data mining research papers 2012-113
Analysis and Comparison of Efficient Techniques of Clustering Algorithms in Data Mining
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SPS Kushwah, K Rawat, P Gupta ,ijitee.org
Abstract—This paper presents the comparison of data mining algorithms for clustering.
These algorithms are among the most influential data mining algorithms in the research
community. With each algorithm, we provide a description of the algorithm, discuss the
Data Mining System Architecture for Training Plan Selection for the Swimmers
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MDP Vaidya, SU Makh ,researchinventy.com
Abstract–In Sports, vast amount and variety of data is generated at different stages. Sports
are using this data to derive valuable information to improve performance, avoid injuries,
organizations, researchers, coaches, players game planning, decision making and even
Association Rule Mining on Distributed Data
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P Dubey
The response time is calculated in this environment using XML data. Keywords
Association rules, Apriori algorithm, parallel and distributed data mining,
Multiprocessing Environment, XML data, response time. ————
A Novel Theory in Risk ? Management by Numerical Pattern Analysis in Data ? Mining
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M Kargar, F Fartash, T Saderi ,cdn.intechopen.com
Page 1. A Novel Theory in Risk-Management by Numerical Pattern Analysis in
Data-Mining 29 X A Novel Theory in Risk?Management by Numerical Pattern
Analysis in Data?Mining Masoud Kargar, Farzaneh Fartash and
ESTIMATION OF CASUAL RELATIONSHIPS AMONG THE DATA ITEMS BY USING STATISTICALDATA MINING TECHNIQUES
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V Ramineni, G Rajendra, K Phaneendra
ABSTRACT: We know that Data mining or Knowledge discovery from databases (KDD) is a
collection of exploration techniques based on advanced analytical methods and tools for
handling a large amount of information. Many data mining techniques are closely related
Exploiting Inter-Sample Information and Exploring Visualization in Data Mining: from Bioinformatics to Anthropology and Aesthetics Disciplines
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K Lin, JH Liu
In this data-overabundant world, revealing and representing comprehensible relationships
behind complicated datasets have become important challenges in data mining. This
chapter presents recent achievements in applying data mining techniques to two
Measuring Students’ Performance with Data Mining
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JP Atanas ,ifrnd.org
Abstract: Understanding the true reasons behind students’ failure, and bringing preventive
measures to this issue at early stages are invaluable in the educational learning process.
Preventing problems such as language deficiency or misclassification of the students in
Meta learning in hybrid multi-agent systems designed for data mining
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K Pešková ,epcc.ed.ac.uk
Discovering patterns in data usually requires deeper understanding of both data and data
mining methods. We have developed a multi-agent system (MAS) which is able to meta
learn over different configurations of computational methods (such as multilayer
Data Mining Techniques and their role in Intrusion Detection Systems
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A Sharma, SN Panda, A Gupta ,jairjp.com
Abstract As more and more crucial data is being loaded on computer servers, the security of
government and commercial industrial servers is the main concern. The Intrusion Detection
Systems can address these problems but they face challenges in robust and changing
Development of a Workbench to Address the Educational Data Mining Bottleneck
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ABSTRACT In recent years, machine-learning software packages have made it easier for
educational data mining researchers to create real-time detectors of cognitive skill as well as
of metacognitive and motivational behavior that can be used to improve student learning.
Developing Cluster Based Data Allocation Scheme by Incremental Mining in LBS Environment
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L Jasmine, D SureshBabu
It will be more precise and accurate if the user clusters and temporal periods are
considered simultaneously. A new data mining algorithm which involves cluster based
incremental mining for user moving patterns in LBS environment.
Cashless Society, Problems and Prospects, Data Mining Research Potentials
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OS Akinola ,ijcst.org
Abstract–No doubt, our modern society is gradually catching the cashless syndrome. E-
payments, ATM cards and others are now the order of the day at our work-places. This paper
takes a keen look into the feasibility of introducing cashless means of business
Comparing Data-mining Algorithms Developed for Longitudinal Observational Databases
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Abstract—Longitudinal observational databases have become a recent interest in the post
marketing drug surveillance community due to their ability of presenting a new perspective
for detecting negative side effects. Algorithms mining longitudinal observation databases
Data mining approaches to fraud detection in telecommunications
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CS Hilas
Abstract—Telecommunications fraud is increasing dramatically each year resulting in loss of
a large amount of Euros worldwide. An invaluable tool for the detection of fraud is the
modeling of telecom users’ behavior. In this paper, a short description of ongoing research
Special Issue Call for Paper Special Issue on: Advanced Data Mining Techniques and Applications Target Journal: International Journal of Database Theory and
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SN Mining
Over the past few years, research and development in data mining has made great
progress. Many successful applications have been reported in journals and conferences. In
general, data mining systems typically help businesses to expose previously unknown
A Process to Comprehend Different Patterns of Data Mining Techniques for Selected Domains
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R Sultana, MD Vani, PV Bhaskhar, P Satish ,ijcset.net
Abstract: This has much in common with traditional work in statistics and machine learning.
However, there are important new issues which arise because of the sheer size of the data.
One of the important problems in data mining is the Classification rule learning which
APPLICATION OF NEURAL NETWORKS IN PREDICTIVE DATA MINING FOR INSURANCE
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P Sehgal, S Gupta, D Kumar ,ijltet.org
Abstract—Data mining tools predict future trends and behaviours allowing businesses to
make proactive and knowledge-driven decisions. This paper presents a study of application
of neural network based techniques of data mining for prediction. Neural networks have
A New Method for Filtered Attribute in Data Mining Using Entropy
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P Gholami, A Bazle, M Eftekhary, P Gholami ,2012
ABSTRACT Filtered Attribute (feature ranking) is one of the main tasks that data mining
algorithms have been proposed and the feature ranking algorithms have been used to
determine the importance and ranking features. The entropy is one of the multi-criteria
Relational and Semantic Data Mining for Biomedical Research
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N Lavrac, PK Novak ,ailab.ijs.si
Abstract The paper first outlines subgroup discovery and selected relational data mining
approaches, with the emphasis on propositionalization and relational subgroup discovery,
which prove to be effective for data analysis in biomedical applications. The core of this
Data Mining for IDS
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SHM Zarch ,irnetexplore.ac.in
Abstract-There has been much interest in applying data mining to computer network
intrusion detection system. This paper provides lessons learned in this task. Based upon our
experiences in getting started on this type of project, we suggest data mining techniques
Agents and Distributed Data Mining in Smart Space: Challenges and Perspectives
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V Gorodetsky ,ips-logistic.com
Abstract. Smart space is a distributed ambient environment with existing, inside it, dynamic
set of inhabitants (living and nonliving) solving various own and common tasks. The mission
of smart space is to provide, for its inhabitants, with context–dependent information,
EXPLOITING DATA MINING TECHNIQUES FOR IMPROVING THE EFFICIENCY OF TIME SERIES DATA USING SPSS-CLEMENTINE
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P Pujari, JB Gupta
ABSTRACT The research work in data mining has achieved a high attraction due to the
importance of its applications This paper addresses some theoretical and practical aspects
on Exploiting Data Mining Techniques for Improving the Efficiency of Time Series Data
Modulbezeichnung: Data Mining
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AV empfohlen für Module ,Modulhandbuch Praktische Informatik ,isl-s-03.htw-saarland.de
The purpose of the course is to develop a facility of learning and identifying, from scientific
and economic model outputs, the structure of the unknown functional relationship between
tuneable parameters and measured outputs in these (typically) large models. These
Application of Bioinformatics and Data Mining in Cancer Prediction
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W Mokharrak, N Al Khalaf, T Altman ,elrond.informatik.tu-freiberg.de
Abstract-Computer-aided cancer prediction and risk assessment has become a very useful
tool and is starting to be taken seriously by the medical community. Advanced bioinformatics
and data mining techniques are used extensively to assist in predicting the chances of an
Data mining techniques for design of ITS student models
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R Chaturvedi, CI Ezeife ,educationaldatamining.org
ABSTRACT An Intelligent Tutoring System (ITS) is a computer system that provides a direct
customized instruction or feedback to students while performing a task in a tutoring system
without the intervention of a human. One of the modules of an ITS system is student
Implementation Benefit to Business Intelligence using Data Mining Techniques
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H Singh
Abstract: This paper is discussing data mining techniques and business operations areas
includes marketing, finance, fraud detection, manufacturing, telecommunication to improve
their business and found excellent results. A wide range of marketing companies requires
SEQUENTIAL PATTERN MINING FROM WEB LOG DATA
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R Shettar
Abstract Sequential Pattern Mining involves applying data mining methods to large web
data repositories to extract usage patterns. The growing popularity of the World Wide Web,
many websites typically experience thousands of visitors every day.
Astronomical Images and Data Mining in the International Virtual Observatory Context
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In the past ten years, the concept of Virtual Observatory (VObs) has increasingly gained
importance in the domain of astrophysics, as a way of seamlessly accessing data in different
wavelength domains stored in digital archives. There are many reasons why the VObs is
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