Predicting the quality of answers using surface linguistic features

Jung Tae Lee, Young In Song, Hae Chang Rim

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

4 Citations (Scopus)

Abstract

Considering the rapidly increasing mass of information on the Web, the quality of documents is a very critical issue in Web information retrieval. This paper presents the importance of surface linguistic features in predicting the quality of user generated documents. A machine learning approach to incorporating surface linguistic features in predicting of document quality is tested on a collection of answers gathered from a community-driven knowledge search service that allows users to ask and answer questions posed by other users. Experimental results show that the features are useful for predicting the quality of answers.

Original languageEnglish
Title of host publicationProceedings - ALPIT 2007 6th International Conference on Advanced Language Processing and Web Information Technology
Pages111-116
Number of pages6
DOIs
Publication statusPublished - 2007
Event6th International Conference on Advanced Language Processing and Web Information Technology, ALPIT 2007 - Luoyang, Henan, China
Duration: 2007 Aug 222007 Aug 24

Publication series

NameProceedings - ALPIT 2007 6th International Conference on Advanced Language Processing and Web Information Technology

Other

Other6th International Conference on Advanced Language Processing and Web Information Technology, ALPIT 2007
CountryChina
CityLuoyang, Henan
Period07/8/2207/8/24

ASJC Scopus subject areas

  • Computer Science(all)
  • Information Systems

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