Extracting significant time varying features from text
Proceedings of the eighth international conference on Information and knowledge management
On the bursty evolution of blogspace
WWW '03 Proceedings of the 12th international conference on World Wide Web
Issues in data stream management
ACM SIGMOD Record
Bursty and Hierarchical Structure in Streams
Data Mining and Knowledge Discovery
Efficient elastic burst detection in data streams
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Newsjunkie: providing personalized newsfeeds via analysis of information novelty
Proceedings of the 13th international conference on World Wide Web
Identifying similarities, periodicities and bursts for online search queries
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
A comparison of several approximate algorithms for finding multiple (N-best) sentence hypotheses
ICASSP '91 Proceedings of the Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
Fast burst correlation of financial data
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Toward a decision informatics paradigm: a real-time, information-based approach to decision making
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Incremental linear discriminant analysis for classification of data streams
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Evolutionary neural networks for anomaly detection based on the behavior of a program
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An Automatically Tuning Intrusion Detection System
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A Cluster Validity Measure With Outlier Detection for Support Vector Clustering
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Discovering Event Evolution Patterns From Document Sequences
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Web Navigation Prediction Using Multiple Evidence Combination and Domain Knowledge
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Detecting changes in content and posting time distributions in social media
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Hi-index | 0.00 |
Modeling and detecting bursts in data streams is an important area of researchwith a wide range of applications. In this paper, we present a novelmethod to analyze and identify correlated burst patterns by considering multiple data streams that coevolve over time. The main technical contribution of our research is the use of a dynamic probabilistic network to model the dependency structures observed within these data streams. Such dependencies provide meaningful information concerning the overall system dynamics and should be explicitly integrated into the burst detection process. Using both synthetic scenarios and two real-world datasets, we compare our method with an existing burst-detection algorithm. Initial experimental results indicate that our approach allows for more balanced and accurate burst quantification.