SMGKM: An Efficient Incremental Algorithm for Clustering Document Collections

Author:

Bagirov Adil,Seifollahi Sattar,Piccardi Massimo,Zare Borzeshi Ehsan,Kruger Bernie

Publisher

Springer Nature Switzerland

Reference29 articles.

1. Arthur, D., Vassilvitskii, S.: $$k$$-means++: the advantages of careful seeding. In: Gabow, H. (ed.) Proceedings of the 18th Annual ACM-SIAM Symposium on Discrete Algorithms [SODA 2007], Philadelphia, pp. 1027–1035 (2007)

2. Bagirov, A.M.: Modified global $$k$$-means algorithm for minimum sum-of-squares clustering problems. Pattern Recogn. 41(10), 3192–3199 (2008)

3. Bagirov, A.M., Ugon, J., Webb, D.: Fast modified global $$k$$-means algorithm for incremental cluster construction. Pattern Recogn. 44(4), 866–876 (2011)

4. Bai, L., Liang, J., Sui, C., Dang, C.: Fast global $$k$$-means clustering based on local geometrical information. Inf. Sci. 245, 168–180 (2013)

5. Banerjee, A., Dhillon, I.S., Ghosh, J., Sra, S.: Clustering on the unit hypersphere using Von Mises-Fisher distributions. J. Mach. Learn. Res. 6, 1345–1382 (2005)

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