Multimodal semantic understanding often has to deal with uncertainty, which means the
obtained messages tend to refer to multiple targets. Such uncertainty is problematic for our …

This accessible, alphabetical guide provides concise insights into a variety of digital
research methods, incorporating introductory knowledge with practical application and …

We undertake a detailed examination of the steps that make up offline experiments for
recommender system evaluation, including the manner in which the available ratings are …

The increasing reliance on digital information necessitates advancements in conversational
search systems, particularly in terms of information transparency. While prior research in …

In the December 2017 issue of SIGIR Forum, Fuhr presented ten" Thou Shalt Not" s (ie,
warnings against bad practices) for IR experimenters. While his article provides a lot of good …

Target selection is a basic yet often implicit decision in the configuration of offline
recommendation experiments. In this paper we research the impact of target sampling on …

In a conversational context, a user converses with a system through a sequence of natural-
language questions, ie, utterances. Starting from a given subject, the conversation evolves …

Previous researches demonstrate that users' actions in search interaction are associated
with relative gains and losses to reference points, known as the reference dependence …

Solving cold-start problems is indispensable to provide meaningful recommendation results
for new users and items. Under sparsely observed data, unobserved user-item pairs are …

Many state-of-the-art recommendation systems leverage explicit item reviews posted by
users by considering their usefulness in representing the users' preferences and describing …