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Due to increased usage of web as a medium of publication by entrepreneurs and federal agencies, a massive amount of data is stored in structured and unstructured forms over the web. This leads to page-cluttering, which makes it difficult to distinguish the content of interest from superfluous data such as billboards, and patent and other announcements. Web Usage Mining (WUM) is a type of data mining technique that identifies usage patterns of web data, so as to perceive and better serve the requirements of web applications. The working of WUM involves three steps - pre-processing, pattern discovery and analysis. This research paper studies the identification of web usage patterns based on the user's interest/choice, thereby creating an intelligent semantics-based web usage mining technique.