Topic Detection and Interest Tracking in a Dynamic Online News Source
Andrew John Kurtz · 2008
Digital libraries in the news domain may contain frequently updated data. Providing personalized access to such dynamic resources is an important goal. In this paper, we investigate the area of filtering online dynamic news sources based on personal profiles. We experimented with an intelligent news–sifting system that tracks topic development in a dynamic online news source. Vocabulary discovery and clustering is used to expose current news topics. User topic interest profiles, generated from explicit and implicit feedback, track user’s interest and are used to customize the news retrieval system’s interface. 2.