One of the main hurdles to improved CLIR effectiveness is resolving ambiguity associated with translation. Availability of resources is also a problem. First we present a technique based on co-occurrence statistics from unlinked corpora which can be used to reduce the ambiguity associated with phrasal and term translation. We then combine this method with other techniques for reducing ambiguity and achieve more than 90% monolingual effectiveness. Finally, we compare the co-occurrence method with parallel corpus and machine translation techniques and show that good retrieval effectiveness can be achieved without complex resources.
Lisa, et al. REF in 1998 proposed a method for resolving ambiguity in query translation and phrasal translation by using statistics co-occurrence analysis from unlinked corpus and combines this technique with other techniques for resolving ambiguity and achieve more than 90% of CLIR performance while compared to the monolingual performance and also author compared their method with machine translation and parallel corpus techniques and they proved that good performance of retrieval can be achieved without the use of complex resources.
Resolving ambiguity for cross-language retrieval
SIGIR '98
Computer Science