{"title":"AttachMate:突出从电子邮件附件中提取","authors":"J. Hailpern, S. Asur, Kyle Rector","doi":"10.1145/2642918.2647419","DOIUrl":null,"url":null,"abstract":"While email is a major conduit for information sharing in enterprise, there has been little work on exploring the files sent along with these messages -- attachments. These accompanying documents can be large (multiple megabytes), lengthy (multiple pages), and not optimized for the smaller screen sizes, limited reading time, and expensive bandwidth of mobile users. Thus, attachments can increase data storage costs (for both end users and email servers), drain users' time when irrelevant, cause important information to be missed when ignored, and pose a serious access issue for mobile users. To address these problems we created AttachMate, a novel email attachment summarization system. AttachMate can summarize the content of email attachments and automatically insert the summary into the text of the email. AttachMate also stores all files in the cloud, reducing file storage costs and bandwidth consumption. In this paper, the primary contribution is the AttachMate client/server architecture. To ground, support and validate the AttachMate system we present two upfront studies (813 participants) to understand the state and limitations of attachments, a novel algorithm to extract representative concept sentences (tested through two validation studies), and a user study of AttachMate within an enterprise.","PeriodicalId":20543,"journal":{"name":"Proceedings of the 27th annual ACM symposium on User interface software and technology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"AttachMate: highlight extraction from email attachments\",\"authors\":\"J. Hailpern, S. Asur, Kyle Rector\",\"doi\":\"10.1145/2642918.2647419\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"While email is a major conduit for information sharing in enterprise, there has been little work on exploring the files sent along with these messages -- attachments. These accompanying documents can be large (multiple megabytes), lengthy (multiple pages), and not optimized for the smaller screen sizes, limited reading time, and expensive bandwidth of mobile users. Thus, attachments can increase data storage costs (for both end users and email servers), drain users' time when irrelevant, cause important information to be missed when ignored, and pose a serious access issue for mobile users. To address these problems we created AttachMate, a novel email attachment summarization system. AttachMate can summarize the content of email attachments and automatically insert the summary into the text of the email. AttachMate also stores all files in the cloud, reducing file storage costs and bandwidth consumption. In this paper, the primary contribution is the AttachMate client/server architecture. To ground, support and validate the AttachMate system we present two upfront studies (813 participants) to understand the state and limitations of attachments, a novel algorithm to extract representative concept sentences (tested through two validation studies), and a user study of AttachMate within an enterprise.\",\"PeriodicalId\":20543,\"journal\":{\"name\":\"Proceedings of the 27th annual ACM symposium on User interface software and technology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 27th annual ACM symposium on User interface software and technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2642918.2647419\",\"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 27th annual ACM symposium on User interface software and technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2642918.2647419","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
AttachMate: highlight extraction from email attachments
While email is a major conduit for information sharing in enterprise, there has been little work on exploring the files sent along with these messages -- attachments. These accompanying documents can be large (multiple megabytes), lengthy (multiple pages), and not optimized for the smaller screen sizes, limited reading time, and expensive bandwidth of mobile users. Thus, attachments can increase data storage costs (for both end users and email servers), drain users' time when irrelevant, cause important information to be missed when ignored, and pose a serious access issue for mobile users. To address these problems we created AttachMate, a novel email attachment summarization system. AttachMate can summarize the content of email attachments and automatically insert the summary into the text of the email. AttachMate also stores all files in the cloud, reducing file storage costs and bandwidth consumption. In this paper, the primary contribution is the AttachMate client/server architecture. To ground, support and validate the AttachMate system we present two upfront studies (813 participants) to understand the state and limitations of attachments, a novel algorithm to extract representative concept sentences (tested through two validation studies), and a user study of AttachMate within an enterprise.