• Dipali Wankhede
• S.G.Tuppad

The increase in the amount of information over the Internet in recent years has led to the risk of data flooding, which has resulted in problems accessing user-related information. In addition, the increase in the number of websites and web pages has made it difficult for webmasters to determine the content of their content. The online user's information needs can be obtained by evaluating the user's web usage. Web Based Data Mining (WUM) is used to extract knowledge from web users. Access logs are accessed by using data mining techniques. One of the WUM applications is a guideline, a privacy filtering technique used to determine whether a user approves a specified item or identifies a list of things that may be important to the user. This article is an architecture that combines product data with user access log data and generates a set of instructions for that user. The operation records interesting results in terms of precision, recall, and metrics.

Usage mining, Online Web Recommendation System, Clustering, Pattern Matching, Boyer Moore, K- means, Recommendation

"Improvising of Web Recommendation system by using K-Means and Bitap Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 11, page no.193-198, November-2017, Available :http://www.jetir.org/papers/JETIR1711036.pdf

"Improvising of Web Recommendation system by using K-Means and Bitap Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 11, page no. pp193-198, November-2017, Available at : http://www.jetir.org/papers/JETIR1711036.pdf