COCI: Conference Organisers and Content Identifier

2026-08-25

AI Summary

本文介绍COCI框架，利用AI技术从征文启事中提取结构化元数据，解决灰色文献难以集成到学术知识图谱的问题。

Abstract

Despite the critical role of grey literature in scholarly communication, artefacts such as Calls for Papers (CfPs) remain largely isolated from modern Scholarly Knowledge Graphs. The unstructured and highly heterogeneous nature of these documents has traditionally hindered their large-scale processing. In this demo paper, we present the Conference Organisers and Content Identifier (COCI), an AI-based framework designed to extract fine-grained, structured metadata from raw CfP texts. COCI employs a multi-stage pipeline that combines Large Language Models (LLMs) with semantic mapping techniques to integrate extracted entities with established knowledge bases, including OpenAlex, DBLP, TIB ConfIDent, and the AIDA Dashboard. By disambiguating authors and semantically aligning topics and conference series, COCI bridges the gap between informal scholarly dissemination and structured Semantic Web resources, laying the foundation for systematic analysis of non-publisher-based academic events.

Problem

• grey literature
• Calls for Papers
• Scholarly Knowledge Graphs
• unstructured
• heterogeneous

Innovation

• Large Language Models
• Semantic Mapping
• Metadata Extraction
• Scholarly Knowledge Graphs