International Journal on Computer Science and Technology (IJCST)
Recommender systems aim at directing users through this information space, toward the resources that best meet their needs and interests by extracting knowledge from the previous users' interactions. Currently much research is focus on web page recommendations using sequential pattern mining techniques. Sequential access pattern mining discovers interesting and frequent user access patterns from web logs. Most of the previous studies have adopted A priori-like sequential pattern mining techniques, which faced the problem on requiring expensive multiple scans of databases. In this paper a traditional sequential pattern mining algorithm called prefix span is modified by incorporating two measures such as, spending time and recent view.