Del 14481 i serien Lecture Notes in Computer Science

Rough Sets

International Joint Conference, IJCRS 2023, Krakow, Poland, October 5–8, 2023, Proceedings

Häftad, Engelska, 2023

AvAndrea Campagner,Oliver Urs Lenz,Shuyin Xia,Dominik Ślęzak,Jarosław Wąs,JingTao Yao

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This book constitutes the refereed proceedings of the International Joint Conference on Rough Sets, IJCRS 2023, held in Krakow, Poland, during October 5–8, 2023. The 43 full papers included in this book were carefully reviewed and selected from 83 submissions.

Produktinformation

Utgivningsdatum2023-12-31
Mått155 x 235 x 38 mm
Vikt1 048 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor644
FörlagSpringer International Publishing AG
ISBN9783031509582

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Rough Set Models.- Selected approaches to conflict analysis inspired by the Pawlak model - case study.- Multi-heuristic Induction of Decision Rules.- Algebraic formulations and geometric interpretations of decision-theoretic rough sets.- Reduction of binary attributes: rough set theory versus formal concept analysis.- An Acceleration Method for Attribute Reduction Based on Attribute Synthesis.- Attribute Reduction Based on the Multi-annulus Model.- Foundations.- Deterministic and Nondeterministic Decision Trees for Decision Tables with Many-valued Decisions from Closed Classes.- Paraconsistent Logics: A Survey Focussing on the Rough Set Approach.- Hexagons of Opposition in Linguistic Three-Way Decisions.- Algebraic Models for Qualified Aggregation in General Rough Sets, and Reasoning Bias Discovery.- Two-sorted Modal Logic for Formal and Rough Concepts.- Kryszkiewicz's Relation for Indiscernibility of Objects in Data Tables Containing Missing Values.- Algebraic, Topological, and Mereological Foundations of Existential Granules.- Aggregation Operators on Shadowed Sets Deriving from Conditional Events and Consensus Operators.- Pawlak, Belnap and the magical number seven.- Three-way Decisions.- Three-way conflict analysis for three-valued situation tables with rankings and reference tuples.- Three-way social network analysis: Triadic measures at three levels.- Cognitive and Social Decision Making: Three-way Decision Perspectives.- New models of three-way conflict analysis for incomplete situation tables.- Granular-ball Three-way Decision- Granular Models.- Unsupervised KeyPhrase Extraction Based on Multi-granular Semantics Feature Fusion.- Multi-Granularity Feature Fusion for Transformer-based Single Object Tracking.- A Multi-Granularity Network for Time Series Forecasting on Multivariate Time Series Data.- Adaptive Multi-Granularity Aggregation Transformer for Image Captioning.- A Causal Disentangled Multi-Granularity Graph Classification Method.- Distances and Similarities.- Towards ML Explainability with Rough Sets, Clustering, and Dimensionality Reduction.- Decision rule clustering - Comparison of the algorithms.- Classifying token frequencies using angular Minkowski $p$-distance.- On kNN class weights for optimising G-mean and F1-score.- Searching of potentially anomalous signals in cosmic-ray particle tracks images using rough k-means clustering combined with eigendecomposition-derived embedding.- Hybrid Approaches.- Crisp-Fuzzy Concept Lattice Based on Interval-Valued Fuzzy Sets.- Normal fuzzy three-way decision based on prospect theory.- On Several New Dempster-Shafer-inspired Uncertainty Measures Applicable for Active Learning.- Rough Fuzzy Concept Analysis via Multilattice.- Applications.- Clustering methods for adaptive e-commerce user interfaces.- Application of federated learning to prediction of patient mortality in vasculitis disease.- A Novel Hybrid Wind Speed Interval Prediction Model using Rough Stacked Autoencoder and LSTM.- Navigational Strategies for Mobile Robots Using Rough Mereological Potential Fields and Weighted Distance to Goal.- Handling intra-class dissimilarity and inter-class similarity for imbalanced skin lesion image classification.- Link Prediction for Attribute and Structure Learning Based on Attention Mechanism.- Cybersecurity and IoT.- A New Data Model for Behavioral Based Anomaly Detection in IoT Device Monitoring.- Preventing Text Data Poisoning Attacks in Federated Machine Learning by an Encrypted Verification Key.- Improving Detection Efficiency: Optimizing Block Size in the Local Outlier Factor (LOF) Algorithm.