logo

EbookBell.com

Most ebook files are in PDF format, so you can easily read them using various software such as Foxit Reader or directly on the Google Chrome browser.
Some ebook files are released by publishers in other formats such as .awz, .mobi, .epub, .fb2, etc. You may need to install specific software to read these formats on mobile/PC, such as Calibre.

Please read the tutorial at this link:  https://ebookbell.com/faq 


We offer FREE conversion to the popular formats you request; however, this may take some time. Therefore, right after payment, please email us, and we will try to provide the service as quickly as possible.


For some exceptional file formats or broken links (if any), please refrain from opening any disputes. Instead, email us first, and we will try to assist within a maximum of 6 hours.

EbookBell Team

Modeling Intention In Email Speech Acts Information Leaks And Recommendation Models 1st Edition Vitor R Carvalho Auth

  • SKU: BELL-2160026
Modeling Intention In Email Speech Acts Information Leaks And Recommendation Models 1st Edition Vitor R Carvalho Auth
$ 31.00 $ 45.00 (-31%)

4.3

18 reviews

Modeling Intention In Email Speech Acts Information Leaks And Recommendation Models 1st Edition Vitor R Carvalho Auth instant download after payment.

Publisher: Springer-Verlag Berlin Heidelberg
File Extension: PDF
File size: 1.62 MB
Pages: 104
Author: Vitor R. Carvalho (auth.)
ISBN: 9783642199554, 3642199550
Language: English
Year: 2011
Edition: 1

Product desciption

Modeling Intention In Email Speech Acts Information Leaks And Recommendation Models 1st Edition Vitor R Carvalho Auth by Vitor R. Carvalho (auth.) 9783642199554, 3642199550 instant download after payment.

Everyday 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.

Related Products