منابع مشابه
Vassilka Deltcheva Ears – an Automatic E-mail Responding System (under the Direction of Michael A. Covington) Ears – an Automatic E-mail Responding System Ears – an Automatic E-mail Responding System I Appreciate My Friends and Colleagues
EARS is an intelligent e-mail responding system, which allows its users to receive timely replies to their computer problems and questions. This project targets the most common computer support requests currently handled by the computer center at The University of Georgia (UGA). The users of the system are UGA students, faculty and staff and for their benefit the system is designed to communica...
متن کاملLearning to classify e-mail
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a supervised learning setting, we investigate the use of random forest for automatic e-mail filing into folders and spam e-mail filtering. We show that random forest is a good choice for these tasks as it runs fast on large an...
متن کاملAssentor®: An NLP-Based Solution to E-mail Monitoring
This paper describes the Natural Language Processing (NLP) component of an e-mail monitoring product called Assentor. Assentor monitors electronic correspondence for brokerage firms. It uses pattern-matching-based information extraction technology to find and quarantine e-mail messages that indicate, among others, customer complaints, insider trading, stock hyping, hard-pressure sales tactics,...
متن کاملIile: an Application of Machine Learning to E-mail Filtering
With the proliferation of electronic mail in the modern era, it becomes ever more important to devise methods for the organization, categorization and searching of such mail. Mail ltering is such a method for the organization of incoming e-mail. In this paper, we critique modern mail lters and describe how Machine Learning techniques could improve upon them without eliminating the beneets they ...
متن کاملifile: An Application of Machine Learning to E-Mail Filtering
The rise of the World Wide Web and the ever-increasing amounts of machine-readable text has caused text classification to become a important aspect of machine learning. One specific application that has the potential to affect almost every user of the Internet is e-mail filtering. The WorldTalk Corporation estimates that over 60 million business people use e-mail [6]. Many more use e-mail purel...
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ژورنال
عنوان ژورنال: Academic Medicine
سال: 2016
ISSN: 1040-2446
DOI: 10.1097/acm.0000000000001029