Multi-view clustering (MVC) has attracted more and more attention in the recent few years by
making full use of complementary and consensus information between multiple views to …

In the big data era, the data are generated from different sources or observed from different
views. These data are referred to as multi-view data. Unleashing the power of knowledge in …

Most existing graph-based clustering methods need a predefined graph and their clustering
performance highly depends on the quality of the graph. Aiming to improve the multiview …

This paper studies clustering of multi-view data, known as multi-view clustering. Among
existing multi-view clustering methods, one representative category of methods is the graph …

Previous multi-view spectral clustering methods are a two-step strategy, which first learns a
fixed common representation (or common affinity matrix) of all the views from original data …

Real data are often with multiple modalities or from multiple heterogeneous sources, thus
forming so-called multi-view data, which receives more and more attentions in machine …

Although numerous multi-view spectral clustering algorithms have been developed, most of
them generally encounter the following two deficiencies. First, high time cost. Second …

Visual text analytics has recently emerged as one of the most prominent topics in both
academic research and the commercial world. To provide an overview of the relevant …

Graph-based multi-view clustering aiming to obtain a partition of data across multiple views,
has received considerable attention in recent years. Although great efforts have been made …

Multi-view data can represent objects from different perspectives and thus provide
complementary information for data analysis. A topic of great importance in multi-view …