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dc.contributor.authorHAAHR, MADS
dc.date.accessioned2010-01-21T14:59:38Z
dc.date.available2010-01-21T14:59:38Z
dc.date.createdJuly-Augusten
dc.date.issued2004
dc.date.submitted2004en
dc.identifier.citationAlan Gray and Mads Haahr `Personalised, Collaborative Spam Filtering? in proceedings of the First Conference on Email and Anti-Spam (CEAS), Mountain View, CA, USA, July-August, 2004en
dc.identifier.otherY
dc.identifier.urihttp://hdl.handle.net/2262/36128
dc.descriptionPUBLISHEDen
dc.description.abstractThe state of the art sees content-based filters tending towards collaborative filters, whereby email is filtered at the MTA with users feeding information back about false positives and negatives. While this improves the ability of the filter to track concept drift in spam over time, such approaches make assumptions implicit in centralised spam filtering, such as that all users consider the same email to be spam. In this paper, we detail and analyse these assumptions and describe how they affect spam filtering. We present an architecture for personalised, collaborative spam filtering and describe the design and implementation of proof-of-concept, peer-to-peer, signature-based system based on the architecture. The evaluation is based on real-world users employing the system as their spam-filtering tool. Preliminary analysis of the results indicates that the implementation is accurate and efficient.en
dc.format.extent99400 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherDistributed Systems Groupen
dc.rightsYen
dc.subjectComputer Science
dc.titlePersonalised, Collaborative Spam Filteringen
dc.typeConference Paperen
dc.contributor.sponsorEnterprise Ireland
dc.type.supercollectionscholarly_publicationsen
dc.type.supercollectionrefereed_publicationsen
dc.identifier.peoplefinderurlhttp://people.tcd.ie/haahrm
dc.identifier.rssinternalid12201


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