{"title":"面向在线协同学习的多模态情感计算研究","authors":"Jinpeng Yang, Yaofeng Xue, Zhitong Zeng, Wei Guo","doi":"10.1109/ICALT.2019.00045","DOIUrl":null,"url":null,"abstract":"Analyzing the emotion interaction of online collaborative learning, this paper proposes a multimodal affective computing model combined with the logical function. The framework of an affective computing is designed, which includes several modules for collection, processing, analysis and visualization of data, sentiment classification and feedback. Finally, the feasibility and validity of the prototype system is verified.","PeriodicalId":356549,"journal":{"name":"2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Research on Multimodal Affective Computing Oriented to Online Collaborative Learning\",\"authors\":\"Jinpeng Yang, Yaofeng Xue, Zhitong Zeng, Wei Guo\",\"doi\":\"10.1109/ICALT.2019.00045\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Analyzing the emotion interaction of online collaborative learning, this paper proposes a multimodal affective computing model combined with the logical function. The framework of an affective computing is designed, which includes several modules for collection, processing, analysis and visualization of data, sentiment classification and feedback. Finally, the feasibility and validity of the prototype system is verified.\",\"PeriodicalId\":356549,\"journal\":{\"name\":\"2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICALT.2019.00045\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICALT.2019.00045","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Multimodal Affective Computing Oriented to Online Collaborative Learning
Analyzing the emotion interaction of online collaborative learning, this paper proposes a multimodal affective computing model combined with the logical function. The framework of an affective computing is designed, which includes several modules for collection, processing, analysis and visualization of data, sentiment classification and feedback. Finally, the feasibility and validity of the prototype system is verified.