Study on Personalized Information Recommendation Based on Web Text Association Rules
Yujie Cao · Information Sciences · 2009
This paper proposes a personalized information recommendation model based on Web text association rules.Firstly,this model extracts the Web transaction set represented by feature items by Web usage preparation and Web text preparation.Secondly,it applies an association rules algorithm to discover frequent feature items set.Finally,the model utilizes frequent feature items graph to generate user interest view and provide personalized information recommendation service.