Individual Information Adaptation Based on Content Description

Today's increasing information supply raises the need for more effective and automated information processing where individual information adaptation (personalization) is one possible solution. Earlier computer systems for personalization lacked the ability to easily define and measure the effectiveness of personalization efforts. Numerous projects failed to live up to the their expectations, and the demand for evaluation increased. This thesis presents some underlying concepts and methods for implementing personalization in order to increase stated business objectives. A personalization system was developed that utilizes descriptions of information characteristics (metadata) to perform content based filtering in a non-intrusive way. Most of the described measurement methods for personalization in the literature are focused on improving the utility for the customer. The evaluation function of the personalization system described in this thesis takes the business operator's standpoint and pragmatically focuses on one or a few measurable business objectives. In order to verify operation of the personalization system, a function called bifurcation was created. The bifurcation function divides the customers stochastically into two or more controlled groups with different personalization configurations. By giving one of the controlled groups a personalization configuration that deactivates the personalization, a reference group is created. The reference group is used to measure quantitatively objectives by comparison with the groups with active personalization. Two different companies had their websites personalized and evaluated: one of Sweden's largest recruitment services and the second largest Swedish daily newspaper. The purpose with the implementations was to define, measure, and increase the business objectives. The results of the two case studies show that under propitious conditions, personalization can be made to increase stated business objectives.