Distributed classification of data streams: An adaptive technique

Alfredo Cuzzocrea; Mohamed Medhat Gaber; Ary Mazharuddin Shiddiqi

doi:10.1007/978-3-319-22729-0_23

Distributed classification of data streams: An adaptive technique

Alfredo Cuzzocrea^*, Mohamed Medhat Gaber, Ary Mazharuddin Shiddiqi

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

Mining data streams is a critical task of actual Big Data applications. Usually, data stream mining algorithms work on resource-constrained environments, which call for novel requirements like availability of resources and adaptivity. Following this main trend, in this paper we propose a distributed data stream classification technique that has been tested on a real sensor network platform, namely, Sun SPOT. The proposed technique shows several points of research innovation, with are also confirmed by its effectiveness and efficiency assessed in our experimental campaign.

Original language	English
Title of host publication	Big Data Analytics and Knowledge Discovery - 17th International Conference, DaWaK 2015, Proceedings
Editors	Takahiro Hara, Sanjay Madria
Publisher	Springer Verlag
Pages	296-309
Number of pages	14
ISBN (Print)	9783319227283
DOIs	https://doi.org/10.1007/978-3-319-22729-0_23
Publication status	Published - 2015
Event	17th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2015 - Valencia, Spain Duration: 1 Sept 2015 → 4 Sept 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9263
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	17th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2015
Country/Territory	Spain
City	Valencia
Period	1/09/15 → 4/09/15

Access to Document

10.1007/978-3-319-22729-0_23

Cite this

Cuzzocrea, A., Gaber, M. M., & Shiddiqi, A. M. (2015). Distributed classification of data streams: An adaptive technique. In T. Hara, & S. Madria (Eds.), Big Data Analytics and Knowledge Discovery - 17th International Conference, DaWaK 2015, Proceedings (pp. 296-309). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9263). Springer Verlag. https://doi.org/10.1007/978-3-319-22729-0_23

Cuzzocrea, Alfredo ; Gaber, Mohamed Medhat ; Shiddiqi, Ary Mazharuddin. / Distributed classification of data streams : An adaptive technique. Big Data Analytics and Knowledge Discovery - 17th International Conference, DaWaK 2015, Proceedings. editor / Takahiro Hara ; Sanjay Madria. Springer Verlag, 2015. pp. 296-309 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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author = "Alfredo Cuzzocrea and Gaber, {Mohamed Medhat} and Shiddiqi, {Ary Mazharuddin}",

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Cuzzocrea, A, Gaber, MM & Shiddiqi, AM 2015, Distributed classification of data streams: An adaptive technique. in T Hara & S Madria (eds), Big Data Analytics and Knowledge Discovery - 17th International Conference, DaWaK 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9263, Springer Verlag, pp. 296-309, 17th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2015, Valencia, Spain, 1/09/15. https://doi.org/10.1007/978-3-319-22729-0_23

Distributed classification of data streams: An adaptive technique. / Cuzzocrea, Alfredo; Gaber, Mohamed Medhat; Shiddiqi, Ary Mazharuddin.
Big Data Analytics and Knowledge Discovery - 17th International Conference, DaWaK 2015, Proceedings. ed. / Takahiro Hara; Sanjay Madria. Springer Verlag, 2015. p. 296-309 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9263).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Shiddiqi, Ary Mazharuddin

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AB - Mining data streams is a critical task of actual Big Data applications. Usually, data stream mining algorithms work on resource-constrained environments, which call for novel requirements like availability of resources and adaptivity. Following this main trend, in this paper we propose a distributed data stream classification technique that has been tested on a real sensor network platform, namely, Sun SPOT. The proposed technique shows several points of research innovation, with are also confirmed by its effectiveness and efficiency assessed in our experimental campaign.

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DO - 10.1007/978-3-319-22729-0_23

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SN - 9783319227283

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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BT - Big Data Analytics and Knowledge Discovery - 17th International Conference, DaWaK 2015, Proceedings

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Cuzzocrea A, Gaber MM, Shiddiqi AM. Distributed classification of data streams: An adaptive technique. In Hara T, Madria S, editors, Big Data Analytics and Knowledge Discovery - 17th International Conference, DaWaK 2015, Proceedings. Springer Verlag. 2015. p. 296-309. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-22729-0_23

Distributed classification of data streams: An adaptive technique

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