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Robustness Evaluation of Entity Disambiguation Using Prior Probes: the Case of Entity Overshadowing ...
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Ranking Clarifying Questions Based on Predicted User Engagement ...
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Combining Lexical and Dense Retrieval for Computationally Efficient Multi-hop Question Answering ...
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Combining Lexical and Dense Retrieval for Computationally Efficient Multi-hop Question Answering ...
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Knowledge Graph Simple Question Answering for Unseen Domains ...
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Analysing the Effect of Clarifying Questions on Document Ranking in Conversational Search ...
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Overview of the CLEF eHealth Evaluation Lab 2019
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In: CLEF 2019: Experimental IR Meets Multilinguality, Multimodality, and Interaction pp 322-339 ; https://hal.archives-ouvertes.fr/hal-03156710 ; CLEF 2019: Experimental IR Meets Multilinguality, Multimodality, and Interaction pp 322-339, pp.322-339, 2019, ⟨10.1007/978-3-030-28577-7_26⟩ (2019)
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CLEF ehealth 2019 evaluation lab
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Kelly, Liadh; Goeuriot, Lorraine; Suominen, Hanna; Neves, Mariana; Kanoulas, Evangelos; Spijker, Rene; Azzopardi, Leif; Li, Dan; Jimmy; Palotti, João; Zuccon, Guido. - : Springer, 2019
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Abstract:
Since 2012 CLEF eHealth has focused on evaluation resource building efforts around the easing and support of patients, their next-of-kins, clinical staff, and health scientists in understanding, accessing, and authoring eHealth information in a multilingual setting. This year’s lab offers three tasks: Task 1 on multilingual information extraction; Task 2 on technology assisted reviews in empirical medicine; and Task 3 on consumer health search in mono- and multilingual settings. Herein, we describe the CLEF eHealth evaluation series to-date and then present the 2019 tasks, evaluation methodology, and resources.
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Keyword:
1700 Computer Science; 2614 Theoretical Computer Science; eHealth; Information extraction; Information management; Information storage and retrieval; Medical informatics; Systematic reviews
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URL: https://espace.library.uq.edu.au/view/UQ:cc956c4
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Improved and Robust Controversy Detection in General Web Pages Using Semantic Approaches under Large Scale Conditions ...
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Neural Vector Spaces for Unsupervised Information Retrieval ...
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