Cultural Computing: Second IFIP TC 14 Entertainment by Ryohei Nakatsu, Visit Amazon's Naoko Tosa Page, search

By Ryohei Nakatsu, Visit Amazon's Naoko Tosa Page, search results, Learn about Author Central, Naoko Tosa, , Fazel Naghdy, Philippe Codognet

This e-book constitutes the refereed lawsuits of the moment IFIP TC 14 leisure Computing Symposium, ECS 2010, held as a part of the twenty first global desktop Congress, WCC 2010, in Brisbane, Australia, in September 2010. The 23 revised complete papers offered including one invited paper have been rigorously reviewed and chosen from quite a few submissions. The papers handle mammoth cultural concerns similar to sensitivity, reminiscence, spirituality, storytelling, racial features and so on. that experience no longer been handled in machine technological know-how and engineering to date. the subjects diversity from maintenance of cultural historical past and standard applied sciences utilizing desktops, treating types and kinds in cultural contents to cultural schooling utilizing desktops.

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Extra info for Cultural Computing: Second IFIP TC 14 Entertainment Computing Symposium, ECS 2010, Held as Part of WCC 2010, Brisbane, Australia, September 20-23, 2010, ... in Information and Communication Technology)

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In: Proc. of the 6th Annual Workshop on Conceptual Graphs, pp. 119–133 (1990) 15. : A General Psychoevolutionary Theory of Emotion. , Kellerman, H. ) Emotion: Theory, Research and Experience, vol. 1, pp. 3–33. Academic Press, New York (1980) 16. : Rational and Affective Linking Across Conceptual Cases – Without Rules. F. ) ICCS 1997. LNCS (LNAI), vol. 1257, pp. 460–473. au Abstract. There is much attention given to emerging technologies like mobile internet because of its increasing popularity.

At this k-value, demographic factors, income, started to show some significance and separated more precisely. In addition, age has clearer influenced on the cluster than the previous k-value. The ‘teenager’ is still the dominating attribute in clustering while there is no effect to clustering with gender. k=6. The cluster of ‘teenager’ is maintained and gender still has no effect towards clustering. Age and occupation seem to be clearer. There are different ages in each cluster such as more than 18 years old, more than 36 years old or between 19-35 years old.

The analysis should generate the appropriate number of clusters for mobile content users, leading to the identification of contents which these clusters of users will be accessing. The experiments are conducted with k-means where k=4,5,6,7 and 8 consecutively. Cluster Analysis for Personalised Mobile Entertainment Content 39 Zoning-Centroid. The evaluation method called ‘Zoning-Centroid’ is proposed in this paper. The distance from the centre of each cluster should be used to determine the cluster’s members in each cluster, and to ensure that they are appropriately distributed.

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