基于研究领域的论文相似性评估方法  

Similarity Evaluation Method for Papers Based on Research Fields

作　　者：马健兵 陈柯 MA Jianbing;CHEN Ke(College of Computer Science,Chengdu University of Information Technology,Chengdu 610000,China)

机构地区：[1]成都信息工程大学计算机学院,四川成都610000

出　　处：《软件导刊》2025年第3期86-91,共6页Software Guide

基　　金：四川省重点研发计划项目(2021YFG0345)。

摘　　要：每年都有大量横跨不同领域的论文发表,部分论文在特定领域深入分析,部分论文则涉及多学科领域,虽然论文的研究领域为了解论文主题提供了指南,但许多研究人员主要依赖自然语言处理技术评估论文的相似性,忽略了研究领域的内在重要性。为此,在利用研究领域及其相互关联的基础上提出一种量化论文相似性的创新方法。首先,使用一组由相关研究领域构建的4级向量描述一篇论文;其次,引入相关性矩阵阐明这些领域间的相互关系;最后,评估论文表示向量与其他论文表示向量的接近程度以计算论文相似度。实验表明,在开放学术图谱的数据集中所提方法优势明显,为研究领域的论文相似性提供了新方法。Every year,a large number of papers spanning different fields are published,some of which delve into specific areas for in-depth analysis,while others involve interdisciplinary fields.Although the research areas of these papers provide guidelines for understanding their topics,many researchers mainly rely on natural language processing techniques to evaluate the similarity of papers,ignoring the inherent importance of the research areas.To this end,an innovative method for quantifying paper similarity is proposed based on the utilization of research fields and their interrelationships.Firstly,describe a paper using a set of 4-level vectors constructed from relevant research fields;Next,introduce a correlation matrix to clarify the interrelationships between these fields,and finally evaluate the similarity between the paper representation vector and other paper representation vectors to calculate the paper similarity.The experiment shows that the proposed method has significant advantages in the dataset of open academic graph,providing a new method for the similarity of research papers in the field.

关 键 词：研究领域 论文相似度 关系矩阵 论文表示 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]