Semantic Evaluation and Identification of Academic Representative Papers

Hongmei Guo (), Xingyu Chen and Zheng Ma
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Hongmei Guo: Institute of Scientific and Technical Information of China
Xingyu Chen: Institute of Scientific and Technical Information of China
Zheng Ma: Institute of Scientific and Technical Information of China

A chapter in Proceedings of 2023 China Science and Technology Information Resource Management and Service Annual Conference (COINFO 2023), 2024, pp 25-32 from Springer

Abstract: Abstract Academic papers are the main output and important knowledge carrier of scientific activities. They have the functions of knowledge flow, diffusion, and transfer. Academic representative paper is very significant to funding project review, talent introduction and institutional evaluation. These existing evaluation methods focus on external features or quantitative indicators based on paper citations. It is insufficient evaluation to semantic content features. In the paper, we draw on the theory of scientific values and design evaluation framework that include two dimensions, namely usage scale utility and knowledge utility of papers. Usage scale utility is reflected in the citation and download usage of the paper by peer scholars and mainly measured with quantitative indicators. The knowledge utility is reflected in the cited content role and mainly measured with semantic content analysis. We propose comprehensive evaluation method and value hierarchy system based on usage scale utility and knowledge utility dimensions. It can assist users to discover and focus on representative academic papers quickly.

Keywords: Academic Representative Papers; Semantic Identification; Semantic Measurement (search for similar items in EconPapers)
Date: 2024
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DOI: 10.2991/978-94-6463-498-3_4

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