Self-representative manifold concept factorization with adaptive neighbors for clustering

Sihan Ma, Lefei Zhang, Wenbin Hu, Yipeng Zhang, Jia Wu, Xuelong Li

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

5 Citations (Scopus)

Abstract

Matrix Factorization based methods, e.g., the Concept Factorization (CF) and Nonnegative Matrix Factorization (NMF), have been proved to be efficient and effective for data clustering tasks. In recent years, various graph extensions of CF and NMF have been proposed to explore intrinsic geometrical structure of data for the purpose of better clustering performance. However, many methods build the affinity matrix used in the manifold structure directly based on the input data. Therefore, the clustering results are highly sensitive to the input data. To further improve the clustering performance, we propose a novel manifold concept factorization model with adaptive neighbor structure to learn a better affinity matrix and clustering indicator matrix at the same time. Technically, the proposed model constructs the affinity matrix by assigning the adaptive and optimal neighbors to each point based on the local distance of the learned new representation of the original data with itself as a dictionary. Our experimental results present superior performance over the state-of-the-art alternatives on numerous datasets.
Original languageEnglish
Title of host publicationProceedings of the 27th International Joint Conference on Artificial Intelligence
EditorsJérôme Lang
PublisherInternational Joint Conferences on Artificial Intelligence
Pages2539-2545
Number of pages7
ISBN (Electronic)9780999241127
DOIs
Publication statusPublished - 2018
Event27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence, IJCAI-ECAI 2018 - Stockholm, Sweden
Duration: 13 Jul 201819 Jul 2018

Conference

Conference27th International Joint Conference on Artificial Intelligence and the 23rd European Conference on Artificial Intelligence, IJCAI-ECAI 2018
CountrySweden
CityStockholm
Period13/07/1819/07/18

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