data mining research papers 2012-106





An Effective Retrieval of Medical Records using Data Mining Techniques
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T Sakthimurugan, S Poonkuzhali ,rspublication.com
ABSTRACT Nowadays, the standard of healthcare domain mainly depends on in the
delivery of modern healthcare and efficiency of healthcare systems. Due to time and cost
constraints, most of the people rely on health care systems to obtain healthcare services. 

 AGENT BASED META LEARNING IN DISTRIBUTED DATA MINING SYSTEM
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SK Sen, S Dash, SP Pattanayak
ABSTRACT The data mining technology is used to identifying patterns and information from
a huge quantity of data. In a single repository data base where data is stored in central site,
then applying data mining algorithms on these data base, patterns are extracted, which is 

 FUZZY CLUSTERING ANALYSIS OF DATA MINING: APPLICATION TO AN ACCIDENT MINING SYSTEM
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Abstract. This paper is concerned with the application of data transforms and fuzzy clustering
to extract useful data. It is possible to distinguish similar information which includes selector
and removes clusters of less importance with respect to describing the data. Clustering 

 Design a Secure Multiparty Computation System for Privacy Preserving Data Mining
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R Sugumar, C Jayakumar, A Rengarajan ,ijcst.org
Abstract–Privacy-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. The aim of a secure multiparty computation task is for the 

 Intrusion Detection System Using Data Mining
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ARVPS Desai, PR Bhaladhare
Abstract—Intrusion Detection Systems (IDSs) have become an efficient defense tool against
network attacks since they allow network administrator to detect policy violations. However,
traditional IDs are vulnerable to original and novel malicious attacks. Also, it is very 

 Using Data Mining Techniques in Macroeconomic Analysis on Romania’s Case
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S STANCU, B MIRCEA, AM CONSTANTIN
Abstract: In the present data mining techniques are the most utilized methods of calculus in
discovering existent relations between different components, objects, phenomenon, etc.
Economic analysis must be achieved by the most advanced methods of calculus, so that 

 Integrating Grey Theory into Kano’s QFD Based on Data Mining to Enhance Supply Market Survey with Purchasing
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CH HSU, ANY CHANG, HUIM KUO ,wseas.org
Abstract:-Supply Market survey, which contain hard to find market survey information,
including market value, market volume, competitor analysis and market forecasts. These
information will enable purchaser to understand the key market drivers within the supplies 

 Comparison of K-means and Backpropagation Data Mining Algorithms
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N Mathuriya, A Bansal ,International Journal ,ijctee.org
Abstract—Data mining has got more and more mature as a field of basic research in
Modern heuristic techniques for combinatorial problems. Advanced topics in computer science
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Decision Tree and Ensemble Learning Based on Ant Colony Optimization Google Books Result Modern heuristic techniques for combinatorial problems . Faculty library sciences Series: Advanced topics in computer science series; Alternative call (PDF) Modern Heuristic Search Methods

Software Agents Michael R. Genesereth Logic Group Computer Science Department Stanford University
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The software world is one of great richness and diversity. Many thousands of software products are available to users today, providing a wide variety of information and services in a wide variety of domains. While most of these programs provide their users with significant Classical complexity theory analyzes and classifies problems by the amount of a resource, usually time or space, that is required by algorithms solving them. It was a fundamental idea, going back to the work of Hartmanis and Stearns in the early 1960s, to measure the required

The combinatorics of network reliability, International Series of Monographs on Computer Science
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This book develops combinatorial tools which are useful for reliability analysis, as demonstrated with a probabilistic network model. Basic results in combinatorial enumeration are reviewed, along with classical theorems on connectivity and cutsets. More developed

Languages and machines: an introduction to the theory of computer science
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Languages and machines : an introduction to the theory of computer . Theory of Computing 2015/2016 (FUB MSc in Computer Science ) Languages and Machines, which is intended for computer scientists in the theoretical foundations of their subject, gives a mathematically sound In the late 1960s and early 1970s, the concepts of graph transformation and graph grammars started to become of interest in picture processing and computer science . The main idea was to generalize well-known rewriting techniques from strings and trees to Parsing is the process of structuring a linear representation in accordance with a given grammar. This definition has been kept abstract on purpose to allow as wide an interpretation as possible. The linear representation may be a sentence, a computer

The Cambridge distributed computing system. International computer science series
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The Development of Component-based Information Systems Google Books Result The Cambridge Distributed Computing System is an early discontinued distributed operating system, . (International computer science series) Bibliography: p. The 100 Best Computer Science Programs in the

Logic and the challenge of computer science
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Nowadays computer science is surpassing mathematics as the primary field of logic applications, but logic is not tuned properly to the new role. In particular, classical logic is preoccupied mostly with infinite static structures whereas many objects of interest in

Computer science unplugged
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For kids ages 7 to 14: This educational 50 minute show is an action-packed, zany time exploring neat ideas in computer science . It has been performed for over 20 years in classrooms, science museums, science festivals, and at educational events. Kids, and the

The Profession of IT, Is Computer Science Science
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COMMUNICATIONS OF THE ACM draw on the same fundamental principles. In 1989, we used the term computing instead of computer science , mathematics, and engineering. Today, computing science, engineering, mathematics, art

Discrete mathematical structures with applications to computer science
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The objectives of the course are: To develop Professional Skills through effective communication To introduce a number of Mathematical Foundation to be serving as tools even today in the development of theoretical computer science To gain some confidence on

Bringing computational thinking to K-12: what is Involved and what is the role of the computer science education community
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When Jeanette Wing [13] launched a discussion regarding the role of computational thinking across all disciplines, she ignited a profound engagement with the core questions of what computer science is and what it might contribute to solving problems across the

Modern DC-to-DC Switchmode Power Converter Circuits (Van Nostrand Reinhold Electrical/ Computer Science and Engineering Series)
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As each area of technology with a potential for significantly impacting any major segment of the electronics industry evolves, it often is accompanied by the development of a succession of new circuits. Each new circuit indeed appears different, employing different components

Information technology research: A practical guide for computer science and informatics
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Information Technology Research: A Practical Guide for Computer

Scientific methods in computer science
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ABSTRACT This paper analyzes scientific aspects of Computer Science . First it defines science and scientific method in

Active learning and its use in computer science
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Student learning and the depth of the students knowledge increase when active learning methods are employed in the classroom. Active learning strategies are discussed in general computer science course work and as used in a theory of computation course. Difficulties

Why the high attrition rate for computer science students: some thoughts and observations
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1. Introduction At our university, there are over four hundred declared majors in Computer Science . Each semester, however, only about fifteen to twenty students graduate in this field. The freshman courses comprise overflowing multiple sections, but the upper level courses make

Form and content in computer science
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The trouble with computer science today is an obsessive concern with form instead of content. No, that is the wrong way to begin. By any previous standard the vitality of computer science is enormous; what other intellectual area ever advanced so far in twenty years

Why women avoid computer science
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COMMUNICATIONS OF THE ACM did these numbers drop, and why more sharply for women than for men For men, the explanation is obvious. Traditional paths to wealth like law, medicine, and business are more certain, and over the
and got more and more widely applied in several other fields. Data mining
has been recognized by many researchers as a key research topic in data handling. Data 

 Redescription Mining With Three Primary Data Mining Functionalities
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MK Kumari, S Varma ,International Journal of Computer Science
Abstract Describing an object in two ways or shifting the vocabulary of the same concept is
Redescription. Not a new problem, Redescription Mining premise had resulted the subsets
of objects that afford multiple definitions, in a given Universal set of the same, and a 

 Identifying and Resolving Higher Educational Problems using Data Mining
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T Arjariya, VK Chaudhari, R Shrivastava, D Varshney
Abstract—The objective of the present paper is advancement of knowledge and theoretical
understanding of the relations among variables for the study and development using data
mining in higher education system and its solution for Madhya Pradesh state. New 

 DISTRI% LSITED DATA MINING-AN APPLICATION FOR THE WT
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AR MIKLER, JT Mares ,cse.unsw.edu.au
Abstract The task ofanaiyzing large volnines ofinforrnation with the goal to find patterns or
relationships that can be exploited in decision processes is referred to as tiara rnining. Given
that the data to be rained is located at remote sites, this process will tax both, the 

 Spatial and Temporal Geovisualisation and Data Mining of Road Traffic Accidents in Christchurch, New Zealand
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Abstract This paper outlines the development of a method for using Kernel Estimation cluster
analysis techniques to automatically identify road traffic accident ‘black spots’ and ‘black
areas’. A Novel data-mining approach has been developed–adding to the generic 

 Use of Data Mining Systems as an Enhancement of Digital Libraries
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P Miocic, S Špiranec ,BOBCATSSS 2012 20th , 2012 ,jessicaemilymoyer.pbworks.com
Abstract: Data mining is one of the fundamental terms in the field of knowledge and
information management as well as in knowledge organization. That process is the
foundation of many databases, and lately, many digital libraries as well. One specific data 

 Algorithms and Measures in Sequence Data Mining
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I RAILEAN, P LENCA, S MOGA, M BORDA ,departements.telecom-bretagne.eu
Sequential pattern mining, first introduced in [1], is one of the most challenging problems in
data mining [3]. It aims to extract the relationships between occurrences of sequential
itemsets ie to look for any specific order of the itemsets. Sequential pattern mining has 

 A BODY SENSOR NETWORK DATA REPOSITORY WITH A DIFFERENT MINING TECHNIQUE
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MC Suman, K Prathyusha
 One major obstacle is managing repositories that store the large amount of sensing
data. To address this issue, we propose a data mining approach inspired by the
experience in the areas of text and natural language processing. 

 APPLICATIONS AND ISSUES OF DATA MINING
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R Hooda, NS Gill ,mairec.org
ABSTRACT Data mining is a technique of data warehousing and is employed to extract
important information or knowledge that may possibly be unknown otherwise. It offers a
support to take appropriate decisions on certain facts and alternatives. There are various 

 Book Recommendation System using Data Mining for the University of Hong Kong Libraries
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S Rajagopal, A Kwan ,ejournal.wp.cite.hku.hk
This paper describes the theoretical design of a Library Recommendation System,
employing kmeans clustering Data Mining algorithm, with subject headings of borrowed
items as the basis for generating pertinent recommendations. Sample data from the 

 Analysis of Attribute Association in Heart Disease Using Data Mining Techniques
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K Srinivas, GR Rao, A Govardhan
Abstract In data mining association rule mining represents a promising technique to find
hidden patterns in large data bases. The main issue about mining association rules in a
medical data is the large number of rules that are discovered, most of which are irrelevant. 

 A Classification of Spirometric Pattern and Modeling Using Statistical Data Mining
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MPD Junwale, AW Bhade, PN Chatur ,ijetae.com
Abstract—Respiratory disease is a medical term that encompasses pathological conditions
affecting the organs and tissues. A lungs disease affects health condition of many people.
Lungs diseases can be curable in early detection. Spirometry is valuable for diagnosing 

 Privacy by design in data mining
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Today, we are able to discover and store increasing amounts of detailed data on human
activities: automated payment systems record our purchases; search engines record logs of
our queries on the Internet; mobile devices record the trajectories of our movements; and 

 CLASSIFICATION PROBLEM IN DATA MINING-BY USING DECISION TREES
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V CHAHAR, N KANDHIL, DRA KUMAR
Abstract The aim of this paper is to present the classification problem in data mining using
decision trees. Simply stated, data mining refers to extracting or mining knowledge from
large amounts of data. Data mining known by different names as–knowledge mining, 

 Data Mining Tasks Performed By Temporal Sequential Pattern
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VS Suntharam ,ijrct.org
Abstract Temporal Data Mining is a rapidly evolving area of research that is at the
intersection of several disciplines, including statistics, temporal pattern recognition, temporal
databases, optimization, visualization, high-performance computing, and parallel 

 Using Instructive Data Mining Methods to Revise the Impact of Virtual Classroom in E-Learning
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MF AlAjmi, S Khan, AS Zamani
Abstract In the past few years, Saudi universities have boarded to utilize e-learning tools and
technologies to expand and look up their educational services. After a few years of carrying
out e-learning programs, a discussion took place within the directors, supervisors, 

 The Study on Privacy Preserving Data Mining for Information Security
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L Xiaohui ,Proc. of SPIE Vol ,spiedl.org
ABSTRACT Privacy preserving data mining have a rapid development in a short year. But it
still faces many challenges in the future. Firstly, the level of privacy has different definitions in
different filed. Therefore, the measure of privacy preserving data mining technology 

 DATA MINING TYPES AND TECHNIQUES: A SURVEY
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S Anand, RR Aggarwal ,mairec.org
ABSTRACT The quantity of data kept in computer files and databases is growing at an
exceptional rate. More refine information from these data is expected. Simple structured or
query language queries are no more sufficient to support the increasing demands for 



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