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Cadre général pour la recherche d'information et l'extraction de connaissances par l'exploration de treillis

Abstract : During the last two decades, data have literrally overwhelmed the world. Indeed a huge amount of heterogenous data is daily produced, so that techniques of Information Retrieval have to evolve to order them and select relevant ones. On the other side, techniques of Knowledge Discovery are able to extract a potentially exponential number of patterns from data, especially association rules, so that new tools have to be defined to help data analysts in their job. Both information retrieval and knowledge discovery address the same issue : they structure and organize data. Nevertheless their points of view are different : the former selects and ranks data whether the latter classifies and clusters them. Formal Concept Analysis (FCA), introduced by R. Wille, uses concept lattices to reveal both an order and a classification inside data. However, it is well known in the FCA community, that these concept lattices may have an exponential size with respect to data. For all these reasons, tools to reduce the size of data, or lattices, are needed. In this thesis, some distributed algorithms for FCA have been designed in order to reduce input data into small pieces. Different decompositions of lattices have also been studied or defined, some based on congruence relations, other on tolerance relations. At last, to help the user in his choices of reduction, a general framework, named LattExp, have been defined. LattExp provides a navigation facility through reductions/decompositions and guide the user in his choices.
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Submitted on : Friday, April 13, 2018 - 9:21:05 AM
Last modification on : Wednesday, October 14, 2020 - 3:55:18 AM


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  • HAL Id : tel-01765724, version 1



Jean-François Viaud. Cadre général pour la recherche d'information et l'extraction de connaissances par l'exploration de treillis. Recherche d'information [cs.IR]. Université de La Rochelle, 2017. Français. ⟨NNT : 2017LAROS012⟩. ⟨tel-01765724⟩



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