Topic Detection and Tracking: Event-Based Information Organization
Topic Detection and Tracking: Event-Based Information Organization
Learning Approaches for Detecting and Tracking News Events
IEEE Intelligent Systems
Corpora for topic detection and tracking
Topic detection and tracking
Text classification and named entities for new event detection
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Novelty detection based on sentence level patterns
Proceedings of the 14th ACM international conference on Information and knowledge management
Using random walks for question-focused sentence retrieval
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Sentence level information patterns for novelty detection
Sentence level information patterns for novelty detection
A comparison of named entity patterns from a user analysis and a system analysis
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
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A new event tracking approach is proposed based on the identification of named entity (NE) patterns such as Who, What, Where and When, and their relationship with news domains such as Politics, Economy, Government and Entertainment. This research comprises three parts. The first part uses a set of user studies to identify NE patterns and their relationship with news domains. Second part is to design a prototype system based on NE patterns. The final part evaluates the prototype event tracking system. This paper described the first part which is to evaluate the importance of NE across news domains. We have achieved a better understanding on NE patterns by identifying the distribution of NE across news domains.