Knowledge Management and Acquisition for Intelligent Systems
Description
This book constitutes the proceedings of the 17th International Workshop on Knowledge Management and Acquisition for Intelligent Systems, PKAW 2020, held in Yokohama, Japan, in January 2021.
The 10 full papers and 5 short papers included in this volume were carefully reviewed and selected from 28 initial submissions. PKAW primarily focuses on the multidisciplinary approach of the human-driven and data-driven knowledge acquisition, which is the key concept that has remained unchanged since the workshop has been established.
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Accelerating the Backpropagation algorithm by Using the NMF-based method on Deep Neural Networks.- Collaborative Data Analysis: Non-Model Sharing-Type Machine Learning for Distributed Data.- ERA: Extracting planning macro-operators from adjacent and non-adjacent sequences.- Deep Neural Network Incorporating CNN and MF for Item-based Fashion Recommendation.- C-LIME: A Consistency-oriented LIME for Time-series Health-Risk Predictions.- Discriminant Knowledge Extraction from Electrocardiograms for Automated Diagnosis of Myocardial Infarction.- Stabilizing the Predictive Performance for Ear Emergence in Rice Crops across Cropping Regions.- Description Framework for Stakeholder-Centric Value Chain of Data to Understand Data Exchange Ecosystem.- Attributed Heterogeneous Network Embedding for Link Prediction.- Automatic Generation and Classification of Malicious FQDN.- Analyzing Temporal Change in LoRa Communication Quality Using Massive Measurement Data.- Challenge Closed-Book Science Exam: A Meta-Learning Based Question Answering System.- Identification of B2B Brand Components and their Performance's Relevance Using a Business Card Exchange Network.- Semi-Automatic Construction of Sight Words Dictionary for Filipino Text Readability.- Automated Concern Exploration in Pandemic Situations - COVID-19 as a Use Case.