An Effective System for Web Page Recommendation Using Pattern Mining Algorithms
Web usage mining is the application of data mining techniques to discover usage patterns from web data, in order to understand and better serve the needs of web-based applications. Web usage mining is parsed into three distinctive phases such as preprocessing, pattern discovery and pattern analysis. Analyzing data through web usage mining can help effective web site management, creating adaptive Web sites, business and support services, personalization, network traffic flow analysis and etc.The aim of this paper is to give web page recommendations with help of preprocessed, analyzed web log data and user profile. In this paper combined effort of clustering and association rule mining is applied for pattern discovery which helps in finding effective usage patterns. This recommendation system provides recommendations based on user’s navigational patterns and gives suitable recommendations to cater to current needs of users. The experimental results performed on real usage data show a significant improvement in the recommendation effectiveness of the proposed system.
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