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Frequent Itemsets Mining in Data Streams Using Reconfigurable Hardware

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New Frontiers in Mining Complex Patterns (NFMCP 2015)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9607))

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Abstract

Data streams are unbounded and infinite flows of data arriving at high rates which cannot be stored for offline processing. Because of this, classical approaches for Data Mining cannot be used straightforwardly in data stream scenario. This paper introduces a single-pass hardware-based algorithm for frequent itemsets mining on data streams that uses the top-k frequent 1-itemsets. Experimental results of the hardware implementation of the proposed algorithm are also presented and discussed.

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Notes

  1. 1.

    Dataset is referred to databases, unstructured data file, relational databases or any other data source. In this paper, dataset is used to refer data streams.

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Authors and Affiliations

  1. Advanced Technologies Application Center, 7a ♯ 21812 e/218 y 222, Rpto. Siboney, Playa, CP 12200, Havana, Cuba

    Lázaro Bustio, Raudel Hernández & José M. Bande

  2. National Institute for Astrophysics, Optics and Electronic, Luis Enrique Erro No 1, Sta. Ma. Tonantzintla, 72840, Puebla, Mexico

    Lázaro Bustio, René Cumplido & Claudia Feregrino

Authors
  1. Lázaro Bustio
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  2. René Cumplido
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  3. Raudel Hernández
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  4. José M. Bande
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  5. Claudia Feregrino
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Corresponding author

Correspondence to Lázaro Bustio .

Editor information

Editors and Affiliations

  1. Università degli Studi di Bari Aldo Moro, Bari, Italy

    Michelangelo Ceci

  2. Università degli Studi di Bari Aldo Moro, Bari, Italy

    Corrado Loglisci

  3. ICAR-CNR, Rende, Italy

    Giuseppe Manco

  4. ICAR-CNR, Rende, Italy

    Elio Masciari

  5. University of North Carolina, Charlotte, North Carolina, USA

    Zbigniew W. Ras

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Bustio, L., Cumplido, R., Hernández, R., Bande, J.M., Feregrino, C. (2016). Frequent Itemsets Mining in Data Streams Using Reconfigurable Hardware. In: Ceci, M., Loglisci, C., Manco, G., Masciari, E., Ras, Z. (eds) New Frontiers in Mining Complex Patterns. NFMCP 2015. Lecture Notes in Computer Science(), vol 9607. Springer, Cham. https://doi.org/10.1007/978-3-319-39315-5_3

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  • DOI: https://doi.org/10.1007/978-3-319-39315-5_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39314-8

  • Online ISBN: 978-3-319-39315-5

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