Multi-view Spectral Clustering via Integrating Label and Data Graph Learning

Sally El Hajjar, Fadi Dornaika, Fahed Abdallah, Hichem Omrani

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Nowadays, one-step multi-view clustering algorithms attract many interests. The main issue of multi-view clustering approaches is how to combine the information extracted from the available views. A popular approach is to use view-based graphs and/or a consensus graph to describe the different views. We introduce a novel one-step graph-based multi-view clustering approach in this study. Our suggested method, in contrast to existing graph-based one-step clustering methods, provides two major novelties to the method called Nonnegative Embedding and Spectral Embedding (NESE) proposed in the recent paper [1]. To begin, we use the cluster label correlation to create an additional graph in addition to the graphs associated with the data space. Second, the cluster-label matrix is constrained by adopting some restrictions to make it more consistent. The effectiveness of the proposed method is demonstrated by experimental results on many public datasets.

Original languageEnglish
Title of host publicationImage Analysis and Processing – ICIAP 2022 - 21st International Conference, 2022, Proceedings
EditorsStan Sclaroff, Cosimo Distante, Marco Leo, Giovanni M. Farinella, Federico Tombari
PublisherSpringer Science and Business Media Deutschland GmbH
Pages109-120
Number of pages12
ISBN (Print)9783031064326
DOIs
Publication statusPublished - 2022
Event21st International Conference on Image Analysis and Processing, ICIAP 2022 - Lecce, Italy
Duration: 23 May 202227 May 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13233 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference21st International Conference on Image Analysis and Processing, ICIAP 2022
Country/TerritoryItaly
CityLecce
Period23/05/2227/05/22

Keywords

  • Cluster label space
  • Graph construction
  • Multi-view clustering
  • Similarity graph
  • Spectral projection matrix

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