Descripción del título
Automatic Ambiguity Resolut...
This is an exciting time for Artificial Intelligence, and for Natural Language Processing in particular. Over the last five years or so, a newly revived spirit has gained prominence that promises to revitalize the whole field: the spirit of empiricism. This book introduces a new approach to the important NLP issue of automatic ambiguity resolution, based on statistical models of text. This approach is compared with previous work and proved to yield higher accuracy for natural language analysis. An effective implementation strategy is also described, which is directly useful for natural language analysis. The book is noteworthy for demonstrating a new empirical approach to NLP; it is essential reading for researchers in natural language processing or computational linguistics
Monografía
monografia Rebiun21515345 https://catalogo.rebiun.org/rebiun/record/Rebiun21515345 m o d cr mnu---uuaaa 121227s1996 gw ob 001 0 eng 990544267 1060821905 1063864149 9783540495932 electronic bk.) 3540495932 electronic bk.) 9783540620044 3540620044 3540495932 10.1007/BFb0021059 doi UPVA 996968439203706 AU@ eng pn AU@ OCLCO GW5XE OCLCA ITD OCLCF UA@ OCLCQ LIP UAB ESU OCLCQ CEF AU@ OCLCA UYQ bicssc TJFM1 bicssc COM004000 bisacsh Franz, Alexander 1966-) Automatic Ambiguity Resolution in Natural Language Processing an Empirical Approach edited by Alexander Franz Berlin, Heidelberg Springer Berlin Heidelberg 1996 Berlin, Heidelberg Berlin, Heidelberg Springer Berlin Heidelberg 1 online resource (xx, 164 pages) 1 online resource (xx, 164 pages) Text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence 0302-9743 1171 Includes bibliographical references and index Previous work on syntactic ambiguity resolution -- Loglinear models for ambiguity resolution -- Modeling new words -- Part-of-speech ambiguity -- Prepositional phrase attachment disambiguation -- Conclusions This is an exciting time for Artificial Intelligence, and for Natural Language Processing in particular. Over the last five years or so, a newly revived spirit has gained prominence that promises to revitalize the whole field: the spirit of empiricism. This book introduces a new approach to the important NLP issue of automatic ambiguity resolution, based on statistical models of text. This approach is compared with previous work and proved to yield higher accuracy for natural language analysis. An effective implementation strategy is also described, which is directly useful for natural language analysis. The book is noteworthy for demonstrating a new empirical approach to NLP; it is essential reading for researchers in natural language processing or computational linguistics English Computer science Artificial intelligence Computer simulation Statistics Artificial intelligence. Computer science. Computer simulation. Statistics. Computer Science. Engineering & Applied Sciences. Electronic books Print version 9783540620044 Lecture notes in computer science. Lecture notes in artificial intelligence 1171