About: Adaptation of machine translation for multilingual information retrieval in medical domain

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Adaptation of machine translation for multilingual information retrieval in medical domain Goto Sponge NotDistinct Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://dx.doi.org/10.1016/j.artmed.2014.01.004], [http://www.sciencedirect.com/science/article/pii/S0933365714000062
Description	In this work, we investigate machine translation (MT) of search queries in the context of cross-lingual information retrieval (IR) in the domain of medicine. The main focus is on MT adaptation techniques to increase translation quality, however we also explore MT adaptation to improve cross-lingual IR directly. The experiments described herein have been performed and thoroughly evaluated for MT quality on the datasets created within the Khresmoi project and for IR performance on the CLEF eHealth 2013 datasets on three language pairs: Czech-English, German-English, and French-English. The search query translation results achieved in our experiments are outstanding - our systems outperformed not only our strong baselines, but also the Google Translate and Microsoft Bing Translator in direct comparison carried out on all the language pairs. In terms of the retrieval performance on this particular test collection, a significant improvement over the baseline has been achieved only for French-English. Throu In this work, we investigate machine translation (MT) of search queries in the context of cross-lingual information retrieval (IR) in the domain of medicine. The main focus is on MT adaptation techniques to increase translation quality, however we also explore MT adaptation to improve cross-lingual IR directly. The experiments described herein have been performed and thoroughly evaluated for MT quality on the datasets created within the Khresmoi project and for IR performance on the CLEF eHealth 2013 datasets on three language pairs: Czech-English, German-English, and French-English. The search query translation results achieved in our experiments are outstanding - our systems outperformed not only our strong baselines, but also the Google Translate and Microsoft Bing Translator in direct comparison carried out on all the language pairs. In terms of the retrieval performance on this particular test collection, a significant improvement over the baseline has been achieved only for French-English. Throu (en)
Title	Adaptation of machine translation for multilingual information retrieval in medical domain Adaptation of machine translation for multilingual information retrieval in medical domain (en)
skos:prefLabel	Adaptation of machine translation for multilingual information retrieval in medical domain Adaptation of machine translation for multilingual information retrieval in medical domain (en)
skos:notation	RIV/00216208:11320/14:10289237!RIV15-MSM-11320___
http://linked.open...avai/riv/aktivita	I P
http://linked.open...avai/riv/aktivity	I, P(GBP103/12/G084)
http://linked.open...iv/cisloPeriodika	3
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Hajič, Jan Popel, Martin Novák, Michal Tamchyna, Aleš Dušek, Ondřej Mareček, David Rosa, Rudolf Hlaváčová, Jaroslava Urešová, Zdeňka Pecina, Pavel
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Univerzita Karlova v Praze / Matematicko-fyzikální fakulta
http://linked.open...dnocenehoVysledku	1574
http://linked.open...ai/riv/idVysledku	RIV/00216208:11320/14:10289237
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	domain; medical; retrieval; information; multilingual; translation; machine; adaptation (en)
http://linked.open.../riv/klicoveSlovo	medical multilingual adaptation information domain machine translation retrieval
http://linked.open...odStatuVydavatele	NL - Nizozemsko
http://linked.open...ontrolniKodProRIV	[7EBA700171FA]
http://linked.open...i/riv/nazevZdroje	Artificial Intelligence in Medicine
http://linked.open...in/vavai/riv/obor	AI
http://linked.open...ichTvurcuVysledku	10 (xsd:int)
http://linked.open...cetTvurcuVysledku	14 (xsd:int)
http://linked.open...vavai/riv/projekt	Center for Large Scale Multi-modal Data Interpretation
http://linked.open...UplatneniVysledku	2014
http://linked.open...v/svazekPeriodika	61
http://linked.open...iv/tvurceVysledku	Hajič, Jan Mareček, David Novák, Michal Pecina, Pavel Popel, Martin Dušek, Ondřej Tamchyna, Aleš Rosa, Rudolf Hlaváčová, Jaroslava Urešová, Zdeňka Goeuriot, Lorraine Jones, Gareth J.F. Kelly, Liadh Leveling, Johannes
issn	0933-3657
number of pages	21 (xsd:int)
http://bibframe.org/vocab/doi	10.1016/j.artmed.2014.01.004
http://localhost/t...ganizacniJednotka	11320

Faceted Search & Find service v1.16.118 as of Jun 21 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software