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020 _a9789042027695
_q(electronic book)
020 _z9789042027688
_q(print)
024 7 _a10.1163/9789042027695
_2DOI
035 _a(OCoLC)608352102
_z(OCoLC)501840931
040 _aNL-LeKB
_cNL-LeKB
_erda
050 4 _aP290
_b.F45 2010eb
072 7 _aLAN
_x006000
_2bisacsh
072 7 _aLAN
_x009060
_2bisacsh
072 7 _aCFX
_2bicssc
072 7 _aLAN009000
_2bisacsh
082 0 4 _a415
_222
100 1 _aFeldman, Anna.
245 1 2 _aA resource-light approach to morpho-syntactic tagging /
_cAnna Feldman and Jirka Hana.
264 1 _aAmsterdam ;
_aNew York, NY :
_bRodopi,
_c2010.
300 _a1 online resource (xiv, 185 pages) :
_billustrations.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_2rdacarrier
490 1 _aLanguage and computers : studies in practical linguistics ;
_vno. 70
504 _aIncludes bibliographical references (p. 133-148) and index.
505 0 0 _aPreliminary Material -- Introduction -- Common tagging techniques -- Previous resource-light approaches to NLP -- Languages, corpora and tagsets -- Quantifying language properties -- Resource-light morphological analysis -- Cross-language morphological tagging -- Summary and further work -- Bibliography -- Tagsets we use -- Corpora -- Language properties -- Citation Index.
506 _aAvailable to subscribing member institutions only.
520 _aWhile supervised corpus-based methods are highly accurate for different NLP tasks, including morphological tagging, they are difficult to port to other languages because they require resources that are expensive to create. As a result, many languages have no realistic prospect for morpho-syntactic annotation in the foreseeable future. The method presented in this book aims to overcome this problem by significantly limiting the necessary data and instead extrapolating the relevant information from another, related language. The approach has been tested on Catalan, Portuguese, and Russian. Although these languages are only relatively resource-poor, the same method can be in principle applied to any inflected language, as long as there is an annotated corpus of a related language available. Time needed for adjusting the system to a new language constitutes a fraction of the time needed for systems with extensive, manually created resources: days instead of years. This book touches upon a number of topics: typology, morphology, corpus linguistics, contrastive linguistics, linguistic annotation, computational linguistics and Natural Language Processing (NLP). Researchers and students who are interested in these scientific areas as well as in cross-lingual studies and applications will greatly benefit from this work. Scholars and practitioners in computer science and linguistics are the prospective readers of this book.
650 0 _aGrammar, Comparative and general
_xMorphosyntax.
650 0 _aComputational linguistics.
650 0 _aLanguage transfer (Language learning)
650 0 _aCross-language information retrieval.
650 7 _aComputational linguistics.
_2fast
650 7 _aCross-language information retrieval.
_2fast
650 7 _aGrammar, Comparative and general
_xMorphosyntax.
_2fast
650 7 _aLanguage transfer (Language learning)
_2fast
700 1 _aHana, Jirka.
776 0 8 _iPrint version:
_aFeldman, Anna.
_tResource-light approach to morpho-syntactic tagging.
_dAmsterdam : Rodopi, 2010
_z9789042027688
_w(OCoLC)497573700
830 0 _aLanguage and Computers
_v70.
830 0 _aRodopi Language and Linguistics Special E-Book Collection, 2007-2014, ISBN: 9789004357983.
856 4 _zDOI:
_uhttp://dx.doi.org/10.1163/9789042027695
999 _c38317
_d38317