Gcon: a graph-based technique for resolving ambiguity in query translation candidates

Authors:
Dong Zhou;Mark Truran;Tim Brailsford;Helen Ashman;James Goulding
Affiliations:
University of Nottingham, Nottingham, UK;University of Teesside, Middlesbrough, UK;University of Nottingham, Nottingham, UK;University of South Australia, Crawley, WA, Australia;University of Nottingham, Nottingham, UK
Venue:
Proceedings of the 2008 ACM symposium on Applied computing
Year:
2008

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Abstract

In the field of cross-language information retrieval (CLIR), the resolution of lexical ambiguity is a key challenge. Common mechanisms for the translation of query terms from one language to another typically produce a set of possible translation candidates, rather than some authoritative result. Correctly reducing a list of possible candidates down to a single translation is an enduring problem. Thus far, solutions have concentrated upon the use of the use of term co-occurrence information to guide the process of resolving translation-based ambiguity. In this paper we introduce a new disambiguation strategy which employs a graph-based analysis of generated co-occurrence data to determine the most appropriate translation for a given term.