in formal concept analysis are the minimal subsets of attributes that induce the formal concepts. An intent for a formal concept is called a closed pattern. In contrast to the

Challenges on Association Rule Mining On Data Streams in Contrast to Classical Association Rule Mining Algorithms
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A Bachmann ,Ausarbeitungen zum Seminar Computational ,fuzzy.cs.uni-magdeburg.de  Keywords: data mining, association rule mining, stream mining, challenges in association rule mining on stream data 1 Introduction Nowadays association rule mining is applied more and more.  on Knowledge Discovery and Data Mining (KDD). Washington DC, USA.

Mining Big Data in Real Time
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Consequently, data streams pose several challenges for data mining algorithm design. First, algorithms must make use of limited resources (time and memory).  [6] B. Liu. Web data mining;

Data Mining: Performance Improvement in Education Sector using Classification and Clustering Algorithm
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Abstract The ability to predict a student s performance is very important in educational environments. Students academic performance is based upon diverse factors like personal, social, Psychological and other environmental variables. A very promising tool to attain

INTEGRATIVE MODEL FOR INCREASING CUSTOMER VALUE USING DATA MINING AND DATA WAREHOUSE
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ABSTRACT While the customer is the king, some customers have a much greater profit potential than others. The fundamental question is to find those high-potential customers in a database that contains hundreds of data items for each of millions of customers. Data

A Study of Data Mining Tools in Knowledge Discovery Process
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ABSTRACT Data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. It uses machine learning, statistical and

Data mining scheme for the characterization of AE signals in steel elements subject to fatigue cracking
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Abstract Early detection of fatigue crack-growth in steel structures is an ongoing challenge. Furthermore, characterization of the different stages of the fatigue lifecycle using NDE techniques is particularly difficult. AE systems have been shown to serve as early

Decision Theoretic in SQL to Prepare Data Sets for Data Mining Analysis
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ABSTRACT The data set for analysis is generally the most time consuming task in a data mining project, requiring many complex SQL queries, joining tables and aggregating columns. Existing SQL aggregations have limitations to prepare data sets because they return one

Data Mining Approaches For Network Intrusion Detection System
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ABSTRACT Data mining has been gaining popularity in knowledge discovery field, particularity with the increasing availability of digital documents in various languages from all around the world. Network intrusion detection is the process of monitoring the events occurring in a

STUDY OF APPLICATIONS OF DATA MINING TECHNIQUES IN EDUCATION
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ABSTRACT Few years ago, the information flow in education field was relatively simple and the application of technology was limited. However, as we progress into a more integrated world where technology has become an integral part of the business processes, the

141765 DATA WAREHOUSING AND DATA MINING LTPC
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Introduction-Issues in Real Time Computing, Structure of a Real Time System. Task Classes, Performance Measures for Real Time Systems, Estimating Program Run times. Task Assignment and Scheduling-

AND RISK ASSESSMENT FOR LANDSLIDES IN THE SHIMEN RESERVOIR WATERSHED OF TAIWAN USING SPATIAL ANALYSIS AND DATA MINING
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ABSTRACT Spatial information technologies and data can be used effectively to investigate and monitor natural disasters contiguously and to support policy-and decision-making for hazard prevention, mitigation and reconstruction. However, in addition to the vastly

USE OF DATA MINING TECHNIQUES FOR PREDICTING ELECTRIC ENERGY DEMAND
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Summary. The project of prediction models was developed in the Data Miner graphic environment, which allows one to determine the hourly electric energy demand for an agricultural and food industry plant. Whilst using data mining techniques, it is not

Role of Neural network in data mining
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ABSTRACT Data Mining means mine data from huge amount of data. It is beneficial in every field like business, engineering, web data etc. In data mining classification of data is very difficult task that can be solving by using different algorithms. In this paper different neural

Data Mining and Application in Accounting and Auditing
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ABSTRACT Traditional manner for making information from data was laid on handy interpret and analyzing. This kind of analyzing of data is so slow and also expensive and objective. It hopes computer technology helps when data using and analyzing is above humane

An Estimation of Privacy in Incremental Data Mining
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ABSTRACT Data are values of qualitative or quantitative variables, belonging to a set of items. In recent years, advances in hardware technology have lead to an increase in the capability to store and record personal data about consumers and individuals. This has lead to

DATA MINING TECHNIQUES FOR ANALYSING THE INVESTMENT BEHAVIOUR OF CUSTOMERS IN LIFE INSURANCE SECTOR IN INDIA
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ABSTRACT Advancement of technology has paved the way for analyzing the different aspects of customers. Technology such as data ware house and data mining has made a significant contribution in almost the entire service sector where companies associated

Neural Networks in Data Mining
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ABSTRACT The application of neural networks in the data mining is very wide. Although neural networks may have complex structure, long training time, and uneasily understandable representation of results, neural networks have high acceptance ability for noisy data and

Related

data mining research papers 2013



Data Mining Social Media for Public Health Applications
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The online population creates a vast organic sensor network composed of individuals reporting on their activities, their social interactions, and the events around them. This firehose of data streams in real time, and is often annotated with context including GPS 

Quality checking and mining nephrology biopsy data
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Categories and Subject Descriptors H.2.8 [Database Management]: Database Applications – data mining. General Terms Experimentation, Management. Keywords Electronic patient record, nephrology, biopsy, data mining. 

Local Density Differ Spatial Clustering in Data Mining
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ABSTRACT Clustering in data mining is a discovery process that groups a set of data objects so that the inter-cluster similarity is minimized and intra-cluster similarity is maximized. In presence of noise and outlier in high dimensional data base it is a difficult task to find out 

Execution of APRIORI Algorithm of Data Mining Directed Towards Tumultuous Crimes Concerning Women
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ABSTRACT Apriori Algorithm is the most popular and useful algorithm of Association Rule Mining of Data Mining. As Association rule of data mining is used in all real life applications of business and industry. Objective of taking Apriori is to find frequent itemsets and to 

Data Mining: A Prediction for Performance Improvement in Online Learning Systems
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ABSTRACT Data mining in education slowly evolves from the need of simple discovery of frequent patterns and regularities in large data sets toward interactive, user-oriented, on- demand decision supporting. Since data to be mined is usually located in a educational 

Sentiment Analysis of Equities using Data Mining Techniques and Visualizing the Trends
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ABSTRACT Markets reflect sensitively towards opinions and sentiments. Investors should be wary of the fact that external factors interact deeply with the share markets and mark their influence over the coming period. National tragedy, low economic growth, IPO releases, 

A New Approach for Improving World Wide Web Techniques in Data Mining
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ABSTRACT Web usage mining is used to discover interesting user naviga-tion patterns and can be applied to many realworld problems, such as improving Web sites/pages, making additional topic or product recommendations, user/customer behavior studies, etc. This 

An Overview of Clustering Analysis Techniques used in Data Mining
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ABSTRACT We live in a time where the need for data mining is prevalent for extracting knowledge and understanding patterns, given the vast amount of data being generated. Clustering is one of the many data mining functionalities which divide data into groups 

Assessing Pancreatic Cancer Risk Associated with Dipeptidyl Peptidase 4 Inhibitors: Data Mining of FDA Adverse Event Reporting System (FAERS)
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ABSTRACT Background: Identifying cancer risks associated with medicinal agents plays an important role in cancer control and prevention. Case reports of cancers associated with pharmacotherapy have been escalating in the Food and Drug Administration Adverse 

Survey of Recent Clustering Techniques in Data Mining
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ABSTRACT Cluster analysis or clustering is the task of assigning a set of objects into groups called clusters. Main task of clustering are explorative data mining, and a common technique for statistical data analysis used in many fields, including machine learning, pattern 

AMETHYST: A System for Mining and Exploring Topical Hierarchies of Heterogeneous Data
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Categories and Subject Descriptors I.7 [Computing Methodologies]: Document and Text Processing; H.2.8 [Database Applications]: Data Mining Keywords Topic Modeling, Network Analysis, Heterogeneous Network, Entity Mining 

Diagnosis of Lung Cancer Prediction System Using Data Mining Classification Techniques
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ABSTRACT Cancer is the most important cause of death for both men and women. The early detection of cancer can be helpful in curing the disease completely. So the requirement of techniques to detect the occurrence of cancer nodule in early stage is increasing. A 

EventCube: Multi-Dimensional Search and Mining of Structured and Text Data
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web data. The system has high potential to be extended in many pow- erful ways and serve as a general platform for search, OLAP (online analytical processing) and data mining on integrated text and structured data. After the 

Integration of Decision Support Systems and Data Mining for Improved Decision Making
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ABSTRACT A data mining (DM) integrated decision support system (DSS) is suggested to improve the performance of the DSS implemented in a police organisation. A prototype of the suggested system is provided. The paper provides an insight into DM-DSS integrated 

A comparative study on blood glucose spectra values to predict dominating patterns using bio-data mining
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ABSTRACT Pattern Mining is the process of extracting or mining the patterns from very large amount of biological datasets. Utilization of Data mining algorithms can reveal biological relevant associations between different genes and gene based expression. In Data 

A Review: Comparative Study of Various Clustering Techniques in Data Mining
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ABSTRACT Clustering is a process of putting similar data into groups. Clustering can be considered the most important unsupervised learning technique so as every other problem of this kind; it deals with finding a structure in a collection of unlabeled data. This paper 

Statistical data mining for symbol associations in genomic databases
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Abstract A methodology is proposed to automatically detect significant symbol associations in genomic databases. A new statistical test is proposed to assess the significance of a group of symbols when found in several genesets of a given database. Applied to symbol 

Privacy-Preserving Data Mining Algorithm Quantum Ant Colony Optimization
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ABSTRACT Bayesian network has been used extensively in data mining. The Privacy- Preserving data mining algorithm based on quantum ant colony optimization is proposed in this paper. The algorithm is based on distributed database. The algorithm is divided into 

SEQUENTIAL PATTERN MINING BASED ON MULTI DIMENSIONAL SEQUENCE DATA–A CASE STUDY
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 INDIAABSTRACT In recent years, emerging applications introduced new constraints for data mining methods. These constraints are typical of a new kind of data.  sizes. Keywords: Data Mining, Sequential Patterns, Sequence Data. 

Diagnosing Coronary Artery Disease via Data Mining Algorithms by Considering Laboratory and Echocardiography Features
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ABSTRACT Background: Coronary artery disease (CAD) is the result of the accumulation of athermanous plaques within the walls of coronary arteries, which supply the myocardium with oxygen and nutrients. CAD leads to heart attacks or strokes and is, thus, one of the 

Importance of Data Mining in Higher Education System
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ABSTRACT Data Mining is used to extract meaningful information and to developed significant relationship among variables stored in large data warehouse .Educational data mining is an emerging discipline concern with developing methods for exploring the unique type of 

Artificial Neural network for Data mining–A study
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ABSTRACT Data mining is defined as the extraction of hidden predictive information from large databases. It finds its application in real world situations such as business, science, technology, and government. A data mining algorithm constitutes a model, a preference 

Data Mining Tools and Technologies used for Competitive Intelligence
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ABSTRACT -Generally, data mining is the process of analyzing data from different perspectives and summarizing it into useful information. This information can be used to increase revenue, cuts costs, or both. Data mining tools predict future trends and behaviors, these 

Evaluating the Influence of Missing Data on Classification Algorithms in Data MiningApplications
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Abstract. This paper presents an analysis regarding the influence of missing data on datasets when submitted to traditional classification algorithms in data mining applications. For this purpose, we use ten UCI datasets and manipulate them to hold controlled levels 

Italian Machine Learning and Data Mining research: The last years
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With the increasing amount of information in electronic form the fields of Machine Learning and Data Mining continue to grow by providing new advances in theory, applications and systems. The aim of this paper is to consider some recent theoretical aspects and 

Early Detection of Lung Cancer Risk Using Data Mining
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ABSTRACT Background: Lung cancer is the leading cause of cancer death worldwide Therefore, identification of genetic as well as environmental factors is very important in developing novel methods of lung cancer prevention. However, this is a multi-layered 

An Overview of Recent Machine Learning Strategies in Data Mining
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ABSTRACT Most of the existing classification techniques concentrate on learning the datasets as a single similar unit, in spite of so many differentiating attributes and complexities involved. However, traditional classification techniques, require to analysis the dataset 

Orange: Data Mining Fruitful and Fun-A Historical Perspective
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General-purpose machine learning software tools have had a short but eventful history. It began with utilities that implemented a specific induction method and reported on an inferred model in a textual form, to be then scrutinized and admired by the user. Such 

Data mining in large sets of complex data
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Introduction Both the amount and the complexity of the data gathered by current scientific and productive enterprises are increasing at an exponential rate, in the most diverse knowledge areas, such as biology, physics, medicine, astronomy, climate forecasting, etc. 

A novel data mining system points out hidden relationships between immunological markers in multiple sclerosis
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Background: Multiple Sclerosis (MS) is a multi-factorial disease, where a single biomarker unlikely can provide comprehensive information. Moreover, due to the non-linearity of biomarkers, traditional statistic is both unsuitable and underpowered to dissect their relationship. Patients 

Neural computing model for prediction of soil cation exchange capacity: a data miningapproach.
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ABSTRACT The advances in computing and information storage have provided vast amounts of data. The challenge has been to extract knowledge from this raw data; this has lead to new methods and techniques such as data mining that can bridge the knowledge gap and 

Application of Data Mining Techniques in Maximum Temperature Forecasting: A Comprehensive
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ABSTRACT There are several applications for Machine Learning (ML), the most significant of which is data mining. It is used to discover the hidden patterns from large volume of raw data. Data mining can be classified into supervised learning (classification and prediction) 

Data Warehousing of Microbial Information Databases for in Silico Mining of a Bioactive Ligand
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 ABSTRACT A bioinformatics data warehouse was developed to support data storage and data mining.  The data mining component of the project was implemented by gridifying and installing Autodock software into a cluster computing facility. 

Big Data and Distributed Data Mining: An Example of Future Networks'
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ABSTRACT This paper describes the perspective on the analytics of big data generated by sensors and devices on the edge of networks. The paper includes a discussion of the importance of data at the edge of networks where some of biggest big data is generated. 

Knowledge discovery from consumer behavior in electronic home appliances market in Chennai by using data mining techniques
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The global economy is improving every year and during the forthcoming decades, marketers need to enter new national markets towards an understanding of how data mining techniques influences consumer behavior, which will be vital for consumer researches. 

Data Mining: A Comparative Study on Various Techniques and Methods
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ABSTRACT Data mining may be viewed as the extraction of patterns and models from observed data or a method used for analytical process designed to explore data. There are many different methods, which may be used to predict the appropriate class for the objects. The 

Predicting Students Academic Performance Using Education Data Mining
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ABSTRACT Education Data Mining is a promising discipline which has an imperative impact on predicting students' academic performance. In this paper, student's performance is evaluated using association rule mining algorithm. Research has been done on 

Factors Affecting the Use of Data Mining in Mozambique
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Factors affecting the use of data mining in Mozambique: Toward a framework to facilitate the use of data mining  Research Questions ? Question 1: What is the level of awareness and adoption of data mining in Mozambique? ? Question 2: What are the factors affecting 

ANew TECHNIQUE INVOLVING DATA MINING IN PROTEIN SEQUENCE CLASSIFICATION
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Abstract Feature selection is more accurate technique in protein sequence classification. Researchers apply some well-known classification techniques like neural networks, Genetic algorithm, Fuzzy ARTMAP, Rough Set Classifier etc for extracting features. This paper 

Design and Implementation of Small Scale Electric Power Management System with Data Mining Method
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Abstract. Conventional electric-power grids generally have unidirectional power flows from the power plant to the consumers. At small factories, however, the problem is that they inefficiently consume electricity because they consume the electrical power depending on 

Mining Big Data in Real Time
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Consequently, data streams pose several challenges for data mining algorithm design. First, algorithms must make use of limited resources (time and memory). 

Hybrid techniques for Privacy preserving in Data Mining
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ABSTRACT With the technology advancements, most of the corporations maintain their huge amount of electronic data in the databases and these databases are accessible using internet. These data are used by data miners to extract useful information. There is a threat 

Scheduling data Mining Applications in Mobile Computing Environments
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Data mining is emerging as a promising topic in mobile computing environments. We have defined a distributed architecture in which mobile devices cooperate in a peer-to-peer style to perform a data mining process, tackling the problem of energy capacity shortage by 

Provenance for data mining
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Abstract Data mining aims at extracting useful information from large datasets. Most data mining approaches reduce the input data to produce a smaller output summarizing the mining result. While the purpose of data mining (extracting information) necessitates this 

A Focus on Different Frauds and Enhancing Business Process in Banking Sector Using Data Mining
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ABSTRACT Significant shifts in the business environment, economic volatility, changing customer and staff expectations, and the adoption of new technology make it increasingly challenging for banks to navigate technology strategy alternatives and prioritize 

Privacy Preserving Data Mining: Comparion of Three Groups and Four Groups Randomized Response Techniques
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ABSTRACT Privacy and accuracy are the important issues in data mining when data is shared. A fruitful direction for future data mining research will be the development of techniques that incorporate privacy concerns. Most of the methods use random permutation techniques to 

Study on Application of Data Mining Technology in Syndrome Differentiation of TCM
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Study on Application of Data Mining Technology in Syndrome Differentiation of TCM Dai Zhiguo 1, , Han Yangyang 2, a  aCorresponding

Emerging Trends in Knowledge Discovery and Data Mining
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Series Editors Randy Goebel, University of Alberta, Edmonton, Canada Jrg Siekmann, University of Saarland, Saarbrcken, Germany Wolfgang Wahlster, DFKI and University of Saarland, Saarbrcken, Germany Volume Editors Takashi Washio Osaka University, The Institute of 

An Approach to Data Mining in Healthcare: Improved K-means Algorithm
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ABSTRACT Nowadays, the application of data mining in the healthcare industry is necessary. Data mining brings a set of tools and techniques that can be applied to discover hidden patterns that provide healthcare professionals an additional source of knowledge for 

Mining Pattern from Road Accident Data: Role of Road User's Behaviour and Implications for improving road safety
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Central Part of Ethiopia) regions. However, though they lack systemic approach, there were some fragmented efforts to show the application of data mining techniques on road safety analysis domain. Tibebe, Abraham and Grosan 

Erratum: Data Mining and Knowledge Discovery for Big Data
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WW Chu (ed.), Data Mining and Knowledge Discovery for Big Data, Studies in Big Data 1, DOI: 10.1007/978-3-642-40837-3, © Springer-Verlag Berlin Heidelberg 2014  In the original online version of this volume, the foreword is missing. It is given on the next page.

Special issue on challenges in knowledge discovery and data mining
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Ten years have passed since Jan Zytkow passed away in the midst of rapid progress in data mining. Jan Zytkow started his research career in physics, where he became interested in the philosophical nature of scientific discovery. Then, he posed a question on how a 

Centric Model Assessment for Collaborative Data Mining
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ABSTRACT Data mining is the task of discovering interesting patterns from large amounts of data. There are many data mining tasks, such as classification, clustering, association rule mining and sequential pattern mining. Sequential pattern mining finds sets of data items 

Early Prediction of Heart Diseases Using Data Mining Techniques
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Abstract Largest-ever study of deaths shows heart diseases have emerged as the number one killer in world. About 25 per cent of deaths in the age group of 25-69 years occur because of heart diseases. If all age groups are included, heart diseases account 

Data Mining: Exploring New Horizons from Huge Data Store
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ABSTRACT DM ie Data Mining is the technique to find out the hidden facts from the large amounts of data. From the historic data, we derive knowledge. Data Mining is important aid for decision making in organizations. Data mining task is the automatic or semi-automatic 

INTEGRATING SOCIAL NETWORK ANALYSIS AND DATA MINING TECHNIQUES INTO EFFECTIVE E-MARKET FRAMEWORK
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ABSTRACT E-commerce has been considered to be a very important source to share business information and establish a relationship between people on a communication network especially the Web which is driven by the internet. Many retailers have introduced online 

A data mining approach for bank telemarketing using the rminer package and r tool
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Abstract Due to the global financial crisis, credit on international markets became more restricted for banks, turning attention to internal clients and their deposits to gather funds. This driver led to a demand for knowledge about client's behavior towards deposits and 

Indian Industrial Position on the Basis of Financial Ratios: A Data Mining Approach
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ABSTRACT An attempt is made to introduce a new method of grading the top ranking industries on the basis of financial ratios. It is well known that the financial ratios are being used as a measure by researchers for many purposes. About 247 companies consist of five major 

Data Mining and Social Network Analysis of Ideation Contests: A Repeated Measures Design
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work theoretically?, How do ideation contests work empirically? and Which research methods are applied to analyze ideation contests? The first question is used to understand ideation as processes from a theoretical perspective. The second question hence is, for 

Swarm Optimization Algorithm for Privacy Preserving in Data Mining
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ABSTRACT Free competition in business can be compromised as data mining techniques reveal critical information about business transactions. Hence, there is a need to ensure prevention of disclosures both of confidential personal information which is contextually 

The limits of p-values for biological data mining.
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Use of p-values is widespread in the sciences, especially so in biomedical research, and also underlies several analytic approaches in data mining. Its original intent is simple enough, but its application and interpretation are far from simple. If data is collected to evaluate an 

Data Mining Techniques: To Predict and Resolve Breast Cancer Survivability
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ABSTRACT Breast cancer is one of the deadliest disease, is the most common of all cancers and is the leading cause of cancer deaths in women worldwide, accounting for 1.6% of deaths and case fatality rates are highest in low-resource countries. The breast cancer 

The disconnect between classical biostatistics and the biological data mining community
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Statistics departments and journals still strongly emphasize a very narrow range of topics and methods and techniques, all driven by a tiny handful of results, many dating from the 1930s. Those methods may well have been good and amazing and quite appropriate for the available 

An Empirical Study of Applications of Data Mining Techniques for Predicting Student Performance in Higher Education
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ABSTRACT Educational institutions are important parts of our society and playing a vital role for growth and development of nation and prediction of student's performance in educational environments is also important as well. Student's academic performance is based upon 

ANALYSIS OF DIFFERENT CLUSTERING TECHNIQUES FOR DETECTING HUMAN EMOTIONS VARIATION THROUGH DATA MINING
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ABSTRACT This paper explored to detect human emotion variation through data mining and analyzing different clustering techniques to be chosen for classification of human emotion. In human beings there are different mood swings exist. People become more moody and 

Data mining application in biomedical informatics for probing into protein stability upon double mutation
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ABSTRACT To explore the mechanism of protein stability change is one of the important topics in protein design. The accurate prediction of protein stability change upon mutation is very useful for enhancing the experimental efficiency in many biological and medical studies. 

Logical programming and data mining as engine for MDA model transformation implementation
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ABSTRACT In this paper, we present the description of our extension to Model Driven Architecture (MDA) methodology using the logical programming paradigm and also a practical example of application of our extension to the development process. Then we 

USING DATA MINING TECHNOLOGY TO EXPLORE LABOR SAFETY STRATEGY-A LESSON FROM THE
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ABSTRACT The working environments of the construction industry in Taiwan generally have higher risks, accounting for over 50% of major occupational injuries in Taiwan. In this study, data mining was used to analyze totally 33,298 cases of labor safety inspection in labor 

An adaptive ensemble classifier for mining concept drifting data streams.
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Abstract Traditional data mining techniques cannot be directly applied to the real-time data streaming environment.  1. Introduction Data stream analysis and mining is a challenging research area in data mining and machine learning. 

New Data Mining Algorithm for Intrusion Detection in Networks
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ABSTRACT An intrusion detection system is a mechanism that monitors network or system activities for malicious activities. Intrusion detection and prevention systems (IDPS) are primarily focused on identifying possible incidents, logging information about them and 

Agents and Data Mining Interaction
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Series Editors Randy Goebel, University of Alberta, Edmonton, Canada Jrg Siekmann, University of Saarland, Saarbrcken, Germany Wolfgang Wahlster, DFKI and University of Saarland, Saarbrcken, Germany Volume Editors Longbing Cao, University of Technology, Sydney, 

Understanding the Potential of Data Mining in Botswana
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ABSTRACT Botswana is a rapidly developing country, with many new organizations establishing presence every year. With this growth in number and size of organizations comes the generations of large amounts of organizational data. These organisations are 

Visual Mining Methods for RNA-Seq Data: Data Structure, Dispersion Estimation and Significance Testing
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ABSTRACT In an analysis of RNA-Seq data from soybeans, initial significance testing using one software package produced very different gene lists from those yielded by another. How can this happen? This paper demonstrates how the disparities between the results were 

An Approach for Accessing Linked Open Data for Data Mining Purposes
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Abstract In the recent time the amount of semantic data publicly available online grows continuously. This data is a valuable source of information that can be inferred by means of different technologies. Apart of reasoning on data semantics classical OLAP or 

Data Mining Framework for Direct Marketing: A Case Study of Bank Marketing
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ABSTRACT Direct marketing has generated an increasing interest among academics and practitioners over the past few years. This is due to competitive market environment, advancement in technology and changing behavior of customers which are difficult to 

Data-mining in NSW: Working towards a new and improved Australian datum
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ABSTRACT Advances in positioning technologies in the last decades have given a large range of usergroups access to positioning at ever-increasing accuracies and improved spatial and temporal resolution. In this context, the limitations of our current Australian 

Replicating Data Mining Techniques for Development: A Case Study of Corruption
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ABSTRACT Data Mining has a reputation in social science for lacking statistical rigour. This study challenges this reputation and argues that, whilst such a method (as with any other) can be abused, it has particular promise as a tool to be used for monitoring and 

GeoDMA-Geographic Data Mining Analyst
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This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues.  Other uses, including reproduction and 

Relational and Semantic Data Mining for Biomedical Research
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Data analysis in biomedical applications aims at extracting potentially new relationships from data and providing insightful representations of detected relationships. Methods for symbolic data analysis are preferred since highly accurate but non-interpretable 

Selection Criteria for Data Mining Software: A Study
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ABSTRACT Nowadays software are flooded in the market, there is a need for selection criteria of software package that should be available for individuals and organizations. As the number of software continues to grow and new features added to the new software the 

A Survey on k-Means Clustering Algorithm Using Different Ranking Methods in Data Mining
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ABSTRACT As the volume of information on the internet is increasing day by day so there is a challenge for website owner to provide proper and relevant information to the internet. So it is the duty of the service provider to provide the relevant and good information to the 

A Survey on Using Data Mining Techniques for Online Social Network Analysis
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Abstract In this paper we take into consideration the concepts of using algorithmic and data mining perspective of Online Social Networks (OSNs), with special emphasis on latest hot topics of research area. There are several factors which has made the study of OSNs gain 

Ensembles of Classification Methods for Data Mining Applications
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ABSTRACT One of the major developments in machine learning in the past decade is the ensemble method, which finds highly accurate classifier by combining many moderately accurate component classifiers. In this research work, new ensemble classification 

Data Mining for Geoinformatics
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Editors Guido Cervone Department of Geography and Institute for CyberScience The Pennsylvania State University State College, PA, USA Research Application Laboratory National Center for Atmospheric Research Boulder, CO, USA Nigel Waters Center of Excellence in GIS 

A Generalized Association Rule Based Method for Privacy Preserving in Data Mining
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ABSTRACT Mining association rules from huge amounts of data is an important issue in data mining, with the discovered information often being commercially valuable. Moreover, companies that conduct similar business are often willing to collaborate with each other by 

Education using Computational Data Mining Models
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ABSTRACT Education has always been important but perhaps never more so in man's history than today. In a technologically oriented society education knowledge and research are crucial to the entire developmental process of a country and its welfare, progress and 

Survey of Advanced Data Mining Application
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ABSTRACT In this paper we have focused a variety of techniques, approaches and different areas of the research which are helpful and marked as the important field of Advanced data mining Technologies. Each place of operation may generate large volumes of data. 

Multichannel Allocation in Data Schemes using Data Mining (DMM) based Methodology for Multi Moving Nodes in Adhoc Computing System
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ABSTRACT In this paper, we present a new data mining algorithm which involves Data mining for multi moving nodes in a adhoc computing environment and quest the mining results to develop multichannel data allocation schemes so as to improve the overall performance 

Bit-table based biclustering and frequent closed itemset mining in high-dimensional binary data
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researchers. 1 Introduction One of the most important research fields in data mining is mining interest- ing patterns (such as sequences, episodes, association rules, correlations or clusters) in large data sets. Frequent itemset 

Mining Meteorological and Forestry Data to Enhance Afforestation in Ethiopia
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 One way to do this is through afforestation. This paper attempts to apply data mining techniques of classification in forestry sector to enhance afforestation in Harerghe region of Ethiopia by recommending suitable tree species for that locality. 

Knowledge discovery in virtual worlds usage data: approaching web mining concepts to 3d virtual environments
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Knowledge Discovery, Data Mining, Usage Data, Virtual Worlds, Web Mining 1. Introduction Online interactive technologies have the potential to reach a large amount of people, whatever age, social environment, or culture. 

Computational Medicine in Data Mining and Modeling
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Editors Goran Rakocevic Mathematical Institute Serbian Academy of Sciences and Arts Belgrade, Serbia Tijana Djukic Faculty of Engineering University of Kragujevac Kragujevac, Serbia Nenad Filipovic Faculty of Engineering University of Kragujevac Kragujevac, Serbia 

A Novel Relational Database Data Mining Method Based on Artificial Neural Network
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Page 1. A Novel Relational Database Data Mining Method Based on Artificial Neural Network GOU Pingzhang 1, a , TANG Yongzhong 2, b  ABSTRACT. This study proposed a novel relational database data mining method based on the artificial neural network. 

Data Mining Recitation Notes Week 3
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Q1: What about the document that minimizes|| y- xi|| 2 over i= 1, 2,, D? This is the main idea. We look at the distance between the two vectors, using some vector distance metric like L2 or L1. But one problem occurs: the document length affects which document is 

A Data Mining Model for Anomaly Detection of Satellite Launch Vehicle
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ABSTRACT Anomaly detection refers to the problem of finding patterns in data that do not conform to expected behavior. Development of advanced anomaly detection and failure diagnosis technologies for satellite launch vehicle (SLV) is a quite significant issue in the 

Rough Sets Theory as Symbolic Data Mining Method: An Application on Complete Decision Table
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ABSTRACT In this study, the mathematical principles of rough sets theory are explained and a sample application about rule discovery from a decision table by using different algorithms in rough sets theory is presented. Keywords: Rough Sets Theory, Data Mining, Complete 

Mining Frequent Pattern from Large Dynamic Database Using Compacting Data Sets
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 2013 Published: 30 June 2013ABSTRACT Frequent pattern mining has been a focused theme in data mining research and the first step in the analysis of data rising in a broad range of applications. Apriori based algorithms have 

Detecting Hot Spots on Crime Data Using Data Mining and Geographical Information System
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ABSTRACT An attempt is made to introduce a new method of mapping the top level crime in various district/cities of Tamilnadu on the basis of crime parameters. Narrative information and crime records are stored digitally across individual police departments, enabling the 

Machine Learning and Data Mining for Sports Analytics
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Abstract Sports analytics had its public breakthrough as early as the 1970s when baseball enthusiasts started developing a range of statistical tools for analyzing players, teams, and strategies. Due to a combination of early successes, increased computational power and 

Data Mining in CRM-a Case Study for an Online Gaming Company
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Page 1. Data Mining in CRM ,a Case Study for an Online Gaming Company Project Work submitted in partial Fulfillment of the Requirements  Master of Science in Information and Media Technologies Data Mining Methods in CRM by Natalya Furmanova 

The Design and Implementation of Intrusion Detection System based on Data MiningTechnology
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ABSTRACT Intrusion detection technology is a research hotspot in the field of information security. This study introduces the types of traditional intrusion detection and data mining technology; Aiming at the defects and limitations of current intrusion detection system, the 

SIMULATION IN MEMS OF THE STATUS OF SPECIFIC GRAVITY OF URINE AND ITS CORRELATION IN DATA MINING
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ABSTRACT The status of specific gravity of urine in respect of parenchymal lesion involved in bacterial infection is of great medical importance for the treatment of the subject. The conclusion of the doctor is based on the accurate results in respect of the status of the 

EFFECTIVEPERSONALIZD WEB USAGE MINING BASED ON CLIENT DATA
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 Page 2. applied data mining techniques to extract usage patterns from Web logs, for the purpose of deriving marketing intelligence. Shahabi et al [15], Yan et al [16], and Nasraoui et al [12] have proposed clustering of user sessions to predict future user behavior. 

Data Stream Mining: the Bounded Rationality
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 and processing methods. Data mining is now moving to the era of bounded rationality. In this  about the environment. These scenarios impose strong constraints in the way we think and design data mining al- gorithms. In short 

Treatment and Research of Massive Data Mining Based on Cloud Computing
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Page 1. Treatment and Research of Massive Data Mining Based on Cloud Computing Peng Wang, Jianan Wang, Jici Ba,Yu Tan Department  com Keywords: Cloud Computing, Data Mining, SPRINT, Hadoop, MapReduceAbstract. 

„D-SEA: A Data Mining Approach to Unfolding
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ABSTRACT Solving inverse problems described by the Fredholm integral equation of first kind is a common challenge in many particle and astroparticle physics experiments. Several algorithms for the solution of these problems exist, most of them aiming at the 

Analysis of KDD CUP 99 Dataset using Clustering based Data Mining
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Abstract The KDD Cup 99 dataset has been the point of attraction for many researchers in the field of intrusion detection from the last decade. Many researchers have contributed their efforts to analyze the dataset by different techniques. Analysis can be used in any type of 

Data Mining 2013 Graphical Models for Discrete Data Part 1: Undirected Graphs (2)
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Model Omitted Interpretation 123 none saturated 12, 13, 23 u123 homogeneous association 12, 13 u123, u23 X2?? X3| X1 12, 23 u123, u13 X1?? X3| X2 13, 23 u123, u12 X1

Botnet Detection Based on Degree Distributions of Node Using Data Mining Scheme
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ABSTRACT. Botnets are collections of compromised computers (Bots) which are remotely controlled by its originator under a common Command-and-Control (C&C) infrastructure. In this paper, we proposed a new general detection strategy. This proposed strategy was 

Analysis and Design of Service-Oriented Framework for Executing Data Mining Services on Grids
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ABSTRACT Data mining services on grids is the need of today's era. Workflow environments are widely used in data mining systems to manage data and execution flows associated to complex applications. Weka, one of the most used open-source data mining systems, 

The application of data mining to explore association rules between metabolic syndrome and lifestyles.
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Abstract This study used an efficient data mining algorithm, called DCIP (the data cutting and inner product method), to explore association rules between the lifestyles of factory workers in Taiwan and the metabolic syndrome. A total of 1,216 workers in four companies 

Classification of Malware Based on Data Mining Approach
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ABSTRACT In recent years, the number of malware families/variants has exploded dramatically. Automatic malware classification is becoming an important research area. Using data mining, we identify seven key features within the Microsoft PE file format that 

Decision Support System In Medical Science Using OLAP  Data Mining
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Abstract The clinical industry collects large amounts of data which, unfortunately, are not turned into useful information for effectivedecision making. For this purpose Decision support systems (DSS) useadvanced technologies such as On-Line Analytical Processing 

Evaluation of Teacher's Performance: A Data Mining Approach
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ABSTRACT Most Organizations use performance appraisal system to evaluate the teacher's performance. The teacher's performance is very important to the students and as well as college management, in which usually involves crisp and uncertain values to evaluate 

Data Mining Approach to Detect Heart Dieses
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Abstract Globally, heart diseases are the number one cause of death. About 80% of deaths occurred in low-and middle income countries. If current trends are allowed to continue, by 2030 an estimated 23.6 million people will die from cardiovascular disease (mainly from 

Improvement of Intrusion Detection System in Data Mining using Neural Network
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ABSTRACT Many researchers have argued that Artificial Neural Networks (ANNs) can improve the performance of intrusion detection systems (IDS). One of the central areas in network intrusion detection is how to build effective systems that are able to distinguish 

Peer-to-peer data mining classifiers for decentralized detection of network attacks
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Abstract Data mining aims to extract from huge amount of data stochastic theories, called knowledge models, to explain or predict complex phenomenon. In this paper we propose new distributed data mining algorithms to recognize network attacks against a set of 

Self-service Product Innovation Based on Data Mining Technology
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ABSTRACT The core of service product innovation is to understand the demands of users. Self- service technology has changed the contact mode between users and the service, thus the traditional way to acquire information of users' demands could no longer meet the 

A Meta Level Data Mining Approach to Predict Software Reusability
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ABSTRACT Software repositories contain wealth of information about software code, designs, execution history, code and design changes, bug database, software release and software evolution. To meet increased pressure of releasing updated or new versions of software 

Predicting Customer Loyalty Using Data Mining Techniques
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ABSTRACT This research aimed on prediction of customer loyalty (Non loyal or Loyal) using the application of data mining in microfinance that helps to build a classification model which supports during loan decision making in the organization.

Data Dependencies Mining In Database by Removing Equivalent Attributes
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 We show that our method is sound, that is, the pruning does not lead to loss of information. Experiments on datasets show that DM_EC can prune more candidates than previous methods Keywords- DBMS Normalization, Data Dependencies Mining, Data Mining 

Use of Artificial Neural Network in Data Mining For Weather Forecasting
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ABSTRACT Knowledge of weather data or climate data in a region is essential for business, society, agriculture and energy applications. The main aim of this paper is to overview on Data mining Process for weather data and to study on weather data using data mining 

Estimation of Missing Values in the Data Mining and Comparison of Imputation Methods
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ABSTRACT Many existing, industrial, and research data sets contain missing values (MVs). There are various reasons for their existence, such as manual data entry procedures, equipment errors, and incorrect measurements. The presence of such imperfections 

Pocket Data Mining
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Mohamed Medhat Gaber · Frederic Stahl Joo Brtolo Gomes Pocket Data Mining Big Data on Small Devices ABC Page 4.  Page 6. Contents 1 Introduction .. 1 1.1 Introduction to Mobile Data Mining

Application of Data Mining Techniques to Efficiently Monitor Chronic Diseases Using Wireless Body Area Networks and Smartphones
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Abstract This paper presents a wireless body area network platform performing daily physical activity recognition using accelerometers, biosignals and smartphones. Various classifiers have been evaluated to identify the one with the best recognition results. 

E-Commerce Knowledge Renovation  Data Mining Processes for Small Business Site Design
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ABSTRACT Websites are used to establish the company's policy and image or picture, to promote and sell of goods or support services and to provide the customer support and to facilitate the communication and enquiries between the end users and the organization in 

ROLE OF DATA MINING IN RETAIL SECTOR
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ABSTRACT Data mining is proved to be one of the important tools for identifying useful information from very large amount of data bases in almost all the industries. Industries are using data mining to increase revenues and reduce costs. This article begins the concept 

Dynamic knowledge mapping guided by data mining: Application on Healthcare.
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ABSTRACT The capitalization of know-how, knowledge management, and the control of the constantly growing information mass has become the new strategic challenge for organizations that aim to capture the entire wealth of knowledge (tacit and explicit). Thus, 

A Review of Data Mining Techniques for Result Prediction in Sports
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ABSTRACT In the current world, sports produce considerable statistical information about each player, team, games, and seasons. Traditional sports science believed science to be owned by experts, coaches, team managers, and analyzers. However, sports organizations have 

An Optimized Approach for Discovering Anomalies in Distributed Data Mining
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ABSTRACT There has been a tremendous increase in the volume of Earth Science data over the last decade from modern satellites, in-situ sensors and different climate models. All these datasets need to be co-analyzed for finding interesting patterns or for searching for 

Data Mining Improves Pipeline Risk Assessment
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Page 1. Data Mining Improves Pipeline Risk Assessment Baoqin Wang 1 , Xuyang Zhou 2 ,

ANALYZING EEG DATA FOR COGNITIVE BEHAVIOUR USING EEGLAB THROUGH DATA MINING
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ABSTRACT This paper is a theoretical analysis of human brain and its activity which is measured by EEG. Electroencephalography (EEG) is the process where electrodes are placed on scalp and brains activity is explored by EEG measurements. This measurement 

Data Dependencies Mining In Database by Removing Equivalent Attributes
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 Experiments on datasets show that DM_EC can prune more candidates than previous methods [5]. Key Words- Data Mining, DD, FD, Normalization  Silva and Melkan off was the first team attempting to discover functional dependencies (FDs) through the data mining technique. 

Data Mining Techniques
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ABSTRACT Data mining is a process which finds useful patterns from large amounts of data. Data mining is the process of analyzing data from different perspectives and summarizing it into useful information. Data mining is the practice of automatically searching large stores 

The Research of Wind Turbine Fault Diagnoses Based on Data Mining
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ABSTRACT Wind turbine is the key equipments of the wind farm, the distribution area is wide, and the working condition is poor, in the event of failure, caused by the loss and consequences are incalculable. Therefore, in order to ensure the safe and stable 

Predicting Customer Churn in Mobile Telephony Industry Using Probabilistic Classifiers inData Mining
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ABSTRACT Customer churn in the mobile telephony industry is a continuous problem owing to stiff competition, new technologies, low switching costs, deregulation by governments, among other factors. To address this issue, players in this industry must develop precise 

SpADS: An R script for mass spectrometry data preprocessing before data mining
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ABSTRACT The recent application of Mass Spectrometry (MS) to Nucleic Acid Programmable Protein Array (NAPPA) technique for proteins identification by non-classical methods leads to the needs of more sophisticated algorithm for peak recognition. NAPPA technique 

A Survey on Data Mining Techniques for the Diagnosis of Coronary Artery Disease
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ABSTRACT The heart disease is a major cause of mortality and death-rate in modern society. Medical assessment is very important but labyrinthine task that should be performed efficiently and accurately. Therefore, in this era of computing and intelligence. It is an easy 

Stock Portfolio Selection using Data Mining Approach
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ABSTRACT Once it is decided that investment is to be made in the stock, the obvious question which arises is: which all stocks should be purchased? Past performance will not guarantee the future, but it is still worthwhile to evaluate the investments based on their ability to 

A data-based method for harmonising heterogeneous data modelling techniques acrossdata mining applications
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ABSTRACT We propose an iterative graphical data visualisation algorithm for optimal model selection. The algorithm is implemented on three domain-partitioning techniques-decision trees, neural networks and support vector machines. Each model is trained and tested on 

Personalized Geographic Information Service based on RIA and Data Mining Technology
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ABSTRACT The integration of GIS and Web technology makes public service-oriented geographic information service feasible. Personalized geographic information service needs geographic information service providers give the correct geographic information at the 

DISCERNING LEARNER'S ERUDITION USING DATA MINING TECHNIQUES
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Abstract Association Rule mining can be used in various areas of education data to bring out the interesting rules about the learner's records. It can be used to bring out the hidden facts in understanding the behavior of the learner in a learning environment, learning style 

The Building of User Model of Personalized Learning Teaching System Based on Data Mining
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Page 1. The Building of user model of Personalized Learning teaching system based on Data Mining Wenyan Rui 1, a , Haiying Mi 2, b  215104, China aemail: ruiwy siit.cn, bemail:

Convergence of IT and Data Mining with other technologies
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ABSTRACT In this age of technology and communication convergence, we cannot help but be impacted by technologies and innovations that center on computers. This paper examines the growing need for a secure environment and a general-purpose analytics engine. The 

ROLE OF DATA MINING IN EDUCATION SECTOR
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ABSTRACT Universities either public or private and its colleges enroll thousands of students into various courses or programs every year. They collect information from students at the time of admissions and store the same in computers. Understanding the benefits of data is 

A Bio-Inspired Approach to Data Mining: A Review
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ABSTRACT Data mining has become a powerful tool to extract hidden patterns of data and is gaining importance as it helps in decision making in all spheres of life. Its various techniques allows users to get refined result of their query. Clustering is the technique which allows 

Realisation of Resourceful Data Mining Services Using Cloud Computing
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ABSTRACT Data security and access control are the most challenging research work going on, at present, in cloud computing. This is because of the users sending their sensitive data to the cloud providers for acquiring their services. In cloud computing, the data is going to 

Research on Personalized Recommendation in E-commerce Service based on Data Mining
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ABSTRACT We propose a new hybrid recommendation algorithm to optimization the cold-start problem with Collaborative Filtering (CF). And we use neighborhood-based collaborative filtering algorithm has obtained great favor due to simplicity, justifiability, and stability. 

Discussion about Big Data Mining Based on Hadoop
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Zhonghua Deng 1, a , Bing Fan 2, b , YingJun Lu 3, c , Zhifang Li 4, d  1,2,3,4 School of Information Management, Wuhan University, China

Improving the Student's Performance Using Educational Data Mining
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The main goal of educational data mining is to improve the student performance. The usage of data mining techniques which achieves the goal in an efficient manner. The 

A Comparison between Data Mining Methods in Anticipation of Financial Distress and Improvement of Anticipation through Combination of Methods
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Every day, we are witnessing multiple crises in the business world. Ever-increasing competition between economic institutions has restricted accessibility to resources and increased probability of financial distress. In consequence of the financial crisis it is 

Studying Data Mining and Data Warehousing with Different E-Learning System
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ABSTRACTData Mining and Data Warehousing are two most significant techniques for pattern detection and concentrated data management in present technology. ELearning is one of the most important applications of data mining. The foremost idea is to provide a 

A Data Analytics Framework for Smart Grids: Spatio-temporal Wind Power Analysis and Synchrophasor Data Mining
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ABSTRACT Under the framework of intelligent management of power grids by leveraging advanced information, communication and control technologies, a primary objective of this study is to develop novel data mining and data processing schemes for several critical 

Efficient Probing For Geological Data Assembly Using Knowledge Mining
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Berkhin P. (2004), Survey of clustering data mining techniques, Datanautics, Inc. Research Papers, available at

Data Mining and Analysis of Economic Data
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ABSTRACT Gross State Domestic Product (GSDP) is a benchmark for economic production conditions of an Indian state. It is also a measure of standard of living of people in a particular region. Estimates of economic growth in an Indian state has important roles, 

The Effect of Clustering in the Apriori Data Mining Algorithm: A Case Study
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ABSTRACT Many organizations collect and store data about their customers, suppliers and business partners. However, much of the useful marketing insights are hidden in that enormous amount of data. Data mining is the process of searching and analyzing data in 

Detecting salient events in large corpora by a combination of NLP and data miningtechniques
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ABSTRACT. In this paper, we present a framework and a system that extracts salient events relevant to a query from a large collection of documents, and which also enables events to be placed along a timeline. Each event is represented by a sentence extracted from the 

A Posteriori Error Analysis in Numerical Approximations of PDE's: A Pilot Study Using Data MiningTechniques
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Abstract We introduced in a new methodology based on data mining techniques for numerical approximation analysis. Our aim is to extend this methodology to a posteriori error analysis in numerical approximations of partial differential equations. Let us consider a 

Spam Mail Detection through Data Mining–A Comparative Performance Analysis
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ABSTRACT As web is expanding day by day and people generally rely on web for communication so e-mails are the fastest way to send information from one place to another. Now a day's all the transactions all the communication whether general or of business 

Highlights of Recent Articles on Data Mining in Genomics and Proteomics
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Advancements in 'Omics' technologies continue to enhance research to solve the world's medical and agricultural problems. The 2012 issues of Data Mining in Genomics Proteomics solicited contributions from leading authors covering various aspects of data 

Data mining and modeling to predict the necessity of vasopressors for sepsis patients
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ABSTRACT Shock is a life-threatening medical condition requiring the administration of powerful drugs-vasopressors. Early identification of these patients is a worthy goal in order to timely prepare them for therapy. A subset composed of the most frequently sampled and 

Privacy Preserving Association Rule Mining in Collaborative Intrusion Detection Systems with Fuzzy Data
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 To achieve this, they share normal and attack data of their IDSs. Since the data are sensitive, they don't want to share explicit data. Now, how these organizations can operate data mining and/ or machine learning on aggregate data without violation on data confidentiality. 

MINING CLOSED REGULAR PATTERNS IN DATA STREAMS
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 171 MINING CLOSED REGULAR PATTERNS IN DATA STREAMS  ABSTRACT Mining regular patterns in data streams is an emerging research area and also a challenging problem in present days because in Data streams new data comes continuously with varying rates. 

Utilizing Data Mining and Factor Analysis for Identifying Activity Base Costing Cost Drivers in Iranian Bank
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ABSTRACT Most of firms are interested to know about the real cost of products and services they provide. In order to measure the real cost, several methods and techniques have been provided in literature. One of the most important and prominent methods is the Activity 

Improvement of Web Data Mining Method and its Application in Personalized Recommendation
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ABSTRACT Personality recommendation system in digital library has good development and applied prospects. It is becoming gradually an important research content in electronic resources intelligent processing. This study proposes a WEB data mining method based 

A Reliable Classifier Model Using Data Mining Approach for Heart Disease Prediction
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ABSTRACT Cardio vascular disease is a major threat to half of the world population. The term heart disease is related to all the diverse diseases affecting the heart. The healthcare industry generates large amount of data that are too difficult to be analysed by traditional 

Accuracy-Privacy Comparison for Enhanced Grouping using a Hybrid Data Mining Technique
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ABSTRACT Privacy preserving data mining techniques play very important role in protecting the sensitive and private information of users from distributed data sets. In this modern field of business world applications the capability of storage and record the personal data or 

Data Mining Partition in Grid Computing
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ABSTRACT Grid computing is nothing but the computing environment in which the resources are shared by multiple systems to obtain a goal. In day today life performance analysis of very large data sets in the computing environment is necessary in many applications. The 

Admission Management through Data Mining using WEKA
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Abstract Most of the institutions opened during last two decades are in self financing mode. In order to meet the expenditure, lot of effort is being taken by the institutions to have good strength of students. This paper proposes the use of data mining techniques in 

A survey on Data Mining approaches for Healthcare
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Abstract Data Mining is one of the most motivating area of research that is become increasingly popular in health organization. Data Mining plays an important role for uncovering new trends in healthcare organization which in turn helpful for all the parties 

Fast Feature Selection for Naive Bayes Classification in Data Stream Mining
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 predictive performance. Index terms - data mining, feature selection, Naïve Bayes classification, stream mining I. INTRODUCTION Predictive data mining involves the creation of classification or regression models. A classification 

The data mining approach for analyzing infrastructure operating conditions
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ABSTRACT Bridges serve as critical structures to the functionality of road networks within an infrastructure system and require regular inspections to ensure they are in safe operating condition for the public. This research developed a data mining approach to analyze and


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