{"title":"自适应传感器协同预测人体移动","authors":"Paul Baumann","doi":"10.1145/2638728.2638843","DOIUrl":null,"url":null,"abstract":"My thesis focuses on the prediction of human mobility. I am interested in gaining a deeper understanding of the factors that influence the performance of human mobility prediction algorithms. The main contributions of my work are: the analyses of different factors that influence the performance of mobility predictors, the design and development of a self-adaptive approach for detecting and recognizing users' relevant places, and estimating users' momentary predictability. The latter contribution aims to enable the possibility for the application scenarios to decide how much to trust the provided predictions and mobility data.","PeriodicalId":20496,"journal":{"name":"Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Adaptive sensor cooperation for predicting human mobility\",\"authors\":\"Paul Baumann\",\"doi\":\"10.1145/2638728.2638843\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"My thesis focuses on the prediction of human mobility. I am interested in gaining a deeper understanding of the factors that influence the performance of human mobility prediction algorithms. The main contributions of my work are: the analyses of different factors that influence the performance of mobility predictors, the design and development of a self-adaptive approach for detecting and recognizing users' relevant places, and estimating users' momentary predictability. The latter contribution aims to enable the possibility for the application scenarios to decide how much to trust the provided predictions and mobility data.\",\"PeriodicalId\":20496,\"journal\":{\"name\":\"Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2638728.2638843\",\"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 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2638728.2638843","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive sensor cooperation for predicting human mobility
My thesis focuses on the prediction of human mobility. I am interested in gaining a deeper understanding of the factors that influence the performance of human mobility prediction algorithms. The main contributions of my work are: the analyses of different factors that influence the performance of mobility predictors, the design and development of a self-adaptive approach for detecting and recognizing users' relevant places, and estimating users' momentary predictability. The latter contribution aims to enable the possibility for the application scenarios to decide how much to trust the provided predictions and mobility data.