Intelligent web traffic mining and analysis

Wang, Abraham and Smith (2005) Journal of Network and Computer Applications 28:147-165

SOMine was used to generate cluster information for pattern analysis in combination with a fuzzy inference system to capture the chaotic trend to provide short-term (hourly) and long-term (daily) Web traffic trend predictions. Empirical results demonstrated that approach is efficient for mining and predicting Web server traffic and could be extended to other Web environments as well.

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Improved Web searching through neural network based index generation

Wang, Alahakoon and Smith (2003) Lecture Notes in Computer Science 2659:151-158

SOMs were used for clustering query logs to identify prominent groups of user query terms for further analysis. Such groups can provide meaningful information regarding web users’ search interests. Identified clusters can further be used for developing an adaptive indexing database for improving conventional search engine efficiency. The proposed hybrid model which combines neural network and indexing for web search applications can provide better data filtering effectiveness and efficiently adapt to the changes based on the web searchers’ interests or behavior patterns.

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