4.7 Article

An adaptive collaboration evaluation model and its algorithm oriented to multi-domain location-based services

期刊

EXPERT SYSTEMS WITH APPLICATIONS
卷 42, 期 5, 页码 2798-2807

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2014.10.014

关键词

Location-based services; Composite evaluation; Quality of Service; User preferences; Collaboration evaluation algorithm

资金

  1. National Natural Science Foundation of China [61074135]
  2. Shanghai Leading Academic Discipline Project [J50103]

向作者/读者索取更多资源

With the rapid development of communication technology and mobile Internet, masses of location-based services which can meet users' requirements are appearing explosively. So the problem that how to select the personalized service with the best quality, which satisfies the requirement of different users, is becoming the research hot spot under mobile Internet environment. As the different QoS of each LBS sequence, it is reasonable to rank all candidate services and then get the best one. In this paper, to solve how to evaluate the LBS sequence service effectively and accurately, first of all, it organizes services which meet the requirement of users according to their location information, the geographic information and preference information. Then, it designs an adaptive control mechanism and select strategy to choose a suitable collaboration evaluation method for the current composition service. And the LBS composition optimization process is presented, which is mainly to find and acquire the appropriate LBS sequences based on user's local QoS constraints. Furthermore, it establishes a collaboration evaluation model to choose the suitable evaluation method for different cases. Finally, the collaboration evaluation method to measure the LBS sequences based on QoS indexes is adopted, which can get the service scheme with globe QoS optimum for different users. These above procedures accomplish the evaluation for location-based services, which can satisfy user preferences efficiently. (C) 2014 Published by Elsevier Ltd.

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