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Constructing Automatic Structured Synthesis Tool for Sci-Tech Literature Based on Move Recognition |
Liu Yi1,Zhang Zhixiong1,2(),Wang Yufei1,2,Li Xuesi1,2 |
1National Science Library, Chinese Academy of Sciences, Beijing 10090, China 2Department of Information Resources Management, School of Economic and Management, University of Chinese Academy of Sciences, Beijing 10090, China |
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Abstract [Objective] This paper utilizes AI technology to construct an automatic structured synthesis tool, which organizes the sci-tech research frameworks structurally and reveals their main points. [Methods] The new tool was developed based on move recognition. First, we identified the research questions, methodology, and progress keywords to extract the most important knowledge points from each literature. Then, we employed hierarchical clustering and cluster label generation methods to synthesize the knowledge. Third, we designed a tree structure for the synthesis outputs. [Results] The proposed tool could automatically synthesize the literature contents and reveal their framework with a “research question, methodology, and progress” tree structure. [Limitations] Insufficient clustering accuracy and difficulty determining cluster numbers reduce our model's synthesis performance. [Conclusions] The synthesis tool based on move recognition could automatically retrieve structured literature contents.
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Received: 14 November 2022
Published: 28 April 2023
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Fund:Special Research Assistant Program of Chinese Academy of Sciences(E1290905);National Science and Technology Library and Literature Center (NSTL) Project(2022XM28) |
Corresponding Authors:
Zhang Zhixiong,ORCID:0000-0003-1596-7487,E-mail:zhangzx@mail.las.ac.cn。
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