Automatic text processing
Topic Detection and Tracking: Event-Based Information Organization
Topic Detection and Tracking: Event-Based Information Organization
ThemeRiver: Visualizing Thematic Changes in Large Document Collections
IEEE Transactions on Visualization and Computer Graphics
Topic Detection, Tracking, and Trend Analysis Using Self-Organizing Neural Networks
PAKDD '01 Proceedings of the 5th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Incorporating topic transition in topic detection and tracking algorithms
Expert Systems with Applications: An International Journal
Topic and Trend Detection in Text Collections Using Latent Dirichlet Allocation
ECIR '09 Proceedings of the 31th European Conference on IR Research on Advances in Information Retrieval
Constructing a Context-Aware Service-Oriented Reputation Model Using Attention Allocation Points
SCC '09 Proceedings of the 2009 IEEE International Conference on Services Computing
Proceedings of the 19th international conference on World wide web
Discovery of significant emerging trends
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Enabling reputation interoperability through semantic technologies
Proceedings of the 6th International Conference on Semantic Systems
Trend Ontology for Knowledge-Based Trend Mining in Textual Information
ITNG '10 Proceedings of the 2010 Seventh International Conference on Information Technology: New Generations
Journal of Theoretical and Applied Electronic Commerce Research
Streaming first story detection with application to Twitter
HLT '10 Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Hip and trendy: Characterizing emerging trends on Twitter
Journal of the American Society for Information Science and Technology
A security and high-availability layer for cloud storage
WISS'10 Proceedings of the 2010 international conference on Web information systems engineering
Overview of the third international workshop on search and mining user-generated contents
Proceedings of the 20th ACM international conference on Information and knowledge management
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Web users while collaborating over social networks and micro-blogging services also contribute to news coverage worldwide. News feeds come from mainstream media as well as from social networks. Often feeds from social networks are more up-to-date and, for user's view, more credible than those that come from mainstream media. But the overwhelming amount of information requires to personally filter through it until one gets what is really needed. In this paper, we describe our idea of a personalized news network built on current Web technologies and our research projects by filtering Twitter and Facebook messages using both trend mining and reputation approaches. Based on the example of Egyptian revolution, we explain the main idea of personalized news.