Chapter

Multilingual Information Access Evaluation I. Text Retrieval Experiments

Volume 6241 of the series Lecture Notes in Computer Science pp 58-61

Document Expansion, Query Translation and Language Modeling for Ad-Hoc IR

  • Johannes LevelingAffiliated withCarnegie Mellon UniversityCentre for Next Generation Localisation, School of Computing, Dublin City University
  • , Dong ZhouAffiliated withCarnegie Mellon UniversityCentre for Next Generation Localisation, Computer Science Department, Trinity College Dublin
  • , Gareth J. F. JonesAffiliated withCarnegie Mellon UniversityCentre for Next Generation Localisation, School of Computing, Dublin City University
  • , Vincent WadeAffiliated withCarnegie Mellon UniversityCentre for Next Generation Localisation, Computer Science Department, Trinity College Dublin

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Abstract

For the multilingual ad-hoc document retrieval track (TEL) at CLEF, Trinity College Dublin and Dublin City University participated in collaboration. Our retrieval experiments focused on i) document expansion using an entry vocabulary module, ii) query translation with Google translate and a statistical MT system, and iii) a comparison of the retrieval models BM25 and language modeling (LM). The major results are that document expansion did not increase MAP; topic translation using the statistical MT system resulted in about 70% of the mean average precision (MAP) achieved compared to Google translate, and LM performs equally or slightly better than BM25. The bilingual retrieval French and German to English experiments obtained 89% and 90% of the best MAP for monolingual English.