Marie-Francine Moens 
Information Extraction: Algorithms and Prospects in a Retrieval Context [PDF ebook] 

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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.

€96.29
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Table des matières

Information Extraction and Information Technology.- Information Extraction from an Historical Perspective.- The Symbolic Techniques.- Pattern Recognition.- Supervised Classification.- Unsupervised Classification Aids.- Integration of Information Extraction in Retrieval Models.- Evaluation of Information Extraction Technologies.- Case Studies.- The Future of Information Extraction in a Retrieval Context.

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Langue Anglais ● Format PDF ● Pages 246 ● ISBN 9781402049934 ● Taille du fichier 4.7 MB ● Maison d’édition Springer Netherland ● Lieu Dordrecht ● Pays NL ● Publié 2006 ● Téléchargeable 24 mois ● Devise EUR ● ID 2147792 ● Protection contre la copie DRM sociale

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