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Foundations of Intelligent Systems: 26th International Symposium, ISMIS 2022, Cosenza, Italy, October 35, 2022, Proceedings [Paperback]

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  • Category: Books (Computers)
  • ISBN-10:  3031165632
  • ISBN-10:  3031165632
  • ISBN-13:  9783031165634
  • ISBN-13:  9783031165634
  • Publisher:  Springer
  • Publisher:  Springer
  • Binding:  Paperback
  • Binding:  Paperback
  • Pub Date:  01-Jun-2022
  • Pub Date:  01-Jun-2022
  • SKU:  3031165632-11-SPRI
  • SKU:  3031165632-11-SPRI
  • Pages:  488
  • Pages:  488
  • Item ID: 105253381
  • List Price: $54.99
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This book constitutes the proceedings of the 26th International Symposium on Foundations of Intelligent Systems, ISMIS 2022, held in Cosenza, Italy, in October 2022. 

The 31 regular papers, 11 short papers and 4 industrial papers presented in this volume were carefully reviewed and selected from 71 submissions. They were organized in topical sections as follows: Social Media and Recommendation; Natural Language Processing; Explainability; Intelligent Systems; Classification and Clustering; Complex Data; Medical Applications; Industrial Applications. 


Social Media and Recommendation.- Granular Emotion Detection in Social Media Using Multi-Discipline
Ensembles.- Sentiment Polarity and Emotion Detection from Tweets Using Distant Supervision and Deep Learning Models.- Disruptive Event Identification in Online Social Network.- Modeling Polarization on Social Media Posts: A Heuristic Approach Using Media Bias.- Sarcasm detection in Tunisian social media comments: Case of COVID-19.- Multimodal Deep Learning and Fast Retrieval for Recommendation.- Natural Language Processing.- Mining news articles dealing with Food Security.- Identification of Paragraph Regularities in Legal Judgements through Clustering and Textual Embedding.- Aspect term extraction improvement based on a hybrid method.- Exploring the Impact of Gender Bias Mitigation Approaches on a Downstream Classification Task.- A semi-automatic data generator for Query Answering.- Explainability,.- XAI to explore robustness of features in adversarial training for cybersecurity.- Impact of Feedback Type on Explanatory Interactive Learning.- LearlC¯