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Semantically linking events for massive scientific literature research

Junsheng Zhang (Institute of Scientific and Technical Information of China, Beijing, China)
Yunchuan Sun (Beijing Normal University, Beijing, China)
Changqing Yao (Institute of Scientific and Technical Information of China, Beijing, China)

The Electronic Library

ISSN: 0264-0473

Article publication date: 7 August 2017



This paper aims to semantically linking scientific research events implied by scientific and technical literature to support information analysis and information service applications. Literature research is an important method to acquire scientific and technical information which is important for research, development and innovation of science and technology. It is difficult but urgently required to acquire accurate, timely, rapid, short and comprehensive information from the large-scale and fast-growing literature, especially in the big data era. Existing literature-based information retrieval systems focus on basic data organization, and they are far from meeting the needs of information analytics. It becomes urgent to organize and analyze scientific research events related to scientific and technical literature for forecasting development trend of science and technology.


Scientific literature such as a paper or a patent is represented as a scientific research event, which contains elements including when, where, who, what, how and why. Metadata of literature is used to formulate scientific research events that are implied in introduction and related work sections of literature. Named entities and research objects such as methods, materials and algorithms can be extracted from texts of literature by using text analysis. The authors semantically link scientific research events, entities and objects, and then, they construct the event space for supporting scientific and technical information analysis.


This paper represents scientific literature as events, which are coarse-grained units comparing with entities and relations in current information organizations. Events and semantic relations among them together formulate a semantic link network, which could support event-centric information browsing, search and recommendation.

Research limitations/implications

The proposed model is a theoretical model, and it needs to verify the efficiency in further experimental application research. The evaluation and applications of semantic link network of scientific research events are further research issues.


This paper regards scientific literature as scientific research events and proposes an approach to semantically link events into a network with multiple-typed entities and relations. According to the needs of scientific and technical information analysis, scientific research events are organized into event cubes which are distributed in a three-dimensioned space for easy-to-understand and information visualization.



This research work was partially supported by the National Natural Science of China (Grant No. 71503240, 61371185 and L1624039).


Zhang, J., Sun, Y. and Yao, C. (2017), "Semantically linking events for massive scientific literature research", The Electronic Library, Vol. 35 No. 4, pp. 724-744.



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