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Dynamic Selection of a Video Content Adaptation Strategy from a Pareto Front

This paper reports on our first enhancement of DCAF, namely to adapt content using the most optimal content adaptation strategy. Until now the combination of Genetic Algorithms with Pareto Optimality in DCAF would produce a Pareto front of optimal content adaptation strategies, all of which would suit the usage environment. However, since their distribution on the Pareto front suggested that there may be a ‘best-fit’ optimal strategy, DCAF was refined to take a step further at selecting a single strategy that would suit the content, usage environment and user profile. This was achieved with the application of Self-Organising Neural Networks.