Existing frequent-sequence mining algorithms perform multiple scans of a database, or a structure that captures the database. In this M.Sc. thesis, I propose a frequent-sequence mining algorithm that mines each database row as it reads it, so that it can potentially complete mining in the time it takes to read the database once. I achieve this by having my algorithm enumerate all sub-sequences from each row as it reads it. Since sub-sequence enumeration is a time-consuming process, I create a method to distribute the work over multiple computers, processors, and thread units, while balancing the load between all resources, and limiting the amount of communication so that my algorithm scales well in regards to the number of computers used. Experimental results show that my algorithm is effective, and can potentially complete the mining process in near the time it takes to perform one scan of the input database.

No description available.

Existing frequent-sequence mining algorithms perform multiple scans of a database, or a structure that captures the database. In this M.Sc. thesis, I propose a frequent-sequence mining algorithm that mines each database row as it reads it, so that it can potentially complete mining in the time it takes to read the database once. I achieve this by having my algorithm enumerate all sub-sequences from each row as it reads it. Since sub-sequence enumeration is a time-consuming process, I create a method to distribute the work over multiple computers, processors, and thread units, while balancing the load between all resources, and limiting the amount of communication so that my algorithm scales well in regards to the number of computers used. Experimental results show that my algorithm is effective, and can potentially complete the mining process in near the time it takes to perform one scan of the input database.

No description available.

Thesis (M.Sc.)--York University, 2006. Graduate Programme in Computer Science. / Typescript. Includes bibliographical references (leaves 261-287). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:MR19658

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1993. / Vita. Abstract. Includes bibliographical references (leaves 112-120). Also available via the Internet.

Thesis (M.S. in Computer Science)--Naval Postgraduate School, March 1992. / Thesis Advisor: Nelson, Michael L. "March 1992." Includes bibliographical references (p. 158-161). Also available in print.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1993. / Vita. Abstract. Includes bibliographical references (leaves 98-104). Also available via the Internet.

Thesis (Ph. D.)--University of Washington, 1999. / Vita. Includes bibliographical references (leaves 160-169).

Thesis (Ph. D.), Oregon Graduate Institute of Science & Technology, 1995.