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Ranking studies for systematic reviews using query adaptation : University of Sheffield's approach to CLEF eHealth 2019 task 2 working notes for CLEF 2019
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Improving ranking for systematic reviews using query adaptation
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CLEF 2017 NewsREEL overview: A stream-based recommender task for evaluation and education
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The Fudan Participation in the 2015 BioASQ Challenge: Large-scale Biomedical Semantic Indexing and Question Answering
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CEA LIST's participation at the CLEF CHiC 2013
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In: 2013 Cross Language Evaluation Forum Conference, CLEF 2013 ; https://hal-cea.archives-ouvertes.fr/cea-01844707 ; 2013 Cross Language Evaluation Forum Conference, CLEF 2013, Sep 2013, Valencia, Spain (2013)
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Abstract:
Conference of 2013 Cross Language Evaluation Forum Conference, CLEF 2013 ; Conference Date: 23 September 2013 Through 26 September 2013; Conference Code:110354 ; International audience ; For our first participation to the CLEF CHiC Lab, we submitted runs to the mul tilingual ad-hoc and multilingual semantic enrichment tasks. Given the strong mul tilingual character of the evaluation corpus, the main objectives of the experiments were to test the efficiency of semantic topic expansion and consolidation based on Explicit Semantic Analysis (ESA) versions in different languages. Another objective was multilingual fusion of results obtained in the different languages of the corpus. ESA was adapted for the 10 languages that are best represented in the Europeana corpus. Wikipedia dumps from March 2012 were used for French and English and from March 2013 for the other languages. One problem that arises when model ing short documents, such as queries, with classical ESA vectors no information is available whether the concept is related to the entire topic only to a part of it. To overcome this problem, two adaptations of ESA (ESA-C) are Wikipedia concepts that are linked to the highest number of concepts from the original topic. In the ad-hoc task, ESA and ESA-C have two roles: to expand the topic with related con cepts and to create consolidated topic models which contain the original topic words along with other related keywords. We submitted both monolingual and multilingual runs without topic expansion and using topic expansion and consolidation with clas sical ESA and ESA-C. The best results are obtained in a multilingual setting with no expansion and ESA-C topic consolidation. For the semantic enrichment task, we propose lists of related Wikipedia concepts using either a monolingual ranking or a voting scheme that surfaces related concepts that appear in the largest number of languages. Here, the best results are obtained in a monolingual ranking configuration that exploits ESA-C.
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Keyword:
[INFO]Computer Science [cs]; Ad hoc tasks; Computational linguistics; Europeana; Expansion; Explicit semantic analysis; Multi-lingual information retrieval; Semantic enrichment; Semantics; Topic model; Topic words; Voting schemes
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URL: https://hal-cea.archives-ouvertes.fr/cea-01844707
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Overview of iCLEF 2008: Search Log Analysis for Multilingual Image Retrieval.
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GeoCLEF 2007: the CLEF 2007 cross-language geographic information retrieval track overview
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From CLEF to TrebleCLEF: promoting technology transfer for multilingual information retrieval
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