Promote industry standardization | Weyin Internet participated in the second meeting of the Knowledge Graph Working Group of the Artificial Intelligence Subcommittee of the National Beacon Committee in 2023

Recently, the second meeting of the Knowledge Graph Working Group of the Artificial Intelligence Subcommittee of the National Beacon Committee in 2023 was held in Chongqing in a combined online and offline format. This meeting was hosted by the China Electronics Technology Standardization Institute and chaired by Li Ruiqi, leader of the knowledge graph working group. More than 70 representatives from 65 units related to the knowledge graph field, including developers, system integrators, user companies, scientific research institutes and universities attended the meeting. Meeting.

At the meeting, Li Ruiqi, leader of the working group, introduced the current progress of the knowledge graph working group, and introduced "Artificial Intelligence Knowledge Graph Application System Part 3: Knowledge Services" and "Integration of Artificial Intelligence Knowledge Graph and Large-scale Pre-training Model" respectively. Part 1: Overall Framework" and "Integration of Artificial Intelligence Knowledge Graph and Large-scale Pre-training Model Part 2: Performance Testing and Evaluation Requirements" and other three national standard proposals. The participating experts held a detailed discussion on the scope of the proposal, the necessity of project establishment, and the rationality, standardization, and applicability of the main contents of the draft standard, and further clarified the direction of revision of the national standard project proposal and the draft standard.

Relying on the technical advantages of years of industry accumulation and knowledge graph standardization, Wenyin Internet was invited to participate in the preparation of standards related to knowledge graphs. In the direction of "large-scale pre-training models to enhance knowledge acquisition", we cooperate with the method The standardization work related to the integration of knowledge graphs and large models in array construction and the research methods of test and evaluation index systems have contributed to the development of international and domestic knowledge graph standards.

Knowledge graph technology, as one of the key technologies for the realization of cognitive intelligence, plays a great role in various scenarios within the enterprise, such as data processing, information security risk management and control, internal operations, knowledge sharing and exchange, etc. Wenyin Internet cooperates with the advancement of the development of knowledge graph standards to improve the construction efficiency of knowledge graphs, promote the in-depth mining and sharing of knowledge in multiple fields, accelerate the implementation of knowledge graphs, reduce system construction costs, and improve the technical quality of knowledge graphs, thereby Better promote the digital transformation of enterprises and empower new directions for enterprise structure optimization and development.

In terms of practical applications, Wenyin Internet focuses on the research and development of large model technology in vertical fields, based on finance, and promotes aviation, medical, media, government affairs, construction and other fields, using large model technology as a base, combines knowledge Graph and natural language understanding technology strengthens the digitization, informatization and scenario-based business documents to help customers efficiently realize the ability to build various business knowledge base systems. Supported by the enterprise knowledge base system, business knowledge is converted into organizational assets, and the information retrieval speed is compressed to the millisecond level, improving the quality of enterprise operations, reducing personal dependence, breaking departmental barriers, and responding to the market more quickly. Through intelligent search and intelligent Q&A, we integrate customer resources to help customers efficiently realize the accumulation of various knowledge bases, as well as the reshaping and upgrading of process automation and business intelligence, further improving the company's capitalization capabilities and achieving more efficient Resource allocation.

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