


To provide personalized recommendations, we extract user's current fine-grained intentions from dialogue context with the guidance of user's inherent preferences.
STRUGGLE SESSION DOUBAN GENERATOR
For human-like dialogue services, we propose multi-style dialogue response generator which selects context-aware speaking style for utterance generation. Based on the observations, we propose a novel CRS model, coined Customized Conversational Recommender System (CCRS), which customizes CRS model for users from three perspectives. (2) Identifying fine-grained intentions, even for the same utterance, different users have diverse finegrained intentions, which are related to users' inherent preference. In this paper, we propose two key points for CRS to improve the user experience: (1) Speaking like a human, human can speak with different styles according to the current dialogue context. However, most CRS methods neglect the importance of user experience. As a human-machine interactive system, it is essential for CRS to improve the user experience. In this paper, we review existing approaches to building such systems, which developments we observe today, which challenges are still open and why the development of conversational recommenders represents one of the next grand challenges of AI.Ĭonversational recommender systems (CRS) aim to capture user's current intentions and provide recommendations through real-time multi-turn conversational interactions.

Conversational recommender systems (CRS) promise to address these limitations. They do not engage in a conversation to find out what we might prefer, they often do not provide explanations for what they recommend, and they may have difficulties remembering what was said 1 min earlier. However, when asked for recommendations, for example, for a restaurant to go to, the limitations of such devices quickly become obvious. Today, we talk more and more to machines like Apple's Siri, for example, to ask them for the weather forecast. Through many sci‐fi movies, we are acquainted with the idea of speaking to such virtual personalities as if they were humans. Animated avatars, which look and talk like humans, are iconic visions of the future of AI‐powered systems.
