Download e-book for iPad: Active Media Technology: 8th International Conference, AMT by Yin-Fu Huang, Shih-Hao Wang (auth.), Runhe Huang, Ali A.

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

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Read or Download Active Media Technology: 8th International Conference, AMT 2012, Macau, China, December 4-7, 2012. Proceedings PDF

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

Example text

Users take part in the topic interaction for the sake of knowing the truth of a news event or expressing their own personal feeling. The relationships among members in a topic group are weak because the group is mainly maintained by user interests [11]. The topic group dissolves when users lose interests in the related topic. 2 Development of a Blog Topic A blog topic can experience the birth, growth, maturity and fade [12]. At the beginning, one blogger sponsors an issue, and other bloggers are attracted to join.

The partitioning is denoted by . The is obtained by a k-means algorithm with a new initialization of the seed points. Note that the is to extract clusters out of dataset. Then each partitioning is broken in some distinct partitions (or clusters). It means converted to clusters denoted by , ,… respectively. After obtaining a pool of clusters, in the second step, a stability value is computed as a tag for each of them. The stability value of the cluster is denoted by . 2 in more detail. A subset of stable clusters having a good diversity is selected by a thresholding scheme in the third step.

On Computational Statistics, COMPSTAT (2002) 30. : Cluster ensembles - a knowledge reuse framework for combining multiple partitions. Journal of Machine Learning Research 3, 583–617 (2002) 31. : A New Criterion for Clusters Validation. , Papadopoulos, H. ) EANN/AIAI 2011, Part II. IFIP AICT, vol. 364, pp. 110–115. Springer, Heidelberg (2011) 32. : A density-based algorithm for discovering clusters in large spatial databases with noise. In: International Conference on Knowledge Discovery and Data Mining, pp.

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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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