On Visualizing Heterogeneous Semantic Networks from Multiple Data Sources

• Main Authors: Maureen, Maureen, Sun, Aixin, LIM, Ee Peng, Datta, Anwitaman, Chang, Kuiyu
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2008
• Subjects: Computer Sciences
• Online Access: https://ink.library.smu.edu.sg/sis_research_smu/7; https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=1006&context=sis_research_smu
• Institution: Singapore Management University

In this paper, we focus on the visualization of heterogeneous semantic networks obtained from multiple data sources. A semantic network comprising a set of entities and relationships is often used for representing knowledge derived from textual data or database records. Although the semantic networks created for the same domain at different data sources may cover a similar set of entities, these networks could also be very different because of naming conventions, coverage, view points, and other reasons. Since digital libraries often contain data from multiple sources, we propose a visualization tool to integrate and analyze the differences among multiple social networks. Through a case study on two terrorism-related semantic networks derived from Wikipedia and Terrorism Knowledge Base (TKB) respectively, the effectiveness of our proposed visualization tool is demonstrated.