Title :
Topic detection and interest tracking in a dynamic online news source
Author :
Kurtz, Andrew J. ; Mostafa, Javed
Author_Institution :
Lab. for Appl. Informatics Res., Indiana Univ., Bloomington, IN, USA
Abstract :
Digital libraries in the news domain may contain frequently updated data. Providing personalized access to such dynamic resources is an important goal. 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 are used to expose current news topics. User interest profiles, generated from explicit and implicit feedback are used to customize the news retrieval system´s interface.
Keywords :
Internet; data mining; digital libraries; information filters; information resources; information retrieval systems; relevance feedback; statistical analysis; user interfaces; vocabulary; data clustering; digital library; dynamic online news source; explicit feedback; implicit feedback; intelligent news-sifting system; news retrieval system interface; online news source filtering; personal profile; personalized access; topic detection; user interest profile; user interest tracking; vocabulary discovery; Displays; Feature extraction; Feedback; Filtering; Informatics; Intelligent systems; Laboratories; Matched filters; Software libraries; Vocabulary;
Conference_Titel :
Digital Libraries, 2003. Proceedings. 2003 Joint Conference on
Print_ISBN :
0-7695-1939-3
DOI :
10.1109/JCDL.2003.1204851
