The ongoing rapid expansion of the Internet greatly increases the necessity of effective
recommender systems for filtering the abundant information. Extensive research for …

Plant traits–the morphological, anatomical, physiological, biochemical and phenological
characteristics of plants and their organs–determine how primary producers respond to …

Cluster or co-cluster analyses are important tools in a variety of scientific areas. The
introduction of this book presents a state of the art of already well-established, as well as …

Due to the serious information overload problem on the Internet, recommender systems
have emerged as an important tool for recommending more useful information to users by …

Probabilistic matrix factorization (PMF) methods have shown great promise in collaborative
filtering. In this paper, we consider several variants and generalizations of PMF framework …

提出一种两阶段评分预测方法. 该方法基于一种新的联合聚类算法(BlockClust)
和加权非负矩阵分解算法. 首先对原始矩阵中的评分模式进行用户和物品两个维度的联合聚类 …

This paper deals with estimation and model selection in the Latent Block Model (LBM) for
categorical data. First, after providing sufficient conditions ensuring the identifiability of this …

A fundamental challenge of bipartite graph representation learning is how to extract
informative node embeddings. Self-Supervised Learning (SSL) is a promising paradigm to …

Multi-task clustering and multi-view clustering have severally found wide applications and
received much attention in recent years. Nevertheless, there are many clustering problems …

Coclustering heterogeneous data has attracted extensive attention recently due to its high
impact on various important applications, such us text mining, image retrieval, and …