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Erschienen in: Knowledge and Information Systems 2/2021

07.11.2020 | Regular Paper

A graph grammar and \(K_{4}\)-type tournament-based approach to detect conflicts of interest in a social network

verfasst von: Saadia Albane, Hachem Slimani, Hamamache Kheddouci

Erschienen in: Knowledge and Information Systems | Ausgabe 2/2021

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Abstract

In this paper, we introduce a new approach based on properties of graph grammars to detect conflicts of interest (COIs) in a field represented in the form of a social network. The approach consists of specializing the adaptive star graph grammar (ASGG) of Drewes et al. (Theor Comput Sci 411:3090–3109, 2010) to express kind of subgraphs that we call \(K_4\)-type tournament graphs, corresponding to COIs, that cannot be generated by the node replacement graph grammar. This approach, called graph grammar and \(K_{4}\)-type tournament-based approach to detect conflicts of interest \((GGK_{4}T-COIs)\), is applied to detect COIs in the review process of papers accepted in an international conference which is represented through a social network. In this contribution, the principle of the used graph grammar is not to consider all the generated language but only subgraphs with some properties (corresponding to special graph queries), which identify parts of the social network representing COIs. For evaluating the performances and the efficiency of our proposition, experimentations have been done by comparing it with concurrent methods in the literature. The obtained results have shown that the approach GG\(K_{4}\)T-COIs performs better than the investigated state-of-the-art approaches in terms of type and number of detected COIs.

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Metadaten
Titel
A graph grammar and -type tournament-based approach to detect conflicts of interest in a social network
verfasst von
Saadia Albane
Hachem Slimani
Hamamache Kheddouci
Publikationsdatum
07.11.2020
Verlag
Springer London
Erschienen in
Knowledge and Information Systems / Ausgabe 2/2021
Print ISSN: 0219-1377
Elektronische ISSN: 0219-3116
DOI
https://doi.org/10.1007/s10115-020-01525-5

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