We have used Galois lattices for mining hydrobiological data. These data are about macrophytes, that are macroscopic plants living in water bodies. These plants are characterized by several biological traits, that own several modalities. Our aim is to cluster the plants according to their common traits and modalities and to find out the relations between traits. Galois lattices are efficient methods for such an aim, but apply on binary data. In this article, we detail a few approaches we used to transform complex hydrobiological data into binary data and compare the first results obtained thanks to Galois lattices.
- Pub Date:
- November 2008
- Computer Science - Artificial Intelligence;
- Quantitative Biology - Quantitative Methods
- International Workshop on Advances in Conceptual Knowledge Engineering (ACKE'07), Regensburg : Allemagne (2007)