Recent advances in deep learning based dialogue systems: A systematic survey
Dialogue systems are a popular natural language processing (NLP) task as it is promising in
real-life applications. It is also a complicated task since many NLP tasks deserving study are …
real-life applications. It is also a complicated task since many NLP tasks deserving study are …
[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 …
KuaiRec: A fully-observed dataset and insights for evaluating recommender systems
The progress of recommender systems is hampered mainly by evaluation as it requires real-
time interactions between humans and systems, which is too laborious and expensive. This …
time interactions between humans and systems, which is too laborious and expensive. This …
Towards topic-guided conversational recommender system
User-centric conversational recommendation with multi-aspect user modeling
Conversational recommender systems (CRS) aim to provide highquality recommendations
in conversations. However, most conventional CRS models mainly focus on the dialogue …
in conversations. However, most conventional CRS models mainly focus on the dialogue …