数据与计算发展前沿 ›› 2019, Vol. 1 ›› Issue (2): 121-134.doi: 10.11871/jfdc.issn.2096-742X.2019.02.011

所属专题: “人工智能”专刊

• 人工智能专刊 • 上一篇    

国际人工智能研究前沿及演进趋势——基于对人工智能期刊论文的突变术语探测分析

唐川1,3,*(),秦小林2,李若男3,王会勇4   

  1. 1. 中国科学院成都文献情报中心,四川 成都 610041
    2. 中国科学院成都计算机应用研究所,四川 成都 610041
    3. 中国科学院大学,经济与管理学院图书情报与档案管理系,北京 100190
    4. 桂林电子科技大学,数学与计算科学学院,广西 桂林 541004
  • 收稿日期:2019-09-25 出版日期:2019-12-20 发布日期:2020-01-15
  • 通讯作者: 唐川 E-mail:tangc@clas.ac.cn
  • 作者简介:唐川,1983年生,现任中国科学院成都文献情报中心副研究员,硕士学历。主要从事信息科技战略研究与信息科技情报分析,研究方法和理论涉及文献计量、科学计量、知识图谱、专利分析等。
    唐川设计了研究思路与方案,完成了数据分析与主要内容撰写。秦小林对12个研究前沿进行了内容解读。李若男完成了数据检索、下载与整理。王会勇对8个研究前沿进行了内容解读。
    Tang Chuan, born in 1983, is an associate researcher at the Chengdu Library and Information Center, Chinese Academy of Sciences. His research interests focus on information technology strategic study and scientific and technological information analysis with those methods and theories involving bibliometrics, scientometrics, knowledge graph, patent information study, etc.
    E-mail:tangc@clas.ac.cn
    Tang Chuan conceived the research scheme, performed data analysis and wrote the manuscript with support from Qin Xiaolin and Wang Huiyong. Qin Xiaolin interpretated 12 research fronts. Li Ruonan performed data retrieval and cleaning. Wang Huiyong interpretated 8 research fronts.
  • 基金资助:
    中国科学院战略规划研究专项项目“主要领域规划状态监测与分析”(GHJ-ZLZX-2019-31);四川省科技厅软科学研究计划项目“四川省新一代人工智能产业现状与发展路径研究”(2018ZR0082);成都市科技局软科学研究项目“新经济时代成都市人工智能产业生态及发展策略研究”(2017-RK00-00275-ZF)

The Frontiers and Trends of Artificial Intelligence Research — An Analysis Based on Burst Term Detection on Journal Articles

Tang Chuan1,3,*(),Qin Xiaolin2,Li Ruonan3,Wang Huiyong4   

  1. 1. Chengdu Library and Information Center, Chinese Academy of Sciences, Chengdu, Sichuan 610041, China
    2. Chengdu Institute of Computer Applications, Chinese Academy of Sciences, Chengdu, Sichuan 610041, China
    3. Department of Library, Information and Archives Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
    4. School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin, Guangxi 541004, China
  • Received:2019-09-25 Online:2019-12-20 Published:2020-01-15
  • Contact: Tang Chuan E-mail:tangc@clas.ac.cn

摘要:

【目的】对2006-2019年人工智能领域的研究前沿及演进趋势开展分析,为相关学者提供参考。【文献范围】从Web of Science核心数据库中,检索到中国计算机学会推荐的人工智能领域A类和B类国际期刊在2006-2019年间发表的28862篇论文。【方法】通过对大量论文数据进行突变术语探测和对代表性论文进行内容解读,分析国际人工智能领域的研究前沿及其演变趋势。【结果】发现2006年以来人工智能领域出现的49个研究前沿,并对其中20个主要研究前沿开展进一步分析,发现总体可分为三个发展阶段,其中近5年内相关研究前沿正在加速涌现。【局限】内容解读范围不足,缺乏期刊以外其他资料与数据的支持,所用工具与算法尚存局限性。【结论】人工智能研究前沿正在面向更深入和更高级的问题加速涌现,并呈多元化发展趋势。

关键词: 人工智能, 研究前沿, 突变术语, 内容解读

Abstract:

[Objective] This paper investigates the frontiers and trends of artificial intelligence research between 2006 and 2019. [Coverage] 28862 articles published between 2006 and 2019 in Class A and Class B journals recommend by China Computer Federation were studied. [Methods] By means of burst term detection on a large number of articles and content analysis on a few articles, this paper investigates the frontiers and trends of artificial intelligence research. [Results] 20 major frontier research topics between 2006 and 2019 were detected, which could be summarized in three development stages. The emergence of frontier research topics has been accelerating in recent 5 years. [Limitations] The coverage of content analysis is not broad enough; the data and information only considers journal research articles; the tool and algorithm employed still have some limitations. [Conclusions] The emergence of frontier research topics of artificial intelligence are accelerated towards more sophisticated problems, enhancing diversity of research topic.

Key words: artificial intelligence, frontier research topics, burst term, content analysis