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