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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.1//EN" "http://www.w3.org/TR/xhtml11/DTD/xhtml11.dtd"> <html xmlns="http://www.w3.org/1999/xhtml" xml:lang="en"> <head> <!-- Global site tag (gtag.js) - Google Analytics --> <script async src="https://www.googletagmanager.com/gtag/js?id=UA-127118448-1"></script> <script> window.dataLayer = window.dataLayer || []; function gtag(){dataLayer.push(arguments);} gtag('js', new Date()); gtag('config', 'UA-127118448-1'); </script> <meta name="generator" content="jemdoc, see http://jemdoc.jaboc.net/" /> <meta http-equiv="Content-Type" content="text/html;charset=utf-8" /> <link rel="stylesheet" href="jemdoc.css" type="text/css" /> <link rel="shortcut icon" type="image/x-icon" href="favicon.ico" /> <title>Patents </title> </head> <body> <table summary="Table for page layout." id="tlayout"> <tr valign="top"> <td id="layout-menu"> <div class="menu-category">Home</div> <div class="menu-item"><a href="index.html" >About me</a></div> <div class="menu-item"><a href="research_interests.html">Research Interests</a></div> <div class="menu-item"><a href="Professional Activities.html">Professional Activities</a></div> <div class="menu-category">Research</div> <div class="menu-item"><a href="publications.html" >Publications</a></div> <div class="menu-item"><a href="patents.html" class="current">Patents</a></div> <div class="menu-item"><a href="RES Project&Founding.html">Projects&Funding</a></div> <div class="menu-category">My Lab</div> <div class="menu-item"><a href="graphme.github.io">GraphME</a></div> </td> </td> <td id="layout-content"> <div id="toptitle"> <h1>Patents </h1> </div> <ul> <p><b>[1] A hypergraph neural network based method for online learning peer assessment score aggregation</b><br> 【in Chinese: 一种基于超图神经网络的在线学习同伴互评分数聚合方法（发明专利，中国）】<br> <b>M. Li</b>, J. Duan, C. Huang, Y. Chen, S. Yang, 2023, China, submitted, CN202310279638.2 <br /> </p> <p> <b>[2] Multimodal data representation method based on modal interaction deep hypergraph neural network</b><br> 【in Chinese: 基于模态交互深层超图神经网络的多模态数据表示方法 （发明专利，中国）】<br> <b>M. Li</b>, J. Shi, J. Liang, Z. Li, X. Wu, 2023, China, submitted, CN202310284501.6 <br /> </p> <p><b>[3] A social recommendation method based on dynamic hypergraph representation learning</b><br> 【in Chinese: 一种基于动态超图表示学习的社交推荐方法 （发明专利，中国）】<br> <b>M. Li</b>, S. Ding, J. Liang, Z. Li, X. Wu, 2023, China, submitted, CN202310291550.2<br /> <p> <p><b>[4] An anomaly detection method based on dynamic hypergraph neural network</b><br> 【in Chinese: 一种基于动态超图神经网络的异常检测方法 （发明专利，中国）】<br> <b>M. Li</b>, S. Yang, J. Liang, Z. Li, X. Wu, 2023, China, submitted, CN202310306909.9<br /> </p> <p><b>[5] A student engagement prediction method based on multimodal hypergraph representation learning</b><br> 【in Chinese: 一种基于多模态超图表示学习的学生参与度预测方法 （发明专利，中国）】<br> <b>M. Li</b>, S. Yang, C. Huang, Y. Chen, S. Zhou, 2023, China, submitted, CN2023104518470<br /> </p> <p><b>[6] A hypergraph continual learning method, system, installation and storage</b><br> 【in Chinese: 一种超图持续学习方法、系统、装置及存储介质 （发明专利，中国）】<br> <b>M. Li</b>, X. Yang, J. Liang, L. Bai, Y. Chen, 2023, China, submitted, CN202310605381.5<br /> </p> <p><b>[7] Data analysis method, system and storage medium based on multi-modal graph neural networks</b><br> 【in Chinese: 基于多模态图神经网络的语义分析方法、系统和存储介质 （发明专利，中国）】<br> <b>M. Li</b>, Y. Chen, C. Huang, J. Liang, 2022, China, <b>granted</b>, ZL202110239109.0 <br /> <p> <p><b>[8] Graph-based social data analysis method, system and storage medium</b><br> 【in Chinese: 社交数据的分析方法、系统及存储介质 （发明专利，中国）】<br> <b>M. Li</b>, L. Zhang, C. Huang, J. Liang, 2022, China, <b>granted</b>, ZL202110246341.7 <br /> <p> <p><b>[9] Cognitive diagnosis method and system based on multimodal complementary graph neural network</b><br> 【in Chinese: 基于多模态互补图神经网络的认知诊断方法和系统 （发明专利，中国）】<br> <b>M. Li</b>, S. Wang, C. Huang, J. Liang, Y. Wang, 2022, China, submitted, CN202210361425.X <br /> <p> <p><b>[10] Student performance prediction method, system, device and storage medium based on graph neural network</b><br> 【in Chinese: 基于图神经网络的成绩预测方法、系统、装置及存储介质 （发明专利，中国）】<br> <b>M. Li</b>, X. Wang, C. Huang, Y. Chen, J. Zhu, 2022, China, submitted, CN202210415206.5 <br /> <p> <p><b>[11] Composite graph construction method, system, device and storage medium for multimodal data</b><br> 【in Chinese: 多模态数据的复合图构建方法、系统、装置及存储介质 （发明专利，中国）】<br> <b>M. Li</b>, S. Yang, J. Liang, Y. Wang, Y. Chen, 2022, China, submitted, CN202210438076.7 <br /> <p> <p><b>[12] Method, system, device and storage medium for graph representation learning for missing modality</b><br> 【in Chinese: 面向模态缺失的图表示学习方法、系统、装置及存储介质 （发明专利，中国）】<br> <b>M. Li</b>, J. Duan, J. Liang, Y. Wang, Y. Chen, 2022, China, submitted, CN202210434473.7 <br /> </p> <p><b>[13] Method, system, device and medium for video engagement prediction based on graph learning </b><br> 【in Chinese: 基于图学习的视频参与度预测方法、系统、装置及介质 （发明专利，中国）】<br> <b>M. Li</b>, X. Ou, J. Liang, L. Bai, 2022, China, submitted, CN202210620916.1 <br /> </p> <p><b>[14] Cognitive diagnosis method, system and storage medium based on graph neural network</b><br> 【in Chinese: 基于文本主驱动的学习者多模态情感分析方法及装置 （发明专利，中国）】<br> C. Huang, J. Zhang, <b>M. Li</b>, X. Wu, F. Jiang, Y. Tu, 2022, China, submitted, CN202210776860.9 <br /> </p> <p><b>[15] Cognitive diagnosis method, system and storage medium based on graph neural network</b><br> 【in Chinese: 基于图神经网络的认知诊断方法、系统和存储介质 （发明专利，中国）】<br> C. Huang, Y. Chen, <b>M. Li</b>, Q. Huang, 2022, China, submitted, CN202210253979.8<br /> <p><b>[16] Data processing for knowledge tracking based on graph convolution: method, system and storage medium</b><br> 【in Chinese: 基于图卷积的知识追踪数据处理方法、系统和存储介质 （发明专利，中国）】<br> C. Huang, Q. Huang, <b>M. Li</b>, X. Wang, T. He, 2021, China, <b>granted</b>, ZL201911230785.7 <br /> </p> <p><b>[17] Interpretable knowledge level tracking method, system and storage medium</b><br> 【in Chinese: 可解释性知识水平追踪方法、系统和存储介质 （发明专利，中国）】<br> C. Huang, Q. Huang, <b>M. Li</b>, X. Wang, 2022, China, <b>granted</b>, ZL202010801341.4 <br /> </p> <p><b>[18] Facial expression recognition model training, recognition method, system, device and interface</b><br> 【in Chinese: 人脸表情识别模型训练、识别方法、系统、装置及介质 （发明专利，中国）】<br> Q. Huang, C. Huang, <b>M. Li</b>, F. Jiang, J. Yu, 2021, China, submitted, CN202111024230.8 <br> </p> <p><b>[19] Entity alignment method, device and storage medium for multimodal knowledge graph</b><br> 【in Chinese: 多模态知识图谱的实体对齐方法、装置及存储介质 （发明专利，中国）】<br> J. Zhu, C. Huang, Z. Han, J. Zhu, C. Huang, Z. Han, M. Li,, 2023, granted, ZL202110686557.5 <br /> </p> <p><b>[20] A causal-driven teaching resource dynamic organization method supported by teaching and learning behavior data</b><br> 【in Chinese: 教与学行为数据支持下因果驱动的教学资源动态组织方法 （发明专利，中国）】<br> Q. Huang, C. Huang, Y. Wang, <b>M. Li</b>, Y. Tu, 2022, China, submitted, CN202211233241.1 <br /> </p> </ul> </td> </tr> </table> </body> </html>
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