ABSTRACT
Interaction with hypermedia documents is a required feature for new sophisticated yet flexible multimedia applications. This paper presents an innovative adaptive technique to stream hypervideo that takes into account user behaviour. The objective is to optimize hypervideo prefetching in order to reduce the latency caused by the network. This technique is based on a model provided by a Markov Decision Process approach. The problem is solved using two methods: classical stochastic dynamic programming algorithms and reinforcement learning. Experimental results under stochastic network conditions are very promising.
- MPEG-21, MPEG Group, Multimedia Framework, http://www.cselt.it/mpegGoogle Scholar
- B. Trousse, Evaluation of the Prediction Capability of a User behaviour Mining Approach for Adapative Web Sites, Proc. RIAO 2000, 6th Conference on Content-Based Multimedia Information Access, Paris, France, 2000.Google Scholar
- Apple, QuickTimeVR, http://quicktime.apple.comGoogle Scholar
- N. Sawhney, D. Balcom, I. Smith, Authoring and navigating video in space and time: A Framework and Approach towards Hypervideo, IEEE Multimedia, 4, 4, 1997 http://www.lcc.gatech.edu/gallery/hypercafe Google ScholarDigital Library
- J. Tolva, MediaLoom, An Interactive Authoring Tool for HyperVideo, M.S. Project Paper, Georgia Institute of Technology, 1998.Google Scholar
- I. Zukerman, D. Albrecht, Predictive Statistical Models for User Modeling User Modeling and User-Adapted Interaction, 2001. Google ScholarDigital Library
- M. Crovella, P. Barford, The Network Effects of Prefetching, Proc. of Infocom'98, IEEE, April 1998.Google Scholar
- Y. Aumann et al., Predicting Event Sequences: Data Mining for Prefetching Web-pages, Proc. of KDD'98.Google Scholar
- K. Aberer, S. Hollfelder, Resource Prediction and Admission Control for Interactive Video Browsing Scenarios Using Application Semantics, GMD Report No. 40, September 1998. Google ScholarDigital Library
- D. Albrecht, I. Zukerman, A. Nicholson, Pre-sending Documents on the WWW: A comparative Study, Proc. IJCAI'99, August 1999. Google ScholarDigital Library
- T. Syeda-Mahmood, Learning and Tracking Browsing Behavior of Users using Hidden Markov Models, IBM Make It Easy Conference, 2001.Google Scholar
- T. Syeda-Mahmood, D. Ponceleon, Learning video browsing behavior and its application in the generation of video previews, Proc. ACM Multimedia 20001. Google ScholarDigital Library
- A. Kohrs, B. Merialdo, Creating user-adapted Websites by the use of collaborative filtering, Interacting with Computers, Volume 13, Issue 6, August 2001.Google Scholar
- R. Grigoraş, V. Charvillat, M. Douze, Self-adaptive multimedia content, Proc. ECMCS, September 2001.Google Scholar
- R. E. Bellman, Dynamic programming, Princeton University Press, 1957. Google ScholarDigital Library
- D. P. Bertsekas, J. N. Tsitsikis, Neurodynamic programming, Athena Scientific, Belmond, Massachusetts, 1996. Google ScholarDigital Library
- M. L. Puterman, Markov decision processes: discrete stochastic dynamic programming, Wiley-Interscience, New York, 1994. Google ScholarDigital Library
- R. S. Sutton, A. G. Barto, Reinforcement Learning: An Introduction, MIT Press, Cambridge, Massachusetts, 1998. Google ScholarDigital Library
Index Terms
- Optimizing hypervideo navigation using a Markov decision process approach
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