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Knowledge Engineering With Big Data (BigKE): A 54-Month, 45-Million RMB, 15-Institution National Grand Project
Author(s) -
Xindong Wu,
Huanhuan Chen,
Jun Liu,
Gongqing Wu,
Ruqian Lu,
Nanning Zheng
Publication year - 2017
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2017.2710298
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Starting in July 2016, the Ministry of Science and Technology of China, along with several other national agencies, sponsors a 54-month 45-million RMB (Chinese Yuan) project on knowledge engineering with Big Data (www.bigke.org) for 15 top research and development institutions to study the fundamental theory and the applications of BigKE, a big-data knowledge engineering framework that handles fragmented knowledge modeling and online learning from multiple information sources, nonlinear fusion on fragmented knowledge, and automated demand-driven knowledge navigation. The project seeks to provide petabytescale data and knowledge services in identified application domains. In this paper, we discuss our BigKE framework, and present a novel application scenario for BigKE services.

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