图书情报领域人工智能的研究热点及发展趋势研究

doi:10.13266/j.issn.0252-3116.2019.01.011

图书情报工作 ›› 2019, Vol. 63 ›› Issue (1): 70-80.DOI: 10.13266/j.issn.0252-3116.2019.01.011

• 图书情报与档案管理前沿热点专辑 • 上一篇下一篇

图书情报领域人工智能的研究热点及发展趋势研究

王晰巍^1,2, 贾若男¹, 王铎¹, 郭宇¹

1 吉林大学管理学院长春 130022;
2 吉林大学大数据管理研究中心长春 130022

收稿日期:2018-10-16 修回日期:2018-11-16 出版日期:2019-01-05 发布日期:2019-01-05
作者简介:王晰巍(ORCID:0000-0002-5850-0126),副院长,大数据管理研究中心主任,教授,博士生导师,E-mail:wxw_mail@163.com;贾若男(ORCID:0000-0002-4262-7982),硕士研究生;王铎(ORCID:0000-0002-5060-7893),博士研究生;郭宇(ORCID:0000-0003-1782-7752),副教授,博士。

Research on the Development Trend of Artificial Intelligence Research in Library and Information Field

Wang Xiwei^1,2, Jia Ruonan¹, Wang Duo¹, Guo Yu¹

1 School of Management, Jilin University, Changchun 130022;
2 Research Center for Big Data Management, Jilin University, Changchun 130022

Received:2018-10-16 Revised:2018-11-16 Online:2019-01-05 Published:2019-01-05

摘要/Abstract

摘要： [目的/意义]搜集和分析国内外图书情报领域人工智能研究的相关文献，以期了解人工智能在图书情报领域目前的研究进展及未来的研究趋势，为学术界和产业界的研究提供借鉴和启示。[方法/过程]运用文献分析和知识图谱可视化方法，对国内外图书情报领域人工智能研究的起源和发展、国内外研究热点及未来研究趋势进行对比和可视化分析。[结果/结论]从研究发展趋势看，国内外相关研究成果的数量呈逐年递增态势。从研究热点看，国外研究主要围绕人工智能在信息检索、社交媒体内容分类及情感分析、知识问答方面的应用研究；国内研究主要围绕人工智能在网络舆情分析、图书馆智能搜索和推荐服务、社交媒体网络数据分析方面的研究。从研究趋势看，未来研究应围绕人工智能技术应用在视觉搜索和语义搜索、智慧图书馆服务、社交网络数据挖掘、人工智能对隐私与安全的影响4个主要方向来开展研究。

关键词: 图书情报, 人工智能, 研究热点, 发展趋势

Abstract: [Purpose/significance] The article collects and analyzes relevant literatures on artificial intelligence research in the field of library and information at home and abroad, in order to understand the current research progress and future research trends of artificial intelligence in the field of library and information, and provide reference and research for academic and industrial research.[Method/process] Using literature analysis and knowledge map visualization method, the origin and development of artificial intelligence research in the field of library and information at home and abroad, domestic and foreign research hotspots and future research trends are compared and visualized.[Result/conclusion] From the perspective of research and development trends, the number of relevant research results at home and abroad is increasing year by year. From the research hotspots, foreign research mainly focuses on the application research of artificial intelligence in information retrieval, social media content classification and sentiment analysis, and knowledge question and answer. Domestic research mainly focuses on artificial intelligence in network public opinion analysis, library intelligent search and recommendation services, and social media network data analysis. From the research trend, future research should focus on the four main directions of artificial intelligence technology application visual search and semantic search, smart library service, social network data mining, and artificial intelligence impact on privacy and security.

Key words: library and information, artificial intelligence, research hotspot, development trend

中图分类号:

TP18

王晰巍, 贾若男, 王铎, 郭宇. 图书情报领域人工智能的研究热点及发展趋势研究[J]. 图书情报工作, 2019, 63(1): 70-80.

Wang Xiwei, Jia Ruonan, Wang Duo, Guo Yu. Research on the Development Trend of Artificial Intelligence Research in Library and Information Field[J]. LIS, 2019, 63(1): 70-80.

参考文献

[1] 石纯一.人工智能原理[M].北京:清华大学出版社,1993.
[2] 麦肯锡.2017全球人工智能报告[EB/OL].[2018-07-24].http://www.360doc.com/content/17/0910/19/37263053_686042639.shtml.
[3] 猎豹全球智库.2018中国人工智能报告[EB/OL].[2018-07-24].https://www.jiemian.com/article/2005999.html.
[4] 清华大学中国科技政策研究中心.中国人工智能报告2018[EB/OL].[2018-07-24]. https://wemedia.ifeng.com/71852099/wemedia.shtml.
[5] STRONGMAN K T, BROWN R. Visual search with meaningful and non-meaningful material[J].Quarterly journal of experimental psychology, 1966, 18(2):164-168.
[6] PRINZ W, ATAIAN D. Two components and two stages in search performance:a case study in visual search[J].Acta psychologica, 1973, 37(4):255-277.
[7] SALTON G, YANG C S, YU C T. A theory of term importance in automatic text analysis[J]. Journal of the American Society for Information Science & Technology, 2014, 26(1):33-44.
[8] NARENDRA K S, PARATHASARANTHY K. Identification and control of dynamical systems using neural networks[J].IEEE transactions on neural networks,1990,1(1):4-27.
[9] BNLSARI A. Some analytical solutions to the general approximation problem for feedforward neural networks[J].Neural networks,1993(6):991-996.
[10] MORRIS A. Expert systems for library and information services-A review[J]. Information processing & management,1991,27(6):713-724.
[11] 张春博,丁堃,贾龙飞.国际人工智能领域计量与可视化研究——基于AAAI年会论文的分析[J].图书情报工作,2012,56(22):69-76.
[12] 王菲菲,赵旭.论文层面计量视角下的核心文献价值测度与识别研究——以人工智能领域为例[J].情报理论与实践,2017, 40(6):91-98.
[13] SOCHER R, PERELYGIN A,WU J,et al.Recursive deep models for semantic compositionality over a sentiment treebank[C]//Proceedings of the 2013 conference on empirical methods in natural language processing. Stroudsburg:Association for Computational Linguistics,2013:1631-1642.
[14] HINTON G,DENG L,YU D,et al.Deep neural networks for acoustic modeling in speech recognition:the shared views of four research groups[J].IEEE signal processing magazine,2012,29(6):82-97.
[15] KALCHBRENNER N, GREFENSTETTE E, LIUNSOM P. A convolutional neural network for modelling sentences[EB/OL].[2018-07-24]. https://arxiv.org/pdf/404.2188.pdf.
[16] NESHATI M, FALLAHNEJAD Z, BEIGY H. On dynamicity of expert finding in community question answering[J]. Information processing & management, 2017,53(5):1026-1042.
[17] LI G, LU T, DING X, et al. Predicting collaborative edits of questions and answers in online Q&A sites[J]. Journal of Internet technology, 2016, 17(6):1187-1194.
[18] 耿立大.自然语言信息加工和人工智能[J].数据分析与知识发现,1983(1):30-35.
[19] 刘伟权,钟义信.自然语言处理与全文情报检索[J].情报理论与实践,1997(1):43-46.
[20] 李蕾,郭祥昊.基于语义网络的概念检索研究与实现[J].情报学报,2000,19(5):525-531.
[21] 刘贤锋.基于BP神经网络预测企业竞争情报搜集成本[J].情报理论与实践,2007,30(5):646-649.
[22] 张秀华,赵伟.基于径向基神经网络的数字馆藏质量评价研究[J].情报理论与实践,2009, 32(5):61-64.
[23] 张玉峰,晏创业.基于机器学习的知识检索模型研究[J].图书情报知识,2002(4):6-9.
[24] 罗蔚.数字化信息服务的个性化发展:从可适应到自适应[J].情报资料工作,2010,31(2):74-76.
[25] 逯万辉.基于深度学习的学术期刊选题同质化测度方法研究[J].情报资料工作,2017(5):105-112.
[26] 庞英智.Web数据挖掘技术在电子商务中的应用[J].情报科学,2011(2):235-240.
[27] 邓仲华,刘伟伟, 陆颖隽.基于云计算的大数据挖掘内涵及解决方案研究[J].情报理论与实践,2015,38(7):103-108.
[28] 陈臣.基于大数据的图书馆个性化智慧服务体系构建[J].情报资料工作,2013(6):75-79.
[29] ZHANG R, DING G, ZHANG F, et al. The information retrieval technology of dynamic feedback artificial intelligence based on the neural network[C]//International conference on smart city and systems engineering. Washington:IEEE, 2017:250-253.
[30] ZHU Y J, YAN E J,SONG I Y.The use of a graph-based system to improve bibliographic information retrieval:system design, implementation, and evaluation[J].Journal of The Association for Information Science and Technology,2017,68(2):480-490.
[31] RAHOMAN M M, ISHISE R. A proposal of a temporal semantics aware linked data information retrieval framework[J]. Journal of intelligent information systems, 2018, 50(3):573-595.
[32] ZOONEN W V, VAN DER MEER,TONI, GLA. Social media research:the application of supervised machine learning in organizational communication research[J]. Computers in human behavior, 2016, 63:132-141.
[33] LEE I. Social media analytics for enterprises:typology, methods, and processes[J]. Business horizons, 2018,61(2):119-210.
[34] YOO S Y, SONG J I, JEONG O R. Social media contents based sentiment analysis and prediction system[J]. Expert systems with applications, 2018,105:102-111.
[35] ATTIAOUI D, MARTIN A, YAGHLANE B B. Belief measure of expertise for experts detection in question answering communities:case study stack overflow[J]. Procedia computer science, 2017, 112:622-631.
[36] 侯治平,黄少杰,廉同辉,等.基于语义关联分析的学术网络舆情传播研究——以科学网屠呦呦获诺贝尔奖博文为例[J]. 情报杂志, 2017, 36(5):118-123.
[37] 陈建英,朱晖,刘小芳.基于灰色关联计算的网络民族舆情事件监测模型研究[J].情报杂志,2017,36(12):126-131,179.
[38] 吴鹏,刘恒旺,沈思.基于深度学习和OCC情感规则的网络舆情情感识别研究[J].情报学报,2017,36(9):972-980.
[39] 李晨晖,张兴旺,秦晓珠.基于大数据的文化遗产数字图书馆移动视觉搜索机制建设研究[J].情报理论与实践, 2018,41(4):139-144,133.
[40] 齐云飞,赵宇翔,朱庆华.关联数据在数字图书馆移动视觉搜索系统中的应用研究[J].数据分析与知识发现,2017,1(1):81-90.
[41] 张兴旺.以信息推荐为例探讨图书馆人工智能体系的基本运作模式[J].情报理论与实践,2017,40(12):69-74.
[42] 李红巍.基于本体相似度和时间衰减的动态个性化推荐算法[J].图书情报工作,2017,61(S1):95-98.
[43] 李慧,柴亚青.基于属性特征的评论文本情感极性量化分析[J].数据分析与知识发现,2017,1(10):1-11.
[44] 齐林峰.利用实体解析的跨社交媒体同一用户识别[J].图书情报工作,2017,61(6):107-114.
[45] 张继东.移动社交网络环境下基于情景化偏好的用户行为感知研究[J].情报理论与实践,2017,40(1):110-114.
[46] 胡蓉,唐振贵,朱庆华.混合需求驱动的文内视觉资源移动视觉搜索框架[J].情报学报,2018,37(3):285-293.
[47] GAO F,ZHANG X, HUANG Y, et al. Data-driven lightweight interest point selection for large scale visual search[J]. IEEE transactions on multimedia, 2018, 20(10):2774-2787.
[48] MENEMENCIOGLU O,ORAK I M. An attempt at automatic label generation for object entry and exit on multimedia with a semantic search[J]. Tem journal-technology education management informatrics,2018,7(1):25-32.
[49] 夏立新,白阳,张心怡.融合与重构:智慧图书馆发展新形态[J].中国图书馆学报,2018,44(1):35-49.
[50] GAO Y P.Implementation of an intelligent library system Based on WSN and RFID[J].International journal of online engineering,2018,14(5):221-224.
[51] YI K, CJEN T, CONG G. Library personalized recommendation service method based on improved association rules[J]. Library hi tech, 2018,36(3):443-457.
[52] SIMOVIC A. A big data smart library recommender system for an educational institution[J]. Library hi tech, 2018,36(3):498-523.
[53] WANG Y, BACIU G, LI C. Cognitive visualization of popular regions discovered from geo-tagged social media data[J]. International Journal of cognitive informatics & natural intelligence, 2018, 12(1):14-28.
[54] VERSPOOR K, OFOPHI B, GRANDA M R. CommViz:visualization of semantic patterns in large social communication networks[J].Information visualization, 2018,17(1):66-88.
[55] 王林森,王学义.微博内向型传导热点发现与预测算法研究[J].图书情报工作,2018,62(3):71-77.
[56] WEI P, ZHOU Z. Research on security of information sharing in Internet of Things based on key algorithm[J].Future generation computer systems, 2018,88:599-605.
[57] BASALLO Y A, SENTI V E, SANCHEZ N M. Artificial intelligence techniques for information security risk assessment[J].IEEE Latin America transactions, 2018, 16(3):897-901.
[58] 胡刃锋.产学研协同创新隐性知识共享机制.北京:光明日报出版社,2018.

图书情报领域人工智能的研究热点及发展趋势研究

Research on the Development Trend of Artificial Intelligence Research in Library and Information Field

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