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AI framework COCI extracts structured metadata from conference calls for papers

By PulseAugur Editorial · [1 sources] ·

A new AI-powered framework called COCI has been developed to extract structured metadata from Conference Calls for Papers (CfPs). This system uses Large Language Models and semantic mapping to identify and link entities like authors, topics, and conference series with existing knowledge bases such as OpenAlex and DBLP. COCI aims to integrate informal scholarly dissemination with structured Semantic Web resources, enabling better analysis of academic events not tied to traditional publishers. AI

IMPACT This framework could streamline the integration of grey literature into scholarly knowledge graphs, improving the discoverability and analysis of academic events.

RANK_REASON The item describes a research paper detailing a new AI-based framework for metadata extraction. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI framework COCI extracts structured metadata from conference calls for papers

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42 / 100
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The item describes a research paper detailing a new AI-based framework for metadata extraction. [lever_c_demoted from research: ic=1 ai=1.0]
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paper, product
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Angelo Salatino, Francesco Osborne, Alexis Vizcaino, Aliaksandr Birukou, Enrico Motta ·

    COCI: Conference Organisers and Content Identifier

    arXiv:2608.24559v1 Announce Type: cross 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…

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