When large language models meet personalization: Perspectives of challenges and opportunities
The advent of large language models marks a revolutionary breakthrough in artificial
intelligence. With the unprecedented scale of training and model parameters, the capability …
intelligence. With the unprecedented scale of training and model parameters, the capability …
A survey of graph neural networks for recommender systems: Challenges, methods, and directions
Recommender system is one of the most important information services on today's Internet.
Recently, graph neural networks have become the new state-of-the-art approach to …
Recently, graph neural networks have become the new state-of-the-art approach to …
Reinforcement learning based recommender systems: A survey
Recommender systems (RSs) have become an inseparable part of our everyday lives. They
help us find our favorite items to purchase, our friends on social networks, and our favorite …
help us find our favorite items to purchase, our friends on social networks, and our favorite …
Learning intents behind interactions with knowledge graph for recommendation
Knowledge graph (KG) plays an increasingly important role in recommender systems. A
recent technical trend is to develop end-to-end models founded on graph neural networks …
recent technical trend is to develop end-to-end models founded on graph neural networks …
Large language models as zero-shot conversational recommenders
In this paper, we present empirical studies on conversational recommendation tasks using
representative large language models in a zero-shot setting with three primary …
representative large language models in a zero-shot setting with three primary …
A survey on accuracy-oriented neural recommendation: From collaborative filtering to information-rich recommendation
Influenced by the great success of deep learning in computer vision and language
understanding, research in recommendation has shifted to inventing new recommender …
understanding, research in recommendation has shifted to inventing new recommender …
Conversational information seeking
Conversational information seeking (CIS) is concerned with a sequence of interactions
between one or more users and an information system. Interactions in CIS are primarily …
between one or more users and an information system. Interactions in CIS are primarily …
[HTML][HTML] Advances and challenges in conversational recommender systems: A survey
Recommender systems exploit interaction history to estimate user preference, having been
heavily used in a wide range of industry applications. However, static recommendation …
heavily used in a wide range of industry applications. However, static recommendation …
Secure artificial intelligence of things for implicit group recommendations
The emergence of Artificial Intelligence of Things (AIoT) has provided novel insights for
many social computing applications, such as group recommender systems. As the distances …
many social computing applications, such as group recommender systems. As the distances …
Leveraging large language models in conversational recommender systems
L Friedman, S Ahuja, D Allen, Z Tan… - arXiv preprint arXiv …, 2023 - arxiv.org
A Conversational Recommender System (CRS) offers increased transparency and control to
users by enabling them to engage with the system through a real-time multi-turn dialogue …
users by enabling them to engage with the system through a real-time multi-turn dialogue …