Applying Natural Language Processing Techniques for Effective Persian- English Cross-Language Information Retrieval

Much attention has recently been paid to natural language processing in information storage and retrieval. This paper describes how the application of natural language processing (NLP) techniques can enhance cross-language information retrieval (CLIR). Using a semi-experimental technique, we took Farsi queries to retrieve relevant documents in English. For translating Persian queries, we used a bilingual machinereadable dictionary. NLP techniques such as tokenization, morphological analysis and part of speech tagging were used in pre-and- post translation phases. Results showed that applying NLP techniques yields more effective CLIR performance.