DocumentCode :
3531338
Title :
A novel similarity evaluating model based on RFCA and ICS
Author :
Shi, Chongyang ; Niu, Zhendong
Author_Institution :
Sch. of Comput. Sci., Beijing Inst. of Technol., Beijing, China
fYear :
2010
fDate :
5-8 July 2010
Firstpage :
114
Lastpage :
119
Abstract :
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.
Keywords :
data analysis; feature extraction; formal concept analysis; information retrieval; attribute approximation; featural evaluating model; information content similarity; object approximation; rough formal concept analysis; similarity degree; similarity evaluating model; similarity score; structural evaluating model; Approximation methods; Computational modeling; Context; Databases; Integrated circuit modeling; Lattices; Semantics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Information Management (ICDIM), 2010 Fifth International Conference on
Conference_Location :
Thunder Bay, ON
Print_ISBN :
978-1-4244-7572-8
Type :
conf
DOI :
10.1109/ICDIM.2010.5664235
Filename :
5664235
Link To Document :
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