E.L. Johnson and H. Kargupta. Collective, hierarchical clustering from distributed heterogeneous data. In Zaki and Ho [73], pages 221--244. Home/Search Document Not in Database Summary Related Articles Check |
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Data Mining - Challenges, Models, Methods and Algorithms - Hegland (2003) (Correct)
....5.3 shows the dendrogram obtained using hierarchical agglomerative clustering for the iris data set. One can see that again the clusters obtained are almost identical with the classes of the iris. In the case of a database which was distributed over p processors an algorithm is presented in [46] for single link clustering which has O(pN ) time and O(pN) space complexity. The communication costs of the algorithm are O(N ) The algorithm has the following three steps: Apply the hierarchical clustering algorithm at each site. Transmit the local dendrograms to the facilitator site. ....
E.L. Johnson and H. Kargupta. Collective, hierarchical clustering from distributed heterogeneous data. In Zaki and Ho [73], pages 221--244.
Data Mining - Challenges, Models, Methods and Algorithms - Hegland (2003) (Correct)
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E.L. Johnson and H. Kargupta. Collective, hierarchical clustering from distributed heterogeneous data. In Zaki and Ho [73], pages 221--244.
Agent-Based Distributed Data Mining: The KDEC Scheme - Klusch, Lodi, Moro (Correct)
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Johnson, E., Kargupta, H.: Collective, hierarchical clustering from distributed heterogeneous data. In Zaki, M., Ho, C., eds.: Large-Scale Parallel KDD Systems. Lecture Notes in Computer Science. Springer-Verlag (1999) 221--244
Distributed Clustering Based on Sampling Local Density.. - Klusch, Lodi, Moro (2003) (Correct)
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Erik Johnson and Hillol Kargupta. Collective, hierarchical clustering from distributed heterogeneous data. In M. Zaki and C. Ho, editors, LargeScale Parallel KDD Systems, Lecture Notes in Computer Science, pages 221--244. Springer-Verlag, 1999.
A Dissimilarity Measure for Clustering High- and Infinite.. - Socolovsky (2002) (Correct)
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E. JOHNSON AND H. KARGUPTA, Collective, Hierarchical Clustering from Distributed Heterogeneous Data, Lecture Notes in Computer Science 1759, Springer Verlag, 2000.
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