An efficient e-mail filtering using time priority measurement

  • Authors:

  • Yuki Kadoya;Masao Fuketa;Elsayed Atlam;Kazuhiro Morita;Shinkaku Kashiji;Jun-ichi Aoe

  • Affiliations:

  • Department of Information Science and Intelligent Systems, Faculty of Engineering, University of Tokushima, Minamijosanjima, Tokushima 770-8506, Japan;Department of Information Science and Intelligent Systems, Faculty of Engineering, University of Tokushima, Minamijosanjima, Tokushima 770-8506, Japan;Department of Statistics and Computer Science, Faculty of Science, Tanta University, Egypt and Department of Information Science and Intelligent Systems, Faculty of Engineering, University of Toku ...;Department of Information Science and Intelligent Systems, Faculty of Engineering, University of Tokushima, Minamijosanjima, Tokushima 770-8506, Japan;Department of Information Science and Intelligent Systems, Faculty of Engineering, University of Tokushima, Minamijosanjima, Tokushima 770-8506, Japan;Department of Information Science and Intelligent Systems, Faculty of Engineering, University of Tokushima, Minamijosanjima, Tokushima 770-8506, Japan

  • Venue:
  • Information Sciences—Informatics and Computer Science: An International Journal
  • Year:
  • 2004

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Abstract

Although E-mail systems are one of the most useful communication tools for business, education, etc., missing important E-mail messages become a very serious problem. It is very useful filtering supports for users to pick up important messages or to neglect unnecessary messages. This paper presents a method of determining the time priority for E-mail messages. Multi-attribute rules are defined to detect complex time expressions and a set pattern-matching machine is proposed. It enables us to protect missing messages with important time information because the presented method can classify and rank them according to time priority measurement automatically. From the simulation results of determining time priority, the presented pattern-matching method is about 4 times faster than the traditional string pattern-matching method. From the results of filtering 5172 sentences, it is verified that precision and recall of the presented method becomes 95% and 96%, respectively. From the experimental results of determining 10 highest messages among 100 E-mail, it is verified that filtering time by the proposed measurement is from 9.7 to 16.6 faster than a non-filtering method.