Kernels on linguistic structures for answer extraction

Alessandro Moschitti, Silvia Quarteroni

Research output: Chapter in Book/Report/Conference proceedingConference contribution

26 Citations (Scopus)

Abstract

Natural Language Processing (NLP) for Information Retrieval has always been an interesting and challenging research area. Despite the high expectations, most of the results indicate that successfully using NLP is very complex. In this paper, we show how Support Vector Machines along with kernel functions can effectively represent syntax and semantics. Our experiments on question/answer classification show that the abovemodels highly improve on bag-of-words on a TREC dataset.

Original languageEnglish
Title of host publicationACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference
Pages113-116
Number of pages4
Publication statusPublished - 1 Dec 2008
Externally publishedYes
Event46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-08: HLT - Columbus, OH, United States
Duration: 15 Jun 200820 Jun 2008

Other

Other46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-08: HLT
CountryUnited States
CityColumbus, OH
Period15/6/0820/6/08

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ASJC Scopus subject areas

  • Language and Linguistics
  • Computer Networks and Communications
  • Linguistics and Language

Cite this

Moschitti, A., & Quarteroni, S. (2008). Kernels on linguistic structures for answer extraction. In ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference (pp. 113-116)