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Document expansion, query translation and language modeling for ad-hoc IR

Leveling, Johannes orcid logoORCID: 0000-0003-0603-4191, Zhou, Dong, Jones, Gareth J.F. orcid logoORCID: 0000-0003-2923-8365 and Wade, Vincent (2010) Document expansion, query translation and language modeling for ad-hoc IR. In: Multilingual Information Access Evaluation I, Corfu, Greece. ISBN 978-3-642-15753-0

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.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Workshop
Refereed:Yes
Uncontrolled Keywords:Language modelling; LM; mean average precision; MAP
Subjects:Computer Science > Information retrieval
DCU Faculties and Centres:Research Institutes and Centres > Centre for Next Generation Localisation (CNGL)
Research Institutes and Centres > National Centre for Language Technology (NCLT)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: Multilingual Information Access Evaluation I. Text Retrieval Experiments. Lecture Notes in Computer Science 6241. Springer-Verlag. ISBN 978-3-642-15753-0
Publisher:Springer-Verlag
Official URL:http://www.springerlink.com/content/m28681051tgkt7...
Copyright Information:© 2010 Springer-Verlag. The original publication is available at www.springerlink.com
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License
ID Code:16031
Deposited On:09 Jun 2011 08:52 by Shane Harper . Last Modified 25 Oct 2018 10:51
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