Abstract
In last decade, there is a paradigm shift in technology in the sense that large numbers of users over the internet share the valuable information with others. Users working in this field work at different levels for information sharing. As these users share the information with each other, there is a need of efficient collaborative mechanism among them to achieve efficiency and accuracy at each level. So to achieve high level of efficiency and accuracy, a distributed context aware collaborative filtering (CF) approach for service selection is proposed in this paper. Users profiles are created as a database repository from the previous data of different users and their respective interests. For the new user who wants to avail a particular service, system matches the request with the existing users profiles and if the match is found then a suitable service is recommended to him based upon his profile. To select the relevant contents of user choice that match his profile with the existing users, a Distributed Filtering Metric (DFM) is included which is based upon user input. Moreover, the intersection of existing users profiles and their interests is also included in this metric to have high level of accuracy. Specifically, we have taken an example of movie selection as a service offered to the users by some network. The underlying network chosen is Wireless Mesh Networks (WMNs) which are emerged as a new powerful technology in recent years due to the unique features such as low deployment cost and easy maintenance. A novel Context Aware Service Selection (CASS) algorithm is proposed. The performance of the proposed algorithm is evaluated with respect to efficiency and accuracy. The results obtained show that the proposed approach has high level of efficiency and accuracy.