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Cross language information retrieval based on concept base and language grid

This paper describes query translation using multiple language resources and concept base method for the Cross Language Information Retrieval (CLIR). In the proposed method, the queries are translated by multiple machine translation systems on the Language Grid. Then the queries are expanded by translated compound words, noun phrases with the bilingual dictionary. At the same time, document related to the translated query are retrieved with a TF-IDF term weighting model. Then, top 100 retrieved documents are re-ranked by a specificity-considered concept base with noun phrases and compound words extracted from the query. Re-ranked results are combined with the results retrieved by the Probabilistic model. For the evaluation of the proposed method, we use the average precision of the interpolated recall and precision at to compare with the NTCIR1 participation systems. The proposed system achieved the highest precision compared with the NTCIR1 participating systems.