By Mohammed J. Zaki, Jeffrey Xu Yu, B. Ravindran, Vikram Pudi

This e-book constitutes the lawsuits of the 14th Pacific-Asia convention, PAKDD 2010, held in Hyderabad, India, in June 2010.

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Extra info for Advances in Knowledge Discovery and Data Mining, Part II: 14th Pacific-Asia Conference, PAKDD 2010, Hyderabad, India, June 21-24, 2010, Proceedings

Example text

This is due to the fact that FEDRA operates using only 2 points while LMDS employs the whole local dataset at each node. Similar quality results were obtained from DL -Isomap during the evaluation of Helix. Our algorithm managed to recover the circle structure of Helix (Figures 3(g), 3(h)) providing results comparable to L-Isomap (Figure 3(f)) and Isomap (Figure 3(e)). The inability of DF -Isomap to work with a limited number of landmark points was more evident this time, producing an arc instead of a circle.

Morgan Kaufmann, San Francisco (2002) 5. : Local relevance weighted maximum margin criterion for text classification. In: SIAM SDM, pp. 1135–1146 (2009) 6. : Distributed similarity search in high dimensions using locality sensitive hashing. In: ACM EDBT, pp. 744–755 (2009) 7. : Parallelizing the qr algorithm for the unsymmetric algebraic eigenvalue problem. In: SIAM JSC, pp. 870–883 (1994) 8. : What is the nearest neighbor in high dimensional spaces? In: VLDB, pp. 506–515 (2000) 9. : Collective pca from distributed heterogeneous data.

The results obtained from 3D Clusters inspired the application of D-Isomap on a DDM problem. As evaluation dataset, we used the titles of all papers published in ECDL, ECML/PKDD, FOCS, KDD, SIGMOD, SODA and VLDB conferences between 2006 and 2008 2 . The dataset consists of 2167 papers, represented as 4726-dimensional vectors using a TF-IDF populated vector space model [4]. We randomly distributed the dataset among M peers (M = 10, 15, 2 The authors would like to thank Dr. G. Tsatsaronis who kindly provided the dataset.

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