Cognitive Analysis on Web Server Log Metaheuristic Algorithm and Distributed ARM
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Abstract
Web use is increasing daily, Web use mining (WUM) and frequent pattern mining make it easier to assess cognitive evaluation from Web server log. This cognitive analysis is helping the organization decision makers to take on strategy decisions. Association rule mining (ARM) is considered one the most excellent method for identifying frequent patterns from data source. Here our aim is to find frequently used elements such as urls, the greatest number of used urls, set of urls. These elements are browsed together in the way as we can identify website consumer behavior. In this paper we have proposed an algorithm that are a comprehensive approach of Metaheuristic (Genetic algorithm) and Multicore processing named as GMARM (Genetic Multi-core Association Rule Mining). Here we enter web usage data to a preprocessing tool which is Genetic algorithm-based preprocessing, then we apply association rule mining to find out user behavior pattern using MARM algorithm. MARM algorithm finds gain of multi-core processor, preprocessed data passed to distributed processors.
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