Granular Emotion Detection in Social Media Using Multi-Discipline Ensembles
Robert H. Frye and David C. Wilson
Sentiment Polarity and Emotion Detection from Tweets Using Distant Supervision and Deep Learning Models
Muhamet Kastrati, Marenglen Biba, Ali Shariq Imran and Zenun Kastrati
Disruptive Event Identification in Online Social Network
Aditi Seetha, Satyendra Singh Chouhan, Sanskar Soni, Dev Milan Mehta and Vinush Vishwanath
Modeling Polarization on Social Media Posts: A Heuristic Approach Using Media Bias
Sadia Kamal, Jade Gullic and Arunkumar Bagavathi
Sarcasm detection in Tunisian social media comments: Case of COVID-19
Asma Mekki, Inès Zribi, Mariem Ellouze and Lamia Hadrich Belguith
Multimodal Deep Learning and Fast Retrieval for Recommendation
Luigi Portinale and Daniele Ciarlo
Mining news articles dealing with Food Security
Hugo Deléglise, Agnès Bégué, Roberto Interdonato, Elodie Maître d’Hôtel, Mathieu Roche and Maguelonne Teisseire
Identification of Paragraph Regularities in Legal Judgements through Clustering and Textual Embedding
Graziella De Martino and Gianvito Pio
Aspect term extraction improvement based on a hybrid method
Sarsabene Hammi, Souha Mezghani Hammami and Lamia Hadrich Belguith
Exploring the Impact of Gender Bias Mitigation Approaches on a Downstream Classification Task
Nasim Sobhani and Sarah Jane Delany
A semi-automatic data generator for Query Answering
Fabrizio Angiulli, Alessandra Del Prete, Fabio Fassetti and Simona Nisticò
XAI to explore robustness of features in adversarial training for cybersecurity
Malik Al-Essa, Giuseppina Andresini, Annalisa Appice and Donato Malerba
Impact of Feedback Type on Explanatory Interactive Learning
Misgina Tsighe Hagos, Kathleen M. Curran and Brian Mac Namee
Learning and Explanation of Extreme Multi-Label Deep Classification Models for Media Content
Marco Minici, Francesco Sergio Pisani, Massimo Guarascio, Erika De Francesco and Pasquale Lambardi
An Interpretable Machine Learning Approach to Prioritizing Factors Contributing to Clinician Burnout
Malvika Pillai, Karthik Adapa, Meagan Foster, Ian Kratzke, Nadia Charguia and Lukasz Mazur
A general-purpose method for applying Explainable AI for Anomaly Detection
John Sipple and Abdou Youssef
More Sanity Checks for Saliency Maps
Lars Holmberg, Carl Johan Helgstrand and Niklas Hultin
Deep Reinforcement Learning for Automated Stock Trading: Inclusion of Short Selling
Eeshaan Asodekar, Arpan Nookala, Sayali Ayre and Anant Nimkar
Scaling Posterior Distributions over Differently-Curated Datasets: A Bayesian-Neural-Networks Methodology
Alfredo Cuzzocrea, Selim Soufargi, Alessandro Baldo and Edoardo Fadda
Ensembling Sparse Autoencoders for Network Covert Channel Detection in IoT Ecosystems
Nunziato Cassavia, Luca Caviglione, Massimo Guarascio, Angelica Liguori and Marco Zuppelli
Towards Automation of Pollen Monitoring: Image-Based Tree Pollen Recognition
Elzbieta Kubera, Agnieszka Kubik-Komar, Alicja Wieczorkowska, Krystyna Piotrowska-Weryszko, Paweł Kurasiński and Agata Konarska
Rough Sets for Intelligence on Embedded Systems
Katrina Nesterenko and Rory Lewis
Context as a Distance Function in ConSQL
Hasan Jamil
Detecting Anomalies with LatentOut: Novel Scores, Architectures, and Settings
Fabrizio Angiulli, Fabio Fassetti and Luca Ferragina
Richness Fallacy
Mieczysław Kłopotek and Robert Kłopotek
Adapting loss functions to learning progress improves accuracy of classification in neural networks
Andreas Knoblauch
Multiscale and multivariate time series clustering: A new approach
Jannai Tokotoko, Rodrigue Govan, Hugues Lemonnier and Nazha Selmaoui-Folcher
Improve Calibration Robustness of Temperature Scaling by Penalizing Output Entropy
Jun Zhang, Wen Yao, Xiaoqian Chen and Ling Feng
Understanding Negative Calibration from Entropy Perspective
Jun Zhang, Wen Yao, Xiaoqian Chen and Ling Feng
A New Clustering Preserving Transformation for k-Means Algorithm Output
Mieczysław Kłopotek
A Transformer-Based Framework for Geomagnetic Activity Prediction
Yasser Abduallah, Jason T. L. Wang, Chunhui Xu and Haimin Wang
AS-SIM: an approach to Action-State Process Model Discovery
Alessio Bottrighi, Marco Guazzone, Giorgio Leonardi, Stefania Montani, Manuel Striani and Paolo Terenziani
Combining Active Learning and Fast DNN Ensembles for Process Deviance Discovery
Francesco Folino, Gianluigi Folino, Massimo Guarascio and Luigi Pontieri
Temporal Graph-based CNNs (TG-CNNs) for Online Course Dropout Prediction
Zoe Hancox and Samuel Relton
Graph Convolutional Networks Using Node Addition and Edge Reweighting
Wen-Yu Lee
Audio Super-Resolution via Vision Transformer
Simona Nisticò, Luigi Palopoli and Adele Pia Romano
Similarity embedded temporal Transformers: Enhancing stock predictions with historically similar trends
Kenniy Olorunnimbe and Herna Viktor
Investigating noise interference on speech towards applying the Lombard effect automatically
Grazina Korvel, Krzysztof Kąkol, Povilas Treigys and Bożena Kostek
Towards Polynomial Adaptive Local Explanations for Healthcare Classifiers
Jamie Duell, Xiuyi Fan and Monika Seisenberger
Towards Tailored Intervention in Medicine Using Patients’ Segmentation
Petr Berka, Maciej Pondel, David Chudán and Agnieszka Siennicka
Application of association rules to classify IBD patients
Agnieszka Dardzinska and Anna Kasperczuk
Unsupervised Learning Based Rule Generating System with Temporal Features Extractions Tuned for Tinnitus Retraining Therapy
Xin Zhang, Xinyan Shi and Pamela Thompson
TrueDetective 4.0: a Big data architecture for real time anomaly detection
Luciano Argento, Erika De Francesco, Pasquale Lambardi, Paolo Piantedosi and Carlo Romeo
Optimising the Machine Translation Workflow: Analysis, Development, Benchmarking, Testing and Maintenance
Nicola Poeta, Enrico Giai and David Turnbull
Classification vs Recommendation methods for Therapeutics Recommendation
Seda Polat Erdeniz, Michael Schrempf, Diether Kramer and Alexander Felfernig
Document Layout Analysis with Variational Autoencoders : an Industrial Application
Gabriele Valvano, Giacomo Veneri and Ali Youssef