Document Type
Conference Proceeding
Publication Date
10-2011
Abstract
With the rapid growth in users on social networks, there is a corresponding increase in user-generated content, in turn resulting in information overload. On Twitter, for example, users tend to receive uninterested information due to their non-overlapping interests from the people whom they follow. In this paper we present a Semantic Web approach to filter public tweets matching interests from personalized user profiles. Our approach includes automatic generation of multi-domain and personalized user profiles, filtering Twitter stream based on the generated profiles and delivering them in real-time. Given that users interests and personalization needs change with time, we also discuss how our application can adapt with these changes.
Repository Citation
Kapanipathi, P.,
Orlandi, F.,
Sheth, A. P.,
& Passant, A.
(2011). Personalized Filtering of the Twitter Stream. .
https://corescholar.libraries.wright.edu/knoesis/649
Included in
Bioinformatics Commons, Communication Technology and New Media Commons, Databases and Information Systems Commons, OS and Networks Commons, Science and Technology Studies Commons
Comments
Presented at the 10th International Semantic Web Conference, Bonn, Germany, October 23-27, 2011.
PowerPoint that accompanied paper can be found at http://www.slideshare.net/pavankapanipathi/personalizedtwitterstreamiswcspim11.