{"title":"基于知识关联的资源聚合方法研究","authors":"Xu Du, Liqiu Ke, Hao Li, Juan Yang","doi":"10.1109/eitt.2017.60","DOIUrl":null,"url":null,"abstract":"With the rapid growth of digital learning resources, the problem of learners' information overload has become increasingly prominent. Aiming at the problem of resource aggregation and personalized needs in digital learning, this paper proposes a resource aggregation method based on knowledge element correlation. The main contributions are threefold. Firstly, to depict the correlation between learning resources and knowledge elements, this paper propose a multi-dimensional weights strategy; Secondly, to depict the relationships among knowledge points, this paper proposes a concept of hierarchical knowledge elements tuples; and thirdly, to maintain and explore the relationships of knowledge points, a mechanism of multi-views is proposed.","PeriodicalId":412662,"journal":{"name":"2017 International Conference of Educational Innovation through Technology (EITT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Resource Aggregation Method Based on Knowledge Correlation\",\"authors\":\"Xu Du, Liqiu Ke, Hao Li, Juan Yang\",\"doi\":\"10.1109/eitt.2017.60\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid growth of digital learning resources, the problem of learners' information overload has become increasingly prominent. Aiming at the problem of resource aggregation and personalized needs in digital learning, this paper proposes a resource aggregation method based on knowledge element correlation. The main contributions are threefold. Firstly, to depict the correlation between learning resources and knowledge elements, this paper propose a multi-dimensional weights strategy; Secondly, to depict the relationships among knowledge points, this paper proposes a concept of hierarchical knowledge elements tuples; and thirdly, to maintain and explore the relationships of knowledge points, a mechanism of multi-views is proposed.\",\"PeriodicalId\":412662,\"journal\":{\"name\":\"2017 International Conference of Educational Innovation through Technology (EITT)\",\"volume\":\"12 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference of Educational Innovation through Technology (EITT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/eitt.2017.60\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Conference of Educational Innovation through Technology (EITT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/eitt.2017.60","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Resource Aggregation Method Based on Knowledge Correlation
With the rapid growth of digital learning resources, the problem of learners' information overload has become increasingly prominent. Aiming at the problem of resource aggregation and personalized needs in digital learning, this paper proposes a resource aggregation method based on knowledge element correlation. The main contributions are threefold. Firstly, to depict the correlation between learning resources and knowledge elements, this paper propose a multi-dimensional weights strategy; Secondly, to depict the relationships among knowledge points, this paper proposes a concept of hierarchical knowledge elements tuples; and thirdly, to maintain and explore the relationships of knowledge points, a mechanism of multi-views is proposed.