6. The method as recited in claim 2 , wherein the feature vector f (q f , q e ) includes at least two of the feature functions selected from bilingual dictionary-based translation score, bidirectional translation score, frequency in Web mining snippets, and monolingual query suggestion-based feature.
2. The method as recited in claim 1 , wherein the cross-lingual query similarity score of the input query in source language q e and the candidate query in target language q f is computed using an equation sim CL (q f ,q e )=w·φ(ƒ(q f ,q e )), where sim CL (q f , q e ) is the cross-lingual query similarity score, ƒ(q f , q e ) is a feature vector, φ is a mapping from an input feature space onto a kernel space, and w is a weight vector in the kernel space.