Using and improving cosine similarity algorithm for building and managing question bank
Corressponding author's email:
pvtinh@hcmuaf.edu.vnKeywords:
Near Duplicate Detection, Text similarity, Cosine similarity, Weighted Cosine Similarity, Question bankAbstract
The bank of multiple-choice questions is a core component of the evaluation system to ensure the quality of training in educational institutions. The current research focuses only on the method of creating the exam from the prepared question bank, but it does not focus on the prevention of duplicate material in the question bank. As the number of questions in the question bank increases, the management of questions contents become more difficult and the duplication of question content becomes unavoidable. In this study, we propose using and improving the Cosine similarity algorithm by weighting the keywords (shingles) used to detect the duplicate content of questions in the exams or in question bank to ensure that exams are generated more accurately.
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