LAUSR

High Utility Product Mining (HUPM) is a developing theme in data mining. Contrasted with conventional high utility mining, HUPM estimates the utility of products by considering their duration (number of products in sequence). In this paper proposed a novel structure of mining high utility product sets from web services alludes to discover the product sets with high benefits. Essentially, the High Utility Web Access Sequence (HUWAS) tree is utilized to create the sequence tree reliant on the internal and external utility values of the web access sequence. By considering these values, patterns are generated and strengthened by using Fuzzy Logic (FL). Fuzzy can predict the high utility values by fixing thresholds. The performance of the approach is evaluated by using execution measures such as accuracy, time and memory consumption. Broad Performance examinations demonstrated that our novel methodology is effective and outperforms the existing utility-based mining approach. This exploration paper proposes an improved high utility pattern way to deal with mining the high utility products with less computation time and less memory space when larger web products are investigated for complex datasets.