Paper: Resolving Translation Ambiguity And Target Polysemy In Cross-Language Information Retrieval

ACL ID P99-1028
Title Resolving Translation Ambiguity And Target Polysemy In Cross-Language Information Retrieval
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1999
Authors

This paper deals with translation ambiguity and target polysemy problems together. Two monolingual balanced corpora are employed to learn word co-occurrence for translation ambiguity resolution, and augmented translation restrictions for target polysemy resolution. Experiments show that the model achieves 62.92% of monolingual information retrieval, and is 40.80% addition to the select-all model. Combining the target polysemy resolution, the retrieval performance is about 10.11% increase to the model resolving translation ambiguity only.