Exploiting query logs and field-based models to address term mismatch in an HIV/AIDS FAQ retrieval system

Thuma, E., Rogers, S., and Ounis, I. (2013) Exploiting query logs and field-based models to address term mismatch in an HIV/AIDS FAQ retrieval system. In: Métais, E., Meziane, F., Saraee, M., Sugumaran, V. and Vadera, S. (eds.) Natural Language Processing and Information Systems: 18th International Conference on Application of Natural Language to Information Systems, NLDB2013, Salford, UK, June 2013, Proceedings. Series: Lecture Notes in Computer Science (7934). Springer: Berlin, pp. 77-89. ISBN 9783642388231

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Publisher's URL: http://www.springer.com/computer/ai/book/978-3-642-38823-1

Abstract

One of the main challenges in the retrieval of Frequently Asked Questions (FAQ) is that the terms used by information seekers to express their information need are often different from those used in the relevant FAQ documents. This lexical disagreement (aka term mismatch) can result in a less effective ranking of the relevant FAQ documents by retrieval systems that rely on keyword matching in their weighting models. In this paper, we tackle such a lexical gap in an SMS- Based HIV/AIDS FAQ retrieval system by enriching the traditional FAQ document representation using terms from a query log, which are added as a separate field in a field-based model.We evaluate our approach using a collection of FAQ documents produced by a national health service and a corresponding query log collected over a period of 3 months. Our results suggest that by enriching the FAQ documents with additional terms from the SMS queries for which the true relevant FAQ documents are known and combining term frequencies from the different fields, the lexical mismatch problem in our system is markedly alleviated, leading to an overall improvement in the retrieval performance in terms of Mean Reciprocal Rank (MRR) and recall.

Item Type:Book Sections
Status:Published
Glasgow Author(s) Enlighten ID:Ounis, Professor Iadh and Rogers, Dr Simon and Thuma, Mr Edwin
Authors: Thuma, E., Rogers, S., and Ounis, I.
College/School:College of Science and Engineering > School of Computing Science
Publisher:Springer
ISBN:9783642388231
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