Learning to rank answers on large online QA collections

Mihai Surdeanu, Massimiliano Ciaramita, Hugo Zaragoza

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

141 Citations (Scopus)

Abstract

This work describes an answer ranking engine for non-factoid questions built using a large online community-generated question-answer collection (Yahoo! Answers). We show how such collections may be used to effectively set up large supervised learning experiments. Furthermore we investigate a wide range of feature types, some exploiting NLP processors, and demonstrate that using them in combination leads to considerable improvements in accuracy.

Original languageEnglish (US)
Title of host publicationACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference
Pages719-727
Number of pages9
StatePublished - 2008
Externally publishedYes
Event46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-08: HLT - Columbus, OH, United States
Duration: Jun 15 2008Jun 20 2008

Other

Other46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-08: HLT
CountryUnited States
CityColumbus, OH
Period6/15/086/20/08

Fingerprint

internet community
Supervised learning
ranking
Engines
experiment
learning
Experiments
Natural Language Processing
Online Communities
Ranking
Experiment

ASJC Scopus subject areas

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

Cite this

Surdeanu, M., Ciaramita, M., & Zaragoza, H. (2008). Learning to rank answers on large online QA collections. In ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference (pp. 719-727)

Learning to rank answers on large online QA collections. / Surdeanu, Mihai; Ciaramita, Massimiliano; Zaragoza, Hugo.

ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. 2008. p. 719-727.

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

Surdeanu, M, Ciaramita, M & Zaragoza, H 2008, Learning to rank answers on large online QA collections. in ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. pp. 719-727, 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-08: HLT, Columbus, OH, United States, 6/15/08.
Surdeanu M, Ciaramita M, Zaragoza H. Learning to rank answers on large online QA collections. In ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. 2008. p. 719-727
Surdeanu, Mihai ; Ciaramita, Massimiliano ; Zaragoza, Hugo. / Learning to rank answers on large online QA collections. ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference. 2008. pp. 719-727
@inproceedings{cd690308e18a4e57a76a1c5026c7df54,
title = "Learning to rank answers on large online QA collections",
abstract = "This work describes an answer ranking engine for non-factoid questions built using a large online community-generated question-answer collection (Yahoo! Answers). We show how such collections may be used to effectively set up large supervised learning experiments. Furthermore we investigate a wide range of feature types, some exploiting NLP processors, and demonstrate that using them in combination leads to considerable improvements in accuracy.",
author = "Mihai Surdeanu and Massimiliano Ciaramita and Hugo Zaragoza",
year = "2008",
language = "English (US)",
isbn = "9781932432046",
pages = "719--727",
booktitle = "ACL-08: HLT - 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference",

}

TY - GEN

T1 - Learning to rank answers on large online QA collections

AU - Surdeanu, Mihai

AU - Ciaramita, Massimiliano

AU - Zaragoza, Hugo

PY - 2008

Y1 - 2008

N2 - This work describes an answer ranking engine for non-factoid questions built using a large online community-generated question-answer collection (Yahoo! Answers). We show how such collections may be used to effectively set up large supervised learning experiments. Furthermore we investigate a wide range of feature types, some exploiting NLP processors, and demonstrate that using them in combination leads to considerable improvements in accuracy.

AB - This work describes an answer ranking engine for non-factoid questions built using a large online community-generated question-answer collection (Yahoo! Answers). We show how such collections may be used to effectively set up large supervised learning experiments. Furthermore we investigate a wide range of feature types, some exploiting NLP processors, and demonstrate that using them in combination leads to considerable improvements in accuracy.

UR - http://www.scopus.com/inward/record.url?scp=80052136505&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=80052136505&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:80052136505

SN - 9781932432046

SP - 719

EP - 727

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

ER -