Message retrieval and classification from chat room servers using Bayesian networks

Debbie Zhang, Simeon J. Simoff, John K. Debenham

    Research output: Chapter in Book / Conference PaperConference Paper

    Abstract

    Chat rooms and newsgroup on the internet is a valuable, and often free of charge, source of information. In this paper, a design of smart chat room bots that automatically retrieve and filter on line messages is proposed. The design is based on internet technology and Bayesian Networks. Technical details of connecting to and retrieving data from web based chat room servers are presented. A Naive Bayesian network classifier is implemented using frequency of the keywords that mostly appear in the selecting messages as input features. A prototype of such a message classification system has been implemented. It has been trialed on detecting investment related messages from four Australian chat room sites.
    Original languageEnglish
    Title of host publicationICIIP 2006: Proceedings of the International Conference on Intelligent Information Processing, 20-23 September, 2006, Adelaide Australia
    PublisherSpringer
    Number of pages6
    Publication statusPublished - 2006
    EventInternational Conference on Intelligent Information Processing -
    Duration: 1 Jan 2006 → …

    Conference

    ConferenceInternational Conference on Intelligent Information Processing
    Period1/01/06 → …

    Keywords

    • information storage and retrieval systems
    • Bayesian statistical decision theory
    • web mining
    • data mining
    • online chat groups
    • messages

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