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More About This Textbook
Overview
Multimedia Information Retrieval: Content-Based Information Retrieval from Large Text and Audio Databases 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 serves to bridge the gap between classic ranking of text documents and modern information retrieval where composite multimedia documents are searched for relevant information.
Multimedia Information Retrieval: Content-Based Information Retrieval from Large Text and Audio Databases begins to pave the way for speech retrieval; only recently has the search for information in speech recordings become feasible. This book provides the necessary introduction to speech recognition while discussing probabilistic retrieval and text retrieval, key topics in classic information retrieval. The book then discusses speech retrieval, which is even more challenging than retrieving text documents because word boundaries are difficult to detect, and recognition errors affect the retrieval effectiveness. This book also addresses the problem of integrating information retrieval and database functions, since there is an increasing need for retrieving information from frequently changing data collections which are organized and managed by a database system.
Multimedia Information Retrieval: Content-Based Information Retrieval from Large Text and Audio Databases serves as an excellent reference source and may be used as a text for advanced courses on the topic.
Editorial Reviews
Booknews
A reference offering a review of the search techniques required to find information in large digital data repositories, such as digital libraries and multimedia databases, particularly emphasizing speech retrieval. Sch<:a>uble (Swiss Federal Institute of Technology) provides a tour through Multimedia Information Retrieval (MMIR), probabilistic retrieval, and text retrieval in classic Information Retrieval, introducing the issues inherent in retrieval of speech recordings, and integrating information and retrieval database functions. The volume features a case study recording the issues raised in accessing a library catalogue whose cards were scanned and converted into text by Optical Character Recognition (OCR). Annotation c. by Book News, Inc., Portland, Or.Product Details
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Table of Contents
1. Introduction. 2. Probabilistic Retrieval. 3. Text Retrieval. 4. Automatic Speech Recognition. 5. Speech Retrieval. 6. Case Study: Retrieving Scanned Library Cards. 7. Integrating Information Retrieval and Database Functions. 8. Outlook. A: Theorems and Proofs. Bibliography. Index.