57 citations · 180 across the 49 of their papers we have counts for
8 papers · 1 filter
Streamlining Evaluation with ir-measures
Sean MacAvaney, Craig Macdonald, Iadh Ounis
We present ir-measures, a new tool that makes it convenient to calculate a diverse set of evaluation measures used in information retrieval. Rather than implementing its own measur…
DVM-CAR: A large-scale automotive dataset for visual marketing research and applications
Jingmin Huang, Bowei Chen, Lan Luo +2
There is a growing interest in product aesthetics analytics and design. However, the lack of available large-scale data that covers various variables and information is one of the…
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…
Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval
Xiao Wang, Craig Macdonald, Nicola Tonellotto +1
Pseudo-relevance feedback mechanisms, from Rocchio to the relevance models, have shown the usefulness of expanding and reweighting the users' initial queries using information occu…