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Multimodal graph-based analysis over the DBLP repository: critical discoveries and hypotheses by Gabriel P. Gimenes; Hugo Gualdron; Jose F. Rodrigues; Mario Gazziro is a scholarly article available to read on EtoBox.

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The use of graph theory for analyzing network-like data has gained central importance with the rise of the Web 2.0. However, many graph-based techniques are not welldisseminated and neither explored at their full potential, what might depend on a complimentary approach achieved with the combination of multiple techniques. This paper describes the systematic use of graph-based techniques of different types (multimodal) combining the resultant analytical insights around a common domain, the Digital Bibliography & Library Project (DBLP). To do so, we introduce an analytical ensemble based on statistical (degree, and weakly-connected components distribution), topological (average clustering coefficient, and effective diameter evolution), algorithmic (link prediction/machine learning), and algebraic techniques to inspect non-evident features of DBLP at the same time that we interpret the heterogeneous discoveries found along the work. As a result, we have put together a set of techniques demonstrating over DBLP what we call multimodal analysis, an innovative process of information understanding that demands a wide technical knowledge and a deep understanding of the data domain. We expec

Author

Gabriel P. Gimenes; Hugo Gualdron; Jose F. Rodrigues; Mario Gazziro

Publisher

ACM

Published

2015

Language

EN