Recommender systems help people find relevant content in a personalized way. One main
promise of such systems is that they are able to increase the visibility of items in the long tail …

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 …

The growing use of Recommender Systems (RS) across various industries, including e-
commerce, social media, news, travel, and tourism, has prompted researchers to examine …

Conversational recommender systems (CRS) promise to provide a more natural user
experience for exploring and discovering items of interest through ongoing conversation …

Recommender Systems (RSs) are used to provide users with personalized item
recommendations and help them overcome the problem of information overload. Currently …

Conversational Recommendation System (CRS) is a rapidly growing research area that has
gained significant attention alongside advancements in language modelling techniques …

In a recommender system, a user's interaction is often biased by the items' displaying
positions and popularity, as well as the user's self-selection. Most existing recommendation …

Due to strong capabilities in conducting fluent, multi-turn conversations with users, Large
Language Models (LLMs) have the potential to further improve the performance of …

This article considers the problem of maintaining the long-term fairness of item exposure in
interactive recommender systems under the dynamic setting that user preference and item …

In the travel industry, Tourism Recommender Systems (TRS) are gaining popularity as they
simplify trip planning for travelers by offering personalized recommendations for …