Learner preferences prediction with mixture embedding of knowledge and behavior graph
To solve the problems of inaccurate prediction of learner preference and insufficient utilization of structural information in the knowledge recommendation model, for the knowledge structure and learner behavior structure in the learner’s preference prediction model, the model of learner preferences...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2021-08-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021125/ |
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| _version_ | 1841539295891947520 |
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| author | Xiaoguang LI Lei GONG Xiaoli LI Xin ZHANG Ge YU |
| author_facet | Xiaoguang LI Lei GONG Xiaoli LI Xin ZHANG Ge YU |
| author_sort | Xiaoguang LI |
| collection | DOAJ |
| description | To solve the problems of inaccurate prediction of learner preference and insufficient utilization of structural information in the knowledge recommendation model, for the knowledge structure and learner behavior structure in the learner’s preference prediction model, the model of learner preferences predication with mixture embedding of knowledge and behavior graph was proposed.First, considering using graph convolution network (GCN) to fit structural information, GCN was extended to knowledge graph and behavior graph, the purpose of which was to obtain learners’ overall learning pattern and individual learning pattern.Then, the difference between knowledge structure and behavior structure was used to fit learners’ individual preferences, and recurrent neural network was used to encode and decode learners’ preferences to obtain the distribution of learners’ preference distribution.The experimental results on the real datasets demonstrate that the proposed model has a good effect on predicting learner preferences. |
| format | Article |
| id | doaj-art-a42760677eb940a6adcc4e919784d1a3 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2021-08-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-a42760677eb940a6adcc4e919784d1a32025-01-14T07:22:22ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2021-08-014213013859743413Learner preferences prediction with mixture embedding of knowledge and behavior graphXiaoguang LILei GONGXiaoli LIXin ZHANGGe YUTo solve the problems of inaccurate prediction of learner preference and insufficient utilization of structural information in the knowledge recommendation model, for the knowledge structure and learner behavior structure in the learner’s preference prediction model, the model of learner preferences predication with mixture embedding of knowledge and behavior graph was proposed.First, considering using graph convolution network (GCN) to fit structural information, GCN was extended to knowledge graph and behavior graph, the purpose of which was to obtain learners’ overall learning pattern and individual learning pattern.Then, the difference between knowledge structure and behavior structure was used to fit learners’ individual preferences, and recurrent neural network was used to encode and decode learners’ preferences to obtain the distribution of learners’ preference distribution.The experimental results on the real datasets demonstrate that the proposed model has a good effect on predicting learner preferences.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021125/knowledge graphbehavior graphGCNknowledge recommendation |
| spellingShingle | Xiaoguang LI Lei GONG Xiaoli LI Xin ZHANG Ge YU Learner preferences prediction with mixture embedding of knowledge and behavior graph Tongxin xuebao knowledge graph behavior graph GCN knowledge recommendation |
| title | Learner preferences prediction with mixture embedding of knowledge and behavior graph |
| title_full | Learner preferences prediction with mixture embedding of knowledge and behavior graph |
| title_fullStr | Learner preferences prediction with mixture embedding of knowledge and behavior graph |
| title_full_unstemmed | Learner preferences prediction with mixture embedding of knowledge and behavior graph |
| title_short | Learner preferences prediction with mixture embedding of knowledge and behavior graph |
| title_sort | learner preferences prediction with mixture embedding of knowledge and behavior graph |
| topic | knowledge graph behavior graph GCN knowledge recommendation |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021125/ |
| work_keys_str_mv | AT xiaoguangli learnerpreferencespredictionwithmixtureembeddingofknowledgeandbehaviorgraph AT leigong learnerpreferencespredictionwithmixtureembeddingofknowledgeandbehaviorgraph AT xiaolili learnerpreferencespredictionwithmixtureembeddingofknowledgeandbehaviorgraph AT xinzhang learnerpreferencespredictionwithmixtureembeddingofknowledgeandbehaviorgraph AT geyu learnerpreferencespredictionwithmixtureembeddingofknowledgeandbehaviorgraph |