An Improved Approach to Find Frequent Web Access Patterns from Web Logs

Computer Engineering

Web usage mining refers to programmed revelation of examples and related information, gathered or created as an after effect of client connections with one or more Web destinations. Principle objective is to investigate the behavioral examples and profiles of clients interfacing with a Web page. The found examples are represented as collections of pages, objects, or resources that are frequently accessed by groups of users with common interests. Web usage mining consists of three phases, namely pre-processing, pattern discovery, and pattern analysis. . In the pattern discovery phase, frequent pattern discovery algorithms applied on raw data. In the pattern analysis phase interesting knowledge is extracted from frequent patterns and these results can be used further. By our Literature Survey we have found that most of the frequent pattern mining algorithms are either not scalable or too complex so we propose a new an effective method for mining frequent item sets which is comparatively more scalable as well as simple and will provide better mining performance.

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