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http://dx.doi.org/10.36498/kbigdt.2020.5.1.77

Developing Graphic Interface for Efficient Online Searching and Analysis of Graph-Structured Bibliographic Big Data  

You, Youngseok (강원대학교 컴퓨터과학과)
Park, Beomjun (강원대학교 컴퓨터과학과)
Jo, Sunhwa (강원대학교 컴퓨터과학과)
Lee, Suan (인하대학교 VOICE AI 연구소)
Kim, Jinho (강원대학교 컴퓨터과학과)
Publication Information
The Journal of Bigdata / v.5, no.1, 2020 , pp. 77-88 More about this Journal
Abstract
Recently, many researches habe been done to organize and analyze various complex relationships in real world, represented in the form of graphs. In particular, the computer field literature data system, such as DBLP, is a representative graph data in which can be composed of papers, their authors, and citation among papers. Becasue graph data is very complex in storage structure and expression, it is very difficult task to search, analysis, and visualize a large size of bibliographic big data. In this paper, we develop a graphic user interface tool, called EEUM, which visualizes bibliographic big data in the form of graphs. EEUM provides the features to browse bibliographic big data according to the connected graph structure by visually displaying graph data, and implements search, management and analysis of the bibliographc big data. It also shows that EEUM can be conveniently used to search, explore, and analyze by applying EEUM to the bibliographic graph big data provided by DBLP. Through EEUM, you can easily find influential authors or papers in every research fields, and conveniently use it as a search and analysis tool for complex bibliographc big data, such as giving you a glimpse of all the relationships between several authors and papers.
Keywords
Graph Data; Bibliographic Big Data; Graphic Interface; Visualization Tool;
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