CNCC2023 will be held in Shenyang from October 26 to 28, during which 129 technical forums will be held, covering more than 30 directions such as artificial intelligence, security, computing +, software engineering, education, network, chip, cloud computing, etc. This article introduces the "Knowledge Graph + Language Model" Empowering General Artificial Intelligence] Technology Forum to be held on October 26.
Language is "shape", knowledge is "heart", and map is "bone". This technical forum invited experts from all walks of life in industry, academia and research to discuss the integration of knowledge graph and large-scale language models, and jointly explore a new path for the development of general AI.
To register and learn more about the technical forum, please identify the QR code below to enter the official website of CNCC2023.
Language is "shape", knowledge is "heart", and map is "bone". Language is the carrier of knowledge, knowledge is the foundation of intelligence, and large language models and knowledge graphs are computing means to represent and process knowledge. Language models complement the ability to understand language, while knowledge graphs enrich the way knowledge is represented. The complementary integration of the two can provide a better intelligent foundation for the realization of general AI. The 7th Knowledge Graph Technology Forum - "Knowledge Graph + Language Model Empowering General AI" Technical Forum invited experts from all walks of life in industry, academia and research to discuss the integration of knowledge graph and large-scale language model, and jointly explore a new path for the development of general AI.
Forum arrangement
| order | topic | Keynote speaker | unit |
| 1 | Knowledge graph in the era of large models | Bai Shuo | Hang Seng Electronics Limited |
| 2 | Large model application experience | Zhou Ming | Founder and CEO of Lanzhou Technology |
| 3 | ChatGPT-like language large model and new progress of knowledge graph | Wang Xin | Tianjin University |
| 4 | The application of knowledge and large model fusion technology in the field of telecommunications | Li Fangming | Huawei |
| 5 | SPG+LLM bidirectionally enhanced portable business paradigm | Liang Lei | Ant Group |
| 6 | Panel link | All guests | Bai Shuo, Zhou Ming, Wang Haofen, Wang Xin, Liang Lei, Li Fangming |
Chairman of the Forum
Chen Huajun
Professor at Zhejiang University
CCF Distinguished Speaker, Executive Committee Member of CCF Open Source Development Committee, research interests include knowledge graph, big data systems, natural language processing, etc. Professor of School of Computer Science and Technology, Zhejiang University, Vice President of Zhejiang Digital Intelligence Science and Technology Research Association, Young and Middle-aged Experts with Outstanding Contributions in Zhejiang Province, and Lead Initiator of OpenKG, Chinese Open Knowledge Graph. One work or correspondence in Nature Machine Intelligence, Nature Communications, NeurIPS, ICML, ICLR, IJCAI, AAAI, ACL, EMNLP, KDD, VLDB, ICDE, WWW, SIGIR, Brief. He has published many papers in top international conferences or journals such as Bioinformatics, Nucleic Acids Res., and Proc. IEEE. He has won the ISWC Best Paper Award of the International Semantic Web Conference, the IJCKG Best Paper Award of the International Knowledge Graph Joint Conference, the second prize of Zhejiang Science and Technology Progress Award, the first prize of Technical Invention Award of the Ministry of Education, the first prize of Qian Weichang Science and Technology Award of China Society of Chinese Information, the Alibaba Excellent Academic Cooperation Award, the first prize of Excellent Publication of China Industry Information Media Publishing Group, and the first prize of the First Excellent Textbook Award of Zhejiang University.
Co-Chairs
Lin Junyu
Director of CCF, Deputy Secretary-General of CCF Computer Application Committee
Senior engineer, Institute of Information Engineering, Chinese Academy of Sciences
Distinguished member of CCF, deputy secretary-general of CCF Computer Application Special Committee, standing member of CCF Professional Ethics and Academic Ethics Committee, executive member of CCF Computer Terminology Review Committee, Ph.D., associate researcher, editorial board member of CCCF journals, postdoctoral fellow of Institute of Information Engineering, Chinese Academy of Sciences, participated in the completion of more than 30 projects of the National Natural Science Foundation of China, the National Information Security Project, the Strategic Leading Science and Technology Project of the Chinese Academy of Sciences, various national defense science and technology projects and provincial and ministerial projects. He has won 1 second prize of provincial and ministerial science and technology progress award, 1 second prize of scientific and technological invention category, and applied for 12 patent authorizations and software copyrights. He has published more than 60 academic papers in international journal conferences. Main research directions: big data, future networks, knowledge engineering.
Forum speaker
Bai Shuo
Director of CCF, Chairman of CCF Shanghai
Chief Scientist of Hang Seng Electronics Limited
Advisory member of CCF Blockchain Committee, Ph.D., researcher, doctoral supervisor. He is currently the Chief Scientist and President of the Research Institute of Hang Seng Electronics Co., Ltd. He studied under the famous computational linguist Professor Ma Xiwen. As the person in charge, he led the team to undertake the natural science foundation project and develop the "Tianluo" search engine system. Participated in the national information security major project, planned information security pre-research projects, and participated in the establishment of the National Computer Network Emergency Coordination Technology Center (CNCERT/CC). During his work at the Shanghai Stock Exchange, he led the upgrading of a large number of important information systems such as core trading system, supervision system, enterprise-level data warehouse, etc., and the electronic information disclosure project of XBRL listed companies. Since 2018, he has been the chairman of Danvor Intelligent Technology Co., Ltd. He has published more than 40 papers and 1 academic monograph.
Knowledge graph in the era of large models
This report first introduces the development route of the big model and its two major breakthroughs in artificial intelligence, long-distance correlation and invisible resources, secondly, the digital intelligence in the financial field is explained in detail, and from the description logic to the knowledge graph, the four characteristics of the knowledge graph are obtained, and the history and current situation of reasoning are introduced in detail.
Zhou Ming
CCF Fellow, Vice Chairman of CCF
Founder and CEO of Lanzhou Technology
He was the President of the International Society of Computational Linguistics and Vice President of Microsoft Research Asia. Zhou Ming received his Ph.D. from Harbin Institute of Technology in 1991 and later taught at Tsinghua University. He joined Microsoft Research Asia in 1999 and has long led NLP research. Published about 100 ACL articles, Google H-Index 106. In 2021, he founded Lanzhou Technology, engaged in the research and development of lightweight large models and a new generation of NLP products, and won the highest award of Beijing HICOOL (2021) Entrepreneurship Competition.
Large model application experience
This lecture explores the experience and experience of large models in application. First, we introduce Mencius general large model training, including steps such as dataset preparation, hyperparameter tuning, and model optimization. We then discussed how to build and apply industry big models to specific scenarios such as search, meeting analytics, customer service, and more. In these scenarios, large models need to be combined with the user's scenarios and data to make the most of it.
Wang Xin
Secretary-General of CCF Information Systems Committee
Professor at Tianjin University
Professor/PhD supervisor, Faculty of Intelligence and Computing, Tianjin University, Deputy Dean of School of Artificial Intelligence. Chief scientist of the National Key R&D Program, member of the expert group of teaching resources and new teaching materials construction project in key areas of the Ministry of Education, and leader of the virtual teaching and research department of the knowledge engineering course group of the Ministry of Education. Distinguished member of CCF, Secretary-General of CCF Information System Committee, Executive Member of CCF Database Committee. Research interests: knowledge graph, graph database, big data processing. He has published more than 150 papers in domestic and foreign academic journals and conferences such as IEEE TKDE, IEEE TPDS, SIGMOD, ICDE, IJCAI, AAAI, WWW, CIKM, ISWC, Chinese Journal of Computers, Journal of Software, etc. He has served as Chairman of the Program Committee for DASFAA 2023, APWeb-WAIM 2020, JIST2019 and several International Conference Program Committees. He serves as the associate editor of Computer Engineering and Applications, the international journal KBS, and the editorial board of BDR, DSE, NLP Journal. He has won the special prize of Tianjin Teaching Achievement Award and the first prize of Tianjin Science and Technology Progress Award.
ChatGPT-like language large model and new progress of knowledge graph
At present, the language large model represented by ChatGPT is exerting profound influence in many fields of artificial intelligence, which can be regarded as the latest progress of "connectionism"; The knowledge graph represents the cutting-edge development in the field of artificial intelligence knowledge engineering and is the culmination of "symbolism". This report first introduces the working principle of language large model and ChatGPT, and discusses the change of ChatGPT-like language model on the human-computer interaction mode in information system. Then, the basic methods, technologies and applications of knowledge graph are introduced. Finally, the possible ways to realize the combination of "nerve + symbol" by interacting with the knowledge graph of ChatGPT language large model are explored.
Liang Lei
Head of Knowledge Engine at Ant Group
His main technical directions are knowledge graph, graph learning and reasoning engine, search engine and AI engineering. In 2018, he began to lead the construction of ant knowledge graph, and the projects leading the incubation have successively won the BU President Special Award, Data Science Award, Outstanding Achievement Award, etc., and the platform capability has passed CESI evaluation certification, and currently leads IEEE 2807.2 financial knowledge graph standardization and SPG knowledge graph semantic standardization and other work.
SPG+LLM bidirectionally enhanced portable business paradigm
SPG, a new generation of knowledge graph semantic framework, defines a new technology paradigm compatible with the construction domain map of big data system, which constructs a machine-understandable knowledge symbology through data knowledge and knowledge semantic standardization/symbolization. However, LLM is difficult to capture and obtain factual knowledge due to the black-box probability model, and there are many hallucinations and logical errors, which is difficult to implement in the enterprise data upgrade. In this sharing, the new technology framework built by SPG + LLM that can be migrated across scenarios will be introduced by combining business applications such as knowledge extraction based on LLM, automatic construction of ER2SPG maps, and controllable packet generation, and the recent business cases and technology explorations will be introduced to accelerate the implementation of controllable AI technology.
Li Fangming
Huawei large-model technical expert, Pangu Communications' large-model NetGPT technical leader
Dr. Li Fangming has long been engaged in the application research of AI technology in the field of intelligent operation and maintenance, and is currently responsible for the design and development of large models in the telecom industry, as well as the application research of large models and knowledge combination technology in the telecom industry.
The application of knowledge and large model fusion technology in the field of telecommunications
The era of large models has arrived, and application exploration in various industries and vertical fields is emerging one after another. This report introduces some phased achievements of the application and exploration of knowledge and large model fusion technology in the telecom industry. Firstly, the target application scenarios and main challenges of the telecom industry are introduced, and then how to solve existing problems through knowledge and large-model fusion technology to improve network intelligence and O&M efficiency. Finally, the future is prospected, and the development trend of knowledge and large model fusion technology and more potential application directions and scenarios in the telecom industry are discussed.
Other guests
Wang Haofen
Secretary General of CCF Shanghai, Deputy Director of CCF Terminology Working Committee
Distinguished researcher of Tongji University
This year marks CNCC's 20th anniversary. Over the past two decades, CNCC has gradually developed to cover 129 technical forums in dozens of directions, with more than 700 domestic and foreign speakers actively participating and more than 13,000 people registering as an annual event in the field of computing. Twenty years of continuous surpassing, as an annual event with many participants, large scale and high level in the field of domestic computing, CCF will carefully plan to bring participants a cutting-edge collision and look forward to the future technology feast, so that every participant can enhance their professional value and gain momentum in the super large professional platform of CNCC! Wait for you to come, act now, welcome to participate and register!