000728236 000__ 02739cam\a2200445Ii\4500 000728236 001__ 728236 000728236 005__ 20230306141001.0 000728236 006__ m\\\\\o\\d\\\\\\\\ 000728236 007__ cr\cn\nnnunnun 000728236 008__ 150720s2015\\\\si\a\\\\ob\\\\000\0\eng\d 000728236 020__ $$a9789812875525$$qelectronic book 000728236 020__ $$a9812875522$$qelectronic book 000728236 020__ $$z9789812875518 000728236 035__ $$aSP(OCoLC)ocn914166002 000728236 035__ $$aSP(OCoLC)914166002 000728236 040__ $$aN$T$$beng$$erda$$epn$$cN$T$$dGW5XE$$dN$T$$dIDEBK$$dYDXCP$$dAZU 000728236 049__ $$aISEA 000728236 050_4 $$aQA76.9.N38 000728236 08204 $$a006.3/5$$223 000728236 1001_ $$aChen, Wenliang,$$eauthor. 000728236 24510 $$aSemi-supervised dependency parsing$$h[electronic resource] /$$cWenliang Chen, Min Zhang. 000728236 264_1 $$aSingapore :$$bSpringer,$$c2015. 000728236 300__ $$a1 online resource (viii, 144 pages) :$$billustrations. 000728236 336__ $$atext$$btxt$$2rdacontent 000728236 337__ $$acomputer$$bc$$2rdamedia 000728236 338__ $$aonline resource$$bcr$$2rdacarrier 000728236 504__ $$aIncludes bibliographical references. 000728236 5050_ $$a1 Introduction -- 2 Dependency Parsing Models -- 3 Overview of Semi-supervised Dependency Parsing Approaches -- 4 Training with Auto-parsed Whole Trees -- 5 Training with Lexical Information -- 6 Training with Bilexical Dependencies -- 7 Training with Subtree Structures -- 8 Training with Dependency Language Models -- 9 Training with Meta Features -- 10 Closing Remarks. 000728236 506__ $$aAccess limited to authorized users. 000728236 520__ $$aThis book presents a comprehensive overview of semi-supervised approaches to dependency parsing. Having become increasingly popular in recent years, one of the main reasons for their success is that they can make use of large unlabeled data together with relatively small labeled data and have shown their advantages in the context of dependency parsing for many languages. Various semi-supervised dependency parsing approaches have been proposed in recent works which utilize different types of information gleaned from unlabeled data. The book offers readers a comprehensive introduction to these approaches, making it ideally suited as a textbook for advanced undergraduate and graduate students and researchers in the fields of syntactic parsing and natural language processing. 000728236 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed July 21, 2015). 000728236 650_0 $$aNatural language processing (Computer science) 000728236 650_0 $$aGrammar, Comparative and general$$xParsing. 000728236 650_0 $$aMathematical linguistics. 000728236 650_0 $$aDependency grammar. 000728236 7001_ $$aZhang, Min,$$eauthor. 000728236 852__ $$bebk 000728236 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-981-287-552-5$$zOnline Access$$91397441.1 000728236 909CO $$ooai:library.usi.edu:728236$$pGLOBAL_SET 000728236 980__ $$aEBOOK 000728236 980__ $$aBIB 000728236 982__ $$aEbook 000728236 983__ $$aOnline 000728236 994__ $$a92$$bISE