Machine Learning Email Prediction System (MLEPS)
نویسندگان
چکیده
منابع مشابه
Email Reply Prediction: A Machine Learning Approach
Email has now become the most-used communication tool in the world and has also become the primary business productivity applications for most organizations and individuals. With the ever increasing popularity of emails, email over-load and prioritization becomes a major problem for many email users. Users spend a lot of time reading, replying and organizing their emails. To help users organize...
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For several years now, email has grown rapidly as the most-used communications tool on the internet. One advantage of the Internet is the ease with which people can communicate online. The popularity of online communication has created an explosion of users who regularly access the internet to connect with others. Many people use email to stay in touch with relatives and friends who live far aw...
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Email has become one of the frequently used forms of communication. Everyone has at least one email account. Inflow of spam messages is a major problem faced by email users. Currently there are many spam filtering techniques. As the spam filtering techniques came up, spammers improved their methods of spamming. Thus, an effective spam filtering technique is the timely requirement. In this paper...
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Machine learning is a branch of artificial intelligence concerned with the creation and study of systems that can learn from data. A machine learning system could be trained to distinguish between spam and non-spam (ham) emails. We aim to analyze current methods in machine learning to identify the best techniques to use in content-based spam filtering.
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Our use of ordinary desktop applications (such as email, Web, calendars) is often a manifestation of the activities with which we are engaged (Moran, Cozzi, & Farrell 2005). Planning a conference trip involves sending travel expense forms, and visits to airline and hotel sites. Renovating a kitchen involves sketches, product specifications, emails with the architect and spreadsheets for trackin...
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ژورنال
عنوان ژورنال: International Journal for Infonomics
سال: 2010
ISSN: 1742-4712
DOI: 10.20533/iji.1742.4712.2010.0037