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International Conference on Intelligent Tutoring Systems

ITS 2020: Intelligent Tutoring Systems pp 371–377Cite as

WebApriori: A Web Application for Association Rules Mining

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Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12149))

Abstract

This paper presents a web application for Association Rules Mining (ARM). It utilizes Apriori that is the most widely used algorithm for this type of data mining tasks. The web application is called WebApriori and offers a modern responsive web interface and a web service to scientific communities working in the field of ARM. It is also appropriate for educational purposes. WebApriori implements an Apriori engine that can efficiently discover the hidden associations in data and it is capable to process different types of datasets. Part of the process involves the removal of redundant associations rules. The asynchronous communication between the front-end, back-end, web service and Apriori engine layers efficiently handles multiple concurrent user requests.

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Notes

  1. 1.

    https://webapriori.iee.ihu.gr.

  2. 2.

    https://github.com/terminal0gr/webapriori.

References

  1. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules. In: Proceedings of 20th International Conference on Very Large Data Bases, VLDB 1994, pp. 487–499 (1994)

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  2. Ashrafi, M.Z., Taniar, D., Smith, K.: Redundant association rules reduction techniques. In: Zhang, S., Jarvis, R. (eds.) AI 2005. LNCS (LNAI), vol. 3809, pp. 254–263. Springer, Heidelberg (2005). https://doi.org/10.1007/11589990_28

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  3. Hall, M., Frank, E., Holmes, G., Pfahringer, B., Reutemann, P., Witten, I.H.: The WEKA data mining software: an update. ACM SIGKDD Explor. Newslett. 11(1), 10–18 (2009)

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  4. Vojír, S., Zeman, V., Kuchar, J., Kliegr, T.: Easyminer.eu: web framework for interpretable machine learning based on rules and frequent itemsets. Knowl.-Based Syst. 150, 111–115 (2018). https://doi.org/10.1016/j.knosys.2018.03.006

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Author information

Authors and Affiliations

  1. Department of Information and Electronic Engineering, International Hellenic University, 57400, Sindos, Thessaloniki, Greece

    Konstantinos Malliaridis, Stefanos Ougiaroglou & Dimitris A. Dervos

Authors
  1. Konstantinos Malliaridis
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  2. Stefanos Ougiaroglou
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  3. Dimitris A. Dervos
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Corresponding author

Correspondence to Stefanos Ougiaroglou .

Editor information

Editors and Affiliations

  1. Athabasca University, Athabasca, AB, Canada

    Vivekanandan Kumar

  2. University of West Attica, Egaleo, Greece

    Christos Troussas

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Cite this paper

Malliaridis, K., Ougiaroglou, S., Dervos, D.A. (2020). WebApriori: A Web Application for Association Rules Mining. In: Kumar, V., Troussas, C. (eds) Intelligent Tutoring Systems. ITS 2020. Lecture Notes in Computer Science(), vol 12149. Springer, Cham. https://doi.org/10.1007/978-3-030-49663-0_44

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  • DOI: https://doi.org/10.1007/978-3-030-49663-0_44

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-49662-3

  • Online ISBN: 978-3-030-49663-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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