data mining papers





spatial data-mining


multimedia data-mining-03


multimedia data-mining





data-exploration-and data-mining

java data-mining-package

semantic data-mining


detection-system-based-on data-mining

deployment-of data-mining

attacks-and data-mining


using data-mining




chromatographic-data-using data-mining



integrating data-mining


preserving data-mining

remote data-mining

temporal data-mining

binaries-by data-mining

grid-based data-mining


time-series data-mining-method
















data ware housing research papers


peer-to-peer data-warehousing

data-quality-problems-in data-warehousing

mobility data-warehousing-and-mining

modelling-of data-warehousing



peta-scale data-warehousing-at-yahoo

real-time data-warehousing

gfinder data-warehousing

spatio-temporal data-warehousing

spatio-temporal data-warehousing-02

materialized-views-in data-warehousing


data mining research papers 2015

Mining Musician Similarity based on Meta Paths
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authors use three kinds of search queries: M (music), MR (music and review), and allintitle.When comparing with data from, we get more 100% recall for various artistsand X. Serra, Unifying Low-Level and High- Level Music Similarity Measures, IEEE Transactions on

Energy saving in smart homes based on consumer behaviour data
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Not in all publications, the detailed procedure, how periodic patterns are mined is explainedThe resulting clusters represent activities that can be stored and tracked in real time data. Clustering is executed after the sequence mining and results in a compressed representation of

Unsupervised Learning of Multiple Languages Using Recurrent Neural Networks
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to stop growing in an exponential manner (Figure 2). However, we know that increasing the amount of training data would increaseR. Bertolami, H. Bunke, and J. Schmidhuber, A Novel Connectionist System for Unconstrained Handwriting Recognition, IEEE Transactions on

False rumors detection on sina weibo by propagation structures
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(1,0,1) (0,0,-1) Fig. 6: Example of Labeled Propagation Tree 2Note that this data structure contains only part of the information con- tained in the message propagation tree model in Section II.Then each sequence qi is searched by querying intext:qi intitle:false rumor.

Discovering Information Explaining API Types Using Text Classification
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For this reason we selected APIs with common application domains so that annotators could label the data without special training.for s, t if t is mentioned in s as a code term more than once once TRUE for s, t if t is mentioned in s as a code term only once inTitle TRUE for

Interactive Classification of Keyword Search Queries
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accuracy of 90%. 9 Page 17. Nettleton et al. [53] apply a systematic datamining process to 12,000 user queries and click data. As key elements of activity, they use the query posed by the user, document selections and the user behavior with respect to the presented results.

A Survey of Sequence Patterns in Data Mining Techniques
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Abstract Data mining techniques are used in many areas in the world to retrieve the useful knowledge from the very large amount of data. Sequence pattern mining is the important techniques in data mining concepts with the wide range of applications. The applications

Dataset Fingerprints: Exploring Image Collections Through Data Mining
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Abstract As the amount of visual data increases, so does the need for summarization tools that can be used to explore large image collections and to quickly get familiar with their content. In this paper, we propose dataset fingerprints, a new and powerful method based

Impact of Known Input Output Attacks in Euclidean Distance Preserving Perturbation for Privacy Preserving Data Mining
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Abstract: rivacy preserving Data Mining considers the problem of running data mining algorithms on confidential data that is not supposed to be revealed even to the party running the algorithm. In this technique, some statistical data that is to be released, so that it can

Comparative Study of Frequent Item Set in Data Mining
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ABSTRACT In this paper, we are an overview of already presents frequent item set mining algorithms. In these days frequent item set mining algorithm is very popular but in the frequent item set mining computationally expensive task. Here we described different

Cognition of Parameters' Role on Vertical Control Device for Aerodynamic Characteristics of Aircraft Using Data Mining
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Abstract The new concept to place the vertical airfoil device as control surface has been discovered so as to improve the aerodynamic performance of aircraft. The concept was predicated on not only the several devices as vortex generator and winglet but also the

Design and Implementation of Content Based Image Retrieval Using Data Mining and Image Processing Techniques
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Abstract: Now a days people are interested in using digital images. There is a great need for developing an efficient technique for finding the images. In order to find an image, image has to be represented with certain features. Color, texture and size are three important

Lumping versus splitting: the need for biological data mining in precision medicine
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Biological data mining is playing an increasingly important role throughout the spectrum of biological and biomedical research with broad implications for the understanding of life science questions such as the tree of life and practical applications of such knowledge to

Classification Algorithms and Comparison in Data Mining
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ABSTRACT In present days, tons of data and information exist for each and everyone, Data can now be kept in many various kinds of databases as well as information repositories, besides being available online or in hard copy. With such big amount of data, a need for

Discovery of Acupoints and Combinations with Potential to Treat Vascular Dementia: A Data Mining Analysis
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The prevalence of vascular dementia (VaD) is high among the elderly. Acupuncture, a popular therapeutic method in China, can improve memory, orientation, calculation, and self- managing ability in VaD patients. However, in clinical acupuncture and acupuncture

KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework
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Data Mining (DM) is the process for automatic discovery of high level knowledge by obtaining information from real world, large and complex data sets [26], and is the core step of a broader process, called Knowledge Discovery from Databases (KDD). In addition to

Improving Cities Sustainability through the Use of Data Mining in a Context of Big City Data
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Abstract:Nowadays, cities consume more energy to fuel their day-to-day activities. With the rise of electrical devices we face more challenges associated with energy control and distribution. Apart from this, we also spend a lot of energy trying to either heating or

Data Mining in Healthcare for Heart Diseases
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ABSTRACT: Data Mining is the area of research which means digging of useful information or knowledge from previous data. There are different techniques used for the data mining. Data mining may used in different fields including Healthcare. Heart or Cardiovascular

Use of Data Mining Techniques to Improve the Effectiveness of Sales and Marketing
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Abstract: Classification and patterns extraction from customer data is very important factors for business support and decision making. Identification of newly emerging trends is needed in business process. Sales patterns from inventory data indicate market trends and can be

A global immune deficit in Alzheimer's disease and mild cognitive impairment disclosed by a novel data mining process
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Abstract. Alzheimer's disease (AD) is the most common form of dementia, while mild cognitive impairment (MCI) causes a slight but measurable decline in cognitive abilities. A person with MCI has an increased risk of developing AD or another dementia. Thus, it is of Data preprocessing is an often neglected but major step in the data mining process. The data collection is usually a process loosely controlled, resulting in out of range values, eg, impossible data combinations (eg, Gender: Male; Pregnant: Yes), missing values, etc.

Techniques for Web Mining of Various Forms of Existence of Data on Web: A Review
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Abstract: Information extraction is known to be the task of extracting knowledge from any meaningful text automatically. It provides services to the users who retrieve the information by firing query on Internet. When huge amount of information is extracted from large

Data mining for the internet of things: literature review and challenges
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The massive data generated by the Internet of Things (IoT) are considered of high business value, and data mining algorithms can be applied to IoT to extract hidden information from data. In this paper, we give a systematic way to review data mining in knowledge view,

The Analysis of Physical Effects on Presence in the 4D Attraction Film using the Data Mining
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Abstract A 4D attraction film is an entertainment presentation system combining a 3D film with physical effects that provide other experience in senses. A wide variety of devices that the audience can be immersed in the story should be reflected in the contents production


Adapting the Weka Data Mining Toolkit to a Grid Based Environment.
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Abstract. Data Mining is playing a key role in most enterprises, which have to analyse great amounts of data in order to achieve higher profits. Nevertheless, due to the large datasets involved in this process, the data mining field must face some technological challenges.

Weka-gdpm: Integrating classical data mining toolkit to geographic information systems
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Abstract. Geographic data preprocessing is the most effort and time consuming step in spatial data mining. In order to facilitate geographic data preprocessing and increase the practice of spatial data mining, this paper presents Weka-GDPM, an interoperable module

Analyzing association rule mining and clustering on sales day data with xlminer and weka
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Abstract In the era of intense competition among organizations, retaining a customer is a collaborative process. Business organizations are adopting different strategies to facilitate their customers in verity of ways, so that these customers keep on buying from them.

Performance analysis of Data Mining algorithms in Weka
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Abstract: The retail industry collects vast amounts of data on sales, customer buying history, goods, and service with ease of use of modern computing technology. This paper elaborates the use of data mining technique to help retailers to identify customer profile for a retail

Extending the Weka Data Mining Toolkit to support Geographic Data Preprocessing
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Large amounts of geographic data have been used more and more in many areas in different application domains such as urban planning, transportation, telecommunication, marketing, etc. These data are stored under Geographic Database Management Systems

A Novel Approach for WEKAStudy On Data Mining Tools
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Abstract-Mining tools to solve large amounts of problems such as classification, clustering, association rule, neural networks, it is a open access tools directly communicates with each tool or called from java code to implement using this. In this paper we present machine

Fuzzy-rough data mining with Weka
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There are a number of tabs towards the top of the window which are activated when a dataset is loaded. We ll only be considering the Pre process, Classify and Select attributes tabs in this tutorial. Click Open file and navigate to wherever the heart2. arff dataset is

A comparative analysis of different data mining using WEKA
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Abstract: Clustering is an adaptive procedure in which objects are clustered or grouped together, based on the principle of maximizing the intra-class similarity and minimizing the inter-class similarity. Various clustering algorithms have been developed which results to

Analysis of Employment Data Mining for University Student based on Weka Platform
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Abstract: This paper took the historical data of university graduates employment and the employment guidance as the study object and purposes, tried to find out the useful information hidden in the historical data of employment through the data mining of the

A new Predictive Model of Mutagenicity, with statistical analysis and validation using data-mining tools in WEKA
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Results The dataset was first normalized in the [-1, 1] range by simply scaling each descriptor column with its maximum absolute value. After a search in the parameters-space of the learning algorithm kernel function to find the optimal (C,)=(16, 8) assignmentfor

Educational Data Mining: Performance Evaluation of Decision Tree and Clustering Techniques Using WEKA Platform
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Abstract Data Mining plays a vital role in information management technology. It is a computational process of finding patterns from large databases. It mainly focuses on extracting knowledge from the given or the available data. Different knowledge extracting

A comparison study on performance analysis of data mining algorithms in classification of local area news dataset using weka tool
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Abstract Data mining (the analysis step of the" Knowledge Discovery in Databases" process, or KDD),[1] a field at the intersection of computer science and statistics, is the process that attempts to discover patterns in large data sets. It utilizes methods at the intersection of

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ABSTRACT Data mining is the extraction of intriguing (relevant, constructive, previously unexplored and substantially valuable) patterns or information from huge stack of data. In other words, it is the exploration of links, associations and overall patterns that prevail in

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ABSTRACT One of the most complex legal activities that law enforcement agencies across the world are facing is to analyze the crime data so that forecasting of crime trends can be done. This involves predicting the behaviour of criminals so that Proactive Preventive

Project 8: Naive Bayes classifier in WEKA Data Mining in Bioinformatics
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The purpose of the tutorials is to familiarise yourself with one of the key algorithms that are widely applied in data mining and bioinformatics. Each exercise consists of 3 work packages. At the end of the course you will present your results for each of the work

Analysis of Bayes, Neural Network and Tree Classifier of Classification Technique in Data Mining using WEKA
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ABSTRACT In today's world, gigantic amount of data is available in science, industry, business and many other areas. This data can provide valuable information which can be used by management for making important decisions. But problem is that how can find

Analysis of WEKA Data Mining Algorithm REPTree, Simple Cart and RandomTree for Classification of Indian News
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Abstract The amount of data in the world and in our lives seems ever increasing and there's no end to it. The Weka workbench is an organized collection of state-of-the-art machine learning algorithms and data pre-processing tools. The basic way of interacting with these

Performance Analysis of Different Classification Methods in Data Mining for Diabetes Dataset Using WEKA Tool
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dataset. Keywords- Data mining, Classification algorithms, WEKA tool I. INTRODUCTION

Build a model to predict the success of students by hereditary and social factors using the tool for data mining Weka
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Abstract: All countries pay great attention to education and the ways of its improvement and promotion. Young people are those who will continue to build the country's future and therefore these efforts are necessary. Build a model to predict the success of students will

Data Mining for Staff Recruitment in Education System using WEKA
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ABSTRACT: Education system is the essential component of the country development. It plays a major role to development of country. Thus the teaching staff who can develop the youth, they must be the qualified, nationalizes and dedicated. This analysis is based on

Data mining and machine learning in e-Science Central using Weka
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This paper describes the integration and use of elements of the Weka open source machine learning toolkit within the cloud based data analytics e-Science Central Platform. The purpose of this is to extend the data mining capabilities of the e- Science Central platform using

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ABSTRACT In this study, the data storage techniques which are necessary to perform the data mining applications have been anaysed. In the data mining applications, the data are processed through some stages until the analysis stage. The proper performance of these

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ABSTRACT In the new area of data intensive science, data mining techniques receiving more attention. Nowadays, data analysts can rely on a broad number of tools, ranging in functionality,target computer architectures. Data mining is an analytic process

An Experimental Analysis of Clustering Algorithms in Data Mining using Weka Tool
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Abstract:Cluster analysis divides data into meaningful or useful groups (clusters). It is a process for discovering groups and identifying interesting patterns. There are different types of clusters: Well-separated clusters, Center-based clusters, Contiguous clusters, Density-

Effect of WEKA Filters on the Performance of the NavieBayes Data Mining Algorithm on Arrhythmia and Parkinson's Datasets
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Revised: 10/05/2014 Accepted: 22/05/2014 Published: 3/05/2014 Abstract-Data mining is the process of selecting, exploring and modeling a large database in order to discover model and pattern that are unknown [1]. Enormous gathered data in Health care

Comparing the Performance of Data Mining Tools: WEKA and DTREG
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Abstract:The objective of the paper is to compare two data mining tools on the basis of various estimation criteria. The data mining tools which are evaluated are WEKA and DTREG. These tools are used to build multilayer perceptron which is a data mining model

Evaluating Performance of Data Mining Classification Algorithm in Weka
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Abstract Data mining is a technique that uses different types of algorithms to find relationships and trends in large datasets to promote decision support. The data sizes accumulated from various fields are exponentially increasing; data mining techniques that

Enhancing Forensic Investigation in Large Capacity Storage Devices using WEKA: A Data Mining Tool
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ABSTRACT Data mining applications have been growing tremendously in today s world. One of the important applications of data mining is its usage in forensic investigation especially when a large amount of data is involved. This project explains why forensic