data mining research papers 2012 section 8





Comparative Study on Email Spam Classifier using Data Mining Techniques
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Abstract—In this e-world, most of the transactions and business is taking place through e-
mails. Nowadays, email becomes a powerful tool for communication as it saves a lot of time
and cost. But, due to social networks and advertisers, most of the emails contain unwanted 

A Framework for Evaluating the Smoothness of Data-Mining Results
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The data-mining literature is rich in problems that are formalized as combinatorial-
optimization problems. An indicative example is the entity-selection formulation that has
been used to model the problem of selecting a subset of representative reviews from a 

 A data mining E-learning tool: description and case study
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F Maiorana, A Mongioj, M Vaccalluzzo ,Proceedings of the World , 2012
Abstract—Data analysis and data mining techniques are recognized as important disciplines
that deliver ‘sophisticated domain knowledge’. The Association of Computing Machinery
(ACM) and the IEEE-Computer Society suggest in the 2013 draft Computer Science 

 Role and Applications of Genetic Algorithm in Data Mining
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G Verma, V Verma ,International Journal of Computer , 2012
ABSTRACT Data mining has as goal to extract knowledge from large databases. To extract
this knowledge, a database may be considered as a large search space, and a mining
algorithm as a search strategy. In general, a search space consists of an enormous 

 Detection and summarization of genuine review using Visual Data Mining
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ABSTRACT In earlier days we were asking our friends or relatives for their opinions
regarding products which we want to purchase from the merchants. But now a day’s E-
commerce is gaining more and more popularity. Whatever query we are having, we can 

 Spam Mail Filtering Technique using Different Decision Tree Classifiers through Data MiningApproach-A Comparative Performance Analysis
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S Chakraborty, B Mondal ,International Journal of Computer , 2012
ABSTRACT In recent years the highestdegree of communication happens through e-mails
which are often affected by passive or active attacks. Effective spam filtering measures are
the timely requirement to handle such attacks. Many efficient spam filters are available 

 NETWORK INTRUSION DETECTION USING DATA MINING AND NETWORK BEHAVIOUR ANALYSIS
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A Youssef, A Emam ,International Journal of Computer Science, 2012
ABSTRACT Intrusion detection has become a critical component of network administration
due to the vast number of attacks persistently threaten our computers. Traditional intrusion
detection systems are limited and do not provide a complete solution for the problem. 

 Effective Data Mining Through Neural Network
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SPS Dhande ,International Journal, 2012
Abstract:-With the continuous development of database technology and the extensive
applications of database management system, the data volume stored in database
increases rapidly and in the large amounts of data much important information is hidden. If 

 A Data Mining Framework for Prevention and Detection of Financial Statement Fraud
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R Gupta, NS Gill ,International Journal of Computer , 2012
ABSTRACT Financial statement fraud has reached the epidemic proportion globally.
Recently, financial statement fraud has dominated the corporate news causing debacle at
number of companies worldwide. In the wake of failure of many organisations, there is a 

 MINING CLOSED FREQUENT INTERVALS FROM INTERVAL DATA
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AK Mahanta, M Dutta ,International Journal of Applied, 2012
 MINING CLOSED FREQUENT INTERVALS FROM INTERVAL
DATA Anjana K. Mahanta1 and Mala Dutta2 Abstract: Interval data is widely encountered
in several areas of data mining applications. In the context 

Efficient Sampling and Handling of Variance in Tuning Data Mining Models
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P Koch, W Konen ,Parallel Problem Solving from Nature-PPSN XII, 2012 ,Springer
Computational Intelligence (CI) provides good and robust working solutions for global
optimization. CI is especially suited for solving difficult tasks in parameter optimization when
the fitness function is noisy. Such situations and fitness landscapes frequently arise in real 

 Data mining by means of generalized patterns
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L Cagliero, E Baralis ,2012 ,dbdmg.polito.it
The data mining and knowledge discovery (KDD) process accomplishes the task of
converting the raw data into useful information [107]. The core part of data mining process
entails the application of predictive or descriptive techniques to analyze the data of 

 A Composite Strategy for the Legal and Ethical Use of Data Mining
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D Payne, BJL Landry , Journal of Management, Knowledge and Learning, 2012 ,issbs.si
An increasingly popular business practice, data mining provides for the extraction of
information from existing data to identify trends such as consumer purchasing practices and
can foster greater efficiency in companies’ marketing efforts. There are corresponding 

 An Efficient Randomization Algorithm for Privacy Preserving Data Mining
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WT Chembian, J Janet ,European , 2012 ,europeanjournalofscientificresearch.
Abstract Managing Huge volume of personal data and sharing of these data is proved to be
beneficial for data mining application. Privacy-preserving data mining (PPDM) is one of the
newest trends in privacy and security research. In many cases, users are unwilling to 

 Two Stage Data Mining Technique for Fast Monsoon Onset Prediction
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D John, KK Sindhu, BB Meshram ,International Journal, 2012
Abstract—The onset of monsoon is eagerly awaited in the Indian sub-continent as it has
deep impact in the economic and social domain and hence has been monitored and studied
in great depth. With the advent of satellite imagery, it’s now possible to monitor the 

 A Semantic Model for Multimodal Data Mining in Healthcare Information Systems
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Abstract. Electronic health records (EHRs) are representative examples of multimodal/
multisource data collections; including measurements, images and free texts. The diversity
of such information sources and the increasing amounts of medical data produced by 

 Comparing accuracy in predicting stock returns between using regression techniques anddata mining approach
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S Kazemian, S Kazemian ,African Journal of Business , 2012
Size and volatility of the stock price of companies listed on the stock exchange is one of the
most important factors influencing the financial markets. Predicting the influencing factors
such as price and stock returns in the stock market is essential to the large number of 

 An Overview of Mining Frequent Itemsets Over Data Streams Using Sliding Window Model
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K Jothimani, AS Thanamani ,International Journal, 2012 ,ijettcs.org
 [7] J. Cheng, Y. Ke,W. Ng, Maintaining frequent itemsets over high-speed data streams, Proc.
10th Pacific-Asia Conf. on Knowledge Discovery and Data Mining, Singapore, 2006,
pp.462–467. Page 4.  6th IEEE Conf. on Data Mining, Hong Kong, China, 2006, pp. 928–932. 

 The Effect of Data Mining Based on Association Rules in Strategic Management
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M Rasaulian, A Saeed ,J. Basic. Appl. Sci. Res, 2012
ABSTRACT Strategic planning in the organizations asks for high consideration in required
data mining. The challenge with which the strategists confront is the interchangeable nature
of the data. Applying data mining is a suitable mean for managers.

 Conceptual Mapping of Insurance Risk Management to Data Mining
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D Singh, P Kumar ,International Journal of Computer , 2012
ABSTRACT Insurance industry contributes largely to the economy therefore risk
management in this industry is very much necessary. In the insurance parlance, the risk
management is a tool identifying business opportunities to design and modify the 

 From Exemplar Extraction to Network Visualization for Relational Data Mining
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F Blanchard, M Herbin ,2012 ,hal.inria.fr
The data mining is interested in discovering knowledge from data. Nowadays finding
interesting patterns or structures is a crucial task in the field of data analysis. This paper
addresses the problem of the extraction of representative elements from a dataset. This 

 A Teaching Experience on a Data Mining Module
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F Maiorana, CVA Doria , of Information Systems EducationCurricula , 2012 ,fedcsis.org
Abstract—Data mining is recognized as an important field where one has the possibility to
become accustomed both with analysis techniques and methods and with a state of mind.
By means of data mining it is possible to develop critical skills that are essential in today’s 

 Customer Behavior Analysis using CBA (Data Mining Approach)
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KV Nagendra, C Rajendra ,National Conference on Research trends in , 2012 ,ijecce.org
Abstract-With the rampant competition in the domestic and international business, the
Customer Relationship Management (CRM) has become one of matters of concern to the
enterprise. CRM takes the customers as the center, it gives a new life to the enterprise 

 A Hybrid PSO with Dynamic Inertia Weight and GA Approach for Discovering Classification Rule in Data Mining
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SM Uma, KR Gandhi, E Kirubakaran , Journal of Computer , 2012
ABSTRACT Data Mining is the efficient knowledge discovery form database. It is also form of
knowledge discovery essential for solving problem in specific domain like health care,
business and other field. The proposed system is based on population based on heuristic 

 Mining Regular Patterns in Data Streams Using Vertical Format
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GV Kumar, M Sreedevi, NVSP Kumar ,International Journal of , 2012 ,174.142.16.66
 Discovering knowledge in data streams is an important research area in data mining
and knowledge discovery process. Mining Frequent patterns [4, 5] from static
databases has been broadly studied in Stream data mining [1 

 An Approach to mining massive Data
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R Bharathi, NN Keswani ,IJCA Proceedings on , 2012
 Big Data is generated by number of sources like Social Networking and Media, Mobile Devices,
Internet Transactions, Networked Devices and Sensors Data mining is the process of extracting
interesting, non- trivial, implicit, previously unknown and potentially useful patterns or 

 Compact Tree for Associative Classification of Data Stream Mining
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KP Lakshmi, CRK Reddy ,2012
 In recent years, data streams have become ubiquitous because of the large number of applications
which generate huge volumes of data in an automated way [2]. Many existing data mining methods
cannot be applied directly on data streams because of the fact that, the data 



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