Abstract
Open-ended questions are questions that allow someone to give a free-form answer. Analysis and evaluation of answers to open-ended questions require automation. Experts who develop standards of free-form answers use uncertain information. Uncertainty may appear in cases of synonymy, polysemy, insufficiency or redundancy of the object description. Therefore, fuzziness is the most common type of uncertainty in activities related to the evaluation of answers to open-ended questions. This paper describes the methodology for evaluation free-form answers using knowledge discovery methods. Methods of knowledge discovery consider the uncertainty and fuzziness in the answers to open-ended questions. This article also describes the architecture of the expert system of electronic testing that implements the developed methodology.
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Acknowledgements
This paper has been approved within the framework of the federal target project “R&D for Priority Areas of the Russian Science-and-Technology Complex Development for 2014-2020”, government contract No 14.607.21.0164 on the subject “The development of architecture, methods and models to build software and hardware complex semantic analysis of semi-structured information resources on the Russian element base” (Application Code «2016-14-579-0009-0687»).
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Zarubin, A., Koval, A., Filippov, A., Moshkin, V. (2017). Application of Syntagmatic Patterns to Evaluate Answers to Open-Ended Questions. In: Kravets, A., Shcherbakov, M., Kultsova, M., Groumpos, P. (eds) Creativity in Intelligent Technologies and Data Science. CIT&DS 2017. Communications in Computer and Information Science, vol 754. Springer, Cham. https://doi.org/10.1007/978-3-319-65551-2_11
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