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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Tian-qiang Huang Yang-qiang Yu Kai Li Wen-fu Zeng |
| Copyright Year | 2009 |
| Abstract | DBSCAN is a typical density-based clustering algorithm, but it is time-consuming to ascertain the parameter Eps and it does not perform well on multi-density datasets because of the global parameter Eps. In this paper, we use must-link constraints to ascertain the parameter Eps for each density distribution effectively and automatically, which will be used to deal with multi-density data sets for traditional DBSCAN algorithm. Experimental results reveal that our algorithm can reckon the parameter of DBSCAN for multi-density data sets with constraints effectively. |
| Starting Page | 375 |
| Ending Page | 379 |
| File Size | 532667 |
| Page Count | 5 |
| File Format | |
| ISBN | 9781424438358 |
| DOI | 10.1109/AICI.2009.393 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2009-11-07 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Computer science Shape Databases Clustering methods Clustering algorithms DBSCAN Mathematics Must-link constraint Multi-density Data mining Artificial intelligence Computational intelligence |
| Content Type | Text |
| Resource Type | Article |
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