000			03176cam a2200361 i 4500
001			16506504
005			20121207115639.0
008			101018t20112011enka b 001 0 eng
010			_a 2010044578
020			_a9780521896139
035			_a(OCoLC)ocn671573419
040			_aDLC _beng _cDLC _erda _dYDX _dYDXCP _dCDX _dDLC
042			_apcc
050	0	0	_aQA76.9.N38 _bM53 2011
082	0	0	_a005.437 MIH-RAD _222
084			_aCOM042000 _2bisacsh
100	1		_aMihalcea, Rada, _d1974-
245	1	0	_aGraph-based natural language processing and information retrieval _cRada Mihalcea, Dragomir Radev.
260			_aCambridge ; _bCambridge University Press, _c2011
300			_aviii, 192 pages : _billustrations ; _c24 cm
504			_aIncludes bibliographical references and index.
505	8		_aMachine generated contents note: Part I. Introduction to Graph Theory: 1. Notations, properties, and representations; 2. Graph-based algorithms; Part II. Networks: 3. Random networks; 4. Language networks; Part III. Graph-Based Information Retrieval: 5. Link analysis for the world wide web; 6. Text clustering; Part IV. Graph-Based Natural Language Processing: 7. Semantics; 8. Syntax; 9. Applications.
520			_a"This book extensively covers the use of graph-based algorithms for natural language processing and information retrieval"--
520			_a"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"--
650		0	_aNatural language processing (Computer science)
650		0	_aGraphical user interfaces (Computer systems)
700	1		_aRadev, Dragomir, _d1968-
856	4	2	_3Publisher description _uhttp://catdir.loc.gov/catdir/enhancements/fy1101/2010044578-d.html
856	4	1	_3Table of contents only _uhttp://catdir.loc.gov/catdir/enhancements/fy1101/2010044578-t.html
856	4	2	_3Contributor biographical information _uhttp://catdir.loc.gov/catdir/enhancements/fy1101/2010044578-b.html
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
955			_brg11 2010-10-18 (telework) _crg11 2010-10-18 (telework) ONIX to Gen Sci/Tech (STM) _axd04 2011-06-09 1 copy rec'd., to CIP ver.
999			_c112456 _d112456