A novel similarity evaluating model based on RFCA and ICS
Chongyang Shi, Zhendong Niu · 2010
In this paper, a similarity evaluating model based on rough formal concept analysis and information content similarity is proposed which evaluates the similarity degree between the concepts. We use the information content approach to automatically obtain part of similarity scores of two concepts which makes up the normal featural and structural evaluating models. Then through our model, the similarity of two concepts can be directly calculated from the lower object approximations and lower attribute approximations based on the rough formal concept analysis. An extensive experimental evaluation on two real datasets shows that when adjusting the influence from the object to certain degree, it outperforms other related works.