- Updated: July 18, 2026
- 1 min read
Knowledge Graph and Accurate Portrait Construction of Scientific and Technological Academic Conferences
In recent years, the rapid growth of scientific research has made academic conferences a pivotal platform for knowledge exchange. Our latest study, Knowledge Graph and Accurate Portrait Construction of Scientific and Technological Academic Conferences, explores how deep learning, knowledge‑graph technology, and semantic similarity can transform conference data into actionable insights.
We introduce a comprehensive pipeline that extracts entities, computes semantic similarity, predicts trends, and visualizes results through an interactive knowledge graph. This approach enables researchers to quickly locate relevant papers, collaborators, institutions, and emerging topics.
Key contributions include:
- Advanced named‑entity recognition tailored for conference proceedings.
- Semantic text similarity models that cluster related works.
- Trend prediction algorithms for forecasting hot research areas.
- A scalable graph storage solution integrated with a custom search engine.
- Rich visualisation components that present the knowledge graph in an intuitive UI.
Read the full paper on arXiv and explore related resources on our site: Knowledge Graph Blog, AI Research Services.
For inquiries, contact the authors or visit our Contact Page.
Andrii Bidochko
CTO UBOS
Andrii Bidochko is an AI entrepreneur and researcher focused on AI agents, reinforcement learning, and autonomous systems. He writes about the technologies shaping the future of machine intelligence, from frontier models and agent architectures to real-world AI applications.