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Grid-based framework for high-performance processing of scientific knowledge

delete2013-03-20
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PRE
AI
C
Chang-Hoo Jeong
Y
Yunsoo Choi
H
Hong-Woo Chun
S
Sa-Kwang Song
H
Hanmin Jung
S
Sang‐Kwan Lee
S
Sung-Pil Choi *
DOI:10.1007/s11042-013-1411-2delete
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摘要

摘要

En 中文
An essential matter in the knowledge-based information society is how to extract useful information quickly from a large volume of literature. Since most existing data mining frameworks deal with structured input data, many limitations are faced in analyzing unstructured scientific literature and extracting new information. This study proposes a scientific-knowledge processing framework, which offers high performance by using grid computing technology for extracting important entities and their relations from the scientific literature. Since the grid computing provides a large volume of data storage and high-speed computing, the proposed framework can efficiently analyze the massive body of scientific literature and process knowledge. The workflow tool that we have developed for the proposed framework enables users to easily design and execute complicated applications that consist of complicated scientific-knowledge processes. The experimental results showed that the proposed framework reduced working time by approximately 83 % when the number of running nodes was assigned in accordance with the workload ratio of each step in scientific-knowledge processes. As a result, it is possible to effectively process a large volume of scientific literature by flexibly adjusting the number of computing nodes that constitute the grid environment as the number of documents for processing increases.
Keyword:
Scientific-knowledge processing
Grid computing
Workflow
Data mining framework
Text mining

期刊

Multimedia Tools and Applications 封面图
Multimedia Tools and Applications
IF:
3
论文数:
1.9W
被引数:
3.2W

机构

C
catholic university pusan
学者数:
177
论文数: 172
被引数: 0
K
korea institute of science & technology information (kisti)
学者数:
1.1K
论文数: 998
被引数: 0
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