Abstract
To date, attempts for applying syntactic information in the document-based retrieval model dominant have led to little practical improvement, mainly due to the problems associated with the integration of this kind of information into the model. In this article we propose the use of a locality-based retrieval model for reranking, which deals with syntactic linguistic variation through similarity measures based on the distance between words. We study two approaches whose effectiveness has been evaluated on the CLEF corpus of Spanish documents.KeywordsInformation RetrievalRelevant DocumentData FusionRetrieval ModelQuery TermThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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