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 …

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

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

Session-based recommendation uses short interaction sequences of anonymous users to
predict the next item most likely to be clicked, and many methods have been proposed …

With the long-term accumulation of high-quality educational data, artificial intelligence (AI)
has shown excellent performance in knowledge tracing (KT). However, due to the lack of …

The high complexity of graph neural networks (GNNs) on large-scale networks hinders their
industrial application. Graph condensation (GCond) was recently proposed to condense the …

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

Abstract Deep Neural Networks (DNN) based collaborative filtering has been successful in
recommending services by effectively generalizing graph-structured data. However, most …