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PERC: A Personal Email Classifier.

Authors :
Lalmas, Mounia
MacFarlane, Andy
Rüger, Stefan
Tombros, Anastasios
Tsikrika, Theodora
Yavlinsky, Alexei
Shih-Wen Ke
Bowerman, Chris
Oakes, Michael
Source :
Advances in Information Retrieval (9783540333470); 2006, p460-463, 4p
Publication Year :
2006

Abstract

Improving the accuracy of assigning new email messages to small folders can reduce the likelihood of users creating duplicate folders for some topics. In this paper we presented a hybrid classification model, PERC, and use the Enron Email Corpus to investigate the performance of kNN, SVM and PERC in a simulation of a real-time situation. Our results show that PERC is significantly better at assigning messages to small folders. The effects of different parameter settings for the classifiers are discussed. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540333470
Database :
Supplemental Index
Journal :
Advances in Information Retrieval (9783540333470)
Publication Type :
Book
Accession number :
32882910
Full Text :
https://doi.org/10.1007/11735106_41