Paper Info
Title
A Visualization of Research Papers Based on the Topics and Citation Network
Abstract
Survey of research papers is not an easy task for novice researchers, because they are not always good at finding all appropriate keywords for the survey. Moreover, it is not easy for them to understand positions of papers in their research fields instantly, even when they use famous search engines like Google Scholar, it may often take a long time for them to find scholarly literature. On the other hand, many researchers have presented citation visualization techniques for surveying research papers. However, it is still often difficult to observe the complicated relations across multiple research fields or traverse the entire relations in their interest. In this paper, we proposed a visualization technique for citation networks applying topic-based paper clustering. Our technique categorizes papers applying LDA (Latent Dirichlet Allocation), and constructs clustered networks consisting of the papers.
Year
DOI
Venue
2015
10.1109/iV.2015.58
International Conference on Information Visualisation
Keywords
Field
DocType
Citation network visualization, edge bundling, topic-based clustering
Data science,Latent Dirichlet allocation,Information visualization,Visualization,Computer science,Citation,Citation network,Cluster analysis,Creative visualization,Traverse
Conference
ISSN
Citations 
PageRank 
1550-6037
8
0.46
References 
Authors
7
3
Name
Order
Citations
PageRank
Rina Nakazawa180.46
Takayuki Itoh250365.85
Takafumi Saito318023.77