This paper proposes a general framework for searching large distributed repositories. Examples of such repositories include sites with music/video content, distributed digital lib...
We present a new unsupervised learning technique for the discovery of temporal clusters in large data sets. Our method performs hierarchical decomposition of the data to find stru...
In this paper, an application of feature extraction from music data is first introduced to motivate our research of finding approximate repeating patterns from sequence data. An a...
Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selec...
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...