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Text Retrieval with External Information

Aimof this paper is to propose a statistical strategy based on the Partial Least Squares Regression (PLSR) in order to exploit external information in Text Mining processes. We focus on Text Retrieval, a procedure aimed at finding interesting information in large textual collections. In order to exploit external information, often available in collections, we assume a dependence structure between two sets of textual variables. By means of PLSR a latent structure taking into account word similarities and external information is obtained. Projection of documents and queries on the obtained latent structure allows effective document retrieval. The suggested strategy is applied to data which consist of two sets of variables: words of journal article abstracts and their respective keywords. The investigated approach enables more effective documents retrieval, as it takes into account the external information given by the