M. Harbach, T. Muders, Ralf Groeper, Matthew Smith
{"title":"使用Mind Meshes进行邮件分类","authors":"M. Harbach, T. Muders, Ralf Groeper, Matthew Smith","doi":"10.1109/DEST.2011.5936621","DOIUrl":null,"url":null,"abstract":"While efficient email triage is a well-known problem, the currently used email filtering solutions are still rudimentary and machine centric. Most filtering solutions work best if humans add machine interpretable keywords to the subject line of emails. More natural filtering options, such as project membership lists or content-based filtering, are very time consuming to set up and maintain. Especially in research ecosystems, significant fluctuation in team members, organisations and projects themselves is common. Research projects are also usually managed in an ad-hoc manner, making static filtering rules a sub-optimal solution. In this paper we therefore introduce the Mind Mesh paradigm, a novel human-friendly information management approach. Based on a self-describing graph structure, organisational structures, projects, and collaborations are modelled. Leveraging this information, the system can automate and support administrative processes such as email filtering, based on an understanding of the project structures. It relieves users of the necessity to maintain machine interpretable rules by hand and adapts to new situations by itself.","PeriodicalId":297420,"journal":{"name":"5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Email triage with Mind Meshes\",\"authors\":\"M. Harbach, T. Muders, Ralf Groeper, Matthew Smith\",\"doi\":\"10.1109/DEST.2011.5936621\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"While efficient email triage is a well-known problem, the currently used email filtering solutions are still rudimentary and machine centric. Most filtering solutions work best if humans add machine interpretable keywords to the subject line of emails. More natural filtering options, such as project membership lists or content-based filtering, are very time consuming to set up and maintain. Especially in research ecosystems, significant fluctuation in team members, organisations and projects themselves is common. Research projects are also usually managed in an ad-hoc manner, making static filtering rules a sub-optimal solution. In this paper we therefore introduce the Mind Mesh paradigm, a novel human-friendly information management approach. Based on a self-describing graph structure, organisational structures, projects, and collaborations are modelled. Leveraging this information, the system can automate and support administrative processes such as email filtering, based on an understanding of the project structures. It relieves users of the necessity to maintain machine interpretable rules by hand and adapts to new situations by itself.\",\"PeriodicalId\":297420,\"journal\":{\"name\":\"5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-06-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DEST.2011.5936621\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DEST.2011.5936621","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
While efficient email triage is a well-known problem, the currently used email filtering solutions are still rudimentary and machine centric. Most filtering solutions work best if humans add machine interpretable keywords to the subject line of emails. More natural filtering options, such as project membership lists or content-based filtering, are very time consuming to set up and maintain. Especially in research ecosystems, significant fluctuation in team members, organisations and projects themselves is common. Research projects are also usually managed in an ad-hoc manner, making static filtering rules a sub-optimal solution. In this paper we therefore introduce the Mind Mesh paradigm, a novel human-friendly information management approach. Based on a self-describing graph structure, organisational structures, projects, and collaborations are modelled. Leveraging this information, the system can automate and support administrative processes such as email filtering, based on an understanding of the project structures. It relieves users of the necessity to maintain machine interpretable rules by hand and adapts to new situations by itself.