Web Personalization using Amalgamation of Web Navigational Patterns & User Profiles
Keywords:
Web Personalization, Navigational pattern, User ProfilesAbstract
Web personalization proposes customized Web sites to users or anticipates personalised Web things to them based on their individual discoveries regarding user profiles or navigational patterns. User profiles are fundamentally made to display particular user guiding habits that were found through web usage research. The frequent sequential patterns that are derived from online usage data utilizing frequent sequential pattern mining techniques are what are known as navigational patterns. In this research, a novel method for online personalization is developed using the information from user profiles and navigational habits. A set of active navigational patterns, user profiles, and the prediction period are first read as input. Next, user profiles and navigational patterns are compared to determine the anticipated pages. Then, considering the most crucial user characteristics and navigational patterns, each page's ranking is calculated. The best top n-pages are then recommended. Two data sets from the KDDCUP and scholarly websites were used in the testing. The findings demonstrate that the suggested method successfully provides web users with a wealth of data for anticipating and recommending tailored web pages. The suggested approach permits a 6.3-fold increase in traffic that is tolerable with a maximum latency saving ratio of 7.5.
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