Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Newsjunkie: providing personalized newsfeeds via analysis of information novelty
Proceedings of the 13th international conference on World Wide Web
Manifold-ranking based image retrieval
Proceedings of the 12th annual ACM international conference on Multimedia
WWW '05 Proceedings of the 14th international conference on World Wide Web
HLT '01 Proceedings of the first international conference on Human language technology research
Predicting News Story Importance Using Language Features
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Mining city landmarks from blogs by graph modeling
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Learning the importance of latent topics to discover highly influential news items
KI'10 Proceedings of the 33rd annual German conference on Advances in artificial intelligence
Processing continuous text queries featuring non-homogeneous scoring functions
Proceedings of the 21st ACM international conference on Information and knowledge management
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With the popularity of reading news online, the idea of assembling news articles from multiple news sources and digging out the most important stories has become very appealing. In this paper we present a novel algorithm to rank assembled news articles as well as news sources according to their importance and authority respectively. We employ the visual layout information of news homepages and exploit the mutual reinforcement relationship between news articles and news sources. Specifically, we propose to use a label propagation based semi-supervised learning algorithm to improve the structure of the relation graph between sources and new articles. The integration of the label propagation algorithm with the HITS like mutual reinforcing algorithm produces a quite effective ranking algorithm. We implement a system TOPSTORY which could automatically generate homepages for users to browse important news. The result of ranking a set of news collected from multiple sources over a period of half a month illustrates the effectiveness of our algorithm.