An evolutionary clustering approach based on temporal aspects for context-aware service recommendation

2018 ◽  
Vol 11 (1) ◽  
pp. 119-138 ◽  
Author(s):  
Haithem Mezni ◽  
Sofiane Ait Arab ◽  
Djamal Benslimane ◽  
Karim Benouaret
Author(s):  
Thyagaraju G. S. ◽  
U. P. Kulkarni

In this paper the authors have presented design and implementation of context aware service recommendation engine for cell phone. Context aware service recommendation engine for mobile is designed to automatically adopt its behavior to changing environment. To achieve this, an important issue to be addressed is how to effectively select services for adaptation according to the user’s current context. In this paper, the authors propose an intelligent service recommendation model. They formulate the service adaptation process by using artificial intelligence techniques like Bayesian Network, fuzzy logic and rough sets based decision table. Bayesian Network to classify the incoming call (high priority call, low priority call and unknown calls), fuzzy linguistic variables and membership degrees to define the context situations, the decision rules for adopting the policies of implementing a service.


2009 ◽  
Vol 29 (3) ◽  
pp. 892-895 ◽  
Author(s):  
Run-cai HUANG ◽  
Yi-wen ZHUANG ◽  
Ji-liang ZHOU ◽  
Qi-ying CAO

2013 ◽  
Vol 22 (1) ◽  
pp. 50-74 ◽  
Author(s):  
Wenjia Niu ◽  
Jun Lei ◽  
Endong Tong ◽  
Gang Li ◽  
Liang Chang ◽  
...  

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