data mining research papers 2012-109

data mining research papers 2012-109







Predicting the Number of Blood Donors through their Age and Blood Group by using Data Mining Tool
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ABSTRACT The growing demand in the blood bank sector makes it necessary to exploit the whole potential of stored data efficiently. Data mining can contribute with important benefits to the blood bank sector, it can be a fundamental tool to analyze the data gathered by

Emerging Trends in Utilization of Data Mining in Criminal Investigation: An Overview
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ABSTRACT In this paper, an introspective overview is made about the various contemporary and evolving techniques in data mining which are extensively used in criminal analysis and investigation. Data mining encompasses a range of techniques each designed to interpret

1 Data mining, Classification and Clustering with Morphological features of Microbes
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ML Chayadevi, GT Raju, D Kaur, S Singh ,International ABSTRACT The idiosyncrasies of the medical profession makes medical image mining a challenge. Image mining deals with the extraction of implicit knowledge, image data relationship, or other patterns not explicitly stored in the images. It is very difficult to

A Novel Configuration-Driven Data Mining Framework for Health and Usage Monitoring Systems
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D He, E Bechhoefer, M Al-Kateb, J Ma, P Joshi ,cdn.intechopen.com Health and Usage Monitoring Systems (HUMS) and Condition Based Maintenance (CBM) systems are closely related systems since the data collected by HUMS can be effectively used by CBM systems to generate condition and health indicators of air-crafts in order to

High-Speed Data Stream Mining using VFDT
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 than 10,000 examples) often leads to overfitting or \data dredging (eg, [11, 7]). Thus overfitting avoidance becomes the main concern, and only a fraction of the available computational power is used [3]. In contrast, in many(if not most) present-day data mining applications, the

Prediction of Soil Erosion Depth Due to Increase in Forest fire Danger Rate by Data Mining
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TL Divya, MN Vijayalakshmi ABSTRACT Forest areas and unfarmed land fires have been witnessed in the history for loss of soil nutrient. Forest Fires is one of the sources of trouble for a long time. Fires for larger hectare have huge pressure over the ecological system . It is required to calculate the

Study Analysis of data mining Algorithms: Case Study
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D Dwivedi ,sciencepub.net ABSTRACT In this paper we study the Data analysis has many facets, ranging from statistics to engineering. In this paper we discussed basically data mining algorithms for data analysis. Now we can uses of cluster analysis, precedence analysis, and data mining methods are

Data Mining Classification Methods Applied in Drug Design
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M Stachov, L Sobek ABSTRACT Data mining incorporates a group of statistical methods used to analyze a set of information, or a data set. It operates with models and algorithms, which are powerful tools with the great potential. They can help people to understand the patterns in certain chunk

Visualization of Clandestine Labs from Seizure Reports: Thematic Mapping and Data MiningResearch Directions
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H William ABSTRACT The problem of spatiotemporal event visualization based on reports entails subtasks ranging from named entity recognition to relationship extraction and mapping of events. We present an approach to event extraction that is driven by data mining and

DATA MINING ANALYSIS OVER A DATABASE OF MATERIALS OF PORTUGUESE PAINTINGS FROM THE 15TH AND 16TH CENTURIES
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VH Antunes, O Anunciao, A Candeias, AI Seruya ,morana-rtd.com We used a method based on decision tree learning, Fisher s exact test and permutation testing and it was possible to find a ground layer technique that distinguishes António Nogueira s Ferreira do Alentejo retable from other paintings in our database. This

Applications of Data Mining
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ABSTRACT Data Mining is a powerful tool capable of handling decision making and for forecasting future trends of market. Data Mining tools and techniques can be successfully applied in various fields in various forms. In this paper, we will explain various

UNLOCKING REFERRAL NETWORKS THROUGH DATA MINING AND SOCIAL NETWORK ANALYSIS
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D Sundaramoorthi, M Lavieri, H Zhao ,haskayne.ucalgary.ca ABSTRACT In this study, we couple data mining techniques with social network analysis (SNA) to discover the structural design of physician referral systems. This combined methodology reveals underlying patterns of organization among general practitioners (GPs) and

Detecting Telecommunication Fraud using Neural Networks through Data Mining
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MI Akhter, MG Ahamad ABSTRACT Neural computing refers to a pattern recognition methodology for machine learning. The resulting model from neural computing is often called an artificial neural network (ANN) or a neural network. Neural networks have been used in many business

EVOLUTION OF DATA WAREHOUSE AND DATA MINING
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ABSTRACT Data warehouse is the requisite of all present competitive business communities? ie profitable and non-profitable as well as educational institutions where data is complex, huge and dynamic. The technology advent is not in a day but emerging from late 1980s.

CS/STAT 5525 Project Proposal: Mining of Crime and Terrorism Data
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J Cadena, B Kamali, D Mishra, K Morgan ,filebox.vt.edu  the jurisdiction. We use data mining techniques to create a model that identifies areas with high and low crime rates. Then, we  as possible. Index Terms- crime data mining, resource allocation, law enforcement data mining I. INTRODUCTION

Methods for efficient utilization of SOM in data mining
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The Self-Organizing Map (SOM) algorithm has been widely implemented in various software tools and libraries, for example, the SOM Toolbox [5]. However, for a common practitioner a difficulty with applying the SOM in data mining has been that there is no wide consensus

Fast Mining of Temporal Data Clustering
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DS Babu, K Navya  Unlike static data, there is a high amount of dependency among temporal data and many application areas ranging from multimedia information processing to temporal data mining the proper treatment of data dependency or correlation becomes critical in temporal data

Prediction and decision making in Health Care using Data Mining
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ABSTRACT Tendency for data mining application in healthcare today is great, because healthcare sector is rich with information, and data mining is becoming a necessity. Healthcare organizations produce and collect large volumes of information on daily basis.

Text Mining for Sentiment Analysis of Twitter Data
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From the perspective of decision makers, this collection of messages provides a precious source of information. In this paper, we present the use of Weka data mining tools to extract useful information for classifying sentiment of tweets collected from Twitter.

Association Rule Mining for Gene Expression Data
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OV Kale, BF Momin ,irnetexplore.ac.in  Keywords ,Gene Expression Data, Data Mining, High Confident Association Rules, Bioinformatics. I. INTRODUCTION  [3] G. Cong, K.-L. Tan, A. Tung, and F. Pan, Mining Frequent Closed Patterns in Microarray Data, Proc. Fourth IEEE Int l Conf. Data Mining (ICDM), vol. 4, pp.

Deriving Serial and Parallel Spikes Data in Neural Science Using Data Mining Techniques
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JA Srinivas Bobba Abstract In this paper we introduce the notion of mining for frequent episodes under certain temporal constraints; the structure of these temporal constraints is motivated by the application. We present algorithms for discovering serial and parallel episodes under

Energy Efficient Data Mining in Multi-Feature Sensor Networks Using Improved Leach Communication Protocol
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ABSTRACT Wireless Sensor Networks (WSNs) with large number of sensor nodes are used to monitor the sensing filed. Sensor node energy efficiency and sensor network data-transfer reliability are the primary design parameters. Some applications may require

Clustering Technique in Data Mining for Text Documents
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MJS Priya, MS Priyadharshini ABSTRACT Feature selection is an important method for improving the efficiency and accuracy of text categorization algorithms by removing redundant and irrelevant terms from the Data warehouse. The semantic clustering and feature selection method is proposed to improve

A STUDY OF RETAIL OUTLETS TO OPTIMIZE THE SALE AND STOCK PROBLEMS USINGDATA MINING
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MSP Singh, BK Sharma ,VISION CATALYST ,visioncatalyst.in ABSTRACT In retail sector it is quiet typical to manage the sale and the outlets requirements. Most of the time it is observed that suddenly the demand of certain items get increased remarkably and the outlets become unable to fulfill the customer requirements as the

Designing Neural Network based Data mining Algorithm
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C TT II, C EE ABSTRACT Designing Neural network based Data mining algorithm can be done by combining ANN s strategy of learning process to interpret or evaluate data. This article discusses the concept of Neural Networks, how it can be efficiently used in the field of

Data Mining in a System of a Candidate Selection Process
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RMA Baracho, MT Dias Abstract Data mining and information retrieval has been research areas increasingly important in the information age where fast, accurate access to information becomes an essential factor in decision-making in various fields of knowledge. The main goal of this

Format Conversions for Open Source Data Mining Implementation in Digital Economy Ranking
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M ZURINI ,framework ,economyinformatics.ase.ro The terms of digital economy and e-readiness are introduced and presented in the present area of evolution of economy stage within Europe and not only. The main aspects treated in the European University Institute ranking for e-readiness are briefly covered. An open

I om Data Mining to Knowledge Discovery: Overview
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J Naisbett ,cacs.louisiana.edu -John Naisbett act explosive growth of many business, government, and scientific databases- -: ar outpaced our ability to interpret and digest this data, creating a need a new generation of tools and techniques for automated and intelligent~ analysis. These tools and

Rule based Classification of BSE Stock Data with Data Mining
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A Rajput, SP Saxena, RP Aharwal, R Soni ,irphouse.com ABSTRACT Data mining aims to discover hidden knowledge, unknown patterns, and new rules from large databases that are potentially useful and ultimately understandable for making crucial decisions. This paper focuses for the rule based classification model of historical

DataAprori algorithm: Implementation of scalable Data Mining by using Aprori algorithm
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MA Alam, S Jain, R Biswas ,International Journal ,upo.es ABSTRACT Data Mining is concerned with the development and applications of algorithms for discovery of a priori unknown relationships associations, groupings, classifiers from data. Association rule mining (ARM) is a knowledge discovery technique used in various data

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