An Inquiry into the Utilization of Behavior of Users in Personalized Web
Nowadays we see successive transformation of the Web into its personalized form. In order to personalize the content to suit each user's requirements we need to acquire the user's interests. Utilization of implicit feedback is the most suitable and unobtrusive way of doing so. In this paper we present various forms of implicit feedback and their application in the estimation of user's interests. We propose a method of link recommendation based on the recorded actions users take while visiting a website. We employ collaborative filtering to predict user interest to unvisited pages. We present an evaluation of our method using the web portal of our faculty where personalized recommendation of links to interesting events is provided for visitors.
implicit feedback recommendation user actions navigational patterns interest estimation personal calendar