Paper details knowledge graph construction for academic conference data

This paper explores the application of deep learning and knowledge graph technology to analyze scientific and technological academic conference data. It details key techniques such as named entity recognition, semantic text similarity, and trend prediction to construct accurate portraits of conferences. The goal is to help researchers efficiently extract valuable information from the massive volume of conference data, supporting the development of conference knowledge services. AI

RANK_REASON This is a research paper detailing a methodology for analyzing academic conference data using knowledge graphs and deep learning techniques. [lever_c_demoted from research: ic=1 ai=1.0]

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• deep learning
• Knowledge Graph
• named entity recognition
• scientific and technological academic conferences

• paper
• other

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