Unsupervised semantic segmentation in the time series domain is a much-studied problem
due to its potential to detect unexpected regularities and regimes in poorly understood data …

We develop a technique to identify abnormally correlated user accounts in Twitter, which are
very unlikely to be human operated. This new approach of bot detection considers cross …

Unsupervised semantic segmentation in the time series domain is a much studied problem
due to its potential to detect unexpected regularities and regimes in poorly understood data …

Given a large collection of time series, such as web-click logs, electric medical records and
motion capture sensors, how can we efficiently and effectively find typical patterns? How can …

Given a large, online stream of multiple co-evolving event sequences, such as sensor data
and Web-click logs, that contains various types of non-linear dynamic evolving patterns of …

The advent of GPS technologies generates location data-streams and accentuates the
importance of develo** practical tools that can process and analyze the vast amounts of …

In wireless ad hoc networks, clustering is one of the most important approaches for many
applications. A connected k-hop clustering network is formed by electing clusterheads in k …

The recent explosion in the adoption of search engines and new media such as blogs and
Twitter have facilitated the faster propagation of news and rumors. How quickly does a piece …

Given a large volume of multi-dimensional data streams, such as that produced by IoT
applications, finance and online web-click logs, how can we discover typical patterns and …

Online news, blogs, SNS and many other Web-based services has been attracting
considerable interest for business and marketing purposes. Given a large collection of time …