The current development in deep learning is witnessing an exponential transition into
automation applications. This automation transition can provide a promising framework for …

Educational Data Mining (EDM) has emerged as a vital field of research, which harnesses
the power of computational techniques to analyze educational data. With the increasing …

Graph-based multi-view clustering, with its ability to mine potential associations between
data samples, has attracted extensive attention. However, existing methods directly learn …

Traditional knowledge graph embedding (KGE) aims to map entities and relations into
continuous space vectors to provide high-quality data feature representation for downstream …

Modern online education has the capacity to provide intelligent educational services by
automatically analyzing substantial amounts of student behavioral data. Knowledge Tracing …

Abstract Concept map provides a concise structured representation of knowledge in the
educational scenario. It consists of various concepts connected by prerequisite …

Recent status-of-the-art methods for multivariate time series forecasting can be categorized
into graph-based approach and global-local approach. The former approach uses graphs to …

Accurate user modeling is crucial for point-of-interest (POI) recommendation as it can
significantly improve user satisfaction with recommended POIs and enrich user experience …

Self-supervised graph-level representation learning aims to learn discriminative
representations for subgraphs or entire graphs without human-curated labels. Recently …

Real-life objects typically contain complex structures, and the graph is a prevalent
presentation for describing such objects. Multi-graph multi-label (MGML) learning is a …