Paper: Multilingual Pseudo-Relevance Feedback: Performance Study of Assisting Languages

ACL ID P10-1137
Title Multilingual Pseudo-Relevance Feedback: Performance Study of Assisting Languages
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2010
Authors

In a previous work of ours Chinnakotla et al. (2010) we introduced a novel framework for Pseudo-Relevance Feed- back (PRF) called MultiPRF. Given a query in one language called Source, we used English as the Assisting Language to improve the performance of PRF for the source language. MulitiPRF showed re- markable improvement over plain Model Based Feedback (MBF) uniformly for 4 languages, viz., French, German, Hungar- ian and Finnish with English as the as- sisting language. This fact inspired us to study the effect of any source-assistant pair on MultiPRF performance from out of a set of languages with widely differ- ent characteristics, viz., Dutch, English, Finnish, French, German and Spanish. Carrying this further, we looked into the effect of using two assisting languages to- gether ...