Translation Probabilities in Cross-language Information Retrieval

Translation ambiguity is a major problem in dictionary-based cross-language information retrieval. To attack the problem, indirect disambiguation approaches, which do not explicitly resolve translation ambiguity, rely on query-structuring techniques such as a structured Boolean model and Pirkola’s method. Direct disambiguation approaches try to assign translation probabilities to translation equivalents, normally by employing co-occurrence statistics of target language terms from target documents as disambiguation clues. Thus far, translation probabilities have not been well explored in terms of statistical query translation models, query formulation, or cross-lingual retrieval models, etc. In order to study the impact of translation probabilities on retrieval effectiveness in direct disambiguation approaches, this paper empirically investigates the following issues: different disambiguation factors affecting the calculation of translation probabilities, the comparison of cross-lingual query formulation techniques involving translation probabilities, the relationship between the accuracy of translation disambiguation and retrieval effectiveness, and the relationship between top n translations and retrieval effectiveness.