Using Concept Lattices as a Visual Assistance for Attribute Selection

The increasing size of structured data that are digitally available 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.

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