Using Concept Lattice for Visual Navigation Assistance and Attribute Selection

Jean Villerd (1) , Sylvie Ranwez (1) , Michel Crampes (1)

1 LGI2P - Laboratoire de Génie Informatique et Ingénierie de Production

The increasing size of structured data that are digitally avail- able emphasizes the crucial need for more suitable representation tools than the traditional textual list of results. A suitable visual representation should both reflect the database's structure for navigation purpose and allow performing visual analytical tasks for knowledge extraction purpose. In this paper we present a visual navigation method that uses a Galois lattice to represent the database's structure. Our method takes advantage of this structure to provide a progressive and coherent navigation in the database. Two views are jointly presented. The first one represents the overall structure of the database while in the second one more precise views are successively given during the navigation process. Moreover, beyond the navigation task, we aim to propose a visual assistance for more analytical tasks. We show how this representation, combined with data analysis techniques, can be used both for navigation and attribute selection while keeping users' mental map.

Mots clés: Formal Concept Analysis; Information Visualization

Domaines: Intelligence artificielle [cs.AI]; Interface homme-machine [cs.HC]

Jean Villerd, Sylvie Ranwez, Michel Crampes. Using Concept Lattice for Visual Navigation Assistance and Attribute Selection. 16th International Conference on Conceptual Structures (ICCS 2008), Jul 2008, Toulouse, France. pp.41-48. ⟨hal-00807618⟩