Information Extraction: Algorithms and Prospects in a Retrieval Context

Name: Information Extraction: Algorithms and Prospects in a Retrieval Context
Brand: Springer
SKU: 9789048172467
Price: 99.65 EUR
Availability: InStock

Autor: Marie-Francine Moens

Jazyk:

Väzba: Brožovaná

Vydavateľ: Springer

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Information extraction regards the processes of structuring and combining content that is explicitly...

Informácie o knihe

Autor

Marie-Francine Moens

Jazyk

Angličtina

Väzba

Kniha - Brožovaná

Vydalo

2010

Stránok

246

EAN

9789048172467

ISBN

9048172462

Enbook ID

01975438

Vydavateľ

Springer

Hmotnosť

419

Rozmery

160 x 240 x 15

Kompletný popis

Information extraction regards the processes of structuring and combining content that is explicitly stated or implied in one or multiple unstructured information sources. It involves a semantic classification and linking of certain pieces of information and is considered as a light form of content understanding by the machine. 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.§The book is aimed at researchers and software developers interested in information extraction and retrieval, but the many illustrations and real world examples make it also suitable as a handbook for students.This book covers content recognition in text, elaborating on past and current most successful algorithms and their application in a variety of settings: news filtering, mining of biomedical text, intelligence gathering, competitive intelligence, legal information searching, and processing of informal text. Today, there is considerable interest in integrating the results of information extraction in retrieval systems, because of the demand for search engines that return precise answers to flexible information queries.

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Information Extraction: Algorithms and Prospects in a Retrieval Context

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