Page 230 - JOURNAL OF LIBRARY SCIENCE IN CHINA 2018 Vol. 42

Extended English abstracts of articles published in the Chinese edition of Journal of Library Science in China 2016 Vol.42 229

visualization technology to analyze the visualization of the intensity,structure and content of the
topics. Through the interaction of the core areas of research questions,the evolution path and
trend of research methods and key technologies of the topics,and the macro evolution trend,meso
evolution process and microscopic evolution details can be revealed. It can effectively help to
quickly digest and understand information and refine the topic evolution analysis results to reveal
the complex process of topics evolution.
The experiment on ‘big data study in library and intelligence field in the past 10 years’ proves the
visualization analysis method proposed in this paper could effectively demonstrate the complicated
process of topics evolution in a discipline. Compared with the other visualization analysis
methods,the proposed method based on topic strength,structure and internal basic knowledge unit
evolution could visualize and analyze the core research points,the primary research methods,the
key technology topics evolution path and trends and the evolution trend from the macro-angle,the
evolution process from meso-angle and the evolution particulars from the micro angle,so as to
better analyze the complicated topics evolution process. The proposed method is applicable only to
scientific papers including key words and needs to be expanded to include other data resources.
The practical significance lies in:1)Proposing the dynamic topics identification method to
provide reference to related research；2)Proposing a multidimensional topics evolution analysis
model and an innovative visualization method which can be used to analyze the topics evolution
rules and discover scientific and technological knowledge,etc；3)The findings can be used in
scientific and research management to support decision-making,raise research efficiency and help
to promote the scientific and technological innovation in related fields.

Linked data-oriented method of entity linking discovery

①a *
GAO Jinsong ,ZHOU Ximan & LIANG Yanqi
The World Wide Web has been developed into a global data space,which links web data and
database data. Linked data is one of the best tools to achieve this information evolution. Linked
data publish data in a structured form to interlink resources. With the depth of linked data being
deeply applied,more and more data are published on the web as linked data. The published web
information also has been transformed into linked data in automatic or semi-automatic ways.
Practically,there are still only a few connections between the released linked dataset,and it is
inconvenient to share data. So based on the entity linking discovery,we can discover the real
relation between entities,build the entity linking according to the publishing standard,realize the
goal of discovering potential entity linking,enhance the interlinking between datasets,and then
increase the accuracy of published linked data.

* Correspondence should be addressed to GAO Jinsong, Email: jsgao@mail.ccnu.edu.cn, ORCID:0000-0003-0022-5923