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

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

This ebook constitutes the refereed lawsuits 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 geared up in topical sections on know-how multi-agent structures, information mining, ontology mining, net reasoning, social purposes of energetic media, human-centered computing, personalization and edition, clever electronic paintings and e-learning.

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

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In: Proc. ACM Symposium on Applied Computing, pp. 846–852 (2011) 7. : Semantic event detection in baseball videos based on a multioutput hidden Markov model. In: Proc. ACM Symposium on Applied Computing, pp. 929–936 (2011) 8. : Scene-based event detection for baseball videos. Journal of Visual Communication and Image Representation 18(1), 1–14 (2007) 9. : Baseball video indexing using patternization of scenes and hidden Markov model. In: Proc. IEEE International Conference on Image Processing, pp.

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. When the topic enters into the growth phase, users actively express opinions or spread the topic. While the topic group rapidly grows up, some ordinary users can become opinion leaders that are influential in giving birth to the public opinion.

The total stability of cluster is defined as: ∑ (2) This procedure is applied for each cluster available in the pool clusters obtained in the first step. It means this procedure must be iterated times, where is computed as equation 3. ∑ (3 Third step is simply done be a thresholding. It means that the clusters with higher stability values are selected for next step and other are omitted. In forth step, the selected clusters are used to produce final clusters in a coassociation based model. In the step it is to construct the co-association matrix and then to apply a hierarchical clustering.

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