Abstract
Collaborative Declarative Modeling combines the flexibility of abstract declarative description of a scene with the integration of views and opinions of multiple designers. One of the stages where this integration applies is the scene understanding phase, where solutions corresponding to the submitted description are visualized and evaluated. In the current work we propose a mechanism for collaborative solution evaluation based on previous feedback with respect to each collaborating designer’s preferences. Designers are grouped into clusters of preference revealing the proximity of their evaluations for previously seen solutions. These clusters are formed upon criteria ensuring wide inter-cluster preference representation and thorough intra-cluster compactness. Clusters subsequently participate through representative designers to the formation of the consensus solution set corresponding to the submitted description. The proposed mechanism allows adjustment of parameters controlling intuitive characteristics of the collaborative declarative design methodology such as importance of each designer and strictness in solution evaluation.
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Doulamis, N., Bardis, G., Dragonas, J., Miaoulis, G., Plemenos, D. (2009). Collaborative Evaluation Using Multiple Clusters in a Declarative Design Environment. In: Plemenos, D., Miaoulis, G. (eds) Artificial Intelligence Techniques for Computer Graphics. Studies in Computational Intelligence, vol 159. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85128-8_9
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DOI: https://doi.org/10.1007/978-3-540-85128-8_9
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