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OverviewEveryday more than half of American adult internet users read or write email messages at least once. The prevalence of email has significantly impacted the working world, functioning as a great asset on many levels, yet at times, a costly liability. In an effort to improve various aspects of work-related communication, this work applies sophisticated machine learning techniques to a large body of email data. Several effective models are proposed that can aid with the prioritization of incoming messages, help with coordination of shared tasks, improve tracking of deadlines, and prevent disastrous information leaks. Carvalho presents many data-driven techniques that can positively impact work-related email communication and offers robust models that may be successfully applied to future machine learning tasks. Full Product DetailsAuthor: Vitor R. CarvalhoPublisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K Edition: 2011 Volume: 349 Dimensions: Width: 15.50cm , Height: 0.70cm , Length: 23.50cm Weight: 0.760kg ISBN: 9783642199554ISBN 10: 3642199550 Pages: 104 Publication Date: 06 November 2011 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Awaiting stock  The supplier is currently out of stock of this item. It will be ordered for you and placed on backorder. Once it does come back in stock, we will ship it out for you. Table of ContentsIntroduction.- Email “Speech Acts”.- Email Information Leaks.- Recommending Email Recipients.- User Study.- Conclusions.-Email Act Labeling Guidelines.- User Study Supporting Material.ReviewsFrom the reviews: “The targeted audience consists mainly of computer scientists, either researchers in machine learning or professionals who use email services in their work. The book would also be useful in education, especially to generate assignments for advanced students. Readers should have a machine learning background, but in general this monograph is easily readable. It provides a brief but comprehensive introduction to the peculiarities of email problems and the appropriate methods for addressing them. The updated bibliography and related work sections are useful for further study.” (Lefteris Angelis, ACM Computing Reviews, June, 2012) From the reviews: The targeted audience consists mainly of computer scientists, either researchers in machine learning or professionals who use email services in their work. The book would also be useful in education, especially to generate assignments for advanced students. Readers should have a machine learning background, but in general this monograph is easily readable. It provides a brief but comprehensive introduction to the peculiarities of email problems and the appropriate methods for addressing them. The updated bibliography and related work sections are useful for further study. (Lefteris Angelis, ACM Computing Reviews, June, 2012) Author InformationTab Content 6Author Website:Countries AvailableAll regions |
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