| 000 | 03280cam a2200385 i 4500 | ||
|---|---|---|---|
| 001 | 16506504 | ||
| 003 | OSt | ||
| 005 | 20150408114154.0 | ||
| 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 _222 _bMRG |
| 084 |
_aCOM042000 _2bisacsh |
||
| 100 | 1 |
_aMihalcea, Rada, _d1974- _940478 |
|
| 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 |
||
| 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) _940479 |
|
| 650 | 0 |
_aGraphical user interfaces (Computer systems) _940480 |
|
| 700 | 1 |
_aRadev, Dragomir, _d1968- _940481 |
|
| 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 |
||
| 942 |
_2ddc _cDVD |
||
| 999 |
_c32349 _d266849 |
||