Data mining : (Record no. 19468)

MARC details
000 -LEADER
fixed length control field 06904cam a2200733Ii 4500
001 - CONTROL NUMBER
control field ocn761318489
003 - CONTROL NUMBER IDENTIFIER
control field OCoLC
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20230823095433.0
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS--GENERAL INFORMATION
fixed length control field m o d
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr cn|||||||||
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 111117s2011 njua ob 001 0 eng d
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2011002190
040 ## - CATALOGING SOURCE
Original cataloging agency DG1
Language of cataloging eng
Description conventions rda
-- pn
Transcribing agency DG1
Modifying agency YDXCP
-- N$T
-- IEEEE
-- ZMC
-- OCLCQ
-- COO
-- DEBSZ
-- AFU
-- OCLCA
-- FTU
-- CDX
-- AZU
-- E7B
-- UIU
-- REDDC
-- A7U
-- OCLCF
-- EBLCP
-- NNO
-- OCLCQ
-- NLGGC
-- MNU
019 ## -
-- 748937827
-- 752380865
-- 764717811
-- 796754453
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781118029145
Qualifying information (oBook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1118029143
Qualifying information (oBook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781118029121
Qualifying information (ePDF)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1118029127
Qualifying information (ePDF)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781118029138
Qualifying information (ePub)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1118029135
Qualifying information (ePub)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Cancelled/invalid ISBN 9780470890455
Qualifying information (cloth)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Cancelled/invalid ISBN 0470890452
Qualifying information (cloth)
024 8# - OTHER STANDARD IDENTIFIER
Standard number or code 9786613239747
029 1# - (OCLC)
OCLC library identifier AU@
System control number 000049649519
029 1# - (OCLC)
OCLC library identifier AU@
System control number 000051473113
029 1# - (OCLC)
OCLC library identifier CHNEW
System control number 000722280
029 1# - (OCLC)
OCLC library identifier DEBSZ
System control number 372810292
029 1# - (OCLC)
OCLC library identifier DEBSZ
System control number 377432350
029 1# - (OCLC)
OCLC library identifier DEBSZ
System control number 396995837
029 1# - (OCLC)
OCLC library identifier DEBSZ
System control number 425883833
029 1# - (OCLC)
OCLC library identifier DEBSZ
System control number 43099298X
029 1# - (OCLC)
OCLC library identifier NZ1
System control number 14926884
029 1# - (OCLC)
OCLC library identifier NZ1
System control number 15921981
029 1# - (OCLC)
OCLC library identifier NLGGC
System control number 338981586
035 ## - SYSTEM CONTROL NUMBER
System control number (OCoLC)761318489
Canceled/invalid control number (OCoLC)748937827
-- (OCoLC)752380865
-- (OCoLC)764717811
-- (OCoLC)796754453
037 ## - SOURCE OF ACQUISITION
Stock number 10.1002/9781118029145
Source of stock number/acquisition Wiley InterScience
Note http://www3.interscience.wiley.com
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA76.9.D343
Item number K36 2011
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM
Subject category code subdivision 021030
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3/12
Edition number 23
084 ## - OTHER CLASSIFICATION NUMBER
Classification number 54.64
Source of number bcl
049 ## - LOCAL HOLDINGS (OCLC)
Holding library MAIN
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Kantardzic, Mehmed.
245 10 - TITLE STATEMENT
Title Data mining :
Remainder of title concepts, models, methods, and algorithms /
Statement of responsibility, etc Mehmed Kantardzic.
250 ## - EDITION STATEMENT
Edition statement Second edition.
264 #1 -
-- [Piscataway, New Jersey] :
-- IEEE Press ;
-- Hoboken, NJ :
-- Wiley,
-- [2011]
264 #4 -
-- ©2011
300 ## - PHYSICAL DESCRIPTION
Extent 1 online resource (xvii, 534 pages) :
Other physical details illustrations
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
-- cr
-- rdacarrier
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references (pages 510-528) and index.
505 00 - FORMATTED CONTENTS NOTE
Title Data-Mining Concepts --
-- Preparing the Data --
-- Data Reduction --
-- Learning from Data --
-- Statistical Methods --
-- Decision Trees and Decision Rules --
-- Artificial Neural Networks --
-- Ensemble Learning --
-- Cluster Analysis --
-- Association Rules --
-- Web Mining and Text Mining --
-- Advances in Data Mining --
-- Genetic Algorithms --
-- Fuzzy sets and Fuzzy Logic --
-- Visualization Methods --
-- Appendix A --
-- Appendix B: Data-Mining Applications.
520 ## - SUMMARY, ETC.
Summary, etc This book reviews state-of-the-art methodologies and techniques for analyzing enormous quantities of raw data in high-dimensional data spaces, to extract new information for decision making. The goal of this book is to provide a single introductory source, organized in a systematic way, in which we could direct the readers in analysis of large data sets, through the explanation of basic concepts, models and methodologies developed in recent decades.
520 ## - SUMMARY, ETC.
Summary, etc "Now updated--the systematic introductory guide to modern analysis of large data sets. As data sets continue to grow in size and complexity, there has been an inevitable move towards indirect, automatic, and intelligent data analysis in which the analyst works via more complex and sophisticated software tools. This book reviews state-of-the-art methodologies and techniques for analyzing enormous quantities of raw data in high-dimensional data spaces to extract new information for decision-making. This Second Edition of Data Mining: Concepts, Models, Methods, and Algorithms discusses data mining principles and then describes representative state-of-the-art methods and algorithms originating from different disciplines such as statistics, machine learning, neural networks, fuzzy logic, and evolutionary computation. Detailed algorithms are provided with necessary explanations and illustrative examples, and questions and exercises for practice at the end of each chapter. This new edition features the following new techniques/methodologies: Support Vector Machines (SVM)--developed based on statistical learning theory, they have a large potential for applications in predictive data mining; Kohonen Maps (Self-Organizing Maps - SOM)--one of very applicative neural-networks-based methodologies for descriptive data mining and multi-dimensional data visualizations; DBSCAN, BIRCH, and distributed DBSCAN clustering algorithms--representatives of an important class of density-based clustering methodologies; Bayesian Networks (BN) methodology often used for causality modeling; Algorithms for measuring Betweeness and Centrality parameters in graphs, important for applications in mining large social networks; CART algorithm and Gini index in building decision trees; Bagging & Boosting approaches to ensemble-learning methodologies, with details of AdaBoost algorithm; Relief algorithm, one of the core feature selection algorithms inspired by instance-based learning; PageRank algorithm for mining and authority ranking of web pages; Latent Semantic Analysis (LSA) for text mining and measuring semantic similarities between text-based documents; New sections on temporal, spatial, web, text, parallel, and distributed data mining. More emphasis on business, privacy, security, and legal aspects of data mining technologyThis text offers guidance on how and when to use a particular software tool (with the companion data sets) from among the hundreds offered when faced with a data set to mine. This allows analysts to create and perform their own data mining experiments using their knowledge of the methodologies and techniques provided. The book emphasizes the selection of appropriate methodologies and data analysis software, as well as parameter tuning. These critically important, qualitative decisions can only be made with the deeper understanding of parameter meaning and its role in the technique that is offered here. This volume is primarily intended as a data-mining textbook for computer science, computer engineering, and computer information systems majors at the graduate level. Senior students at the undergraduate level and with the appropriate background can also successfully comprehend all topics presented here."--Publisher's description.
588 0# -
-- Online resource and print version record; title from PDF title page (IEEE Xplore, viewed March 14, 2014).
526 ## - STUDY PROGRAM INFORMATION NOTE
Department Management Information Systems
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining.
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element COMPUTERS
General subdivision Database Management
-- Data Mining.
Source of heading or term bisacsh
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data mining.
Source of heading or term fast
-- (OCoLC)fst00887946
655 #4 - INDEX TERM--GENRE/FORM
Genre/form data or focus term Electronic books.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Print version:
Main entry heading Kantardzic, Mehmed.
Title Data mining.
Edition 2nd ed.
Place, publisher, and date of publication Hoboken, N.J. : John Wiley : IEEE Press, ©2011
International Standard Book Number 9780470890455
Record control number (DLC) 2011002190
-- (OCoLC)700735391
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://dx.doi.org/10.1002/9781118029145">http://dx.doi.org/10.1002/9781118029145</a>
Public note Wiley Online Library
994 ## -
-- 92
-- DG1

No items available.