Author
Willmore, Christopher P.
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.; Attribution-NonCommercial-NoDerivs 3.0 United States
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
CC BY-NC-ND. 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.;