Abstract
This paper presents Sherlock, a semi-automatic quiz generation system for educational purposes. By exploiting semantic and machine learning technologies, Sherlock not only offers a generic framework for domain independent quiz generation, but also provides a mechanism for automatically controlling the difficulty level of the generated quizzes. We evaluate the effectiveness of the system based on three real-world datasets.
| Original language | English |
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| Title of host publication | 13th International Semantic Web Conference |
| Place of Publication | Italy |
| Publication status | Published - 2014 |