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New applications of Formal Concept Analysis: a Need for New Pattern Domains

Jean-François Boulicaut 1
1 DM2L - Data Mining and Machine Learning
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : We survey the results obtained by our research group (joint work with Jérémy Besson and Loïc Cerf, Kim-Ngan T. Nguyen, Marc Plantevit, and Céline Robardet) concerning the design of pattern domains to support knowledge discovery and information retrieval in arbitrary n-ary relations. Our contribution is related to Formal Concept Analysis and its recent developments in direction of, for instance, Triadic Concept Analysis. We focus on a real data mining perspective. It means that we need for both the design of scalable constraint-based mining algorithms and fault-tolerant approaches to support the discovery of relevant patterns from noisy data.
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Submitted on : Wednesday, June 29, 2016 - 3:48:04 PM
Last modification on : Wednesday, July 8, 2020 - 12:43:50 PM


  • HAL Id : hal-01339184, version 1


Jean-François Boulicaut. New applications of Formal Concept Analysis: a Need for New Pattern Domains. Formal Concept Analysis meets Information Retrieval FCAIR 2013 co-located with ECIR, Mar 2013, Moscow, Russia, 24th March 2013, Russia. pp.2-4. ⟨hal-01339184⟩



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