This three-volume set LNAI 15708-15709-15110 constitutes the proceedings of the International Joint Conference on Rough Sets, IJCRS 2025, held in Chongqing, China, during May 11-13, 2025.
The 90 full papers included in these volumes were carefully reviewed and selected from 187 submissions. They are organized in topical sections as follows:
Part I: Rough Set Models and Foundations; Fuzzy Rough Sets and Rough Fuzzy Sets; and Granular Computing.
Part II: Rough Set Applications; Feature Selection and Knowledge Discovery; and Cognitive Computing.
Part III: Three-way Data Analytics and Decision; Medicine and Health Data Mining; and Applications of Deep Learning and Soft Computing.

.- Rough Set Applications. .- Comparison of Complexity of Regular and Oblivious Decision Trees for Decision Tables from Closed Classes. .- Applying Rough Set based Feature Selection Method to Spam Classification. .- What Is Inside Agent Brain: Application of Learning from Examples Using Rough Sets (LEM2) Rule Induction Algorithm to Explain Actions of Vision based Machine Learning Agents Trained with Proximal Policy Optimization. .- Quick Neighborhood Rough Set for Hierarchical Classification. .- (θ¿θ*) Operator Driven Intuitionistic Fuzzy Matrix Composite Operation and Its Optimal Application in Medical Diagnosis. .- User and Item sub contexts Induced Fuzzy Concept Set for Recommendation. .- Rough Set Theory Applied to Feature Selection. .- Fusing Land Use Knowledge with Multi granularity Temporal and Spatial Dependencies for Traffic Accident Prediction. .- A Hybrid Multi attribute Group Decision making Method Using Normal Cloud Model and Multi granularity Information. .- Anomaly Detection Using Fuzzy Information Entropy for Incomplete Data. .- Feature Selection and Knowledge Discovery. .- Feature Selection Based on Cross Neighborhood Granular Ball Layer. .- A Dynamic Unsupervised Feature Selection Method Based on Information Sets and Fuzzy Rough Sets. .- Distance guided Pseudo Label Graph Clustering Network. .- Robust Feature Selection Based on Intuitionistic Hesitant Fuzzy Cross Correlation and Manifold Learning. .- Adaptive Correlation Incorporated Latent Feature Analysis for Online Sparse Streaming Feature Selection. .- Accelerated Feature Selection Based on Granular ball Rough Sets. .- Online Multi label Stream Feature Selection Based on Neighborhood Approximation Error Rate and Label Correlation. .- Cross view Fuzziness and Intra view Uncertainty based Weight Reconstruction for Multi view Feature Selection. .- Finding Consistent Pairwise Comparisons with Genetic Algorithms. .- Multi view Unsupervised Feature Selection Guided by Diversity and Consensus Structure. .- Cognitive Computing. .- Legal Similar Case Retrieval Model Based on Concept Tree and Optimal Transport. .- Enhancing Knowledge Tracing via Random Layer wise Adversarial Training. .- Incomplete Multi view Clustering Based on Joint Concept Decomposition and Anchor Graph Learning. .- Frequency sensitive Sparse Transformer with Multi Granularity Refinement Network for Image Restoration. .- TSKE: A Dual Branch Model for Knowledge Graph Embedding with Joint Textual and Structural Information. .- Efficient Local Causal Structure Learning with Privacy Preservation. .- The Connections Between Approximate Three way Concept Lattice and Three way Approximate Concept Lattices. .- Concept Oriented Attribute Reduction in Three way Concept Analysis. .- Deterministic and Nondeterministic Decision Trees for Recognition of Properties of Decision Rule Systems. .- Concept Reduction Method Based on Attribute (Object) Reduction.