A Self-Relevant CNN-SVM Model for Problem Classification in K-12 Question-Driven Learning
With the development and progress of science and technology, the learning patterns also evolve. In Question-Driven learning, students clarify and validate what they learn by answering questions. Such a large number of questions needs good management. A well-performed management can avoid the situati...
Main Authors: | Eric Hsiao-Kuang Wu, Sung-En Chen, Jhao-Jhong Liu, Yu-Yen Ou, Min-Te Sun |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9265190/ |
Similar Items
-
Instruction2vec: Efficient Preprocessor of Assembly Code to Detect Software Weakness with CNN
by: Yongjun Lee, et al.
Published: (2019-09-01) -
Cross-Domain Text Sentiment Analysis Based on CNN_FT Method
by: Jiana Meng, et al.
Published: (2019-05-01) -
Bin2Vec: A Better Wafer Bin Map Coloring Scheme for Comprehensible Visualization and Effective Bad Wafer Classification
by: Junhong Kim, et al.
Published: (2019-02-01) -
Benchmarking authorship attribution techniques using over a thousand books by fifty Victorian era novelists
by: Gungor, Abdulmecit
Published: (2018) -
Segmentation and detection of cattle branding images using CNN and SVM classification
by: Carlos SILVA, et al.
Published: (2020-05-01)