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Overview of the ShARe/CLEF eHealth evaluation lab 2014
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In: Kelly, Liadh orcid:0000-0003-1131-5238 , Goeuriot, Lorraine orcid:0000-0001-7491-1980 , Suominen, Hanna, Schreck, Tobias, Leroy, Gondy, Mowery, Danielle L., Velupillai, Sumithra, Chapman, Wendy, Martinez, David, Zuccon, Guido and Palotti, Joao (2014) Overview of the ShARe/CLEF eHealth evaluation lab 2014. In: Conference and Labs for the Evaluation Forum (CLEF 2014), 15-18 Sept 2014, Sheffield, UK. ISBN 978-3-319-11382-1 (2014)
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ShARe/CLEF eHealth evaluation lab 2014, task 3: user-centred health information retrieval
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In: Goeuriot, Lorraine orcid:0000-0001-7491-1980 , Kelly, Liadh orcid:0000-0003-1131-5238 , Li, Wei B. orcid:0000-0001-7347-3501 , Palotti, Joao, Pecina, Pavel, Zuccon, Guido, Hanbury, Allan, Jones, Gareth J.F. orcid:0000-0002-4033-9135 and Mueller, Henning (2014) ShARe/CLEF eHealth evaluation lab 2014, task 3: user-centred health information retrieval. In: Conference and Labs for the Evaluation Forum (CLEF 2014), 15-18 Sept 2014, Sheffield, UK. (2014)
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Khresmoi professional: multilingual, multimodal professional medical search
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In: Kelly, Liadh orcid:0000-0003-1131-5238 , Dungs, Sebastian, Kriewel, Sascha, Hanbury, Allan, Goeuriot, Lorraine orcid:0000-0001-7491-1980 , Jones, Gareth J.F. orcid:0000-0002-4033-9135 , Langs, Georg and Mueller, Henning (2014) Khresmoi professional: multilingual, multimodal professional medical search. In: 36th European Conference on Information Retrieval (ECIR 2014), 13-16 Apr 2014, Amsterdam, Netherlands. (2014)
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Adaptation of machine translation for multilingual information retrieval in the medical domain
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Goeuriot, Lorraine; Kelly, Liadh; Dušek, Ondřej; Hlaváčová, Jaroslava; Pecina, Pavel; Jones, Gareth J.F.; Hajič, Jan; Mareček, David; Urešová, Zdeňka; Rosa, Rudolf; Popel, Martin; Novák, Michal; Leveling, Johannes; Tamchyna, Aleš
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In: Pecina, Pavel, Dušek, Ondřej, Goeuriot, Lorraine orcid:0000-0001-7491-1980 , Hajič, Jan, Hlaváčová, Jaroslava, Jones, Gareth J.F. orcid:0000-0002-4033-9135 , Kelly, Liadh orcid:0000-0003-1131-5238 , Leveling, Johannes orcid:0000-0003-0603-4191 , Mareček, David, Novák, Michal, Popel, Martin, Rosa, Rudolf, Tamchyna, Aleš and Urešová, Zdeňka (2014) Adaptation of machine translation for multilingual information retrieval in the medical domain. Artificial Intelligence in Medicine, 61 (3). pp. 165-185. ISSN 1873-2860 (2014)
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Abstract:
Objective. We investigate machine translation (MT) of user search queries in the context of cross-lingual information retrieval (IR) in the medical domain. The main focus is on techniques to adapt MT to increase translation quality; however, we also explore MT adaptation to improve eectiveness of cross-lingual IR. Methods and Data. Our MT system is Moses, a state-of-the-art phrase-based statistical machine translation system. The IR system is based on the BM25 retrieval model implemented in the Lucene search engine. The MT techniques employed in this work include in-domain training and tuning, intelligent training data selection, optimization of phrase table configuration, compound splitting, and exploiting synonyms as translation variants. The IR methods include morphological normalization and using multiple translation variants for query expansion. The experiments are performed and thoroughly evaluated on three language pairs: Czech–English, German–English, and French–English. MT quality is evaluated on data sets created within the Khresmoi project and IR eectiveness is tested on the CLEF eHealth 2013 data sets. Results. The search query translation results achieved in our experiments are outstanding – our systems outperform not only our strong baselines, but also Google Translate and Microsoft Bing Translator in direct comparison carried out on all the language pairs. The baseline BLEU scores increased from 26.59 to 41.45 for Czech–English, from 23.03 to 40.82 for German–English, and from 32.67 to 40.82 for French–English. This is a 55% improvement on average. In terms of the IR performance on this particular test collection, a significant improvement over the baseline is achieved only for French–English. For Czech–English and German–English, the increased MT quality does not lead to better IR results. Conclusions. Most of the MT techniques employed in our experiments improve MT of medical search queries. Especially the intelligent training data selection proves to be very successful for domain adaptation of MT. Certain improvements are also obtained from German compound splitting on the source language side. Translation quality, however, does not appear to correlate with the IR performance – better translation does not necessarily yield better retrieval. We discuss in detail the contribution of the individual techniques and state-of-the-art features and provide future research directions.
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Keyword:
Information retrieval; Machine translating; Medical information retrieval
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URL: http://doras.dcu.ie/20117/
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ShARe/CLEF eHealth evaluation lab 2014, task 3: user-centred health information retrieval
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In: Goeuriot, Lorraine orcid:0000-0001-7491-1980 , Kelly, Liadh orcid:0000-0003-1131-5238 , Li, Wei B. orcid:0000-0001-7347-3501 , Palotti, Joao, Zuccon, Guido, Hanbury, Allan, Jones, Gareth J.F. orcid:0000-0002-4033-9135 and Mueller, Henning (2014) ShARe/CLEF eHealth evaluation lab 2014, task 3: user-centred health information retrieval. CLEF 2014 Online Working Notes, 1180 . pp. 43-61. ISSN 1613-0073 (2014)
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Khresmoi professional: multilingualsSemantic search for medical professionals
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In: Kelly, Liadh orcid:0000-0003-1131-5238 , Hanbury, Allan, Jones, Gareth J.F. orcid:0000-0003-2923-8365 , Goeuriot, Lorraine orcid:0000-0001-7491-1980 and Mueller, Henning (2013) Khresmoi professional: multilingualsSemantic search for medical professionals. In: SIGIR 2013 Health Search and Discovery HSD workshop, 1 Aug 2013, Dublin, Ireland. (2013)
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