| Summary: | 碩士 === 世新大學 === 資訊管理學研究所(含碩專班) === 100 === As the booming of social network sites (SNSs), people adapt to communicate and share information via internet recently. According to great business opportunities emerging in SNSs, entrepreneurs strive to explore kinds of potential possibilities to make use data collected from SNSs. For example, recently the well-known Search Engine Site, Google, has released Google+ to integrate the task of keyword search with social network. Therefore, the related web pages returned from Search Engine might be much more toward individual needs.
In this paper, we propose a new method to consider the mutual interests of friends on social networks while ranking the orders of related web pages returned from search engines. A web-browsing log of 1112 users kept by InsightXplorer Ltd. is explored, and the simulation results show the proposed method could improve Google Search in page ranks and precision values (P@Ns).
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