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Semantic Attributes for Citation Relationships: Creation and Visualization

  • Sergey Parinov
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 755)

Abstract

This paper presents a method to process a content of research papers in binary PDF format at a server side that gives research information systems new features of citation content analysis. This method efficiently generates JSON versions of PDF documents that allows an easier recognition of papers’ references, in-text references, citation context, etc. As a result, one can parse an extended set of citation data, including a location of citations in a research paper’s structure, frequency of mentioning for the same references, style of reference mentioning and so on. Based on these data we upgrade traditional citation relationships by adding some semantic attributes. Formatting these semantic data according W3C Web Annotation Data Model and integrating the data with some annotation tools, we visualize citation relationships, its semantic attributes and related statistics as annotations for readers of PDF documents from a research information system.

Keywords

Research information system PDF.js PDF to JSON conversion Citation relationships Semantic attributes Citation content analysis Visualization 

Notes

Acknowledgments

A part of this research (related with the annotation tool development) is funded by Russian Foundation for Basic Research, grant 12-07-00518-a. Another part – the approach development for extracting citation content data with focus on the supercomputer simulation of interactions among the agents and research community environment is funded by RSF grant (project No. 14-18-01968).

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Central Economics and Mathematics Institute of RASMoscowRussia
  2. 2.Russian Presidential Academy of National Economy and Public AdministrationMoscowRussia

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