A Context-Aware Decision Engine for Content Adaptation
IEEE Pervasive Computing
Enhancing pervasive Web accessibility with rule-based adaptation strategy
Expert Systems with Applications: An International Journal
Reinforcement learning for dynamic multimedia adaptation
Journal of Network and Computer Applications
Adapting multimedia Internet content for universal access
IEEE Transactions on Multimedia
Digital item adaptation: overview of standardization and research activities
IEEE Transactions on Multimedia
Optimal adaptation decision-taking for terminal and network quality-of-service
IEEE Transactions on Multimedia
QoS-based adaptation service selection broker
Future Generation Computer Systems
Scalable multimedia delivery with QoS management in pervasive computing environment
The Journal of Supercomputing
A survey on content adaptation systems towards energy consumption awareness
Advances in Multimedia
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In heterogeneous environments, universal multimedia access (UMA) is proposed to provide multimedia content services. Multimedia adaptation is one of technologies to perform UMA, in which adaptation decision-taking engine (ADTE) is a key component. Though there are many models of ADTE existing, it needs to be reconsidered for personalized content services. In this paper, a novel model of ADTE is proposed based on decision tree termed adaptation decision tree (ADT) in which adaptation decision is viewed as sequence decision: modality decision and format decision. Correspondingly, user preferences are divided into two types: user modality preferences and user format preferences. By utilizing user preferences, the ADT model is built up. Before making decision, an optimal multimedia variation set (OMVS) with respect to user modality preferences is constructed and any element here is with the shortest distance to user format preferences for every modality. Therefore, adaptation decision can be executed by letting the element in OMVS travel along the ADT one by one. Finally, the first element that reaches the leaf with the logical value true is the decision result, or the one with the smallest value in distance is the decision variation if no elements get to proper leaf. Quantitative analysis and experimental simulation prove that the model is effective and efficient to cope with adaptation decision in multimedia adaptation especially in dynamic user preferences and resource-limited cases.