Concept Analysis on Structured, Multi-valued and Incomplete Data

This paper presents an approach to Concept Analysis of structured, multivalued and incomplete data currently present in life science knowledge bases. We are concerned with tree structured objects, whose size may be variable. We focus on the composition relations between attributes in the learning process. The interest of the method is the ability to take into account both structural and value parts of the objects. An application on a coral knowledge base illustrates the advantages of the method.

• Type: Conference
• Year: 2007
• Where: CLA
• Authors: David Grosser, Henri Ralambondrainy
• Keywords: Artificial Intelligence, CLA 2007, Knowledge Base, Science Knowledge Bases, Tree Structured Objects