Recommendations of Personal Web Pages Based on User Navigational Patterns
Yin‐Fu Huang, Jia-Tang Jhang · International Journal of Machine Learning and Computing · 2014
In this paper, we propose a web recommendation system where user navigational patterns can be extracted from web logs.First, the recommendation system discovers user concepts from web logs step-by-step, and then extracts the navigation patterns among these concepts.These navigational patterns are then used to generate recommendation web pages by matching the navigation behavior of a user personal knowledge base.The pages in a recommendation list are ranked according to their hub scores which are computed based on page connectivity information.The experimental results show that the web pages recommended by our system are of better quality and acceptable for humans from various domains, based on human evaluators ranking as well as quality-value-based performance measures.