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Graph-Based Natural Language Processing and Information Retrieval

Graph-Based Natural Language Processing and Information Retrieval

Hardback (16 Jun 2011)

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Publisher's Synopsis

Graph theory and the fields of natural language processing and information retrieval are well-studied disciplines. Traditionally, these areas have been perceived as distinct, with different algorithms, different applications and different potential end-users. However, recent research has shown that these disciplines are intimately connected, with a large variety of natural language processing and information retrieval applications finding efficient solutions within graph-theoretical frameworks. This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval. It brings together topics as diverse as lexical semantics, text summarization, text mining, ontology construction, text classification and information retrieval, which are connected by the common underlying theme of the use of graph-theoretical methods for text and information processing tasks. Readers will come away with a firm understanding of the major methods and applications in natural language processing and information retrieval that rely on graph-based representations and algorithms.

About the Publisher

Cambridge University Press

Cambridge University Press dates from 1534 and is part of the University of Cambridge. We further the University's mission by disseminating knowledge in the pursuit of education, learning and research at the highest international levels of excellence.

Book information

ISBN: 9780521896139
Publisher: Cambridge University Press
Imprint: Cambridge University Press
Pub date:
DEWEY: 005.437
DEWEY edition: 22
Language: English
Number of pages: 202
Weight: 436g
Height: 236mm
Width: 165mm
Spine width: 11mm