108 citations · 289 across the 16 of their papers we have counts for
18 papers
Reproducing Personalised Session Search over the AOL Query Log
Sean MacAvaney, Craig Macdonald, Iadh Ounis
Despite its troubled past, the AOL Query Log continues to be an important resource to the research community -- particularly for tasks like search personalisation. When using the q…
On Approximate Nearest Neighbour Selection for Multi-Stage Dense Retrieval
Craig Macdonald, Nicola Tonellotto
Dense retrieval, which describes the use of contextualised language models such as BERT to identify documents from a collection by leveraging approximate nearest neighbour (ANN) te…
Query Embedding Pruning for Dense Retrieval
Nicola Tonellotto, Craig Macdonald
Recent advances in dense retrieval techniques have offered the promise of being able not just to re-rank documents using contextualised language models such as BERT, but also to us…
On Single and Multiple Representations in Dense Passage Retrieval
Craig Macdonald, Nicola Tonellotto, Iadh Ounis
The advent of contextualised language models has brought gains in search effectiveness, not just when applied for re-ranking the output of classical weighting models such as BM25,…
IntenT5: Search Result Diversification using Causal Language Models
Sean MacAvaney, Craig Macdonald, Roderick Murray-Smith +1
Search result diversification is a beneficial approach to overcome under-specified queries, such as those that are ambiguous or multi-faceted. Existing approaches often rely on mas…
Graph Neural Pre-training for Enhancing Recommendations using Side Information
Zaiqiao Meng, Siwei Liu, Craig Macdonald +1
Leveraging the side information associated with entities (i.e. users and items) to enhance the performance of recommendation systems has been widely recognized as an important mode…