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Methods to discover laws are reviewed from among both statistical approach and artificial intelligence approach with more emphasis placed on the latter. Dimensions discussed are variable dependency checking, passive or active data gathering, single or multiple laws discovery, static (equilibrium) or dynamic (transient) behavior, quantitative (numeric) or qualitative or structural law discovery, and use of domain-general knowledge. Some of the representative discovery systems are also briefly discussed in conjunction with the methods used in the above dimensions.
Kenichi YOSHIDA Fuminori ADACHI Takashi WASHIO Hiroshi MOTODA Teruaki HOMMA Akihiro NAKASHIMA Hiromitsu FUJIKAWA Katsuyuki YAMAZAKI
The volume of mass unsolicited electronic mail, often known as spam, has recently increased enormously and has become a serious threat not only to the Internet but also to society. This paper proposes a new spam detection method which uses document space density information. Although the proposed method requires extensive e-mail traffic to acquire the necessary information, it can achieve perfect detection (i.e., both recall and precision is 100%) under practical conditions. A direct-mapped cache method contributes to the handling of over 13,000 e-mail messages per second. Experimental results, which were conducted using over 50 million actual e-mail messages, are also reported in this paper.