基于大数据的高校图书馆知识创新服务研究
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摘要
大数据时代,数据成为一种重要的生产因素。高校图书馆运用大数据技术,深入挖掘学术科研数据和读者学术行为数据,帮助读者获得学术资源中的隐性知识、掌握前瞻性的研究视野、建立完善的知识结构、提升读者的知识创新能力,从而将图书馆演变为知识创新服务中心。该文将这种大数据驱动下的知识服务定义为高校图书馆的知识创新服务,梳理了目前知识服务的现状,提出高校图书馆知识创新服务平台的功能模型,利用大数据技术提供对海量数据的实时分析和挖掘能力、语义网技术提供计算机理解和处理事务的能力和判断与推理能力、人工智能技术持续提高自我性能以帮助人类完成那些一开始无法明确定义的任务的能力,来实现八大创新功能:利用可视化知识图谱,呈现知识网络全貌;智能摘要,帮助读者粗加工大量的文本信息;智能构建个人知识专题;关键词联想,激发思维联想;个性化、精准化智能推荐;个人学术轨迹管理与"我的关注领域"呈现;统一检索与全文检索;开放学科语义维护功能。由此,高校图书馆的知识服务将站在全数据和智能化的起点上,可望打造为一个创新的服务体系,提供一种全新的服务生态。
In the era of Big Data, data has become an important production factor. University libraries use Big Data technology to dig deeper into academic and scientific data and readers' academic behavior data, helping readers gain access to tacit knowledge in academic resources, master forward-looking research horizons, establish a sound knowledge structure, and enhance readers' knowledge innovation capabilities. This will transform the library into a knowledge innovation service center. This article defines this kind of big data-driven knowledge service as the knowledge innovation service of university libraries,sorts out the current status of knowledge services, and proposes a functional model of a university library knowledge innovation service platform. Big data technology provides real-time analysis and mining capabilities for massive data; Semantic Web technology provides the ability to understand and process transactions, and has certain judgment and reasoning capabilities; artificial intelligence technology provides the ability to continuously improve self-performance and help humans complete those tasks those who cannot be clearly defined.Based on these technologies, this paper proposes eight innovative functions of the library knowledge innovation service platform:using the visual knowledge map to present the whole picture of the knowledge network; intelligent summary helping the reader rough out a large amount of text information; intelligently constructing personal knowledge topics; Lenovo, inspiring thinking association;personalized, accurate intelligent recommendation; personal academic trajectory management and "my area of concern" presentation;unified retrieval and full-text retrieval; opening discipline semantic maintenance. This makes the knowledge service of university libraries stand at the starting point of full data and intelligence, and is expected to be an innovative service system and provide a new service ecosystem.
In the era of Big Data, data has become an important production factor. University libraries use Big Data technology to dig deeper into academic and scientific data and readers' academic behavior data, helping readers gain access to tacit knowledge in academic resources, master forward-looking research horizons, establish a sound knowledge structure, and enhance readers' knowledge innovation capabilities. This will transform the library into a knowledge innovation service center. This article defines this kind of big data-driven knowledge service as the knowledge innovation service of university libraries,sorts out the current status of knowledge services, and proposes a functional model of a university library knowledge innovation service platform. Big data technology provides real-time analysis and mining capabilities for massive data; Semantic Web technology provides the ability to understand and process transactions, and has certain judgment and reasoning capabilities; artificial intelligence technology provides the ability to continuously improve self-performance and help humans complete those tasks those who cannot be clearly defined.Based on these technologies, this paper proposes eight innovative functions of the library knowledge innovation service platform:using the visual knowledge map to present the whole picture of the knowledge network; intelligent summary helping the reader rough out a large amount of text information; intelligently constructing personal knowledge topics; Lenovo, inspiring thinking association;personalized, accurate intelligent recommendation; personal academic trajectory management and "my area of concern" presentation;unified retrieval and full-text retrieval; opening discipline semantic maintenance. This makes the knowledge service of university libraries stand at the starting point of full data and intelligence, and is expected to be an innovative service system and provide a new service ecosystem.
引文
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[2]唐晓波,魏巍.知识融合:大数据时代知识服务的增长点[J].图书馆学研究,2015,(5):9-14.
[3]董玮,詹庆东.图书馆知识服务模式辨析[J].图书馆学研究,2016,(3):72-79.
[4]胡莲香.走向大数据知识服务:大数据时代图书馆服务模式创新[J].农业图书情报学刊,2014,(2):173-177.
[5]张新娜.大数据时代智慧图书馆建设路径分析[J].图书馆研究,2014,(1):9-13.
[6]李晨晖等.大数据知识服务平台构建关键技术研究[J].情报资料工作,2013,(2):29-34.
[7]张娟等.面向大数据的图书馆单元信息知识服务系统研究--以养生知识服务平台为例[J].现代情报,2017,(10):49-52.
[8]刘庆麟.现代数字图书馆技术架构下高校重点学科的知识服务[J].电子测试,2015,(4):95-95.
[9]范兴丰.基于云计算和大数据的知识服务平台架构研究[J].无限互联科技,2016,(21):50-52.
[10]陈川.基于学科元数据中心的知识服务平台建设研究与应用[J].情报理论与实践,2014,(5):57-60.
[11]余传明,安璐.从小数据到大数据--观点检索面临的三个挑战[J].情报理论与实践,2016,(2):13-19.
[12]邓景康.大数据环境下清华大学图书馆的实践[N].中国新闻出版报,2013-8-29(5).
[13]袁辉等.用户行为模型在图书馆“智慧门户”建设中的应用与探索[J].图书情报工作,2017,(7):57-61.
[14]赵晓黎,孙济庆等.中外文献数据库资源与知识服务探析[J].现代情报,2016,36(8):3-9.
[15]梁迎丽,刘陈.人工智能教育应用的现状分析、典型特征与发展趋势[J].中国电化教育,2018,(3):24-30.
[16]新一代人工智能具有五大特点[DB/OL].http://www.scio.gov.cn/32344/32345/35889/36946/zy36950/Document/1559026/1559026.htm,2018-10-10.
[17]柳益君.大数据挖掘视角下的图书馆智慧服务--模型、技术和服务[J].现代情报,2017,37(11):81-86.
[18]许云峰.大数据技术及行业应用[M].北京:北京邮电大学出版社,2016.
[19]程学旗等.大数据系统和分析技术综述[J].软件学报,2014,25(9):1889-1908.
[20]任磊等.大数据可视分析综述[J].软件学报,2014,25(9):1909-1936.