New PDF release: Active Media Technology: 8th International Conference, AMT

By Yin-Fu Huang, Shih-Hao Wang (auth.), Runhe Huang, Ali A. Ghorbani, Gabriella Pasi, Takahira Yamaguchi, Neil Y. Yen, Beijing Jin (eds.)

ISBN-10: 3642352359

ISBN-13: 9783642352355

ISBN-10: 3642352367

ISBN-13: 9783642352362

This e-book constitutes the refereed court cases of the eighth overseas convention on energetic Media know-how, AMT 2012, held in Macau, China, in December 2012. The sixty five revised complete papers have been conscientiously reviewed and chosen from a a variety of submissions. The papers are equipped in topical sections on knowledge multi-agent platforms, info mining, ontology mining, internet reasoning, social purposes of lively media, human-centered computing, personalization and model, shrewdpermanent electronic artwork and e-learning.

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Additional info for Active Media Technology: 8th International Conference, AMT 2012, Macau, China, December 4-7, 2012. Proceedings

Example text

The consensus partitions obtain A Clustering Ensemble Baseed on a Modified Normalized Mutual Information Metric 39 d fair, all experiments are averaged over 10 independdent To be more general and runs. In all experimentatio ons there are 120 independent partitions obtained by 120 independent runs of k-meeans clustering algorithm with different initialized sseed points and different k paraameter, ranging from k to 2*k. After selecting a subsett of clusters, to extract the finall partition from them, the real number of clusters is serrved by the consensus functions.

576–585. Springer, Heidelberg (2011) 26. : A Metric to Evaluate a Cluster by Eliminating Effect of Complement Cluster. , Edelkamp, S. ) KI 2011. LNCS, vol. 7006, pp. 246–254. Springer, Heidelberg (2011) 27. : An Innovative Combination of Particle Swarm Optimization, Learning Automaton and Great Deluge Algorithms for Dynamic Environments. International Journal of the Physical Sciences 6(22), 5121– 5127 (2011) 42 H. Parvin, B. Maleki, and S. Parvin 28. : A New N-gram Feature ExtractionSelection Method for Malicious Code.

Then we may assume a second partition , / , where denotes the union of all “positive” clusters in and others are in / . A cluster in is positive cluster for if more than half of its data points also belongs to . A Clustering Ensemble Based on a Modified Normalized Mutual Information Metric Now, define , , by ∑ 37 which is calculated as [9]: . ∑ , (1) ∑ ∑ denotes the number of shared patterns where is the total number of samples and between clusters and ; is the number of patterns in the cluster are the number of patterns in the cluster of partition .

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Active Media Technology: 8th International Conference, AMT 2012, Macau, China, December 4-7, 2012. Proceedings by Yin-Fu Huang, Shih-Hao Wang (auth.), Runhe Huang, Ali A. Ghorbani, Gabriella Pasi, Takahira Yamaguchi, Neil Y. Yen, Beijing Jin (eds.)


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