Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
396217 | Information Sciences | 2007 | 19 Pages |
In part II of this paper, firstly, we study the relationship between the AFS (Axiomatic Fuzzy Zet) and FCA (Formal Concept Analysis, which has become a powerful theory for data analysis, information retrieval, and Knowledge discovery) and some algebraic homomorphisms between the AFS algebras and the concept lattices are established. Then, the numerical approaches to determining membership functions proposed in part I of this paper are used to study the fuzzy description and data clustering problems by mimicking human reasoning process. Finally, illustrative examples show that the framework of AFS theory offers a far more flexible and effective approach to artificial intelligence system analysis and design with applications to knowledge acquisition and representations in practice.