A study of user profile representation for personalized cross language information retrieval
Purpose With an increase in the amount of multilingual content on the World Wide Web, users are often striving to access information provided in a language of which they are non native speakers. The purpose of this paper is to present a comprehensive study of user profile representation techniques and investigate their use in personalized cross language information retrieval (CLIR) systems through the means of personalized query expansion. Design/methodology/approach The user profiles consist of weighted terms computed by using frequency based methods such as tf idf and BM25, as well as various latent semantic models trained on monolingual documents and cross lingual comparable documents. This paper also proposes an automatic evaluation method for comparing various user profile generation techniques and query expansion methods. Findings Experimental results suggest that latent semantic weighted user profile representation techniques are superior to frequency based methods, and are particularly suita.
Aslib J. Inf. Manag.