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Discovering Association Rules Using R. A Case Study on Retail’s Database

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Computer Science – CACIC 2018 (CACIC 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 995))

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Abstract

Today, the high competitiveness in retail businesses requires them to seek new strategies to ensure their survival. To this end, organizations have understood that the data located in their transactional databases can be used as raw material to boost business growth, if they can be exploited properly. The research’s main objective is to apply Data Mining techniques for the discovery of association rules from purely commercial transactional data, taking as a study period 10-year in a household appliances and furniture retail entity. The selection’s phase and preparation data are described as well as its cost in man/hours. In the modeling phase, the Apriori and Eclat algorithms implemented in the arules package of the R tool were executed, where both the resulting associations and execution time were compared. The results show relevant patterns in the buying behavior of customers such as those that relate items and accessories’ prices.

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Authors and Affiliations

  1. Universidad Nacional de Asunción, Asunción, Paraguay

    Juan Manuel Báez Acuña, Clara Anuncia Paredes Cabañas, Gustavo Sosa-Cabrera & María E. García-Díaz

Authors
  1. Juan Manuel Báez Acuña
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  2. Clara Anuncia Paredes Cabañas
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  3. Gustavo Sosa-Cabrera
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  4. María E. García-Díaz
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Corresponding author

Correspondence to Gustavo Sosa-Cabrera .

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Editors and Affiliations

  1. National University of La Plata, La Plata, Argentina

    Patricia Pesado

  2. National University of Buenos Aires Center, Buenos Aires, Argentina

    Claudio Aciti

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Acuña, J.M.B., Cabañas, C.A.P., Sosa-Cabrera, G., García-Díaz, M.E. (2019). Discovering Association Rules Using R. A Case Study on Retail’s Database. In: Pesado, P., Aciti, C. (eds) Computer Science – CACIC 2018. CACIC 2018. Communications in Computer and Information Science, vol 995. Springer, Cham. https://doi.org/10.1007/978-3-030-20787-8_14

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  • DOI: https://doi.org/10.1007/978-3-030-20787-8_14

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20786-1

  • Online ISBN: 978-3-030-20787-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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