Activities per year
Abstract
Semi-supervised classification is drawing increasing attention in the era of big data, as the gap between the abundance of cheap, automatically collected unlabeled data and the scarcity of labeled data that are laborious and expensive to obtain is dramatically increasing. In this paper, we introduce a unified framework for semi-supervised classification based on building-blocks from density-based clustering. This framework is not only efficient and effective, but it is also statistically sound. Experimental results on a large collection of datasets show the advantages of the proposed framework.
Original language | English |
---|---|
Title of host publication | Proceedings of the 30th International Conference on Scientific and Statistical Database Management : SSDBM '18 |
Editors | Michael Bohlen, Johann Gamper, Peer Kroger, Dimitris Sacharidis |
Number of pages | 12 |
Publisher | Association for Computing Machinery |
Publication date | 9. Jul 2018 |
Article number | 11 |
ISBN (Electronic) | 978-1-4503-6505-5 |
DOIs | |
Publication status | Published - 9. Jul 2018 |
Event | International Conference on Scientific and Statistical Database Management - Bolzano-Bozen, Italy Duration: 9. Jul 2018 → 11. Jul 2018 Conference number: 30 http://ssdbm2018.inf.unibz.it/ |
Conference
Conference | International Conference on Scientific and Statistical Database Management |
---|---|
Number | 30 |
Country/Territory | Italy |
City | Bolzano-Bozen |
Period | 09/07/2018 → 11/07/2018 |
Internet address |
Keywords
- Density-based clustering
- Semi-supervised classification
Fingerprint
Dive into the research topics of 'A unified framework of density-based clustering for semi-supervised classification'. Together they form a unique fingerprint.Related activities
- 1 Conference presentations
-
A unified framework of density-based clustering for semi-supervised classification
Zimek, A. (Speaker)
9. Jul 2018 → 11. Jul 2018Activity: Talks and presentations › Conference presentations