scholarly journals A Novel Approach for Secure Hidden Community Mining in Social Networks using Data Mining Techniques

2014 ◽  
Vol 87 (7) ◽  
pp. 12-19
Author(s):  
R. RenugaDevi ◽  
M. Hemalatha
Author(s):  
Anahit Martirosyan ◽  
Thomas Tran ◽  
Azzedine Boukerche

Context is any information/knowledge about an application and user that can be used by an e-commerce system to provide efficient services to the users of the system. In this article, we propose to extend usage of context as compared to previously designed context-aware e-commerce systems. While in previous work, context was mainly considered for mobile e-commerce systems, we propose to build and use context for e-commerce systems in general. The context is employed to tailor an e-commerce application to the preferences and needs of users and provide insights into purchasing activities of users and particular e-commerce stores by means of using Data Mining techniques. This article proposes a model of context that includes micro-, macro- and domain contexts that constitute knowledge about the application and its user on different levels of granularity. The article also proposes a technique for extracting groups in social networks. This knowledge is part of macro-context in the proposed model of context. Moreover, the article discusses some of the challenges of incorporating context with e-commerce systems, emphasizing on the privacy issue, with an ultimate goal of developing intelligent e-commerce systems.


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