Affiliations: Department of Computer Science and Engineering,
Shanghai Jiao Tong University, Shanghai, China | China Xinhua Network Co. Ltd, Beijing, China
Note: [] Corresponding author: Xiaoxin Tang, Department of Computer
Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China.
E-mail: [email protected]
Abstract: Context-awareness has become a key issue in Human-Computer
Interaction(HCI) to provide better user experience under multi-device and
multi-modal environment. With this intuition, we have proposed a web service
based framework, which associates interactions with services, and provided
service selection mechanism using context knowledge to achieve smart
interaction migration [1]. A fundamental problem of such a
service-oriented framework for interaction migration is to design an effective
while scalable algorithm for service selection. In this paper, we propose a
service selection algorithm considering not only context information and user
preferences but also inter-service relations such as relative location. Our
algorithm detects interaction hot spots within user active scope
and presents the best service combination based on evaluation of interaction
effectiveness. We also conduct simulation and the results illustrate that our
algorithm is effective and scalable for interaction service selection.
