Business Intelligence and Analytics play a key role in both operational and strategic decision -making in a company. But most analysts and researchers would agree that the quality of this decision-making is hampered by the freshness and availability of data to populate it. Web servers record and accumulate data about user interactions whenever requests for resources are received. Analyzing the Web access logs can help in understanding the user behavior in buying pattern. From the business and applications point of view, knowledge obtained from the web usage patterns could be directly applied to efficiently manage activities related to e-business, e-services and e-education. Accurate web usage information could help to attract new customers, retain current customers, improve cross marketing/sales, effectiveness of promotional campaigns, tracking leaving customers etc. This paper proposes a novel similarity algorithm (WEBTRASIM) for web user session trajectories based on URL’s of interest (UOI) and Time of Interest (TOI), which can be used in personalization, system improvement, site modification, business intelligence, usage characterization and so forth. Experimental evaluation using web access log of a Company’s web server also supports the validity of the findings.
Faculty Member & Research Guide in Computer Applications,
School of Management & Business Studies,
Mahatma Gandhi University