Structured Translation for Cross-Language Information Retrieval
Structured Translation for Cross-Language Information Retrieval
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Date
2000-06-21
Authors
Sperer, Ruth
Oard, Douglas W.
Advisor
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Abstract
The paper introduces a query translation model that reflects the
structure of the cross-language information retrieval task. The model
is based on a structured bilingual dictionary in which the
translations of each term are clustered into groups with distinct
meanings. Query translation is modeled as a two-stage process, with
the system first determining the intended meaning of a query term and
then selecting translations appropriate to that meaning that might
appear in the document collection. An implementation of structured
translation based on automatic dictionary clustering is described and
evaluated by using Chinese queries to retrieve English documents.
Structured translation achieved an average precision that was
statistically indistinguishable from Pirkola's technique for very
short queries, but Pirkola's technique outperformed structured
translation on long queries. The paper concludes with some
observations on future work to improve retrieval effectiveness and on
other potential uses of structured translation in interactive
cross-language retrieval applications.
(Also cross-referenced as UMIACS-TR-2000-45, LAMP-TR-052)