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- Title
Bayesian Network Model for Learning Arithmetic Concepts.
- Authors
Yali Lv; Tong Jing; Yuhua Qian; Jiye Liang; Jianai Wu; Junzhong Miao
- Abstract
An object usually belongs to multiple concepts, but some concepts can be judged directly while other concepts need to be inferred indirectly. To learn some arithmetic concepts from positive integer number sets, we address an arithmetic concept Bayesian network (ACBN) model by taking advantage of Bayesian networks. Specifically, we first give an ACBN model to represent the arithmetic concept knowledge and their direct relationships, and then we design an ACBN model learning algorithm based on domain knowledge. Furthermore, to infer indirectly some arithmetic concepts, we design the learning method of evidence concepts based on the idea of knearest neighbors, and then we propose the inference algorithm of the ACBN model. Finally, the experimental results demonstrate that the ACBN model can effectively learn some daily arithmetic concepts.
- Subjects
STUDY &; teaching of arithmetic; BAYESIAN analysis; LEARNING ability; PROBABILISTIC inference; COMPUTER algorithms
- Publication
International Journal of Performability Engineering, 2019, Vol 15, Issue 3, p939
- ISSN
0973-1318
- Publication type
Article
- DOI
10.23940/ijpe.19.03.p23.939948