data mining research papers 2012 section 4
Data Mining Techniques and Their Implementation in Blood Bank Sector–A Review
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A Bhardwaj, A Sharma, VK Shrivastava ,International Journal of , 2012
ABSTRACT This paper focuses on the data mining and the current trends associated with it.
It presents an overview of data mining system and clarifies how data mining and knowledge
discovery in databases are related both to each other and to related fields. Data Mining is
Churn Analysis of Online Social Network Users Using Data Mining Techniques
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Abstract—A churn is defined as the loss of a user in an online social network (OSN).
Detecting and analyzing user churn at an early stage helps to provide timely delivery of
retention solutions (eg, interventions, customized services, and better user interfaces) that
Closures and partial implications in educational data mining
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D Garcia-Saiz, M Zorrilla, JL Balcázar ,ICFCA 2012 International , 2012
Abstract. Educational Data Mining (EDM) is a growing field of use of data analysis
techniques. Specifically, we consider partial implications. The main problems are, first, that a
support threshold is absolutely necessary but setting it right is extremely difficult; and,
Application of Data Mining on the Development of a Disease Distribution Map of Screened Community Residents of Taipei County in Taiwan
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CK Wei, S Su, MC Yang ,Journal of medical systems, 2012 ,Springer
Abstract This study used data mining techniques to investigate disease forms in various
administrative areas and to analyze the differences among various administrative areas in
order to further draw up a disease distribution map. It is hoped that may help formulate
ELF-Miner: using structural knowledge and data mining methods to detect new (Linux) malicious executables
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Abstract Linux malware can pose a significant threat—its (Linux) penetration is exponentially
increasing—because little is known or understood about Linux OS vulnerabilities. We
believe that now is the right time to devise non-signature based zero-day (previously
Quantitative Assessment of Estimation Approaches for Mining over Incomplete Data in Complex Biomedical Spaces: A Case Study on Cerebral Aneurysms
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In this paper an approach to approximate missing data items is presented, which enables data
mining processes to be applied on a larger data set. 1 Introduction Data mining is often being
applied to uncover hidden patterns in vast amounts of data, and for decision support.
A Trend Based Similarity Calculation Approach for Mining Time Series Data
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Y Yang, Y Xia, F Ge, Y Meng, H Yu ,Proceedings of the International , 2012
2006. Characteristic-Based Clustering for Time Series Data. Journal on Data Mining and
Knowledge Discovery, vol. 13, no. 3, pp. 335-364. ACM Proceedings of the tenth ACM SIGKDD
international conference on Knowledge discovery and data mining, pp. 49-58.
Transition in Time Series Data Mining on Correlated Items
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D Sujatha, P Chandra ,International Journal of , 2012
ABSTRACT We are given a large database of customer transactions, where each
transaction consists of transaction-id, the items bought in the transaction and the transaction
time. The whole set of transaction is divided into a number of segments called durations (
Analysis of Spatial Data Mining and Global Autocorrelation
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BK Kumar, GM Yadav ,International Journal, 2012
Abstract—In this paper is to study of the spatial distribution of regional per capita agricultural
total output value in Beijing rural regions of 2005 using exploratory spatial data analysis
method of spatial data mining highlights the importance of spatial interactions and
Data Mining Classifiers for Static Security Evaluation in Power System
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IS Saeh, MW Mustafa ,2012
The process of building binary class classifiers is divided into two components:(i)
comparison the methods, and (ii) selection of the best classifier. Preliminary results of using
eleven algorithms of Decision Tree’s classifiers (DTC) for SSA are presented. A
Data Mining in Cloud Computing
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B Ambulkar, V Borkar ,IJCA Proceedings on National , 2012
ABSTRACT This paper deals with the study of how data mining is used in cloud computing..
Data Mining is a process of extracting potentially useful information from raw data. How
SaaS is very useful in cloud computing. The integration of data mining techniques into
Data Mining Applied to Horse Thermal Comfort
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J Sarubbi, SRM Oliveira, PR Griska, DJ Moura ,2012 ,cigr.ageng2012.org
Abstract. Thermal comfort plays a critical role in body temperature regulation. Heat-
regulation mechanisms, such as changes in peripheral blood flow, are activated by thermal
stress to maintain body homeostasis and it can results in a fluctuation of skin temperature.
INTERNATIONAL JOURNAL OF ENGINEERING SCIENCESMANAGEMENT DATA MINING: INTRODUCTION, PROCESS, APPLICATION AND SURVEY
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P Sahu, A Khan ,Int. J. of Engg. Sci.Mgmt.(IJESM), 2012 ,ijesmjournal.com
Abstract Data mining, a branch of 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
is the process of extracting patterns from
large data sets by combining methods from statistics and artificial intelligence with database
management. Data mining is seen as an increasingly important tool by modern business
Data Mining in Blood Platelets Transfusion using Classification Rule
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DJ Chaudhari, M Ramteke ,IJCA Proceedings on , 2012
ABSTRACT Data mining provides automatic pattern recognition and attempts to uncover
patterns in data that are difficult to detect with traditional statistical methods. Data mining
(sometimes called data or knowledge discovery) is the process of analyzing data from
Realizing Targeted Advertising in Digital Signage with AVA and Data Mining
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P Tian, AV Sanjay, S Malik, K Chiranjeevi , on Engineers and , 2012
Abstract—How to realize targeted advertising in digital signage is an interesting question.
This paper proposed an Intelligent Advertising Framework (IAF), which pioneers the
integration of Anonymous Video Analytics (AVA) and Data Mining technologies to achieve
Text Data Mining of the Electronic Medical Record of the Chronic Hepatitis Patient
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M Kushima, K Araki, M Suzuki, S Araki ,Proceedings of the , 2012
Abstract—This research used a text data mining technique to extract useful information from
nursing records within Electronic Medical Records. Although nursing and passage records
provide a complete account of a patient’s information, they are not being fully utilized.
Security Measures in Data Mining
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A Gupta, V Bibhu, R Hussain ,International Journal of Information , 2012
Abstract—Data mining is a technique to dig the data from the large databases for analysis
and executive decision making. Security aspect is one of the measure requirement for data
mining applications. In this paper we present security requirement measures for the data
Integration of data mining within a Strategic Knowledge Management framework
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S Moayer, S Gardner ,Integration, 2012
Abstract—In today’s globally interconnected economy, knowledge is recognised as a
valuable intangible asset and source of competitive advantage for firms operating in both
established and emerging industries. Within these contexts Knowledge Management (KM)
Database Mining: Bringing Algorithms to Data
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MD Thomas, H Zhang ,memory, 2012 ,wweb.uta.edu
Data Mining and DW • Database Mining – Overview – Spectrum • Database Mining Architectures –
Performance comparison • Association Mining Using SQL-92 and SQL-OR – Approaches –
optimization – Performance comparison • Summary and Challenges Data Mining
Applications of Data Mining in Higher Education
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M Goyal, R Vohra ,2012
Abstract Data analysis plays an important role for decision support irrespective of type of
industry like any manufacturing unit and educations system. There are many domains in
which data mining techniques plays an important role. This paper proposes the use of
Securing advanced metering infrastructure using intrusion detection system with data stream mining
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AMI. From our result and analysis, it shows stream data mining technique shows
promising potential for solving security issues in AMI. cumbersome. In this paper,
we choose to employ anomaly-based IDS using data mining.
A study on the modified attribute oriented induction algorithm of mining the multi-value attribute data
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SM Huang, PY Hsu, WC Wang ,Intelligent Information and Database , 2012 ,Springer
Abstract. Attribute Oriented Induction method (short for AOI)is one of the most
important methods of data mining. 1 Introduction Data mining extracts implicit,
previously unknown and potentially useful information from databases.
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