Music recommender systems (MRSs) have experienced a boom in recent years, thanks to
the emergence and success of online streaming services, which nowadays make available …

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 …

Ranking models lie at the heart of research on information retrieval (IR). During the past
decades, different techniques have been proposed for constructing ranking models, from …

Despite the impressive improvements achieved by unsupervised deep neural networks in
computer vision and NLP tasks, such improvements have not yet been observed in ranking …

A well-known challenge in learning from click data is its inherent bias and most notably
position bias. Traditional click models aim to extract the‹ query, document› relevance and …

The availability of massive data and computing power allowing for effective data driven
neural approaches is having a major impact on machine learning and information retrieval …

Learning a high-dimensional dense representation for vocabulary terms, also known as a
word embedding, has recently attracted much attention in natural language processing and …

Learning-to-Rank deals with maximizing the utility of a list of examples presented to the
user, with items of higher relevance being prioritized. It has several practical applications …

Search engine optimization (SEO) can significantly influence what is shown on the result
pages of commercial search engines. However, it is unclear what proportion of (top) results …

While in a classification or a regression setting a label or a value is assigned to each
individual document, in a ranking setting we determine the relevance ordering of the entire …