000 02827cam a2200337 i 4500
999 _c7235
_d7235
001 16506504
005 20190512132426.0
008 101018t20112011enka b 001 0 eng
010 _a 2010044578
020 _a9780521896139
040 _aDLC
_cDLC
_erda
_dYDX
_dYDXCP
_dCDX
_dDLC
050 0 0 _aQA76.9.N38
_bM53 2011
082 0 0 _a005.437
_222
_bM.R.G
100 1 _aMihalcea, Rada,
_d1974-
245 1 0 _aGraph-based natural language processing and information retrieval /
_cRada Mihalcea, Dragomir Radev.
260 _aCambridge ;
_aNew York :
_bCambridge University Press,
_c2011, ©2011.
300 _aviii, 192 pages :
_billustrations ;
_c24 cm
336 _2rdacontent
_atext
337 _2rdamedia
_aunmediated
338 _2rdacarrier
_avolume
504 _aIncludes bibliographical references (pages 179-190) 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 _3Abstract
_uhttp://repository.fue.edu.eg/xmlui/handle/123456789/3484
942 _cBK
_2ddc