Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Proceedings of the 11th international conference on World Wide Web
WWW '05 Proceedings of the 14th international conference on World Wide Web
Objectrank: authority-based keyword search in databases
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Authority-based keyword search in databases
ACM Transactions on Database Systems (TODS)
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Explaining and Reformulating Authority Flow Queries
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
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As the social interaction of Internet users increases, so does the need to effectively rank social media. We study the challenges of personalized ranking of blog posts. Web search techniques are inadequate since social media lack many of the characteristics of the Web such as rich document content and an extensive hyperlink graph. Further, user behavior in social media has moved beyond keyword based search and must support users who follow a particular blog or theme. In this research, we extend a social media dataset to exploit the associations between authors, blog posts, and categories (topics) of the posts. We then apply personalized authority flow based ranking algorithms based on the random surfer model. We evaluate our personalization approaches through an extensive study on a range of virtual users whose preferences are defined based on intuitive criteria. Our evaluation shows that the accuracy of our personalized recommendations ranges from good to very good for a majority of users, and outperforms reasonable baseline approaches.