Information retrieval architecture and algorithms / (Record no. 3976)

MARC details
000 -LEADER
fixed length control field 04854nam a2200145 4500
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9788132210764 (pb)
040 ## - CATALOGING SOURCE
Transcribing agency CUS
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 025.04
Item number KOW/I
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Kowalski, Gerald
245 ## - TITLE STATEMENT
Title Information retrieval architecture and algorithms /
Statement of responsibility, etc. Gerald Kowalski
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc. London :
Name of publisher, distributor, etc. Springer,
Date of publication, distribution, etc. 2013.
300 ## - PHYSICAL DESCRIPTION
Extent xii, 305p.
505 ## - FORMATTED CONTENTS NOTE
Formatted contents note Information Retrieval System Functions 1<br/>1.1 Introduction 1<br/>1.1.1 Primary Information Retrieval Problems 3<br/>1.1.2 Objectives of Information Retrieval System 6<br/>1.2 Functional Overview of Information Retrieval Systems 10<br/>1.2.1 Selective Dissemination of Information 11<br/>1.2.2 Alerts 12<br/>1.2.3 Items and Item Index 13<br/>1.2.4 Indexing and Mapping to a Taxonomy 13<br/>1.3 Understanding Search Functions 14<br/>1.3.1 Boolean Logic 15<br/>1.3.2 Proximity 16<br/>1.3.3 Contiguous Word Phrases 17<br/>1.3.4 Fuzzy Searches 18<br/>1.3.5 Term Masking 18<br/>1.3.6 Numeric and Date Ranges 19<br/>1.3.7 Vocabulary Browse 20<br/>1.3.8 Multimedia Search 20<br/>1.4 Relationship to Database Management Systems 20<br/>1.5 Digital Libraries and Data Warehouses 22<br/>1.6 Processing Subsystem Overview 24<br/>1.7 Summary 25<br/>1.8 Exercises 26<br/>Data Structures and Mathematical Algorithms 27<br/>2.1 Data Structures 27<br/>2.1.1 Introduction to Data Structures 27<br/>2.1.2 Inverted File Structure 29<br/>2.1.3 N-Gram Data Structures 31<br/>2.1.4 PAT Data Structure 34<br/>2.1.5 Signature File Structure 38<br/>2.1.6 Hypertext and XML Data Structures 40<br/>2.1.7 XML<br/>2.2 Mathematical Algorithms 44<br/>2.2.1 Introduction ^<br/>2.2.2 Bayesian Mathematics 45<br/>2.2.3 Shannon's Theory of Information 47<br/>2.2.4 Latent Semantic Indexing 48<br/>2.2.5 Hidden Markov Models<br/>2.2.6 Neural Networks<br/>2.2.7 Support Vector Machines<br/>2.3 Summary<br/>2.4 Exercises<br/>^ ^ 63<br/>Ingest<br/>3.1 Introduction to Ingest ^<br/>3.2 Item Receipt<br/>3.3 Duplicate Detection<br/>3.4 Item Normalization<br/>3.5 Zoning and Creation of Processing Tokens<br/>3.6 Stemming __<br/>3.6.1 Introduction to the Stemming Process ''<br/>3.6.2 Porter Stemming Algorithm<br/>3.6.3 Dictionary Look-Up Stemmers<br/>3.6.4 Successor Stemmers<br/>3.6.5 Conclusions on Stemming<br/>3.7 Entity Processing<br/>3.7.1 Entity Identification<br/>3.7.2 Entity Normalization<br/>3.7.3 Entity Resolution<br/>3.7.4 Information Extraction<br/>3.8 Categorization ^2<br/>3.9 Citational Metadata ^2<br/>3.10 Summary<br/>3.11 Exercises<br/>Indexing<br/>4.1 What is Indexing<br/>4.1.1 History<br/>4.1.2 Objectives<br/>4.2 Manual Indexing Process<br/>4.2.1 Scope of Indexing<br/>42 2 Precoordination and Linkages<br/>4 3 Automatic Indexing of Text<br/>4.3.1 Statistical Indexing<br/>4.3.2 Natural Language ^25<br/>4.3.3 Concept Indexing<br/>95<br/>4.4 Automatic Indexing of Multimedia 129<br/>4.4.1 Introduction to Mutlimedia Indexing 130<br/>4.4.2 Audio Indexing 121<br/>4.4.3 Image Indexing 124<br/>4.4.4 Video Indexing 126<br/>4.5 Summary ^27<br/>. 139<br/>4.6 Exercises<br/>Search<br/>5.1 Introduction<br/>5.2 Similarity Measures and Ranking 142<br/>5.2.1 Similarity Measures 144<br/>5.3 Hidden Markov Models Techniques 152<br/>5.4 Ranking Algorithms 122<br/>5.5 Relevance Feedback 124<br/>5.6 Selective Dissemination of Information Search 157<br/>5.7 Weighted Searches of Boolean Systems 163<br/>5.8 Multimedia Searching 167<br/>5.9 Summary<br/>. 170<br/>5.10 Exercises<br/>Document and Term Clustering 171<br/>6.1 Introduction to Clustering 171<br/>6.2 Thesaurus Generation 124<br/>6.2.1 Manual Clustering 175<br/>6.2.2 Automatic Term Clustering 176<br/>6.3 Item Clustering 1^4<br/>6.4 Hierarchy of Clusters 1^6<br/>6.4.1 Automatic Hierarchical Cluster Algorithms 189<br/>6.5 Measure of Tightness for Cluster 193<br/>6.6 Issues with Use ofHierarchical Clusters for Search 194<br/>6.7 Summary ^^2<br/>6.8 Exercises<br/>Information Presentation 199<br/>7.1 Information Presentation Introduction 199<br/>7.2 Presentation of the Hits 199<br/>7.2.1 Sequential Listing of Hits 200<br/>7.2.2 Cluster View 201<br/>7.2.3 Network View 205<br/>7.2.4 Timeline Presentation 208<br/>7.3 Display of the Item 210<br/>7.3.1 Indicating Search Terms in Display 210<br/>7.3.2 Text Summarization 211<br/>7.4 Collaborative Filtering 213<br/>7.4.1 Page Ranking as Collaborative Filtering 215<br/>197<br/>7.5 Multimedia Presentation 216<br/>7.5.1 Audio Presentation 216<br/>7.5.2 Image Item Presentation 219<br/>7.5.3 Video Presentation 223<br/>7.6 Human Perception and Presentation 225<br/>7.6.1 Introduction to Information Visualization 226<br/>7.6.2 Cognition and Perception 229<br/>7.7 Summary 233<br/>7.8 Exercises 234<br/>8 Search Architecture 235<br/>8.1 Index Search Optimization 235<br/>8.1.1 Pruning the Index 236<br/>8.1.2 Champion Lists 236<br/>8.2 Text Search Optimization 237<br/>8.2.1 Software Text Seareh Algorithms 239<br/>8.2.2 Hardware Text Search Systems 244<br/>8.3 GOOGLE Scalable Multiprocessor Architecture 249<br/>8.4 Summary 251<br/>8.5 Exercises 252<br/>9 Information System Evaluation 253<br/>9.1 Introduction to Information System Evaluation 253<br/>9.2 Measures Used in System Evaluations 259<br/>9.3 Multimedia Information Retrieval Evaluation 269<br/>9.4 Measurement Example: TREC Evolution 271<br/>9.5 Summary 279<br/>9.6 Exercises 280
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        Central Library, Sikkim University Central Library, Sikkim University General Book Section 29/06/2016 025.04 KOW/I P36880 29/06/2016 General Books
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