| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 404066 | Knowledge-Based Systems | 2008 | 5 Pages |
Abstract
In this paper, a new similarity model is proposed, which based on rough set to evaluate the similarity degree of the two concepts of concept lattice. The proposed method combines featural and structural information into decision and has a higher correlation with human judgement, which can be viewed as the development of Tversky’s similarity model. Compared with other similarity models this approach is convenient to measure the similarity of the concepts of the large contexts, by which we can avoid constructing Hasse diagram and looking through all concepts of the context.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Lidong Wang, Xiaodong Liu,