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Application of Sequential Pattern Mining Algorithm in Commodity Management

Author

Listed:
  • Xiaoli Wang

    (Mudanjiang Medical University, Mudanjiang, China)

  • Fang Wang

    (Mudanjiang Medical University, Mudanjiang, China)

  • Shi Yan

    (Mudanjiang Medical University, Mudanjiang, China)

  • ZhanBo Liu

    (Mudanjiang Medical University, Mudanjiang, China)

Abstract

This article describes how by analyzing historical sales data of supermarkets, once data is cleaned, sampled and put through a series of operations, it can be transformed into a sequence database. Finally, the data is used in the SPM of Map-Reduce algorithm to data mining. This experiment has two stages. In the first stage, the sequences of product categories are mined to place the product categories. In the second stage, the products are mined for each category, add profit targets for calculating sequential pattern values. This is so that it can reorder the results to find the most profit products. Thus, readers can adjust products placement and improve the profits of the supermarket.

Suggested Citation

  • Xiaoli Wang & Fang Wang & Shi Yan & ZhanBo Liu, 2018. "Application of Sequential Pattern Mining Algorithm in Commodity Management," Journal of Electronic Commerce in Organizations (JECO), IGI Global, vol. 16(3), pages 94-106, July.
    • Handle: RePEc:igg:jeco00:v:16:y:2018:i:3:p:94-106
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