An Incremental Density-Based Clustering Technique for Large Datasets-Reference-Cited by-同舟云学术

An Incremental Density-Based Clustering Technique for Large Datasets

Published:2010 Issue: Volume: Page:3-11
ISSN:1867-5662
Container-title:Advances in Intelligent and Soft Computing
language:
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Author:

ur Rehman Saif,Khan Muhammed Naeem Ahmed

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-16626-6_1.pdf

Reference17 articles.

1. Fahim, A.M., Salem, A.M., Torkey, F.A., Ramadan, M.A.: Density Clustering Based on Radius of Data (DCBRD). World Academy of Science, Engineering and Technology (2006)

2. El-Sonbaty, Y., Ismail, M.A., Farouk, M.: An Efficient Density Based Clustering Algorithm for Large Databases. In: Proceedings of the 16th IEEE International Conference on Tools with Artificial Intelligence (2004)

3. Raymond, T.N., Han, J.: Efficient and Effective Clustering Method for Spatial Data Mining. In: Proceeding of the International Conference on Very Large Data Bases, Santiago, Chile, pp. 144–155 (1994)

4. Sudipto, G., Rastogi, R., Shim, K.: CURE: An Efficient Clustering Algorithm for Large Databases. In: Proceeding of the ACM SIGMOD International Conference on Management of Data, Seattle, WA, pp. 73–84 (1998)

5. Karypis, G., Han, E.H., Kumar, V.: Chameleon: Hierarchical Clustering using Dynamic Modeling. IEEE Computer 32, 68–75 (1999)

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