Clustering-aware Graph Construction: A Joint Learning Perspective

05/04/2019
by   Yuheng Jia, et al.
0

As a promising clustering method, graph-based clustering converts the input data to a graph and regards the clustering as a graph partition problem. However, traditional graph clustering methods usually suffer from two main limitations: i), graph clustering is a feed-forward process, and cannot make use of the information from clustering result, which is more discriminative than the original graph; and ii), once the graph is constructed, the clustering process is no longer related to the input data, which may neglect rich information of raw features. To solve the above defects, we propose to learn the similarity graph adaptively, which compromises the information from the raw features, the initial graph and the clustering result. And thus, the proposed model is naturally cast as a joint model to learn the graph and generate the clustering result simultaneously, which is further efficiently solved with convergence theoretically guaranteed. The advantage of the proposed model is demonstrated by comparing with 19 state of-the-art clustering methods on 10 datasets with 4 clustering metrics.

READ FULL TEXT
research
05/21/2019

Clustering with Similarity Preserving

Graph-based clustering has shown promising performance in many tasks. A ...
research
04/25/2019

Discrete Optimal Graph Clustering

Graph based clustering is one of the major clustering methods. Most of i...
research
09/06/2019

Graph-based data clustering via multiscale community detection

We present a graph-theoretical approach to data clustering, which combin...
research
05/12/2022

Ensemble Clustering via Co-association Matrix Self-enhancement

Ensemble clustering integrates a set of base clustering results to gener...
research
12/17/2018

Robust Graph Learning from Noisy Data

Learning graphs from data automatically has shown encouraging performanc...
research
11/19/2022

Graph Augmentation Clustering Network

Existing graph clustering networks heavily rely on a predefined graph an...
research
05/10/2012

Modularity-Based Clustering for Network-Constrained Trajectories

We present a novel clustering approach for moving object trajectories th...

Please sign up or login with your details

Forgot password? Click here to reset