Download e-book for kindle: Advances in Knowledge Discovery and Data Mining, Part II: by Mohammed J. Zaki, Jeffrey Xu Yu, B. Ravindran, Vikram Pudi

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

ISBN-10: 3642136710

ISBN-13: 9783642136719

This publication constitutes the court cases of the 14th Pacific-Asia convention, PAKDD 2010, held in Hyderabad, India, in June 2010.

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

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This, in conjunction with our initial goal for low network cost, highlights the need for a structured, DHT based, P2P network like Chord. Chord is a P2P lookup protocol where peer identifiers are arranged in a circle. Each node has a successor and a predecessor. The successor of a peer is the next node in the identifier circle when moving clockwise. On the other hand, the predecessor, is the next peer in the Distributed Knowledge Discovery with Non Linear Dimensionality Reduction 17 identifier circle when moving counter-clockwise.

Vazirgiannis, and D. Valsamou 13. : Global pca for dimensionality reduction in distributed data mining. In: SDMKD, ch. 19, pp. 327–342. CRC, Boca Raton (2004) 14. : Pca for dimensionality reduction in massive distributed data sets. In: 5th International Workshop on High Performance Data Mining (2002) 15. : A scalable contentaddressable network. In: ACM SIGCOMM, pp. 161–172 (2001) 16. : Global versus local methods in nonlinear dimensionality reduction. In: NIPS, pp. 705–712 (2002) 17. , Hari: Chord: A scalable peerto-peer lookup service for internet applications.

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. In: PKDD (2000) 10. : Computer Networking: A Top-Down Approach Featuring the Internet. Addison-Wesley, Reading (2000) 11. : K-landmarks: Distributed dimensionality reduction for clustering quality maintenance. In: PKDD, pp. 322–334 (2006) 12.

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Advances in Knowledge Discovery and Data Mining, Part II: 14th Pacific-Asia Conference, PAKDD 2010, Hyderabad, India, June 21-24, 2010, Proceedings by Mohammed J. Zaki, Jeffrey Xu Yu, B. Ravindran, Vikram Pudi


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