Probabilistic model for definitional question answering

Kyoung Soo Han, Young In Song, Hae Chang Rim

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

25 Citations (Scopus)

Abstract

This paper proposes a probabilistic model for definitional question answering (QA) that reflects the characteristics of the definitional question. The intention of the definitional question is to request the definition about the question target. Therefore, an answer for the definitional question should contain the content relevant to the topic of the target, and have a representation form of the definition style. Modeling the problem of definitional QA from both the topic and definition viewpoints, the proposed probabilistic model converts the task of answering the definitional questions into that of estimating the three language models: topic language model, definition language model, and general language model. The proposed model systematically combines several evidences in a probabilistic framework. Experimental results show that a definitional QA system based on the proposed probabilistic model is comparable to state-of-the-art systems.

Original languageEnglish
Title of host publicationProceedings of the Twenty-Ninth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
PublisherAssociation for Computing Machinery (ACM)
Pages212-219
Number of pages8
ISBN (Print)1595933697, 9781595933690
DOIs
Publication statusPublished - 2006
Event29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval - Seatttle, WA, United States
Duration: 2006 Aug 62006 Aug 11

Publication series

NameProceedings of the Twenty-Ninth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
Volume2006

Other

Other29th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
CountryUnited States
CitySeatttle, WA
Period06/8/606/8/11

Keywords

  • Definitional question answering
  • Language model
  • Probabilistic model

ASJC Scopus subject areas

  • Engineering(all)
  • Information Systems
  • Software
  • Applied Mathematics

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