Abstract
A major obstacle in data mining applications is the gap between the statistic-based pattern extraction and the value-based decision making. We present a profit mining approach to reduce this gap. In profit mining, we are given a set of past transactions and pre-selected target items, and we like to build a model for recommending target items and promotion strategies to new customers, with the goal of maximizing the net profit. We identify several issues in profit mining and propose solutions. We evaluate the effectiveness of this approach using data sets of a wide range of characteristics.
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© 2002 Springer-Verlag Berlin Heidelberg
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Wang, K., Zhou, S., Han, J. (2002). Profit Mining: From Patterns to Actions. In: Jensen, C.S., et al. Advances in Database Technology — EDBT 2002. EDBT 2002. Lecture Notes in Computer Science, vol 2287. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45876-X_7
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DOI: https://doi.org/10.1007/3-540-45876-X_7
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