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Proceedings Paper

Tocorime Apicu: design and validation of an experimental search engine
Author(s): Reginald L. Walker
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Paper Abstract

In the development of an integrated, experimental search engine, Tocorime Apicu, the incorporation and emulation of the evolutionary aspects of the chosen biological model (honeybees) and the field of high-performance knowledge discovery in databases results in the coupling of diverse fields of research: evolutionary computations, biological modeling, machine learning, statistical methods, information retrieval systems, active networks, and data visualization. The use of computer systems provides inherent sources of self-similarity traffic that result from the interaction of file transmission, caching mechanisms, and user-related processes. These user-related processes are initiated by the user, application programs, or the operating system (OS) for the user's benefit. The effect of Web transmission patterns, coupled with these inherent sources of self-similarity associated with the above file system characteristics, provide an environment for studying network traffic. The goal of the study was client-based, but with no user interaction. New methodologies and approaches were needed as network packet traffic increased in the LAN, LAN+WAN, and WAN. Statistical tools and methods for analyzing datasets were used to organize data captured at the packet level for network traffic between individual source/destination pairs. Emulation of the evolutionary aspects of the biological model equips the experimental search engine with an adaptive system model which will eventually have the capability to evolve with an ever- changing World Wide Web environment. The results were generated using a LINUX OS.

Paper Details

Date Published: 27 July 2001
PDF: 11 pages
Proc. SPIE 4528, Commercial Applications for High-Performance Computing, (27 July 2001); doi: 10.1117/12.434865
Show Author Affiliations
Reginald L. Walker, Univ. of California/Los Angeles (United States)

Published in SPIE Proceedings Vol. 4528:
Commercial Applications for High-Performance Computing
Howard Jay Siegel, Editor(s)

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