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

fYear

2003

fDate

27-31 May 2003

Firstpage

122

Lastpage

124

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Digital Libraries, 2003. Proceedings. 2003 Joint Conference on

Print_ISBN

0-7695-1939-3

Type

conf

DOI

10.1109/JCDL.2003.1204851

Filename

1204851