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Authors: Paula R. C. Silva 1 ; Sérgio M. Dias 2 ; Wladmir C. Brandão 1 ; Mark A. Song 1 and Luis E. Zárate 1

Affiliations: 1 Pontifical Catholic University of Minas Gerais, Brazil ; 2 Federal Service of Data Processing, Brazil

Keyword(s): Formal Concept Analysis, Proper Implications, Social Networks.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Biomedical Engineering ; Data Engineering ; Data Mining ; Databases and Data Security ; Databases and Information Systems Integration ; Enterprise Information Systems ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Management ; Large Scale Databases ; Ontologies and the Semantic Web ; Sensor Networks ; Signal Processing ; Society, e-Business and e-Government ; Soft Computing ; Strategic Decision Support Systems ; Web Information Systems and Technologies

Abstract: From the recent proliferation of online social networks, a set of specific type of social network is attracting more and more interest from people all around the world. It is professional social networks, where the users’ interest is oriented to business. The behavior analysis of this type of user can generate knowledge about competences that people have been developed in their professional career. In this scenario, and considering the available amount of information in professional social networks, it has been fundamental the adoption of effective computational methods to analyze these networks. The formal concept analysis (FCA) has been a effective technique to social network analysis (SNA), because it allows identify conceptual structures in data sets, through conceptual lattice and implication rules. Particularly, a specific set of implications rules, know as proper implications, can represent the minimum set of conditions to reach a specific goal. In this work, we proposed a FCA -based approach to identify relations among professional competences through proper implications. The experimental results, with professional profiles from LinkedIn and proper implications extracted from PropIm algorithm, shows the minimum sets of skills that is necessary to reach job positions. (More)

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Paper citation in several formats:
Silva, P.; Dias, S.; Brandão, W.; Song, M. and Zárate, L. (2017). Formal Concept Analysis Applied to Professional Social Networks Analysis. In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS; ISBN 978-989-758-247-9; ISSN 2184-4992, SciTePress, pages 123-134. DOI: 10.5220/0006333401230134

@conference{iceis17,
author={Paula R. C. Silva. and Sérgio M. Dias. and Wladmir C. Brandão. and Mark A. Song. and Luis E. Zárate.},
title={Formal Concept Analysis Applied to Professional Social Networks Analysis},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS},
year={2017},
pages={123-134},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006333401230134},
isbn={978-989-758-247-9},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 1: ICEIS
TI - Formal Concept Analysis Applied to Professional Social Networks Analysis
SN - 978-989-758-247-9
IS - 2184-4992
AU - Silva, P.
AU - Dias, S.
AU - Brandão, W.
AU - Song, M.
AU - Zárate, L.
PY - 2017
SP - 123
EP - 134
DO - 10.5220/0006333401230134
PB - SciTePress