{"title":"通过吸收认知图上的随机游走来估计课堂理解能力","authors":"Nimit Pattanasri, M. Mukunoki, M. Minoh","doi":"10.1145/1645953.1646226","DOIUrl":null,"url":null,"abstract":"This paper develops a graph-theoretic framework for estimating comprehension in classroom. To deal with imprecise data gathered in classroom, we propose multi-step comprehension propagation over a semantic graph. Random walks on the graph measure students' comprehension with probabilities absorbed at student nodes.","PeriodicalId":286251,"journal":{"name":"Proceedings of the 18th ACM conference on Information and knowledge management","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ComprehEnRank: estimating comprehension in classroom by absorbing random walks on a cognitive graph\",\"authors\":\"Nimit Pattanasri, M. Mukunoki, M. Minoh\",\"doi\":\"10.1145/1645953.1646226\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper develops a graph-theoretic framework for estimating comprehension in classroom. To deal with imprecise data gathered in classroom, we propose multi-step comprehension propagation over a semantic graph. Random walks on the graph measure students' comprehension with probabilities absorbed at student nodes.\",\"PeriodicalId\":286251,\"journal\":{\"name\":\"Proceedings of the 18th ACM conference on Information and knowledge management\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 18th ACM conference on Information and knowledge management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1645953.1646226\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 18th ACM conference on Information and knowledge management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1645953.1646226","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ComprehEnRank: estimating comprehension in classroom by absorbing random walks on a cognitive graph
This paper develops a graph-theoretic framework for estimating comprehension in classroom. To deal with imprecise data gathered in classroom, we propose multi-step comprehension propagation over a semantic graph. Random walks on the graph measure students' comprehension with probabilities absorbed at student nodes.
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