Overview

This volume addresses the future need for sophisticated search techniques that will be required to find relevant information in large digital data repositories, such as digital libraries and other multimedia databases. Because of the dramatically increasing amount of multimedia data available, there is a growing need for new search techniques that provide not only fewer bits, but also the most relevant bits, to those searching for multimedia digital data. This book seeks to bridge the gap between classic ranking of text documents and modern information retrieval where composite multimedia documents are searched for relevant information.

Full Product Details

Author:   Peter Schäuble
Publisher:   Springer
Imprint:   Springer
Edition:   1997 ed.
Volume:   397
Dimensions:   Width: 15.50cm , Height: 1.20cm , Length: 23.50cm
Weight:   1.030kg
ISBN:  

9780792398998

ISBN 10:   0792398998
Pages:   190
Publication Date:   30 April 1997
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

1 Introduction.- 1.1 Towards Lightweight Information.- 1.2 What is Multimedia Information Retrieval?.- 1.3 Examples of Multimedia Information Retrieval Systems.- 1.4 Vector Space Retrieval.- 1.5 Interactive Search Techniques.- 1.6 Evaluation Issues.- 1.7 Similarity Thesauri.- 2 Probabilistic Retrieval.- 2.1 Information Retrieval Events in a Probability Space.- 2.2 Cooper and Robertson’s Probability Ranking Principle.- 2.3 Robertson-Sparck Jones Weighting.- 2.4 Logistic Inference Models.- 3 Text Retrieval.- 3.1 Text Characteristics.- 3.2 Vocabularies for Text Indexing.- 3.3 Weighting and Retrieval Functions.- 4 Automatic Speech Recognition.- 4.1 Speech Sound Waves.- 4.2 Digital Speech Signal Processing.- 4.3 Hidden Markov Model (HMM) Theory.- 4.4 HMM Based Recognition.- 5 Speech Retrieval.- 5.1 Introduction.- 5.2 Speech Recognition.- 5.3 Indexing and Retrieval by N-Grams.- 5.4 Indexing and Retrieval by Word Matching.- 5.5 Metadata Organisation and Query Processing.- 5.6 Recognition Errors and Retrieval Effectiveness.- 5.7 Experiments.- 6 Case Study: Retrieving Scanned Library Cards.- 6.1 Introduction.- 6.2 Probabilistic Term Weighting and Retrieval.- 6.3 Estimating Occurrence Probabilities.- 6.4 Retrieval for One-Word Queries.- 6.5 Including Ordering Information.- 7 Integrating Information Retrieval and Database Functions.- 7.1 Introduction.- 7.2 System Architecture.- 7.3 Transactions on the IR Index.- 7.4 Transaction Manager of the SPIDER IR Server.- 8 Outlook.- A Theorems and Proofs.

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