Quality Measures in Data Mining (Record no. 20481)

MARC details
000 -LEADER
fixed length control field 03780nam a22004815i 4500
001 - CONTROL NUMBER
control field 978-3-540-44918-8
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20170628034551.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
fixed length control field cr nn 008mamaa
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 100301s2007 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783540449188
-- 978-3-540-44918-8
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-3-540-44918-8
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA329-348
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA640-643
072 #7 - SUBJECT CATEGORY CODE
Subject category code TBJ
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code MAT003000
Source bisacsh
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 519
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Guillet, Fabrice J.
Relator term editor.
245 10 - TITLE STATEMENT
Title Quality Measures in Data Mining
Medium [electronic resource] /
Statement of responsibility, etc edited by Fabrice J. Guillet, Howard J. Hamilton.
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg,
-- 2007.
300 ## - PHYSICAL DESCRIPTION
Extent XIV, 314 p.
Other physical details online resource.
336 ## -
-- text
-- txt
-- rdacontent
337 ## -
-- computer
-- c
-- rdamedia
338 ## -
-- online resource
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-- rdacarrier
347 ## -
-- text file
-- PDF
-- rda
490 1# - SERIES STATEMENT
Series statement Studies in Computational Intelligence,
International Standard Serial Number 1860-949X ;
Volume number/sequential designation 43
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Overviews on rule quality -- Choosing the Right Lens: Finding What is Interesting in Data Mining -- A Graph-based Clustering Approach to Evaluate Interestingness Measures: A Tool and a Comparative Study -- Association Rule Interestingness Measures: Experimental and Theoretical Studies -- On the Discovery of Exception Rules: A Survey -- From data to rule quality -- Measuring and Modelling Data Quality for Quality-Awareness in Data Mining -- Quality and Complexity Measures for Data Linkage and Deduplication -- Statistical Methodologies for Mining Potentially Interesting Contrast Sets -- Understandability of Association Rules: A Heuristic Measure to Enhance Rule Quality -- Rule quality and validation -- A New Probabilistic Measure of Interestingness for Association Rules, Based on the Likelihood of the Link -- Towards a Unifying Probabilistic Implicative Normalized Quality Measure for Association Rules -- Association Rule Interestingness: Measure and Statistical Validation -- Comparing Classification Results between N-ary and Binary Problems.
520 ## - SUMMARY, ETC.
Summary, etc Data mining analyzes large amounts of data to discover knowledge relevant to decision making. Typically, numerous pieces of knowledge are extracted by a data mining system and presented to a human user, who may be a decision-maker or a data-analyst. The user is confronted with the task of selecting the pieces of knowledge that are of the highest quality or interest according to his or her preferences. Since this selection is sometimes a daunting task, designing quality and interestingness measures has become an important challenge for data mining researchers in the last decade. This volume presents the state of the art concerning quality and interestingness measures for data mining. The book summarizes recent developments and presents original research on this topic. The chapters include surveys, comparative studies of existing measures, proposals of new measures, simulations, and case studies. Both theoretical and applied chapters are included. Papers for this book were selected and reviewed for correctness and completeness by an international review committee.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering mathematics.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Engineering.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Appl.Mathematics/Computational Methods of Engineering.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence (incl. Robotics).
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Hamilton, Howard J.
Relator term editor.
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer eBooks
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783540449119
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Studies in Computational Intelligence,
-- 1860-949X ;
Volume number/sequential designation 43
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="http://dx.doi.org/10.1007/978-3-540-44918-8">http://dx.doi.org/10.1007/978-3-540-44918-8</a>
912 ## -
-- ZDB-2-ENG
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Source of acquisition Total Checkouts Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     Central Library Central Library 28/06/2017 Springer EBook   E-43660 28/06/2017 28/06/2017 E-Book

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