Kernels on linguistic structures for answer extraction

Alessandro Moschitti, Silvia Quarteroni

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

25 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

Fingerprint

Linguistics
linguistics
Processing
language
Information retrieval
information retrieval
syntax
Support vector machines
Semantics
semantics
experiment
Experiments
Kernel
Natural Language Processing
Bag
Information Retrieval
Support Vector Machine
Syntax
Experiment

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)

Kernels on linguistic structures for answer extraction. / Moschitti, Alessandro; Quarteroni, Silvia.

ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. 2008. p. 113-116.

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

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, 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-08: HLT, Columbus, OH, United States, 15/6/08.
Moschitti A, Quarteroni S. 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. 2008. p. 113-116
Moschitti, Alessandro ; Quarteroni, Silvia. / Kernels on linguistic structures for answer extraction. ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. 2008. pp. 113-116
@inproceedings{d810a61125004512b39d41b14400c8e2,
title = "Kernels on linguistic structures for answer extraction",
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.",
author = "Alessandro Moschitti and Silvia Quarteroni",
year = "2008",
month = "12",
day = "1",
language = "English",
isbn = "9781932432046",
pages = "113--116",
booktitle = "ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference",

}

TY - GEN

T1 - Kernels on linguistic structures for answer extraction

AU - Moschitti, Alessandro

AU - Quarteroni, Silvia

PY - 2008/12/1

Y1 - 2008/12/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=80053417049&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80053417049&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9781932432046

SP - 113

EP - 116

BT - ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference

ER -