activity
20132026
most citedDeclarative Experimentation in Information Retrieval using PyTerrier

108 citations · 421 across the 36 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

cs.CL2022

Entity-Assisted Language Models for Identifying Check-worthy Sentences

Ting Su, Craig Macdonald, Iadh Ounis

We propose a new uniform framework for text classification and ranking that can automate the process of identifying check-worthy sentences in political debates and speech transcrip…

cs.SI2022★ 2 cited

Leveraging Users' Social Network Embeddings for Fake News Detection on Twitter

Ting Su, Craig Macdonald, Iadh Ounis

Social networks (SNs) are increasingly important sources of news for many people. The online connections made by users allows information to spread more easily than traditional new…

cs.IR2022★ 32 cited

Adaptive Re-Ranking with a Corpus Graph

Sean MacAvaney, Nicola Tonellotto, Craig Macdonald

Search systems often employ a re-ranking pipeline, wherein documents (or passages) from an initial pool of candidates are assigned new ranking scores. The process enables the use o…

cs.IR2022★ 2 cited

A Systematic Review and Replicability Study of BERT4Rec for Sequential Recommendation

Aleksandr Petrov, Craig Macdonald

BERT4Rec is an effective model for sequential recommendation based on the Transformer architecture. In the original publication, BERT4Rec claimed superiority over other available s…

cs.IR2022★ 1 cited

Effective and Efficient Training for Sequential Recommendation using Recency Sampling

Aleksandr Petrov, Craig Macdonald

Many modern sequential recommender systems use deep neural networks, which can effectively estimate the relevance of items but require a lot of time to train. Slow training increas…

cs.IR2022

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…