A flexible, efficient and accurate framework for community question answering pipelines

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

1 Citation (Scopus)

Abstract

Although deep neural networks have been proving to be excellent tools to deliver state-of-the-art results, when data is scarce and the tackled tasks involve complex semantic inference, deep linguistic processing and traditional structure-based approaches, such as tree kernel methods, are an alternative solution. Community Question Answering is a research area that benefits from deep linguistic analysis to improve the experience of the community of forum users. In this paper, we present a UIMA framework to distribute the computation of cQA tasks over computer clusters such that traditional systems can scale to large datasets and deliver fast processing.

Original languageEnglish
Title of host publicationACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstrations
PublisherAssociation for Computational Linguistics (ACL)
Pages134-139
Number of pages6
ISBN (Electronic)9781948087650
Publication statusPublished - 1 Jan 2015
Event56th Annual Meeting of the Association for Computational Linguistics, ACL 2018 - Melbourne, Australia
Duration: 15 Jul 201820 Jul 2018

Publication series

NameACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstrations

Conference

Conference56th Annual Meeting of the Association for Computational Linguistics, ACL 2018
CountryAustralia
CityMelbourne
Period15/7/1820/7/18

Fingerprint

Linguistics
Pipelines
Processing
Semantics
Deep neural networks

ASJC Scopus subject areas

  • Software
  • Computational Theory and Mathematics

Cite this

Romeo, S., Martino, G., Barron, A., & Moschitti, A. (2015). A flexible, efficient and accurate framework for community question answering pipelines. In ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstrations (pp. 134-139). (ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstrations). Association for Computational Linguistics (ACL).

A flexible, efficient and accurate framework for community question answering pipelines. / Romeo, Salvatore; Martino, Giovanni; Barron, Alberto; Moschitti, Alessandro.

ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstrations. Association for Computational Linguistics (ACL), 2015. p. 134-139 (ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstrations).

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

Romeo, S, Martino, G, Barron, A & Moschitti, A 2015, A flexible, efficient and accurate framework for community question answering pipelines. in ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstrations. ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstrations, Association for Computational Linguistics (ACL), pp. 134-139, 56th Annual Meeting of the Association for Computational Linguistics, ACL 2018, Melbourne, Australia, 15/7/18.
Romeo S, Martino G, Barron A, Moschitti A. A flexible, efficient and accurate framework for community question answering pipelines. In ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstrations. Association for Computational Linguistics (ACL). 2015. p. 134-139. (ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstrations).
Romeo, Salvatore ; Martino, Giovanni ; Barron, Alberto ; Moschitti, Alessandro. / A flexible, efficient and accurate framework for community question answering pipelines. ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstrations. Association for Computational Linguistics (ACL), 2015. pp. 134-139 (ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of System Demonstrations).
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