Watersheds on Hypergraphs for Data Clustering Fabio Dias, Moussa Mansour, Paola Valdivia, Jean Cousty, Laurent Najman To cite this version: Fabio Dias, Moussa Mansour, Paola Valdivia, Jean Cousty, Laurent Najman. Watersheds on Hyper- graphs for Data Clustering. ISMM 2017 - 13th International Symposium on Mathematical Morphology and Its Applications to Signal and Image Processing, May 2017, Fontainebleau, France. pp.211-221, 10.1007/978-3-319-57240-6_17. hal-01592155 HAL Id: hal-01592155 https://hal.archives-ouvertes.fr/hal-01592155 Submitted on 22 Sep 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Watersheds on hypergraphs for data clustering Fabio Dias1, Moussa R. Mansour2;3, Paola Valdivia2;4, Jean Cousty5, and Laurent Najman5 1 New York University - Tandon School of Engineering, New York, USA.
[email protected] 2 Instituto de Ci^enciasMatem´aticase de Computa¸c~ao,Universidade de S~aoPaulo, S~aoCarlos, Brazil. 3 Jack's Ventures, Perth, Australia. 4 INRIA, Saclay, France. 5 Universit´eParis-Est, LIGM, Equipe A3SI, ESIEE, France. Abstract. We present a novel extension of watershed cuts to hyper- graphs, allowing the clustering of data represented as an hypergraph, in the context of data sciences.