Incomplete Multi-view Clustering

Abstract : Real data often consists of multiple views (or representations). By exploiting complementary and consensus grouping information of multiple views, multi-view clustering becomes a successful practice for boosting clustering accuracy in the past decades. Recently, researchers have begun paying attention to the problem of incomplete view. Generally, they assume at least there is one complete view or only focus on two view problems. However, above assumption is often broken in real tasks. In this work, we propose an IVC algorithm for clustering with more than two incomplete views. Compared with existing works, our proposed algorithm (1) does not require any view to be complete, (2) does not limit the number of incomplete views, and (3) can handle similarity data as well as feature data. The proposed algorithm is based on the spectral graph theory and the kernel alignment principle. By aligning projections of individual views with the projection integration of all views, IVC exchanges the complementary grouping information of incomplete views. Consequently, projections of individual views are made complete and thereby resulting the consensus with accurate grouping information. Experiments on synthetic and real datasets demonstrate the effectiveness of IVC.
Type de document :
Communication dans un congrès
9th International Conference on Intelligent Information Processing (IIP), Nov 2016, Melbourne, VIC, Australia. IFIP Advances in Information and Communication Technology, AICT-486, pp.245-255, 2016, Intelligent Information Processing VIII. 〈10.1007/978-3-319-48390-0_25〉
Liste complète des métadonnées

Littérature citée [17 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01614996
Contributeur : Hal Ifip <>
Soumis le : mercredi 11 octobre 2017 - 16:58:05
Dernière modification le : mercredi 11 octobre 2017 - 17:00:29
Document(s) archivé(s) le : vendredi 12 janvier 2018 - 15:31:27

Fichier

 Accès restreint
Fichier visible le : 2019-01-01

Connectez-vous pour demander l'accès au fichier

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Citation

Hang Gao, Yuxing Peng, Songlei Jian. Incomplete Multi-view Clustering. 9th International Conference on Intelligent Information Processing (IIP), Nov 2016, Melbourne, VIC, Australia. IFIP Advances in Information and Communication Technology, AICT-486, pp.245-255, 2016, Intelligent Information Processing VIII. 〈10.1007/978-3-319-48390-0_25〉. 〈hal-01614996〉

Partager

Métriques

Consultations de la notice

39