A framework to predict the quality of answers with non-textual features

  • Authors:

  • Jiwoon Jeon;W. Bruce Croft;Joon Ho Lee;Soyeon Park

  • Affiliations:

  • University of Massachusetts-Amherst, MA;University of Massachusetts-Amherst, MA;Soong-sil University, Seoul, South Korea;Duksung Women's University, Seoul, South Korea

  • Venue:
  • SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
  • Year:
  • 2006

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Abstract

New types of document collections are being developed by various web services. The service providers keep track of non-textual features such as click counts. In this paper, we present a framework to use non-textual features to predict the quality of documents. We also show our quality measure can be successfully incorporated into the language modeling-based retrieval model. We test our approach on a collection of question and answer pairs gathered from a community based question answering service where people ask and answer questions. Experimental results using our quality measure show a significant improvement over our baseline.