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Conference Papers Year : 2010

Managing Information Fusion with Formal Concept Analysis

Zainab Assaghir
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Mehdi Kaytoue
Amedeo Napoli


The main problem addressed in this paper is the merging of numerical information provided by several sources (databases, experts...). Merging pieces of information into an interpretable and useful format is a tricky task even when an information fusion method is chosen. Fusion results may not be in suitable form for being used in decision analysis. This is generally due to the fact that information sources are heterogeneous and provide inconsistent information, which may lead to imprecise results. In this paper, we propose the use of Formal Concept Analysis and more specifically pattern structures for organizing the results of fusion methods. This allows us to associate any subset of sources with its information fusion result. Once a fusion operator is chosen, a concept lattice is built. With examples throughout this paper, we show that this concept lattice gives an interesting classification of fusion results. When the fusion global result is too imprecise, the method enables the users to identify what maximal subset of sources that would support a more precise and useful result. Instead of providing a unique fusion result, the method yields a structured view of partial results labelled by subsets of sources. Finally, an experiment on a real-world application has been carried out for decision aid in agricultural practices.

Dates and versions

inria-00600215 , version 1 (14-06-2011)



Zainab Assaghir, Mehdi Kaytoue, Amedeo Napoli, Henri Prade. Managing Information Fusion with Formal Concept Analysis. 7th International Conference Modeling Decisions for Artificial Intelligence (MDAI 2010), Oct 2010, Perpignan, France. pp.104-115, ⟨10.1007/978-3-642-16292-3_12⟩. ⟨inria-00600215⟩
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