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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.)

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

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

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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. 226–231. AAAI Press (1996) 33. : SLINK: an optimally efficient algorithm for the single-link cluster method. jp Abstract. Side information such as pairwise constraints is useful to improve the clustering performance in general. However, constraints are not always error free in general.

22–31, 2012. c Springer-Verlag Berlin Heidelberg 2012 Hot Topic Detection in News Blogs from the Perspective of W2T 23 incremental term frequency inverse document frequency model and incremental clustering algorithm to detect new events, and considered the frequency and consecutive time of news reports to evaluate the topic hotness. Chen et al. [3] first extracted hot words based on the distribution over time and life cycle, then identified key sentences and grouped the key sentences into clusters that represent hot topics.

In: Proc. ACM Symposium on Applied Computing, pp. 1–9 (2008) 6. : An event-based video retrieval system by combining broadcasting baseball video and web-casting text. 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.

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