Knowledge Engineering with Big Data

In the era of big data, knowledge engineering faces fundamental challenges induced by fragmented knowledge from heterogeneous, autonomous sources with complex and evolving relationships. The knowledge representation, acquisition, and inference techniques developed in the 1970s and 1980s, driven by research and development of expert systems, must be updated to cope with both fragmented knowledge from multiple sources in the big data revolution and in-depth knowledge from domain experts. This article presents BigKE, a 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.

Authors

• Xindong Wu
• Huanhuan Chen University of Science and Technology of China
• Gongqing Wu Hefei University of Technology
• Jun Liu
• Qinghua Zheng School of Computer Science and Technology, Xi'an Jiaotong University, China Shaanxi Provincial Key Laboratory of Big Data Knowledge Engineering, Xi'an Jiaotong University, China
• Xiaofeng He East China Normal University, Shanghai, China
• Aoying Zhou East China Normal University, Shanghai, China
• Zhong-Qiu Zhao Hefei University of Technology
• Bifang Wei
• Yang Li
• Qiping Zhang
• Shichao Zhang Guangxi Normal University

Keywords

• Knowledge engineering
• Big data
• Data models
• Intelligent systems
• Expert systems
• Computer science
• Google
• Technological Knowledge
• Learning Models
• Knowledge Acquisition
• Online Learning
• Data Streams
• Domain Experts
• End Of The Survey
• Expert System
• Knowledge Representation
• Multiple Sources Of Information
• Pieces Of Knowledge
• Weeks Of Surgery
• Fragmented Knowledge
• Data For Scientific Research
• Food And Drug Administration
• Twitter
• Data Mining
• Transfer Learning
• Concept Drift
• Online Learning Methods
• Knowledge Of Services
• Data Mining Algorithms
• Online Learning Algorithm
• Collaborative Filtering
• Context-aware
• Google Translate
• E-learning System
• Knowledge Integration
• fusion
• knowledge graph