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Information Extraction

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Information Extraction Synopsis

Currently, there is a considerable interest in integrating the results of information extraction in retrieval systems, because of the growing demand for search engines that return precise answers to flexible information queries. Advanced retrieval models satisfy that need and they rely on tools that automatically build a probabilistic model of the content of a (multi-media) document.

The book focuses on content recognition in text. It elaborates on the past and current most successful algorithms and their application in a variety of domains (e.g., news filtering, mining of biomedical text, intelligence gathering, competitive intelligence, legal information searching, and processing of informal text).

An important part discusses current statistical and machine learning algorithms for information detection and classification and integrates their results in probabilistic retrieval models. The book also reveals a number of ideas towards an advanced understanding and synthesis of textual content.

About This Edition

ISBN: 9789048172467
Publication date:
Author: MarieFrancine Moens
Publisher: Springer an imprint of Springer Netherlands
Format: Paperback
Pagination: 246 pages
Series: The Information Retrieval Series
Genres: Library and information sciences / Museology
Information technology industries
Natural language and machine translation
Pattern recognition
Data warehousing
Information retrieval
Artificial intelligence

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