An efficient mobile social search method

With the rapid development of internet technology, social networks and social searches are becoming popularly. Unlike traditional web searches, the social search provides optimal search results according to user preferences. In this paper, we propose a mobile social search method based on popularities and user preferences. The popularity is calculated by collecting the visiting records of users. The user preferences are generated by the actual visiting information among the search results. We process a skyline query to extract the meaningful information from the candidate objects with multiple features. The proposed method ranks social search results by combining user preferences and popularity with the skyline query processing mechanism. To show the superiority of the proposed method, we compare it with the existing method through performance evaluation.