Document filtering with inference networks
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ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
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The VLDB Journal — The International Journal on Very Large Data Bases
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IPTPS'05 Proceedings of the 4th international conference on Peer-to-Peer Systems
Evaluating continuous top-k queries over document streams
World Wide Web
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The World Wide Web (WWW) is experiencing an explosive growth of live content. To timely disseminate end users with fresh content that is relevant to users' interests is a very useful but challenging task. In this paper we design a distributed top-k document dissemination scheme: by inputting query terms and a number k as subscription conditions, end users subscribe to the top-k most relevant documents. When the documents and subscription conditions are distributed, the difficulties are how to forward the personalized top-k documents to the needed users with low forwarding cost. To this end, we propose document forwarding and filtering algorithms on a set of dedicate servers. Experiments based on real query logs and document datasets show the efficiency of our proposed algorithms.