Collaborative browsing system based on semantic mashup with open APIs

Due to a large amount of information available on world wide web, it has been difficult for users to effectively find relevant information. Many web browsing methods and systems have been investigated to apply adaptive approaches which can extract personal interests of the users. In this paper, we propose a semantic mashup-based collaborative browsing (co-browsing) platform for supporting knowledge sharing with other partners. Especially, the semantic mashup scheme can integrate heterogeneous information collected by various Open APIs, and help users to determine which partners should be selected. For evaluating the proposed method, we have implemented a co-browsing platform which can exchange bookmarks, and measured whether the semantic mashup scheme make a positive influence on improving the performance of the co-browsing process.