Machine Learning - Special issue on learning with probabilistic representations
Factorial Hidden Markov Models
Machine Learning - Special issue on learning with probabilistic representations
On-line new event detection and tracking
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
MailCat: an intelligent assistant for organizing e-mail
Proceedings of the third annual conference on Autonomous Agents
Automatic generation of overview timelines
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Improving text categorization methods for event tracking
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Probability and statistics with reliability, queuing and computer science applications
Probability and statistics with reliability, queuing and computer science applications
Inference in Hybrid Networks: Theoretical Limits and Practical Algorithms
UAI '01 Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence
Bursty and hierarchical structure in streams
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
The Journal of Machine Learning Research
Continuous time particle filtering
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Learning continuous time bayesian networks
UAI'03 Proceedings of the Nineteenth conference on Uncertainty in Artificial Intelligence
Information genealogy: uncovering the flow of ideas in non-hyperlinked document databases
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Application of kalman filters to identify unexpected change in blogs
Proceedings of the 8th ACM/IEEE-CS joint conference on Digital libraries
Mining common topics from multiple asynchronous text streams
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Temporal and information flow based event detection from social text streams
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Early online identification of attention gathering items in social media
Proceedings of the third ACM international conference on Web search and data mining
Patterns of temporal variation in online media
Proceedings of the fourth ACM international conference on Web search and data mining
Mining named entities with temporally correlated bursts from multilingual web news streams
Proceedings of the fourth ACM international conference on Web search and data mining
Detecting and Tracking Topics and Events from Web Search Logs
ACM Transactions on Information Systems (TOIS)
Real-time probabilistic data association over streams
Proceedings of the 7th ACM international conference on Distributed event-based systems
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We present a unified model of what was traditionally viewed as two separate tasks: data association and intensity tracking of multiple topics over time. In the data association part, the task is to assign a topic (a class) to each data point, and the intensity tracking part models the bursts and changes in intensities of topics over time. Our approach to this problem combines an extension of Factorial Hidden Markov models for topic intensity tracking with exponential order statistics for implicit data association. Experiments on text and email datasets show that the interplay of classification and topic intensity tracking improves the accuracy of both classification and intensity tracking. Even a little noise in topic assignments can mislead the traditional algorithms. However, our approach detects correct topic intensities even with 30% topic noise.