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Big Graph-based Data Visualization Experiences - The WordNet Case Study
Author(s) -
Enrico G. Caldarola,
Antonio Picariello,
Antonio M. Rinaldi
Publication year - 2015
Publication title -
2015 7th international joint conference on knowledge discovery, knowledge engineering and knowledge management (ic3k)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5220/0005632201040115
Subject(s) - wordnet , computer science , visualization , data visualization , big data , graph , information retrieval , data science , artificial intelligence , data mining , theoretical computer science
In the Big Data era, the visualization of large data sets is becoming an increasingly relevant task due to the great impact that data have from a human perspective. Since visualization is the closer phase to the users within the data life cycle's phases, there is no doubt that an effective, efficient and impressive representation of the analyzed data may result as important as the analytic process itself. This paper presents an experience for importing, querying and visualizing graph database and in particular, we describe as a case study the WordNet database using Neo4J and Cytoscape. We will describe each step in this study focusing on the used strategies for overcoming the different problems mainly due to the intricate nature of the case study. Finally, an attempt to define some criteria to simplify the large-scale visualization of WordNet will be made, providing some examples and considerations which have arisen.

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