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Deep Fusion of Multiple Term-Similarity Measures For Biomedical Passage Retrieval
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Event-based summarization using a centrality-as-relevance model
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A logical representation of Arabic questions toward automatic passage extraction from the Web
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In: ISSN: 1381-2416 ; EISSN: 1572-8110 ; International Journal of Speech Technology ; https://hal.archives-ouvertes.fr/hal-01794688 ; International Journal of Speech Technology, Springer Verlag, 2017, 20 (2), pp.339 - 353. ⟨10.1007/s10772-017-9411-7⟩ (2017)
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An overview of the BIOASQ large-scale biomedical semantic indexing and question answering competition
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In: ISSN: 1471-2105 ; BMC Bioinformatics ; https://hal.sorbonne-universite.fr/hal-01156600 ; BMC Bioinformatics, BioMed Central, 2015, 16 (1), pp.138. ⟨10.1186/s12859-015-0564-6⟩ (2015)
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LIMSI-CNRS@ CLEF 2015: Tree Edit Beam Search for Multiple Choice Question Answering.
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In: Working Notes of CLEF 2015 - Conference and Labs of the Evaluation forum ; CLEF 2015 ; https://hal.archives-ouvertes.fr/hal-02289246 ; CLEF 2015, Sep 2015, Toulouse, France ; http://ceur-ws.org/Vol-1391/ (2015)
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LIMSI-CNRS@ CLEF 2014: Invalidating Answers for Multiple Choice Question Answering.
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In: Working Notes for CLEF 2014 Conference, Sheffield, UK, September 15-18, 2014 ; CLEF 2014 ; https://hal.archives-ouvertes.fr/hal-02290008 ; CLEF 2014, Sep 2014, Sheffield, United Kingdom. pp.1386--1394 (2014)
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SNUMedinfo at CLEFeHealth2013 task 3
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In: http://ceur-ws.org/Vol-1179/CLEF2013wn-CLEFeHealth-ChoiEt2013.pdf (2013)
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Voice-QA: Evaluating the Impact of Misrecognized Words on Passage Retrieval
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In: ISSN: 0302-9743 ; Lecture Notes in Computer Science ; Advances in Artificial Intelligence - IBERAMIA 2012 ; 13th Ibero-American Conference on AI ; https://hal.archives-ouvertes.fr/hal-00825246 ; 13th Ibero-American Conference on AI, Nov 2012, Cartagena de Indias, Colombia. pp.462-471 (2012)
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Finding answers to questions, in text collections or web, in open domain or specialty domains
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In: Next Generation Search Engines: Advanced Models for Information Retrieval ; https://hal.archives-ouvertes.fr/hal-02289728 ; Jouis, Christophe AND Biskri, Ismail AND Ganascia, Jean-Gabriel AND Roux, Magali. Next Generation Search Engines: Advanced Models for Information Retrieval, IGI Global, pp.344--370, 2012 (2012)
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| 11 |
Voice-QA: evaluating the impact of misrecognized words on passage retrieval
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DCU at the NTCIR-9 spokendoc passage retrieval task
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In: Eskevich, Maria orcid:0000-0002-1242-0753 and Jones, Gareth J.F. orcid:0000-0003-2923-8365 (2011) DCU at the NTCIR-9 spokendoc passage retrieval task. In: The 9th NTCIR Workshop Meeting, 6-9 Dec 2011, Tokyo, Japan. ISBN 978-4-86049-056-0 (2011)
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Recuperación de pasajes multilingüe para la búsqueda de respuestas ; Multilingue passage retrieval for question answering
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Gómez, José M.. - : Sociedad Española para el Procesamiento del Lenguaje Natural, 2008
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Question Analysis and Answer Passage Retrieval for Opinion Question Answering Systems
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In: http://www.aclclp.org.tw/clclp/v13n3/v13n3a3.pdf (2007)
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Scoring missing terms in information retrieval tasks
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In: http://hachita.nmsu.edu/ref/Terra-cikm04-MissingTermsIR.pdf (2004)
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| 19 |
Measurement, Experimentation
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In: http://www.cs.otago.ac.nz/sigirfocus/paper_13.pdf
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| 20 |
A Semantic Approach to Boost Passage Retrieval Effectiveness for Question Answering
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In: http://crpit.com/confpapers/CRPITV48Ofoghi.pdf
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Abstract:
In the current state of the rapid growth of information resources and the huge number of requests submitted by users to existing information retrieval systems; recently, Question Answering systems have attracted more attention to meet information needs providing users with more precise and focused retrieval units. As one of the most challenging and important processes of such systems is to retrieve the best related text excerpts with regard to the questions, we propose a novel approach to exploit not only the syntax of the natural language of the questions and texts, but also the semantics relayed beneath them via a semantic question rewriting and passage retrieval task. The semantic structure used to address the surface mismatch of the semantically related passages and queries is FrameNet which is a lexical resource for English constituted based on frame semantics. We have run our proposed approach on a subset of the TREC 2004 factoid questions to retrieve passages containing correct answers from the AQUAINT collection and we have obtained promising results.
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Keyword:
FrameNet; Passage Retrieval; Question Answering; Semantic Boosting
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URL: http://crpit.com/confpapers/CRPITV48Ofoghi.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.83.1433
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