This paper provides a comprehensive overview of user modeling and profiling, essential techniques in information retrieval and recommender systems for delivering personalized experiences. It traces the development from early stereotype…
Continue readingThe paper introduces LLMRS, a recommender system based on Large Language Models (LLM), aimed at improving software purchase suggestions. Traditional recommender systems, while prevalent, often fail to accurately capture user…
Continue readingThe article discusses a survey conducted to understand user expectations and preferences for AI conversational agents that can perceive, respond to, and simulate emotions. It was found that users preferred…
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