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PAKDD
2000
ACM

A Comparative Study of Classification Based Personal E-mail Filtering

14 years 2 months ago
A Comparative Study of Classification Based Personal E-mail Filtering
This paper addresses personal E-mail filtering by casting it in the framework of text classification. Modeled as semi-structured documents, Email messages consist of a set of fields with predefined semantics and a number of variable length free-text fields. While most work on classification either concentrates on structured data or free text, the work in this paper deals with both of them. To perform classification, a naive Bayesian classifier was designed and implemented, and a decision tree based classifier was implemented. The design considerations and implementation issues are discussed. Using a relatively large amount of real personal E-mail data, a comprehensive comparative study was conducted using the two classifiers. The importance of different features is reported. Results of other issues related to building an effective personal E-mail classifier are presented and discussed. It is shown that both classifiers can perform filtering with reasonable accuracy. While the decision ...
Yanlei Diao, Hongjun Lu, Dekai Wu
Added 25 Aug 2010
Updated 25 Aug 2010
Type Conference
Year 2000
Where PAKDD
Authors Yanlei Diao, Hongjun Lu, Dekai Wu
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