{"title":"A framework for adaptive mail classification","authors":"G. Manco, E. Masciari, Andrea Tagarelli","doi":"10.1109/TAI.2002.1180829","DOIUrl":null,"url":null,"abstract":"We introduce a technique based on data mining algorithms for classifying incoming messages, as a basis for an overall architecture for maintenance and management of e-mail messages. We exploit clustering techniques for grouping structured and unstructured information extracted from e-mail messages in an unsupervised way, and exploit the resulting algorithm in the process of folder creation (and maintenance) and e-mail redirection. Some initial experimental results show the effectiveness of the technique, both from an efficiency and a quality-of-results viewpoint.","PeriodicalId":197064,"journal":{"name":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2002-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"14th IEEE International Conference on Tools with Artificial Intelligence, 2002. (ICTAI 2002). Proceedings.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.2002.1180829","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22
Abstract
We introduce a technique based on data mining algorithms for classifying incoming messages, as a basis for an overall architecture for maintenance and management of e-mail messages. We exploit clustering techniques for grouping structured and unstructured information extracted from e-mail messages in an unsupervised way, and exploit the resulting algorithm in the process of folder creation (and maintenance) and e-mail redirection. Some initial experimental results show the effectiveness of the technique, both from an efficiency and a quality-of-results viewpoint.