Lesezeichen (verstecken)6
- LETOR: A Benchmark Collection for Research on Learning to Rank for Information Retrieval
- FriendFeed has recently launched a search feature, and so Facebook search must be coming soon. Real-time Web search (of streams of activities) is a hot topic right now. ...
- Web spam pages use various techniques to achieve higher-than-deserved rankings in a search engine’s results. While human experts can identify spam, it is too expensive to manually evaluate a large number of pages. Instead, we propose techniques to semi-automatically separate reputable, good pages from spam. We first select a small set of seed pages to be evaluated by an expert. Once we manually identify the reputable seed pages, we use the link structure of the web to discover other pages that are likely to be good. In this paper we discuss possible ways to implement the seed selection and the discovery of good pages. We present results of experiments run on the World Wide Web indexed by AltaVista and evaluate the performance of our techniques. Our results show that we can effectively filter out spam from a significant fraction of the web, based on a good seed set of less than 200 sites.
Publikationen (verstecken)8
- Seite 310--343. Springer International Publishing, Cham, (2018)
- Nature, 451 (7174): 6-6 (Januar 2008)
- Proceedings of the 3rd European Semantic Web Conference, Volume 4011 von LNCS, Seite 411-426. Budva, Montenegro, Springer, (Juni 2006)
- WWW, Seite 707-715. ACM, (2006)
- SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, Seite 308--315. New York, NY, USA, ACM Press, (2006)
- SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, Seite 75--82. New York, NY, USA, ACM Press, (2006)
- ECML, Seite 96-107. (2005)
- VLDB, Seite 576-587. (2004)
