arrow
Return

A Study on Big Knowledge and Its Engineering Issues

delete2019-09-01
delete99
PRE
AI
R
Ruqian Lu *
靳小龙 cover
靳小龙 (Xiaolong Jin)
S
Songmao Zhang
M
Meikang Qiu
X
Xindong Wu
DOI:10.1109/TKDE.2018.2866863delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
After entering the big data era, a new term of 'big knowledge' has been coined to deal with challenges in mining a mass of knowledge from big data. While researchers used to explore the basic characteristics of big data, we have not seen any studies on the general and essential properties of big knowledge. To fill this gap, this paper studies the concepts of big knowledge, big-knowledge system, and big-knowledge engineering. Ten massiveness characteristics for big knowledge and big-knowledge systems, including massive concepts, connectedness, clean data resources, cases, confidence, capabilities, cumulativeness, concerns, consistency, and completeness, are defined and explored. Based on these characteristics, a comprehensive investigation is conducted on some large-scale knowledge engineering projects, including the Fifth Comprehensive Traffic Survey in Shanghai, the China's Xia-Shang-Zhou Chronology Project, the Troy and Trojan War Project, and the International Human Genome Project, as well as the online free encyclopedia Wikipedia. We also investigate the recent research efforts on knowledge graphs, where they are analyzed to determine which ones can be considered as big knowledge and big-knowledge systems. Further, a definition of big-knowledge engineering and its life cycle paradigm is presented. All of these projects are accordingly checked to determine whether they belong to big-knowledge engineering projects. Finally, the perspectives of big knowledge research are discussed.
Keywords:
Big data
knowledge engineering
big data knowledge engineering
big knowledge
massiveness characteristics
big-knowledge system
big-knowledge engineering
life cycle
AI Summary

AI Summary

Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Knowledge and Data Engineering cover
IEEE Transactions on Knowledge and Data Engineering
IF:
10.4
Papers:
6.7K
Citations:
3.2W

Organization

H
hefei university of technology
Scholars:
2.5W
Papers: 1.7W
Citations: 35
C
Columbia University
Scholars:
7.1W
Papers: 6.4W
Citations: 263
C
chinese academy of sciences
Scholars:
56.1W
Papers: 44.8W
Citations: 704
researcher View more organizations