Volume : IX, Issue : VII, July - 2019

SIGNIFICANCE STUDY OF USER WEB ACCESS RECORDS MINING FOR BUSINESS INTELLIGENCE

Amish D. Vyas, Dr. Yogesh Kumar Sharma

Abstract :

This paper discusses about how business intelligence on a website could be obtained from users’ access records instead of web logs of “hits”. In this paper, we present the important concepts of Web usage mining and its various practical applications. We further present a novel approach ‘intelligentminer’ (i–Miner) to optimize the concurrent architecture of a fuzzy clustering algorithm (to discover web data clusters) and a fuzzy inference system to analyze the Web site visitor trends. A hyid evolutionary fuzzy clustering algorithm is proposed in this paper to optimally segregate similar user interests. The clustered data is then used to analyze the trends using a Takagi–Sugeno fuzzy inference system learned using a combination of evolutionary algorithm and neural network learning. Due to intense competition on one hand and the customer’s option to choose from several alternatives business community has realized the necessity of intelligent marketing strategies and relationship management. Web usage mining attempts to discover useful knowledge from the secondary data obtained from the interactions of the users with the Web. Web usage mining has become very critical for effective Web site management, creating adaptive Web sites, business and support services, personalization, network traffic flow analysis and so on. In this paper, we present the important concepts of Web usage mining and its various practical applications. Data mining and business intelligence techniques can be integrated in order to develop more advanced decision support systems. They describe the Web mining process as a sequence of steps for the development of advanced decision support systems. By following such a sequence, the authors can develop advanced decision support systems, which integrate data mining with business intelligence, for websites

Keywords :

Article: Download PDF   DOI : 10.36106/ijar  

Cite This Article:

SIGNIFICANCE STUDY OF USER WEB ACCESS RECORDS MINING FOR BUSINESS INTELLIGENCE, Amish D. Vyas, Dr. Yogesh Kumar Sharma INDIAN JOURNAL OF APPLIED RESEARCH : Volume-9 | Issue-7 | July-2019

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