000826670 000__ 03512cam\a2200505Ii\4500 000826670 001__ 826670 000826670 005__ 20230306144414.0 000826670 006__ m\\\\\o\\d\\\\\\\\ 000826670 007__ cr\cn\nnnunnun 000826670 008__ 180305s2018\\\\sz\\\\\\ob\\\\000\0\eng\d 000826670 019__ $$a1030291548 000826670 020__ $$a9783319740546$$q(electronic book) 000826670 020__ $$a3319740547$$q(electronic book) 000826670 020__ $$z9783319740539 000826670 020__ $$z3319740539 000826670 0247_ $$a10.1007/978-3-319-74054-6$$2doi 000826670 035__ $$aSP(OCoLC)on1027218888 000826670 035__ $$aSP(OCoLC)1027218888$$z(OCoLC)1030291548 000826670 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dAZU$$dUAB$$dYDX$$dOCLCF$$dUPM$$dMERER$$dOCLCQ 000826670 049__ $$aISEA 000826670 050_4 $$aQA76.9.N38 000826670 08204 $$a006.3/5$$223 000826670 08204 $$a410$$222 000826670 1001_ $$aGelbukh, Alexander,$$d1962-$$eauthor. 000826670 24510 $$aAutomatic syntactic analysis based on selectional preferences /$$cAlexander Gelbukh, Hiram Calvo. 000826670 264_1 $$aCham, Switzerland :$$bSpringer,$$c2018. 000826670 300__ $$a1 online resource. 000826670 336__ $$atext$$btxt$$2rdacontent 000826670 337__ $$acomputer$$bc$$2rdamedia 000826670 338__ $$aonline resource$$bcr$$2rdacarrier 000826670 347__ $$atext file$$bPDF$$2rda 000826670 4901_ $$aStudies in computational intelligence ;$$vvolume 765 000826670 504__ $$aIncludes bibliographical references. 000826670 5050_ $$aIntroduction -- First approach: sentence analysis using rewriting rules -- Second approach: constituent grammars -- Third approach: dependency trees -- Evaluation of the dependency parser -- Applications -- Prepositional phrase attachment disambiguation -- The unsupervised approach: grammar induction -- Multiple argument handling -- The need for full co-occurrence. 000826670 506__ $$aAccess limited to authorized users. 000826670 520__ $$aThis book describes effective methods for automatically analyzing a sentence, based on the syntactic and semantic characteristics of the elements that form it. To tackle ambiguities, the authors use selectional preferences (SP), which measure how well two words fit together semantically in a sentence. Today, many disciplines require automatic text analysis based on the syntactic and semantic characteristics of language and as such several techniques for parsing sentences have been proposed. Which is better? In this book the authors begin with simple heuristics before moving on to more complex methods that identify nouns and verbs and then aggregate modifiers, and lastly discuss methods that can handle complex subordinate and relative clauses. During this process, several ambiguities arise. SP are commonly determined on the basis of the association between a pair of words. However, in many cases, SP depend on more words. For example, something (such as grass) may be edible, depending on who is eating it (a cow?). Moreover, things such as popcorn are usually eaten at the movies, and not in a restaurant. The authors deal with these phenomena from different points of view. 000826670 588__ $$aDescription based on print version record. 000826670 650_0 $$aNatural language processing (Computer science) 000826670 7001_ $$aCalvo, Hiram,$$eauthor. 000826670 77608 $$iPrint version:$$aGelbukh, Alexander.$$tAutomatic syntactic analysis based on selectional preferences.$$d[Place of publication not identified] : SPRINGER INTERNATIONAL PU, 2018$$z3319740539$$w(OCoLC)1015861881 000826670 830_0 $$aStudies in computational intelligence ;$$vv. 765. 000826670 852__ $$bebk 000826670 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-74054-6$$zOnline Access$$91397441.1 000826670 909CO $$ooai:library.usi.edu:826670$$pGLOBAL_SET 000826670 980__ $$aEBOOK 000826670 980__ $$aBIB 000826670 982__ $$aEbook 000826670 983__ $$aOnline 000826670 994__ $$a92$$bISE