Abstract
| Seminar | |
| Time: | Wed, 16:15-18:00 |
| Location: | B26 Spl |
| Start: |
Clustering is a division of data into groups of similar objects. Each group, called cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. From a machine learning perspective, clustering is unsupervised learning of a hidden data concept. In this seminar several aspects of clustering algorithms will be explored, such as the consideration of various data types, the efficiency in terms of computational requirements, the evaluation of clustering results, and the exciting applications of clustering in various cases, like WWW, economy, biology, text collections.
Talks can be given in English.
Supervisor: Alexandros Nanopoulos (
).
Topics
- Introduction
- Efficient clustering algorithms
- Clustering categorical data
- Evaluation of clustering results
- Clustering in biology
- Clustering text databases
- Clustering WWW pages
- Clustering book collections
- Clustering satellite images
For more information about the topics please see the Script page.
Interested students can register for a topic from now via email to
.