Contribution à l'analyse et l'évaluation des requêtes expertes : cas du domaine médical

Abstract : The research topic of this document deals with a particular setting of medical information retrieval (IR), referred to as expert based information retrieval. We were interested in information needs expressed by medical domain experts like praticians, physicians, etc. It is well known in information retrieval (IR) area that expressing queries that accurately reflect the information needs is a difficult task either in general domains or specialized ones and even for expert users. Thus, the identification of the users' intention hidden behind queries that they submit to a search engine is a challenging issue. Moreover, the increasing amount of health information available from various sources such as government agencies, non-profit and for-profit organizations, internet portals etc. presents oppor- tunities and issues to improve health care information delivery for medical professionals, patients and general public. One critical issue is the understanding of users search strategies and tactics for bridging the gap between their intention and the delivered information. In this thesis, we focus, more particularly, on two main aspects of medical information needs dealing with the expertise which consist of two parts, namely : - Understanding the users intents behind the queries is critically important to gain a better insight of how to select relevant results. While many studies investigated how users in general carry out exploratory health searches in digital environments, a few focused on how are the queries formulated, specifically by domain expert users. We address more specifically domain expert health search through the analysis of query attributes namely length, specificity and clarity using appropriate proposed measures built according to different sources of evidence. In this respect, we undertake an in-depth statistical analysis of queries issued from IR evalua- tion compaigns namely Text REtrieval Conference (TREC) and Conference and Labs of the Evaluation Forum (CLEF) devoted for different medical tasks within controlled evaluation settings. - We address the issue of answering PICO (Population, Intervention, Comparison and Outcome) clinical queries formulated within the Evidence Based Medicine framework. The contributions of this part include (1) a new algorithm for query elicitation based on the semantic mapping of each facet of the query to a reference terminology, and (2) a new document ranking model based on a prioritized aggregation operator. we tackle the issue related to the retrieval of the best evidence that fits with a PICO question, which is an underexplored research area. We propose a new document ranking algorithm that relies on semantic based query expansion leveraged by each question facet. The expansion is moreover bounded by the local search context to better discard irrelevant documents. The experimental evaluation carried out on the CLIREC dataset shows the benefit of our approaches.
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Eya Znaidi. Contribution à l'analyse et l'évaluation des requêtes expertes : cas du domaine médical. Recherche d'information [cs.IR]. Université Paul Sabatier - Toulouse III, 2016. Français. ⟨NNT : 2016TOU30054⟩. ⟨tel-01515377⟩

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