Recommender systems are frequently challenged by the data sparsity probl...
A large catalogue size is one of the central challenges in training
reco...
Performing automatic reformulations of a user's query is a popular parad...
Sequential recommendation is an important recommendation task that aims ...
Doc2Query – the process of expanding the content of a document before
in...
We propose a new uniform framework for text classification and ranking t...
Social networks (SNs) are increasingly important sources of news for man...
Search systems often employ a re-ranking pipeline, wherein documents (or...
BERT4Rec is an effective model for sequential recommendation based on th...
Many modern sequential recommender systems use deep neural networks, whi...
Despite its troubled past, the AOL Query Log continues to be an importan...
We present ir-measures, a new tool that makes it convenient to calculate...
Dense retrieval, which describes the use of contextualised language mode...
Recent advances in dense retrieval techniques have offered the promise o...
The advent of contextualised language models has brought gains in search...
Search result diversification is a beneficial approach to overcome
under...
Leveraging the side information associated with entities (i.e. users and...
Pseudo-relevance feedback mechanisms, from Rocchio to the relevance mode...
Recommendation systems are often evaluated based on user's interactions ...
Many state-of-the-art recommendation systems leverage explicit item revi...
The incompleteness of positive labels and the presence of many unlabelle...
The advent of deep machine learning platforms such as Tensorflow and Pyt...
Effective methodologies for evaluating recommender systems are critical,...
Query reformulations have long been a key mechanism to alleviate the
voc...
There exists a natural tension between encouraging a diverse ecosystem o...
Grocery recommendation is an important recommendation use-case, which ai...
At least ninety countries implement Freedom of Information laws that sta...
Word embeddings and convolutional neural networks (CNN) have attracted
e...