A Memory Efficient Algorithm with Enhance Preprocessing Technique for Web Usage Mining
Nisarg Pathak, Viral Shah, Chandramohan Ajmeera · 2014
Huge amount of data is generated daily by billions of web users. The usage pattern of the web data could be very prized to the company in the field of understanding consumer behavior. Web usage mining includes three phases namely preprocessing, pattern discovery and pattern analysis. The focus of this paper is to establish an algorithm for pattern discovery based on the association between the users accessed web pages. We have proposed a complete preprocessing methodology to identify the distinct users. The foundation of the algorithm is to find the frequently accessed web pages. The biggest constrain for mining web usage patterns are computation overhead and memory overhead. The performance evaluation of algorithm shows that our algorithm is efficient and scalable.