Clustering time series data using the popular subsequence (STS) technique has been widely used in the data mining and wider communities. Recently the conclusion was made that it i...
Structured data represented in the form of graphs arises in several fields of the science and the growing amount of available data makes distributed graph mining techniques partic...
Recently, there is an increasing research efforts in XML data mining. These research efforts largely assumed that XML documents are static. However, in reality, the documents are ...
Qiankun Zhao, Ling Chen 0002, Sourav S. Bhowmick, ...
Mining informative patterns from very large, dynamically changing databases poses numerous interesting challenges. Data summarizations (e.g., data bubbles) have been proposed to c...
We introduce dynamic correlated topic models (DCTM) for analyzing discrete data over time. This model is inspired by the hierarchical Gaussian process latent variable models (GP-L...