SIGSPG

「This team is committed to building an industry-friendly knowledge graph semantic framework based on real business scenarios, effectively linking enterprise big data and AI technology systems represented by LLM, simplifying knowledge semantic representation to the extreme, and realizing two-way enhancement of SPG and LLM based on the OpenSPG knowledge graph engine, accelerating the process of data knowledgeization, and improving the controllability of AI generation.」

Contribution to the community:

1) SPG, a knowledge semantic framework based on industrial-grade real application scenarios with independent intellectual property rights.
2) Deep cooperation with OpenKG to build common sense graphs in various fields and explore new paradigms of knowledge open source.
3) Build SPG+LLM dual-drive technology framework, large model-enhanced knowledge production, and knowledge-enhanced controllable generation framework.
4) Open source release of the first industrial-grade knowledge graph engine OpenSPG to accelerate the implementation of the knowledge graph industry.

slogan:

「Build an industrial-grade knowledge semantic framework, accelerate the knowledgeization of massive data, build a controllable generation technology paradigm, and help enterprises upgrade to intelligence.」

Principal

Lei Liang

Ant Group

Haofen Wang

同济大学

Members

王鑫

天津大学

白硕

恒生电子

周妍

创邻科技

王文广

达观数据

胡芳槐

海乂知信息科技(南京)有限公司

Wen Zhang

Zhejiang University

白龙

中国科学院计算技术研究所

鄂海红

北京邮电大学

安春燕

内蒙古大学

Achievements

White Paper on Knowledge Semantic Framework (SPG)

A new generation of enterprise-level knowledge graph engine, with bidirectional enhancement of large models and knowledge graphs

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