Subjective Knowledge

Subjective knowledge, encompassing human perceptions, opinions, and preferences, is a growing area of research focusing on how to model, quantify, and utilize this inherently variable information in various applications. Current research employs diverse approaches, including transformer-based models, hybrid systems combining symbolic and neural methods, and multitask learning frameworks, to address challenges like subjectivity in image and text analysis, model selection, and human-computer interaction. This field is significant because effectively incorporating subjective knowledge is crucial for improving the accuracy and relevance of AI systems across domains, from recommender systems and sentiment analysis to political news understanding and fairness in computer vision.