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Received: 2005-08-05

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Journal of Zhejiang University SCIENCE A 2005 Vol.6 No.11 P.1290~1296

http://doi.org/10.1631/jzus.2005.A1290


Enhancing the usage pattern mining performance with temporal segmentation of QPop Increment in digital libraries


Author(s):  CAO San-xing, KLEIN R. Rody, LIU Jian-bo

Affiliation(s):  Information Engineering School, Communication University of China, Beijing 100024, China; more

Corresponding email(s):   c3x@cuc.edu.cn, sanko_333@hotmail.com

Key Words:  Media-rich, Digital library, Data migration, Media content, Log mining, QPop


CAO San-xing, KLEIN R. Rody, LIU Jian-bo. Enhancing the usage pattern mining performance with temporal segmentation of QPop Increment in digital libraries[J]. Journal of Zhejiang University Science A, 2005, 6(11): 1290~1296.

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author="CAO San-xing, KLEIN R. Rody, LIU Jian-bo",
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Abstract: 
The convergence of next-generation Networks and the emergence of new media systems have made media-rich digital libraries popular in application and research. The discovery of media content objects’ usage patterns, where QPop Increment is the characteristic feature under study, is the basis of intelligent data migration scheduling, the very key issue for these systems to manage effectively the massive storage facilities in their backbones. In this paper, a clustering algorithm is established, on the basis of temporal segmentation of QPop Increment, so as to improve the mining performance. We employed the standard C-Means algorithm as the clustering kernel, and carried out the experimental mining process with segmented QPop Increases obtained in actual applications. The results indicated that the improved algorithm is more advantageous than the basic one in important indices such as the clustering cohesion. The experimental study in this paper is based on a Media Assets Library prototype developed for the use of the advertainment movie production project for Olympics 2008, under the support of both the Humanistic Olympics Study Center in Beijing, and China State Administration of Radio, Film and TV.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1] Cao, S., Lu, R., 2001. Large-Scale TV Station OA Application Systems Based on Intranet and Web. Proc. CIEYC2001, Beijing Broadcasting Institute Press, Beijing, p.234-237.

[2] Cao, S., Xu, J., Gao, F., 2003. Media Enterprise Resource Planning: Concept and Application Framework. Proc. 8th Intl. Symp. on Broadcast Tech., Hong Kong, p.120-124.

[3] Cao, S., Klein, R., Zheng, G., Geng, W., 2004. Managing Uncertainty in Media Content Platforms. Proc. 4th Intl. Symp. on Management of Technologies. Zhejiang University Press, Hangzhou, p.171-175.

[4] Gandhi, R., 2004. Improved results for data migration and open shop scheduling. LNCS, 3142:658-669.

[5] Hu, L., Meng, F., Hu, M., 2004. A Dynamic Load Balancing System Based on Data Migration. 8th International Conference on Computer Supported Cooperative Work in Design (IEEE Cat. No.04EX709), 1:493-499.

[6] Hu, W., Cao, S., Li, D., 2005. An improved algorithm of media content usage pattern mining based on temporal segmentation and dimensionality superinduction of QPop increases. Computer Science, 22(7B):178-180, 208.

[7] Khuller, S., Kim, Y.A., Wan, Y.C., 2004. Algorithms for data migration with cloning. SIAM Journal on Computing, 33(2):448-461.

[8] Song, Y., 2001. Technology and Choices of Media Assets Management. Proc. 8th Annual Academic Conference of CSMPTE, Beijing, p.4-20.

[9] Todd, S., 1978. Automatic data migration in distributed database system. IBM Technical Disclosure Bulletin, p.387-388.

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