Sustainable Developments of Human-Machine Interaction for Knowledge Discovery and Management

Abstract

Human-machine interaction (HMI) is an important field in knowledge discovery and management, allowing for improved user engagement, decision-making, and efficiency. It involves user-centered design, information architecture, visualization, recommendation systems, collaborative filtering, machine learning, feature extraction, dimensionality reduction, clustering, classification, evaluation, validation, text mining, sentiment analysis, topic modelling, information extraction, opinion mining, and language generation. A case study in the healthcare and agricultural domains demonstrated the practical implementation of HMI in knowledge discovery and highlighted the positive impact of HMI approaches in addressing challenges specific to healthcare knowledge management. In conclusion, HMI plays a pivotal role in knowledge discovery and management, enabling users to effectively explore and extract valuable insights from complex datasets.