{"title":"分析电子邮件通信活动,检测病理行为模式","authors":"M. Negnevitsky, Mark Jyn-Huey Lim, J. Hartnett","doi":"10.23919/FRUCT.2017.8071329","DOIUrl":null,"url":null,"abstract":"E-mail is one of the most popular and widely used form of electronic communication used today. The patterns in the social interactions or contacts between people by e-mail can be analysed using social network analysis and user behaviour analysis. In this paper we provide a review of the work related to the areas of dynamic modelling and link prediction of social networks, and anomaly detection for detecting changes in the behaviour of e-mail usage. We then discuss about the benefits of applying artificial intelligence techniques to these fields.","PeriodicalId":114353,"journal":{"name":"2017 20th Conference of Open Innovations Association (FRUCT)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Analysis of E-mail communication activities for detecting patterns of pathological behaviour\",\"authors\":\"M. Negnevitsky, Mark Jyn-Huey Lim, J. Hartnett\",\"doi\":\"10.23919/FRUCT.2017.8071329\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"E-mail is one of the most popular and widely used form of electronic communication used today. The patterns in the social interactions or contacts between people by e-mail can be analysed using social network analysis and user behaviour analysis. In this paper we provide a review of the work related to the areas of dynamic modelling and link prediction of social networks, and anomaly detection for detecting changes in the behaviour of e-mail usage. We then discuss about the benefits of applying artificial intelligence techniques to these fields.\",\"PeriodicalId\":114353,\"journal\":{\"name\":\"2017 20th Conference of Open Innovations Association (FRUCT)\",\"volume\":\"42 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 20th Conference of Open Innovations Association (FRUCT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/FRUCT.2017.8071329\",\"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 20th Conference of Open Innovations Association (FRUCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/FRUCT.2017.8071329","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analysis of E-mail communication activities for detecting patterns of pathological behaviour
E-mail is one of the most popular and widely used form of electronic communication used today. The patterns in the social interactions or contacts between people by e-mail can be analysed using social network analysis and user behaviour analysis. In this paper we provide a review of the work related to the areas of dynamic modelling and link prediction of social networks, and anomaly detection for detecting changes in the behaviour of e-mail usage. We then discuss about the benefits of applying artificial intelligence techniques to these fields.