Paper
12 March 2002 Using ant-behavior-based simulation model AntWeb to improve website organization
Weigang Li, Marcos Vinicius Pinheiro Dib, Wesley Martins Teles, Vlaudemir Morais de Andrade, Alba Cristina Magalhaes Alves de Melo, Judas Tadeu Cariolano
Author Affiliations +
Abstract
Some web usage mining algorithms showed the potential application to find the difference among the organizations expected by visitors to the website. However, there are still no efficient method and criterion for a web administrator to measure the performance of the modification. In this paper, we developed an AntWeb, a model inspired by ants' behavior to simulate the sequence of visiting the website, in order to measure the efficient of the web structure. We implemented a web usage mining algorithm using backtrack to the intranet website of the Politec Informatic Ltd., Brazil. We defined throughput (the number of visitors to reach their target pages per time unit relates to the total number of visitors) as an index to measure the website's performance. We also used the link in a web page to represent the effect of visitors' pheromone trails. For every modification in the website organization, for example, putting a link from the expected location to the target object, the simulation reported the value of throughput as a quick answer about this modification. The experiment showed the stability of our simulation model, and a positive modification to the intranet website of the Politec.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Weigang Li, Marcos Vinicius Pinheiro Dib, Wesley Martins Teles, Vlaudemir Morais de Andrade, Alba Cristina Magalhaes Alves de Melo, and Judas Tadeu Cariolano "Using ant-behavior-based simulation model AntWeb to improve website organization", Proc. SPIE 4730, Data Mining and Knowledge Discovery: Theory, Tools, and Technology IV, (12 March 2002); https://doi.org/10.1117/12.460232
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Cited by 5 scholarly publications.
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KEYWORDS
Mining

Algorithm development

Detection and tracking algorithms

Information science

Performance modeling

Databases

Networks

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