Foundations of Intelligent Systems [electronic resource] : 25th International Symposium, ISMIS 2020, Graz, Austria, September 23–25, 2020, Proceedings /

Invited Talks -- Complementing Behavioural Modeling with Cognitive Modeling for Better Recommendations -- Nominees for Best Paper Award -- The Construction of Action Rules to Raise Artwork Prices -- Metric-Guided Multi-Task Learning -- Sentiment Analysis with Contextual Embeddings and Self-Attention -- Nominees for Best Student Paper Award -- Interpretable Segmentation of Medical Free-Text Records Based on Word Embeddings -- Decision-Making with Probabilistic Reasoning in Engineering Design -- Hyperbolic embeddings for hierarchical multi-label classification -- Natural Language Processing -- Joint Multiclass Debiasing of Word Embeddings -- Recursive Neural Text Classification using Discourse Tree Structure for Argumentation Mining and Sentiment Analysis Tasks -- Named Entity Recommendations to Enhance Multilingual Retrieval in Europeana.eu -- A Deep Learning Approach to Fake News Detection -- Satirical News Detection with Semantic Feature Extraction and Game-theoretic Rough Sets -- Deep Learning and Embeddings -- Comparing state-of-the-art neural network ensemble methods in soccer predictions -- Static Music Emotion Recognition Using Recurrent Neural Networks -- Saliency detection in hyperspectral images using autoencoder-based data reconstruction -- Mesoscale Anisotropically-Connected Learning -- Empirical Comparison of Graph Embeddings for Trust-Based Collaborative Filtering -- Neural spike sorting using unsupervised adversarial learning -- Digital Signal Processing -- Poriferal Vision: Classifying benthic sponge spicules to assess historical impacts of marine climate change -- Experimental Evaluation of GAN-Based One-Class Anomaly Detection on Office Monitoring -- Ranking Speech Features for their Usage in Singing Classification -- Leveraging Machine Learning in IoT to predict the trustworthiness of Mobile Crowd Sensing data -- A Hierarchical-Based Web-Platform for Crowdsourcing Distinguishable Image Patches -- Performing Arithmetic Using a Neural Network Trained on Digit Permutation Pairs -- Modelling and Reasoning -- CatIO - Framework for Model Based Diagnosis of Cyber-Physical Systems -- Data Publishing: Availibility of data under Security Policies – Preliminary work -- Matrix Factorization based Heuristics Learning for Solving Constraint Satisfaction Problems -- Explaining object motion using answer set programming -- The GraphBRAIN System for Knowledge Graph Management and Advanced Fruition -- Mining Exceptional Mediation Models -- Machine Learning Applications -- Multivariate predictive clustering trees for classification -- Comparison of Machine Learning Methods to Detect Anomalies in the Activity of Dairy Cows -- Clustering Algorithm Consistency in Fixed Dimensional Spaces -- Estimating the Importance of Relational Features by using Gradient Boosting -- Multi-objective Discrete Moth-Flame Optimization for Complex Network Clustering -- Predicting associations between proteins and multiple diseases -- Short Papers -- Exploiting Answer Set Programming for Building Explainable Recommendations -- Tailoring Random Forest for Requirements Classification -- On the Design of a Natural Logic System for Knowledge Bases -- Evaluation of post-hoc XAI approaches through synthetic tabular data -- SimLoss: Class Similarities in Cross Entropy -- Efficient and Precise Classification of CT Scannings of Renal Tumors using Convolutional Neural Networks -- Deep Autoencoder Ensembles for Anomaly Detection on Blockchain -- A Parallelized Variant of Junker’s QUICKXPLAIN Algorithm.

This book constitutes the proceedings of the 25th International Symposium on Foundations of Intelligent Systems, ISMIS 2020, held in Graz, Austria, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 35 full and 8 short papers presented in this volume were carefully reviewed and selected from 79 submissions. Included is also one invited talk. The papers deal with topics such as natural language processing; deep learning and embeddings; digital signal processing; modelling and reasoning; and machine learning applications.