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OverviewThis book constitutes the refereed proceedings of the 19th Principle and Practice of Data and Knowledge Acquisition Workshop, PKAW 2023, held in conjunction with the 20th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2023), in November 2023, in Jakarta, Indonesia. The 9 full papers and 2 short papers included in this volume were carefully reviewed and selected from 28 initial submissions. They are organized in the topical section such as machine learning, natural language processing, and intelligent systems. Full Product DetailsAuthor: Shiqing Wu , Wenli Yang , Muhammad Bilal Amin , Byeong-Ho KangPublisher: Springer Verlag, Singapore Imprint: Springer Verlag, Singapore Edition: 1st ed. 2023 Volume: 14317 Weight: 0.248kg ISBN: 9789819978540ISBN 10: 9819978548 Pages: 146 Publication Date: 04 November 2023 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of ContentsPredicting Peak Demand Days for Asthma-Related Emergency Hospitalisations: A Machine Learning Approach.- Discovering Maximal High Utility Co-location Patterns from Spatial Data.- Exploring the Potential of Image Overlay in Self-Supervised Learning: A Study on SimSiam Networks and Strategies for Preventing Model Collapse.- BoCB: Performance Benchmarking by Analysing Impacts of Cloud Platforms on Consortium Blockchain.- Automated Cattle Behavior Classification Using Wearable Sensors and Machine Learning Approach.- LexiFusedNet: A Unified Approach for Imbalanced Short-text Classification using Lexicon-based Feature Extraction, Transfer Learning and One Class Classifiers.- Information Gerrymandering in Elections.- An Assessment of the Influence of Interaction and Recommendation Approaches on the Formation of Information Filter Bubbles.- Blockchain as a Collaborative Technology - Case Studies in the Real EstateSector in Vietnam.- Indonesian Forest Fire Data Clustering using Spatiotemporal Data Using Grid Density-Based Clustering Algorithm.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |