Hybrid data mining algorithm in cloud computing using MapReduce framework

Siddharth Sahay; Suruchi Khetarpal; Tribikram Pradhan

doi:10.1109/ICACCCT.2016.7831691

Hybrid data mining algorithm in cloud computing using MapReduce framework

Siddharth Sahay, Suruchi Khetarpal, Tribikram Pradhan

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

2 Citations (Scopus)

Abstract

'Data mining' has transformed into a ubiquitous term in the world of IT and Computer Science in recent times. Developments in this field have been countless. Using one of Apriori algorithm's numerous variants with a couple of insightful additions can significantly improve upon the existing standard of Data Mining. In this paper a new approach to considerably reduce the time complexity of the database scan has been proposed. This has been achieved by using the MapReduce framework for Hadoop Distributed File System (HDFS). Coupled with Cloud computing, which handles large data sets and processing remotely, the resultant system - that uses MapReduce for the full table scan, the Pincer-Search Algorithm, and Cloud Computing - is a force to reckon with.

Original language	English
Title of host publication	Proceedings of 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	507-511
Number of pages	5
ISBN (Electronic)	9781467395458
DOIs	https://doi.org/10.1109/ICACCCT.2016.7831691
Publication status	Published - 24-01-2017
Event	2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016 - Ramanathapuram, Tamil Nadu, India Duration: 25-05-2016 → 27-05-2016

Conference

Conference	2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016
Country/Territory	India
City	Ramanathapuram, Tamil Nadu
Period	25-05-16 → 27-05-16

All Science Journal Classification (ASJC) codes

Hardware and Architecture
Signal Processing
Computer Networks and Communications
Computer Science Applications

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10.1109/ICACCCT.2016.7831691

Cite this

Sahay, S., Khetarpal, S., & Pradhan, T. (2017). Hybrid data mining algorithm in cloud computing using MapReduce framework. In Proceedings of 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016 (pp. 507-511). [7831691] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICACCCT.2016.7831691

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title = "Hybrid data mining algorithm in cloud computing using MapReduce framework",

abstract = "'Data mining' has transformed into a ubiquitous term in the world of IT and Computer Science in recent times. Developments in this field have been countless. Using one of Apriori algorithm's numerous variants with a couple of insightful additions can significantly improve upon the existing standard of Data Mining. In this paper a new approach to considerably reduce the time complexity of the database scan has been proposed. This has been achieved by using the MapReduce framework for Hadoop Distributed File System (HDFS). Coupled with Cloud computing, which handles large data sets and processing remotely, the resultant system - that uses MapReduce for the full table scan, the Pincer-Search Algorithm, and Cloud Computing - is a force to reckon with.",

author = "Siddharth Sahay and Suruchi Khetarpal and Tribikram Pradhan",

year = "2017",

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day = "24",

doi = "10.1109/ICACCCT.2016.7831691",

language = "English",

pages = "507--511",

booktitle = "Proceedings of 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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note = "2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016 ; Conference date: 25-05-2016 Through 27-05-2016",

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Sahay, S, Khetarpal, S & Pradhan, T 2017, Hybrid data mining algorithm in cloud computing using MapReduce framework. in Proceedings of 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016., 7831691, Institute of Electrical and Electronics Engineers Inc., pp. 507-511, 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016, Ramanathapuram, Tamil Nadu, India, 25-05-16. https://doi.org/10.1109/ICACCCT.2016.7831691

Hybrid data mining algorithm in cloud computing using MapReduce framework. / Sahay, Siddharth; Khetarpal, Suruchi; Pradhan, Tribikram.

Proceedings of 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 507-511 7831691.

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

TY - GEN

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AU - Khetarpal, Suruchi

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AB - 'Data mining' has transformed into a ubiquitous term in the world of IT and Computer Science in recent times. Developments in this field have been countless. Using one of Apriori algorithm's numerous variants with a couple of insightful additions can significantly improve upon the existing standard of Data Mining. In this paper a new approach to considerably reduce the time complexity of the database scan has been proposed. This has been achieved by using the MapReduce framework for Hadoop Distributed File System (HDFS). Coupled with Cloud computing, which handles large data sets and processing remotely, the resultant system - that uses MapReduce for the full table scan, the Pincer-Search Algorithm, and Cloud Computing - is a force to reckon with.

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BT - Proceedings of 2016 International Conference on Advanced Communication Control and Computing Technologies, ICACCCT 2016

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Hybrid data mining algorithm in cloud computing using MapReduce framework

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All Science Journal Classification (ASJC) codes

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