Abstract
TERENCE is an FP7 ICT European project that is developing an adaptive learning system for supporting poor comprehenders and their educators. Its learning material are books of stories and games. The so-called smart games serve to stimulate story comprehension. This paper focuses on the analysis of flat stories with a specific annotation language and the generation of smart games from the analysed texts, mixing natural language processing and temporal constraint-reasoning technologies. The paper ends commenting on the approach to the automated analysis and extraction of information from stories for specific users and domains, briefly evaluating the benefits of the semi-automated generation process in terms of production costs.
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Acknowledgments
The authors’ work was supported by the TERENCE project. TERENCE is funded by the European Commission through the Seventh Framework Programme for RTD, Strategic Objective ICT-2009.4.2, ICT, Technology-enhanced learning. The contents of the paper reflects only the authors’ view and the European Commission is not liable for it. Gennari work was also supported by the DARE project, financed by the Province of Bozen-Bolzano.
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Gennari, R., Tonelli, S., Vittorini, P. (2013). An AI-Based Process for Generating Games from Flat Stories. In: Bramer, M., Petridis, M. (eds) Research and Development in Intelligent Systems XXX. SGAI 2013. Springer, Cham. https://doi.org/10.1007/978-3-319-02621-3_25
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