Virtual reality for palmtop computers
ACM Transactions on Information Systems (TOIS)
Summarizing text documents: sentence selection and evaluation metrics
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Classification algorithms for NETNEWS articles
Proceedings of the eighth international conference on Information and knowledge management
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Proceedings of the 13th international conference on World Wide Web
GI '04 Proceedings of the 2004 Graphics Interface Conference
A personalized search engine based on web-snippet hierarchical clustering
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
NewsInEssence: summarizing online news topics
Communications of the ACM - The digital society
PeRSSonal's core functionality evaluation: Enhancing text labeling through personalized summaries
Data & Knowledge Engineering
Personalized news categorization through scalable text classification
APWeb'06 Proceedings of the 8th Asia-Pacific Web conference on Frontiers of WWW Research and Development
Development and performance evaluation of a new RSS tool for a Web-based system: RSS_PROYECT
Journal of Network and Computer Applications
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In the last decade, the advances in technology along with the ease of access to information have dramatically changed the World Wide Web status during the last few years. The Internet acts as a means of finding useful information and more specifically news articles. Additionally, more and more people want to utilize their mobile devices towards the scope of reading news articles. The aforementioned situation generates a significant, yet almost untouched problem: easily locating interesting news articles on a daily basis within the space that is available on the small screen device. In our work, we propose a framework that, by utilizing RSS feeds, is able to personalize on the needs of the users and on the capabilities of their device, in order to present to them only a fraction of the news articles and merely the useful information that derives from them. Deploying a generalized, multi-functional mechanism that produces efficient results for the situation described, seems to be a panacea for most of the text-based, information retrieval needs. Within this framework we created PeRSSonal, a mechanism that is able to create personalized, pre-categorized, dynamically generated RSS feeds focalized on the end user's small screen device. The system is based on algorithms that incorporate the user into the categorization and summarization procedures, while the articles are presented back to him/her according to her interests and the client device capacity.