Abstract
In this paper, we present a Cross Language Information Retrieval (CLIR) approach using corpus driven query suggestion. We have used corpus statistics to gather a clue on selecting the right query terms when the translation of a specific query is missing or incorrect. The derived set of queries are ranked to select the top ranked queries. These top ranked queries are further used to perform query formulation. Using the re-formulated weighted query, we perform cross language information retrieval. The results are compared with the results of CLIR system with Google translation of user queries and CLIR with the proposed query suggestion approach. We have English and Tamil corpus of FIRE 2012 dataset and analyzed the effects of the proposed approach. The experimental results show that the proposed approach performs well with the incorrect translation of the queries.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.