MetaCart Sign in to MyCiteSeerX

Include Citations | Advanced Search | Help

Disambiguated Search | Include Citations | Advanced Search | Help

Automatic Induction of Rules for e-mail Classification [12 citations — 2 self]

by Elisabeth Crawford ,  Judy Kay ,  Eric Mccreath
Add To MetaCart

Abstract:

Many users receive large amounts of email. Since a substantial part of that mail is kept for future reference, it is unsurprising that many mail tools allow users to create filtering rules that automatically do actions like saving mail in suitable folders. Unfortunately, most users do not make much use of this facility.

Citations

2526 Induction of decision trees – Quinlan - 1986
236 A Bayesian approach to filtering junk e-mail – Sahami, Dumais, et al. - 1998
210 Email Overload: Exploring Personal Information Management of Email – Whittaker, Sidner - 1997
126 Learning rules that classify e-mail – Cohen - 1996
70 MailCat: An intelligent assistant for organizing e-mail – Segal, Kephart - 1999
63 33 experimental comparison of naive Bayesian and keyword-based antispam filtering with encrypted personal e-mail messages – Androutsopoulos, Koutsias, et al. - 2000
60 Concept features in Re:Agent, an intelligent e-mail agent – Boone - 1998
59 Triggers and barriers to customizing software – Mackay - 1991
52 Efficient top-down induction of logic programs – Cameron-Jones, Quinlan - 1994
45 Learning to Filter SPAM E-Mail: A Comparison of a Naïve Bayesian and a Memory-Based approach – Androutsopoulos, Paliouras, et al. - 2000
41 Interface Agents that Learn: An Investigation of Learning Issues in a Mail Agent Interface. Submitted to Applied – Payne, Edwards - 1995
30 D.: Spamcop: A spam classification & organization program. In: Learning for Text Categorization – Pantel, Lin - 1998
28 ifile: An Application of Machine Learning to E-Mail Filtering – Rennie - 2000
19 Naive-bayes vs. rule-learning in classification of email – Provost - 1999
16 Curbing Junk E-Mail via Secure Classification – Gabber, Jakobsson, et al. - 1998
13 Challenges of the Email Domain for Text Classification – Brutlag, Meek - 2000
13 Filtering junk e-mail: A performance comparison between genetic programming & naive bayes – Katirai - 1999
12 Representation of electronic mail filtering profiles: a user study – Pazzani - 2000
5 A bayesian approach to junk e-mail – Sahami, Dumais, et al. - 1998
2 Design and implementation of the Lucent Personalized Web Assistant (LPWA – Kristol, Gabber, et al. - 1998
2 Spamcop: A spam classi & organization program – PatrickPantel, Lin - 1998
2 Naive-bayes vs. rule-learning in classi of email – Provost - 1999
1 Learning to spam e-mail: A comparison of a naive bayesian and a memory-based approach – Androutsopoulos, Paliouras, et al. - 2000
1 Challenges of the email domain for text classi – Brutlag, Meek - 2000
1 Curbing junk email via secure classi – Gabber, Jakobsson, et al. - 1998
1 Representation of electronic mail pro A user study – Pazzani - 2000
1 i An application of machine learning to e-mail – Rennie - 2000
View or Download | Add to My Collection | Correct Errors