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

• We adopt case-based reasoning to choose a suitable collaboration evaluation method.
• We establish QoS attributes model for LBS which is based on user preferences.
• The algorithm combined ant colony algorithm with Fuzzy Evaluation Algorithm is proposed.
• It evaluates and ranks the LBS composition sequences which can satisfy different users.

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.