Abstract
Clustering is an important data exploration task. Its use in data mining is growing very fast. Traditional clustering algorithms which no longer cater for the data mining requirements are modified increasingly. Clustering algorithms are numerous which can be divided in several categories. Two prominent categories are distance-based and density-based (e.g. K-means and DBSCAN, respectively). While K-means is fast, easy to implement and converges to local optima almost surely, it is also easily affected by noise. On the other hand, while density-based clustering can find arbitrary shape clusters and handle noise well, it is also slow in comparison due to neighborhood search for each data point, and faces a difficulty in setting the density threshold properly. We propose BRIDGE that efficiently merges the two by exploiting the advantages of one to counter the limitations of the other and vice versa. BRIDGE enables DBSCAN to handle very large data efficiently and improves the quality of K-means clusters by removing the noisy points. It also helps the user in setting the density threshold parameter properly. We further show that other clustering algorithms can be merged using a similar strategy. An example given in the paper merges BIRCH clustering with DBSCAN.
Original language | English (US) |
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Title of host publication | Proceedings - 7th International Conference on Database Systems for Advanced Applications, DASFAA 2001 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 32-39 |
Number of pages | 8 |
ISBN (Print) | 0769509967, 9780769509969 |
DOIs | |
State | Published - 2001 |
Event | 7th International Conference on Database Systems for Advanced Applications, DASFAA 2001 - Hong Kong, China Duration: Apr 18 2001 → Apr 21 2001 |
Other
Other | 7th International Conference on Database Systems for Advanced Applications, DASFAA 2001 |
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Country | China |
City | Hong Kong |
Period | 4/18/01 → 4/21/01 |
ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
- Information Systems