Analyzing Price Data to Determine Positive and Negative Product Associations

  • Authors:

  • Ayhan Demiriz;Ahmet Cihan;Ufuk Kula

  • Affiliations:

  • Dept. of Industrial Engineering, Sakarya University, Sakarya, Turkey 54187;Dept. of Industrial Engineering, Kocaeli University, Kocaeli, Turkey;Dept. of Industrial Engineering, Sakarya University, Sakarya, Turkey 54187

  • Venue:
  • ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part I
  • Year:
  • 2009

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Abstract

This paper presents a simple method for mining both positive and negative association rules in databases using singular value decomposition (SVD) and similarity measures. In literature, SVD is used for summarizing matrices. We use transaction-item price matrix to generate so called ratio rules in the literature. Transaction-item price matrix is formed by using the price data of corresponding items from the sales transactions. Ratio rules are generated by running SVD on transaction-item price matrix. We then use similarity measures on a subset of rules found by Pareto analysis to determine positive and negative associations. The proposed method can present the positive and negative associations with their strengths. We obtain subsequent results using cosine and correlation similarity measures.