This paper evaluates the effectiveness of query translation and disambiguation as well as expansion techniques on the CLEF Collections, using the SMART Information Retrieval System. We focus on the query translation, disambiguation and methods used to improve the effectiveness of information retrieval. A dictionary-based method in combination with a statistics-based method is used to avoid the problem of translation ambiguity. In addition, two expansion strategies are tested to see whether they improve the effectiveness of information retrieval: expansion via relevance feedback before and after translation as well as expansion via domain feedback after translation. This method achieved 85.30% of the monolingual counterpart, in terms of average precision.