MARC Record from marc_columbia

LEADER: 06289cam a2200805Ii 4500
001 14711319
005 20220521231908.0
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008 151217s2016 flua ob 001 0 eng d
035 $a(OCoLC)ocn932464061
035 $a(NNC)14711319
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019 $a935251200$a1066464694$a1260357772
020 $a9781498725194$qelectronic bk.
020 $a1498725198$qelectronic bk.
020 $z9781498725187
020 $z149872518X
020 $a9780429158636$q(electronic bk.)
020 $a0429158637$q(electronic bk.)
035 $a(OCoLC)932464061$z(OCoLC)935251200$z(OCoLC)1066464694$z(OCoLC)1260357772
037 $aTANDF_402110$bIngram Content Group
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049 $aZCUA
100 1 $aTan, Ying,$d1964-$eauthor.
245 10 $aAnti-spam techniques based on artificial immune system /$cYing Tan.
264 1 $aBoca Raton :$bCRC Press,$c[2016]
264 4 $c©2016
300 $a1 online resource
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
588 0 $aOnline resource; title from PDF title page (EBSCO, viewed December 18, 2015)
504 $aIncludes bibliographical references and index.
505 0 $aFront Cover; Contents; List of Figures; List of Tables; List of Symbols; Preface; Acknowledgments; Author; Chapter 1: Anti-Spam Technologies; 1.1 Spam Problem; 1.1.1 Definition of Spam; 1.1.2 Scale and Influence of Spam; 1.2 Prevalent Anti-Spam Technologies; 1.2.1 Legal Means; 1.2.2 E-Mail Protocol Methods; 1.2.3 Simple Techniques; 1.2.4 Intelligent Spam Detection Approaches; 1.3 E-Mail Feature Extraction Approaches; 1.3.1 Term Selection Strategies; 1.3.2 Text-Based Feature Extraction Approaches; 1.3.3 Image-Based Feature Extraction Approaches
505 8 $a1.3.4 Behavior-Based Feature Extraction Approaches; 1.4 E-Mail Classification Techniques; 1.5 Performance Evaluation and Standard Corpora; 1.5.1 Performance Measurements; 1.5.2 Standard Corpora; 1.6 Summary; Chapter 2: Artificial Immune System; 2.1 Introduction; 2.2 Biological Immune System; 2.2.1 Overview; 2.2.2 Adaptive Immune Process; 2.2.3 Characteristics of BIS; 2.3 Artificial Immune System; 2.3.1 Overview; 2.3.2 AIS Models and Algorithms; 2.3.3 Characteristics of AIS; 2.3.4 Application Fields of AIS; 2.4 Applications of AIS in Anti-Spam; 2.4.1 Heuristic Methods; 2.4.2 Negative Selection
505 8 $a2.4.3 Immune Network; 2.4.4 Dynamic Algorithms; 2.4.5 Hybrid Models; 2.5 Summary; Chapter 3: Term Space Partition-Based Feature Construction Approach; 3.1 Motivation; 3.2 Principles of the TSP Approach; 3.3 Implementation of the TSP Approach; 3.3.1 Preprocessing; 3.3.2 Term Space Partition; 3.3.3 Feature Construction; 3.4 Experiments; 3.4.1 Investigation of Parameters; 3.4.2 Performance with Different Feature Selection Metrics; 3.4.3 Comparison with Current Approaches; 3.5 Summary; Chapter 4: Immune Concentration-Based Feature Construction Approach; 4.1 Introduction
505 8 $a4.2 Diversity of Detector Representation in AIS; 4.3 Motivation of Concentration-Based Feature Construction Approach; 4.4 Overview of Concentration-Based Feature Construction Approach; 4.5 Gene Library Generation; 4.6 Concentration Vector Construction; 4.7 Relation to Other Methods; 4.8 Complexity Analysis; 4.9 Experimental Validation; 4.9.1 Experiments on Different Concentrations; 4.9.2 Experiments with Two-Element Concentration Vector; 4.9.3 Experiments with Middle Concentration; 4.10 Discussion; 4.11 Summary; Chapter 5: Local Concentration-Based Feature Extraction Approach; 5.1 Introduction
505 8 $a5.2 Structure of Local Concentration Model; 5.3 Term Selection and Detector Sets Generation; 5.4 Construction of Local Concentration-Based Feature Vectors; 5.5 Strategies for Defining Local Areas; 5.5.1 Using a Sliding Window with Fixed Length; 5.5.2 Using a Sliding Window with Variable Length; 5.6 Analysis of Local Concentration Model; 5.7 Experimental Validation; 5.7.1 Selection of a Proper Tendency Threshold; 5.7.2 Selection of Proper Feature Dimensionality; 5.7.3 Selection of a Proper Sliding Window Size; 5.7.4 Selection of Optimal Terms Percentage
520 $aIntroducing research on anti-spam techniques based on the artificial immune system (AIS) to identify and filter spam, this authoritative book provides a centralized source of detailed information on efficient models and algorithms of AIS-based anti-spam techniques --$cEdited summary from book.
650 0 $aSpam filtering (Electronic mail)
650 0 $aArtificial immune systems.
650 6 $aPourriels$xFiltrage.
650 6 $aImmuno-ordinateurs.
650 7 $aCOMPUTERS / Computer Literacy$2bisacsh
650 7 $aCOMPUTERS / Computer Science$2bisacsh
650 7 $aCOMPUTERS / Data Processing$2bisacsh
650 7 $aCOMPUTERS / Hardware / General$2bisacsh
650 7 $aCOMPUTERS / Information Technology$2bisacsh
650 7 $aCOMPUTERS / Machine Theory$2bisacsh
650 7 $aCOMPUTERS / Reference$2bisacsh
650 7 $aSpam filtering (Electronic mail)$2fast$0(OCoLC)fst01737477
650 7 $aArtificial immune systems.$2fast$0(OCoLC)fst00967933
655 0 $aElectronic books.
655 4 $aElectronic books.
776 08 $iPrint version:$aTan, Ying, 1964-$tAnti-spam techniques based on artificial immune system.$dBoca Raton ; London ; New York : CRC Press : Taylor & Francis Group, [2016]$z9781498725187$w(DLC) 2016417322$w(OCoLC)932261908
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio14711319$zTaylor & Francis eBooks
880 4 $6264-00/(Q$c©є℗♭2016
852 8 $blweb$hEBOOKS