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Book Sections Year : 2022

Adjusting the Exploration Flow in Relational Concept Analysis

Abstract

In this paper, we focus on the exploration of multi-relational datasets, and the various ways they can be analyzed using Relational Concept Analysis (RCA), an extension of Formal Concept Analysis (FCA). RCA uses several scaling operators that make the process highly tunable, allowing a high flexibility in the exploration and in the results. In return, the multiplicity of choices that can be made when performing an analysis task potentially overwhelms the expert. We thus propose three overlays for helping users control and foresee the results of their choices. Our proposition is exemplified on a dataset about the hydro-ecological state of watercourses.
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Dates and versions

lirmm-04089524 , version 1 (04-05-2023)

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Amirouche Ouzerdine, Agnès Braud, Xavier Dolques, Marianne Huchard, Florence Le Ber. Adjusting the Exploration Flow in Relational Concept Analysis: An Experience on a Watercourse Quality Dataset. Rakia Jaziri; Arnaud Martin; Marie-Christine Rousset; Lydia Boudjeloud-Assala; Fabrice Guillet. Advances in Knowledge Discovery and Management, 1004 (9), Springer, pp.175-198, 2022, Studies in Computational Intelligence, 978-3-030-90286-5. ⟨10.1007/978-3-030-90287-2_9⟩. ⟨lirmm-04089524⟩
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