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Computational Linguistics and Intelligent Text Processing: by Alexander Gelbukh PDF

By Alexander Gelbukh

ISBN-10: 3319181106

ISBN-13: 9783319181103

ISBN-10: 3319181114

ISBN-13: 9783319181110

The volumes LNCS 9041 and 9042 represent the court cases of the sixteenth overseas convention on Computational Linguistics and clever textual content Processing, CICLing 2015, held in Cairo, Egypt, in April 2015.

The overall of ninety five complete papers awarded was once conscientiously reviewed and chosen from 329 submissions. They have been prepared in topical sections on grammar formalisms and lexical assets; morphology and chunking; syntax and parsing; anaphora answer and notice feel disambiguation; semantics and discussion; laptop translation and multilingualism; sentiment research and emotion detection; opinion mining and social community research; traditional language iteration and textual content summarization; info retrieval, query answering, and data extraction; textual content class; speech processing; and purposes.

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Additional info for Computational Linguistics and Intelligent Text Processing: 16th International Conference, CICLing 2015, Cairo, Egypt, April 14-20, 2015, Proceedings, Part I

Example text

Universal dependency relations. Dependents of predicates are divided into core (top), non-core (middle), and special (bottom) dependents. Dependents marked * are auxiliary verbs rather than real predicates. Note that some relations occur in more than one place. Predicate Head Nominal Head Nominal Dep nsubj nsubjpass dobj iobj nmod Predicate Dep csubj csubjpass ccomp xcomp advcl vocative discourse expl dislocated nummod appos nmod aux* auxpass* cop* No Head acl Other Dep advmod neg mark punct amod det neg case root Compounding compound name mwe goeswith Coordination conj cc punct Other list parataxis remnant reparandum foreign dep subject.

The language-specific documentation for each treebank should specify what language-specific extensions are used (if any), so that users of the treebanks can make informed choices about how to use the resource. Finally, it must be emphasized that the UD scheme is still evolving. The first version of the guidelines, released in October 2014, will remain stable for at least 8 J. Nivre a year (and probably longer) to give the community a chance to explore it and apply it in diferent projects. But it is very unlikely that the first version is also the final version.

3 and 8). The categories at the bottom of the frequency list are of a more or less technical character: the label #Forn (1,495) for foreign words or the label #Idph (754) for idiomatic phrases, or they belong to rather specific cases. In between there are three categories that are theoretically biased and given – similarly as #Gen – by the respective verbal valency frames: #Oblfm for semantically obligatory modifications of verbs (1,927 occurrences, see Fig 7), #Unsp for Actor with an unspecified reference without a counterpart on the surface (201 occurrences), and #Rcp for reciprocal constructions (994 occurrences).

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Computational Linguistics and Intelligent Text Processing: 16th International Conference, CICLing 2015, Cairo, Egypt, April 14-20, 2015, Proceedings, Part I by Alexander Gelbukh


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