This book provides a systematic and comprehensive overview of knowledge graph, covering all aspects including the theoretical foundations, key techniques and methodologies, and various typical applications. Special focus is given to the practical methods for knowledge graph construction and management, especially methods for constructing knowledge graphs from texts and from Encyclopedia, and methods for knowledge fusion and reasoning.It can serve as reference book for researchers and students new to knowledge graph. From this book, the readers will learn how to construct large-scale knowledge graphs from different sources, how to manage multiple knowledge graphs and do reasoning with a knowledge graph. Some basic knowledge on discrete mathematics, probability and statistics, data structure, and databases is required to understand the book content well.
Author Biography:
Dr. Guilin Qi is a professor at Southeast University, China, where he also serves as director of the Institute of Cognitive Intelligence and of the Knowledge Science and Engineering Lab. His research interests include knowledge representation and reasoning, knowledge graphs, uncertainty reasoning, and the semantic web. Prof. Qi is an editorial board member of the Journal of Web Semantics, and has co-edited special issues for the Annals of Mathematics and Artificial Intelligence, International Journal of Approximate Reasoning and Journal of Applied Logic. He has over 20 years of research experiences in knowledge engineering and has led many national and industrial projects on knowledge graphs. Prof. Qi has published more than 100 papers on knowledge engineering and knowledge graphs and holds two patents. He has given many invited talks about knowledge graphs and has given lectures on knowledge graph techniques to postgraduate students. He is one of the leading experts on knowledge graphs in China.
Dr. Huajun Chen is a full professor at the College of Computer Science, Zhejiang University, China. His main research interests include the semantic web, knowledge graphs, and their applications in biomedicine, smart cities etc. He serves as the deputy director of the Key Lab of Big Data Computing of Zhejiang Province, and as associate editor of Elsevier's Journal of Big Data Research. He has over 15 years of research and development experience in knowledge graph and semantic technology, is the principal adviser to Alibaba's e-commerce knowledge graph, and is one of the key founders of OpenKG.
Dr. Kang Liu is associate professor in Institute of Automation, Chinese Academy of Sciences. His research areas include Information Extraction, Web Mining, Question Answering and Machine Learning. He has published more than 60 papers on top tier conferences and journals. He won 2nd place in KDD CUP 2011 Track2, COLING 2014 Best Paper Award, "CCF-Tencent Xiniuniao" Excellence Award (The top award) in 2014, Hanwang Youth Innovation Excellence Award by Chinese Information Processing Society of China in 2014, and Google Focused Research Award in 2015, 2017.
Dr. Haofen Wang is the CTO of Shenzhen Gowild Robotics Co. Ltd. His research interests are mainly about knowledge graph and semantic technologies. Dr. Wang has published more than 75 high quality research papers in which half of them are in top conferences like ISWC, WWW, AAAI, SIGMOD, SIGIR, and ICDE as well as top journals like Journal of Web Semantics, and ACM TIST. Dr. Wang is also one of the leading experts of knowledge graph in China. He has accumulated rich experience in building and consuming knowledge graphs for domains like healthcare and finance as well as for applications like chatbots.
