DocumentCode :
3280790
Title :
Identify Implicit Social Network by RST/FL Framework
Author :
Lai, Hong Feng
Author_Institution :
Dept. of Bus. Manage., Nat. United Univ., Miaoli, Taiwan
fYear :
2009
fDate :
20-22 July 2009
Firstpage :
362
Lastpage :
363
Abstract :
The rapid growth of Internet has transformed the way relationships between companies and their customers. To find the implicit social network and form customer club (community) for customers is a critical requirement in some businesses. The social role analysis attempts to find explicit similarities between actors in the network. Traditional clustering methods based on attributes between actors lack for logic foundation. In this paper, we apply rough set theory to partition objects into equivalence classes interpreting the hidden community. This paper proposes a framework to find the implicit social network based on rough set theory and frame logic to extract and express the social structure and relationship. The development framework includes three levels, i.e. conceptual level, logical level and validation level. In conceptual level, we explore the properties of social network. The logic and validation is based on frame logic. The interface of different level is a mapping from a source model to a target model using a set of transformation rules. Finally, we apply FLORID tools to evaluate the correctness and the adequacy of the model.
Keywords :
Internet; formal logic; pattern clustering; rough set theory; social networking (online); FLORID tools; Internet; clustering methods; conceptual level; customer club; frame logic; identify implicit social network; logic foundation; logical level; rough set theory; social role analysis; transformation rules; validation level; frame logic; implicit social network; rough set theory; social role analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Social Network Analysis and Mining, 2009. ASONAM '09. International Conference on Advances in
Conference_Location :
Athens
Print_ISBN :
978-0-7695-3689-7
Type :
conf
DOI :
10.1109/ASONAM.2009.62
Filename :
5231831
Link To Document :
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