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Advances in FCA-based Applications for Social Networks Analysis

Advances in FCA-based Applications for Social Networks Analysis

Marie-Aude Aufaure, Bénédicte Le Grand
Copyright: © 2013 |Volume: 1 |Issue: 1 |Pages: 17
ISSN: 2166-7292|EISSN: 2166-7306|EISBN13: 9781466631830|DOI: 10.4018/ijcssa.2013010104
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MLA

Aufaure, Marie-Aude, and Bénédicte Le Grand. "Advances in FCA-based Applications for Social Networks Analysis." IJCSSA vol.1, no.1 2013: pp.73-89. http://doi.org/10.4018/ijcssa.2013010104

APA

Aufaure, M. & Le Grand, B. (2013). Advances in FCA-based Applications for Social Networks Analysis. International Journal of Conceptual Structures and Smart Applications (IJCSSA), 1(1), 73-89. http://doi.org/10.4018/ijcssa.2013010104

Chicago

Aufaure, Marie-Aude, and Bénédicte Le Grand. "Advances in FCA-based Applications for Social Networks Analysis," International Journal of Conceptual Structures and Smart Applications (IJCSSA) 1, no.1: 73-89. http://doi.org/10.4018/ijcssa.2013010104

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Abstract

Concept lattices have been widely used for various purposes in many different applications since the 1980s. Recent applications of Formal Concept Analysis include extensions of traditional FCA applications such as data and text mining, machine learning and knowledge management. Progress has also recently been made in software engineering, Semantic Web and databases. New applications have also emerged in the fields of healthcare, ecology, biology, agronomy, business and social networks. This article presents example of successful applications of FCA for Social Networks Analysis. We show the benefit of FCA solutions, as well as their combination with semantics and topology-based approaches. We conclude by presenting FCA-based visualization solutions and open challenges for FCA in the context of large and dynamic data.

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