Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)

A Parallel Computing Method for Entity Recognition based on MapReduce

Authors
Yushui Geng, Peng Li, Jing Zhao
Corresponding Author
Yushui Geng
Available Online September 2016.
DOI
10.2991/icence-16.2016.122How to use a DOI?
Keywords
Entity Recognition; Parallel Computing; MapReduce; Hadoop
Abstract

With the rapid development of industrial automation, there are huge amounts of duplicate data refer to the same entity in the data sets have brought enormous challenges in data analysis. To accommodate the entity recognition of huge amounts of data, this paper presents a parallel computing method for entity recognition based on MapReduce. Through the detailed introduction to the MapReduce framework, running the applications on the Hadoop platform and parallel processing data sets to recognize the data entities. The experiments show that the proposed method greatly enhanced the recognition speed and accuracy, which has better effectiveness to meet the demand for entity recognition than other methods.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)
Series
Advances in Computer Science Research
Publication Date
September 2016
ISBN
978-94-6252-229-9
ISSN
2352-538X
DOI
10.2991/icence-16.2016.122How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Yushui Geng
AU  - Peng Li
AU  - Jing Zhao
PY  - 2016/09
DA  - 2016/09
TI  - A Parallel Computing Method for Entity Recognition based on MapReduce
BT  - Proceedings of the 2nd International Conference on Electronics, Network and Computer Engineering (ICENCE 2016)
PB  - Atlantis Press
SP  - 648
EP  - 653
SN  - 2352-538X
UR  - https://doi.org/10.2991/icence-16.2016.122
DO  - 10.2991/icence-16.2016.122
ID  - Geng2016/09
ER  -