The successful application of natural language processing for information retrieval

Abstract

In this paper, a novel model for monolingual Information Retrieval in English and Spanish language is proposed. This model uses Natural Language Processing techniques (a POS-tagger, a Partial Parser, and an Anaphora Resolver) in order to improve the precision of traditional IR systems, by means of indexing the “entities” and the “relations” between these entities in the documents. This model is evaluated on both the Spanish and English CLEF corpora. For the English queries, there is a maximum increase of 35.11% in the average precision. For the Spanish queries, the maximum increase is 37.18%.