Data Mining Research Papers 2012 Ieee

data mining research papers 2012-116

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data mining research papers 2012-116




Criteria Formation of Effective High-School Graduates Employment Based upon Data MiningMethods
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I Bolodurina, Y Akhmayzyanova ABSTRACT. This work is devoted to the investigation of the main factors influencing high-school graduates employment. This investigation is conducted using Data Mining methods. Two approaches to the identification of hidden patterns in data are employed. The first method

Fast Locality Sensitive Hashing Algorithm For Approximate Nearest Neighbor Search: A Practical Data Mining Approach
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A large amount of satellite images with high dimensionality and complexity is being collected, processed and stored periodically by the National Geophysical Data Center (NGDC) in collaboration with National Oceanic and Atmospheric Administration (NOAA).

Classification Algorithms for Data Mining: A Survey
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ABSTRACT Classification is a model finding process that is used for portioning the data into different classes according to some constrains. In other words we can say that classification is process of generalizing the data according to different instances. Several major kinds of

The fuzzy data mining generalized association rules for quantitative values
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TP Hong, KY Lin ,140.127.198.19 ABSTRACT Due to the increasing use of very large databases and data warehouses, mining useful information and helpful knowledge from transactions is evolving into an important research area. Most conventional data-mining algorithms identify the relationships among

Application of Data Mining Techniques for Analyzing Violent Criminal Behavior by Simulation Model
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KZ Hussain, M Durairaj, GRJ Farzana ABSTRACT Crime is a major issue where the top priority has given by our government. Criminology is an area that focuses the scientific study of crime and criminal behavior and law enforcement and is a process that aims to identify crime characteristics. It is one of the

Phishing Attack Detection, Classification and Proactive Prevention using Fuzzy Logic and Data Mining Algorithm
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RJ Ferolin, CU Kang ,20 ABSTRACT. This paper presents a design for removing phishing sites or phishing pages that are hosted probably without the knowledge of the website owner or host server. Initially the system assesses and classifies phishing emails using Fuzzy Logic and the RIPPER Data

MineTool-M 2: An Algorithm for Data Mining of 2D Simulation Data
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TB Sipes, H Karimabadi ,elrond.informatik.tu-freiberg.de ABSTRACT Extraction of knowledge from massive and complex data sets generated from peta-scale simulations poses a major obstacle to scientific progress. We propose a new approach to solving this problem by utilizing an innovative feature extraction technique in

Application of Data mining algorithms for Customer Classification
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N Patil, R Lathi ,dypimca.org (Information Technology), human-beings are entering into the information era, in which we are in dire need of some new tools and technologies to deal with such mass data. Data mining is the useful tool to discovering the knowledge from large data. For this we require

ORANGE: DATA MINING FRUITFUL AND FUN
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is a general-purpose machine learning and data mining tool. It features a multilayer architecture suitable for different kinds of users, from inexperienced data mining beginners to programmers who prefer to access the tool

Advanced Data Mining Methods for Environmental Crisis Prediction
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Abstract. In this paper we explore how the data-intensive processes can be applied to benefit the experts who produce daily weather predictions, as well as rarely needed, but crucial and often time-critical risk assessments for emerging environmentally significant

Survey of Data Mining Techniques on Crime Data
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R Krishnamurthy, JS Kumar ,iirpublications.com ABSTRACT There has been an enormous increase in the crime is the recent past. Crime deterrence has become an upheaval task. In this paper, we give comprehensive surveys of efficient and effective methods/techniques on data mining for crime data analysis. It is

A generalized Framework of Privacy Preservation in Distributed Data mining for Unstructured Data Environment
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ABSTRACT The management of unstructured data is recognized as one of the major unsolved problems in the information industry and data mining paradigm. Unstructured data in computerized information that either does not have a data model and there are not easily

Efficient Clustering Technique for Information Retrieval in Data Mining
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ABSTRACT In the emerging new wave of applications where people are the ultimate target of text clustering methods, cluster labels are intended to be read and comprehended by humans. The primary objective of a clustering method should be to focus on providing

Applications of Data Mining Techniques in Life Insurance
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AB Devale, RV Kulkarni ,International Journal ABSTRACT Knowledge discovery in financial organization have been built and operated mainly to support decision making using knowledge as strategic factor. In this paper, we investigate the use of various data mining techniques for knowledge discovery in

Novel Class Detection in Concept-Drifting Data Stream Mining Employing Decision Tree
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 Most existing data mining classifiers can not detect and classify the novel class instances in real-time data stream mining problems like weather conditions, economical changes, astronomical, and intrusion detection etc, untill the classification models are trained with the labeled

Mining Unstructured Data from Web Using Soft Computing
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MSA Deshpande, PR Deshmukh ,International Journal  For a given user s query the search engine searches in the local database and very quickly displays the results. The huge amount of information is retrieved using data mining tools. Classification, Clustering and Association tools etc. are used for data mining technique.

PREDICTION OF BREAST CANCER USING DATA MINING
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ABSTRACT Breast Cancer prediction and diagnosis are two medical applications pose a great challenge to the researchers. Today, about one in eight women over their lifetime have been affected by breast cancer in the United States. Recently the occurrence rate of breast

Issues in Data Mining and Information Retrieval
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ABSTRACT Data mining, as we use the term, is the exploration and analysis of large quantities of data in order to discover meaningful patterns and rules. For the purposes of this book, we assume that the goal of data mining is to allow a corporation to improve its

Research on Data Mining Using Neural Networks
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K Amarendra, KV Lakshmi, KV Ramani ABSTRACT The application of neural networks in the data mining has become wider. Data mining is the search for relationships and global patterns that exist in large databases but arehidden among the vast amount of data, such as a relationship between patient data

Image-Based Campus Positioning System With Data Mining Techniques
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Abstract One of the major data mining applications is mining image data. We want to implement a data mining model to specifically identifying photos taken on Columbia main campus and thus determining the location it is taken as well as its view direction. This

Use of Data Mining Techniques for the Evaluation of Student Performance: A Case Study
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ABSTRACT Data and Information or Knowledge has a significant role on human activities. Data mining is the knowledge discovery process by analyzing the large volumes of data from various perspectives and summarizing it into useful information. Due to the

Assistive Design and Production in Computer Games: Parametric Systems, Data Mining, Visual Analytic
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In this report, we will explain our ongoing work developing assistive user research tools for design and production of a social game named HARDWARE. This game is under development by Blackbird Interactive, social gaming company, with a summer launch date

Fuzzy Genetic Data Mining for Customer Buying Patterns using K-Means Clustering
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ABSTRACT Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. Most conventional data-mining algorithms identify the relationships among transactions using binary values. Transactions

A Survey of Data Mining Techniques for Quality Improvement in Process Industries
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ABSTRACT This paper presents a survey of quality improvement of various products in process industries and present how data mining can be used in manufacturing for improving the quality, maintenance, control and production of a product.

A Review of Application of Data Mining in Earthquake Prediction
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GV Otari, RV Kulkarni ABSTRACT A natural disaster is the effect of a natural hazard (eg, flood, tornado, hurricane, volcanic eruption, earthquake, heatwave, or landslide). Earthquakes, landslides, tsunamis and volcanos are complex physical phenomenon that leads to financial, environmental or

Data mining Application to Design a System for Performance Improvisation of Students in Their Academic Studies
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ABSTRACT This paper presents a system that can be used for a performance improvisation of students in their academic studies. The system accumulates a vast amount of information which is very valuable for analyzing the student s performance and could create a gold

Data Mining Method for Energy System Aplications
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R Selbas, A Sencan, EU Kksille ,cdn.intechopen.com In recent years, data storage capacity of computers increased as well as their speeds. With these advances in the technology, millions of data can be recorded in computer memories. These data can be used for a better service to customers by companies. For example,

Towards Judicial Data Mining: Arguing for Adoption in the Judicial System
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The Judicial System collects huge amounts of data which, unfortunately, are not turned into useful information for effective decision making. Decision support system can now use advanced technologies such as On-line analytical processing and data mining to deliver

IMPLEMENTATION OF DATA MINING IN BANKING SECTOR-A FEASIBILITY STUDY
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V Bhambri ,mairec.org ABSTRACT Banking sector around the globe is using information technology for their day to day operations and banks have realized this fact that their biggest asset is the knowledge and not the financial resources. Banks have started using the latest techniques of data

Data Mining on Moving Object Trajectories
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ABSTRACT Trajectory means a path followed by a moving vehicles or object. Spatio temporal clustering is a process of grouping objects based on their spatial or temporal similarity. It is also known as Trajectory or mobility data. Existing work have mainly focused on moving

CHALLENGES IN HANDLING UNCERTAINTY IN DATA MINING RESEARCH
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A Kajal, I Kajal ABSTRACT The digital information is growing so rapidly in organizations, due to which it s very tedious process to examine some useful information. For this, firstly we classify the explosive growth of information in some pattern, rules etc. which represent useful data. The main

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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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