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    Timestamp-based correlation measures for finding hidden groups in chat rooms

    Author
    Willmore, Christopher P.
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    10905_abstitle-mas.pdf (20.85Kb)
    10906_thesis.pdf (591.8Kb)
    Other Contributors
    Goldberg, Mark;
    Date Issued
    2008-05
    Subject
    Computer science
    Degree
    MS;
    Terms of Use
    This electronic version is a licensed copy owned by Rensselaer Polytechnic Institute, Troy, NY. Copyright of original work retained by author.;
    Metadata
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    URI
    https://hdl.handle.net/20.500.13015/527
    Abstract
    This thesis describes a new two-step algorithm for finding hidden groups from chat transcripts, that is, transcripts of communication where the recipient of a message is not known. The algorithm is presented in two steps: calculating a correlation value between every pair of users in the chat transcript, and finding clusters in the weighted undirected graph that results. The inter-user correlation can be calculated in a number of different ways, some of which are accomplished by projecting individual user transcripts into an inner product space. The clustering step uses the existing iterative-scan algorithm, with some new modifications. This approach is found to work under limited conditions.;
    Description
    May 2008; School of Science
    Department
    Dept. of Computer Science;
    Publisher
    Rensselaer Polytechnic Institute, Troy, NY
    Relationships
    Rensselaer Theses and Dissertations Online Collection;
    Access
    Users may download and share copies with attribution in accordance with a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License. No commercial use or derivatives are permitted without the explicit approval of the author.;
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    • RPI Theses Online (Complete)
    • RPI Theses Open Access

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