INFORMATION RESEARCH

Identification of Interdisciplinary “Technology-Topic” Innovation Combinations: Take Artificial Intelligence Technology Driving the Innovation in LIS as An Example

  • Lu Quan ,
  • Qin Yuxuan ,
  • Chen Jing
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  • 1 Center for Studies of Information Resources, Wuhan University, Wuhan 430072;
    2 Big Data Institute, Wuhan University, Wuhan 430072;
    3 School of Information Management, Central China Normal University, Wuhan 430079

Received date: 2023-03-20

  Revised date: 2023-07-20

  Online published: 2024-02-02

Abstract

[Purpose/Significance] The interdisciplinary application of frontier technology is an important way of scientific and technology innovation. Identifying potential interdisciplinary “technology-topic” innovation combinations in academic literature helps to find the innovation opportunities that drive the development of target disciplinary field, and to seize the commanding heights of scientific and technological innovation.[Method/Process] Based on the idea of combination innovation and the big data of academic papers, it designed the identification framework of interdisciplinary “technology-topic” innovation combinations. First, it formed the fit index of interdisciplinary “technology-topic” combination based on the topic model and word vector model, which evaluated the rationality of combining target discipline field with the frontier technology by referring to the application of frontier technology in other disciplinary fields. Then, through the co-occurrence analysis of frontier technology and target discipline field topic, it constructed the novelty index of interdisciplinary “technology-topic” combination to remove the “technology-topic” combination with insufficient novelty, so as to obtain the fit and novel interdisciplinary “technology-topic” innovation combinations.[Result/Conclusion] This paper explores the innovative applications of artificial intelligence technology in the academic research of library and information science (LIS), and identifies 14 fit and novel interdisciplinary “artificial intelligence technology - LIS topic” innovation combinations. The results show that the framework of this paper is effective in identifying interdisciplinary “technology-topic” innovation combinations, and can provide forward-looking guidance for scientific and technology innovation in various discipline fields.

Cite this article

Lu Quan , Qin Yuxuan , Chen Jing . Identification of Interdisciplinary “Technology-Topic” Innovation Combinations: Take Artificial Intelligence Technology Driving the Innovation in LIS as An Example[J]. Library and Information Service, 2024 , 68(2) : 50 -61 . DOI: 10.13266/j.issn.0252-3116.2024.02.005

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