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http://dx.doi.org/10.9723/jksiis.2015.20.2.001

Mining highly attention itemsets using a two-way decay mechanism in data stream mining  

Chang, Joong-Hyuk (대구대학교 컴퓨터IT공학부)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.20, no.2, 2015 , pp. 1-9 More about this Journal
Abstract
In most techniques of information differentiating for data stream mining, they give larger weight to the information generated in recent compared to the old information. However, there can be important one among the old information. For example, in case of a person was a regular customer in a retail store but has not come to the store in recent, old information with the shopping record of the person can be importantly used in a target marketing for increasing sales. In this paper, highly attention itemsets(HAI) are defined, which mean the itemsets generated in the past frequently but not generated in recent. In addition, a twao-way decay mechanism and a data stream mining method for finding HAI are proposed.
Keywords
Highly attention itemsets; Two-way decay mechanism; Data streams; Data stream mining; Information differentiation;
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