Visualizing and Structuring Semantic Data - Volume 3 Number 2 (Apr. 2013) - IJMLC
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Editor-in-chief
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.
IJMLC 2013 Vol.3(2): 209-213 ISSN: 2010-3700
DOI: 10.7763/IJMLC.2013.V3.304

Visualizing and Structuring Semantic Data

Teemu Mäenpää and Vesa Nyrhilä
Abstract—In this paper is proposed a method for representing semantic data and knowledge. The method is based two foundational concepts: semantic link network and adjacency model. The method allows graph presentations of semantic data and it preserves the semantic relationships between the concepts of the domain. Furthermore with the methodit is possible construct relational model of the semantically rich data.

Index Terms—Adjacency relation systems, semantic link network, data visualization, knowledge representation.

The authors are with the Department of Computer Science, Faculty of Technology, University of Vaasa, Vaasa, FI-65100 Finland (e-mail: teemu.maenpaa@uva.fi, vesa.nyrhila@uva.fi).

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Cite:Teemu Mäenpää and Vesa Nyrhilä, "Visualizing and Structuring Semantic Data," International Journal of Machine Learning and Computing vol. 3, no. 2, pp. 209-213, 2013.

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