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Analyse de documents et du comportement des utilisateurs pour améliorer l'accès à l'information

Abstract : The constant increase of available documents and tools to access them has led to a change of research practices. For a few years now, more and more information retrieval platforms are made available online to the scientific community or the public. This data deluge is a great opportunity for users seeking information. However, it comes with new problems and new challenges to overcome. Formerly, the main issue for researchers was to identify if a particular resource existed. Today, the challenge is more about finding how to access pertinent information. We have identified two distinct levers to limit the impact of this new search paradigm. First, we believe that it is necessary to analyze how the different search platforms are used. To be able to understand and read into users behavior is a necessary step to comprehend what users understand, and to identify what they need to get an in-depth understanding of the operation of such platforms. Indeed, most systems act as black boxes which conceal the underlying transformations applied on data. Users do not need to understand in details how those algorithms work. However, because those algorithms have a major impact on the accessibility of information, and need to be taken into account during the exploitation of search results. Why is the search engine returning those particular results ? Why is this document more pertinent than another ? Such seemingly naive questions are nonetheless essential to undertake an analytical approach of the information search and retrieval task. We think that users have a right and a duty to question themselves about the relevance of such and such tool at their disposal. To help them cope with these issues, we developped a dual-use information search platform. On the one hand, it can be used to observe and understand user behavior. On the other hand, it can be used as a pedagogical medium to highlight research biases users can be exposed to. At the same time, we believe that the tools themselves must be improved. In the second part of this thesis, we study the impact that the quality of documents can have on their accessibility. Because of the increase of documents available online, human operators are less and less able to insure their quality. Thus, there is a need to set up new strategies to improve the way search platform operate and process documents. We propose a new method to automatically identify and correct errors generated by information extraction process such as OCR.
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Axel Jean-Caurant. Analyse de documents et du comportement des utilisateurs pour améliorer l'accès à l'information. Recherche d'information [cs.IR]. Université de La Rochelle, 2018. Français. ⟨NNT : 2018LAROS028⟩. ⟨tel-02317770⟩

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