This book highlights recent research on intelligent systems and nature-inspired computing. It presents 45 selected papers focused on Natural Language Processing from the 23rd International Conference on Intelligent Systems Design and Applications (ISDA 2023), which was held in 5 different cities namely Olten, Switzerland; Porto, Portugal; Kaunas, Lithuania; Greater Noida, India; Kochi, India, and in online mode. The ISDA is a premier conference in the field of artificial intelligence, and the latest installment brought together researchers, engineers, and practitioners whose work involves intelligent systems and their applications in industry. ISDA 2023 had contributions by authors from 64 countries. This book offers a valuable reference guide for all specialists, scientists, academicians, researchers, students, and practitioners in the field of artificial intelligence and Natural Language Processing.
Inhaltsverzeichnis
Automatic Textual Normalization for Hate Speech Detection.- SOTW Semantics Oriented Tagging of Web Pages.- Crowdsourcing Applications in Smart Cities.- Evaluation of Vendor Analysis using AHP At TUV Manufacturing Company.- TESA Tagging of Educational Videos Using Semantics Oriented Artificial Intelligence.- SISRR Semantically Inclined Strategic Learning Model for Software Requirement Recommendation Using Artificial Intelligence.- Isolated Word Recognition based on Power Normalized Cepstrum and Machine Learning Clusters.- A Core Domain Ontology for Specifying the Business View of Enterprise Information Systems.- Datadriven Exploration of Pandemics Psychological Impact and Lifestyle Changes through Clustering Approach.- Explainable Artificial Intelligence for Analytical Customer Relationship Management in Banking and Finance.- Artificial Intelligence based Chatbots is Killing Creative Minds An Effective Discussion on Modern Education.- SIGAN Self Inhibited Graph Attention Network for Text Classification.- Unfolding the Misinformation spread An In Depth Analysis through Explainable Link Predictions and Data Mining.- Schematic review of sentiment analysis techniques.- How can Credit Scoring benefit from Machine Learning SWOT Analysis.
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