Academic Journal
Median evidential c-means algorithm and its application to community detection
| العنوان: | Median evidential c-means algorithm and its application to community detection |
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| المؤلفون: | Zhou, Kuang, Martin, Arnaud, Pan, Quan, Liu, Zhun-Ga |
| المساهمون: | School of Automation, Northwestern Polytechnical University Xi'an (NPU), Declarative & Reliable management of Uncertain, user-generated Interlinked Data (DRUID), GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Télécom Bretagne-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS) |
| المصدر: | ISSN: 0950-7051. |
| بيانات النشر: | HAL CCSD Elsevier |
| سنة النشر: | 2015 |
| المجموعة: | Université de Rennes 1: Publications scientifiques (HAL) |
| مصطلحات موضوعية: | Median clustering, Belief function theory, Community detection, Imprecise communities, Credal partition, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI] |
| الوصف: | International audience ; Median clustering is of great value for partitioning relational data. In this paper, a new prototype-based clustering method, called Median Evidential C-Means (MECM), which is an extension of median c-means and median fuzzy c-means on the theoretical framework of belief functions is proposed. The median variant relaxes the restriction of a metric space embedding for the objects but constrains the prototypes to be in the original data set. Due to these properties, MECM could be applied to graph clustering problems. A community detection scheme for social networks based on MECM is investigated and the obtained credal partitions of graphs, which are more refined than crisp and fuzzy ones, enable us to have a better understanding of the graph structures. An initial prototype-selection scheme based on evidential semi-centrality is presented to avoid local premature convergence and an evidential modularity function is defined to choose the optimal number of communities. Finally, experiments in synthetic and real data sets illustrate the performance of MECM and show its difference to other methods. |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| Relation: | info:eu-repo/semantics/altIdentifier/arxiv/1501.01460; hal-01100902; https://hal.science/hal-01100902; https://hal.science/hal-01100902/document; https://hal.science/hal-01100902/file/median_ecm_1104.pdf; ARXIV: 1501.01460 |
| DOI: | 10.1016/j.knosys.2014.11.010 |
| الاتاحة: | https://hal.science/hal-01100902 https://hal.science/hal-01100902/document https://hal.science/hal-01100902/file/median_ecm_1104.pdf https://doi.org/10.1016/j.knosys.2014.11.010 |
| Rights: | info:eu-repo/semantics/OpenAccess |
| رقم الانضمام: | edsbas.92ED15D1 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1016/j.knosys.2014.11.010 |
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