An Effective Approach for Periodic Web Personalization

Resource type: paper
Resource url: http://portal.acm.org/citation.cfm?id=1248823.1249113&coll=&dl=

According to the paper, periodic web personalization aims to recommend the most relevant resources to a user during a specific time period by analyzing the periodic access patterns of the user from web usage logs. To support effective periodic web personalization, the author construct a user behavior model, called Personal Web Usage Lattice, from the web usage logs using the Fuzzy Formal Concept Analysis Technique. And then, the author deduces the resource that the user is most probably interested in during a given period. In the experimental, the author generates personalized resource for a set of predefined period conditions and measure the performance based on the applicability and satisfaction measures with respect to the different durations of period conditions and the different number of personalized resource (from 1 to 6). The experimental results shows that the proposed approach has achieved very effective web personalization evaluated by the applicability and satisfaction measures for predefined period conditions.