{"title":"The 4W (What-Where-When-Who) Project Goes Social","authors":"M. Migliardi, Marco Gaudina","doi":"10.1109/IMIS.2012.58","DOIUrl":null,"url":null,"abstract":"The 4W (What-Where-When-Who)project has demonstrated that the combination of rich content delivering devices, such as smart phones, together wireless broadband networking and server side computational power can be used to seamlessly weave a mesh of smart services and intelligent environments providing support to human memory capabilities. Our system is capable of capturing user needs and to-dos, infer where those needs and tasks can be efficiently fulfilled/performed and provide timely and localized hints about the identified sweet spots. However, to perform this task an efficient way of classifying user provided needs and to-dos is necessary. In this paper we describe how we leveraged a social-network like approach to populate and enrich our classification engine in a user-controlled, cooperative way.","PeriodicalId":290976,"journal":{"name":"2012 Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMIS.2012.58","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The 4W (What-Where-When-Who)project has demonstrated that the combination of rich content delivering devices, such as smart phones, together wireless broadband networking and server side computational power can be used to seamlessly weave a mesh of smart services and intelligent environments providing support to human memory capabilities. Our system is capable of capturing user needs and to-dos, infer where those needs and tasks can be efficiently fulfilled/performed and provide timely and localized hints about the identified sweet spots. However, to perform this task an efficient way of classifying user provided needs and to-dos is necessary. In this paper we describe how we leveraged a social-network like approach to populate and enrich our classification engine in a user-controlled, cooperative way.