Finding bursts in data streams is attracting much attention in research community due to its broad applications. Existing burst detection methods suffer the problems that 1) the p...
Outlier detection has many important applications in sensor networks, e.g., abnormal event detection, animal behavior change, etc. It is a difficult problem since global informati...
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Extracting entities (such as people, movies) from documents and identifying the categories (such as painter, writer) they belong to enable structured querying and data analysis ov...
Statistics on networks have become vital to the study of relational data drawn from areas such as bibliometrics, fraud detection, bioinformatics, and the Internet. Calculating man...