publication . Conference object . Other literature type . Article . 2010

personalized top-k processing over web 2.0 streams

Parisa Haghani; Sebastian Michel; Karl Aberer;
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  • Published: 26 Oct 2010
  • Publisher: ACM Press
Abstract
Web 2.0 portals have made content generation easier than ever with millions of users contributing news stories in form of posts in weblogs or short textual snippets as in Twitter. Efficient and effective filtering solutions are key to allow users stay tuned to this ever-growing ocean of information, releasing only relevant trickles of personal interest. In classical information filtering systems, user interests are formulated using standard IR techniques and data from all available information sources is filtered based on a predefined absolute quality-based threshold. In contrast to this restrictive approach which may still overwhelm the user with the returned s...
Subjects
free text keywords: Computer science, Data mining, computer.software_genre, computer, Content generation, Data stream mining, Information retrieval, Personal interest, World Wide Web, Sliding window protocol, Web 2.0, Filter (signal processing)
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