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ORCIDCraig Macdonald
Craig MacDonald
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- affiliation: University of Glasgow
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2020 – today
- 2023
[j41]Siwei Liu
, Zaiqiao Meng, Craig Macdonald, Iadh Ounis:
Graph Neural Pre-training for Recommendation with Side Information. ACM Trans. Inf. Syst. 41(3): 74:1-74:28 (2023)- [j40]Xiao Wang, Craig MacDonald, Nicola Tonellotto, Iadh Ounis:
ColBERT-PRF: Semantic Pseudo-Relevance Feedback for Dense Passage and Document Retrieval. ACM Trans. Web 17(1): 3:1-3:39 (2023) - [c242]Xiao Wang, Sean MacAvaney, Craig Macdonald, Iadh Ounis:
Effective Contrastive Weighting for Dense Query Expansion. ACL (1) 2023: 12688-12704 - [c241]Jinyuan Fang, Zaiqiao Meng, Craig Macdonald:
KGPR: Knowledge Graph Enhanced Passage Ranking. CIKM 2023: 3880-3885 - [c240]Antonio Acquavia, Craig Macdonald, Nicola Tonellotto:
Static Pruning for Multi-Representation Dense Retrieval. DocEng 2023: 7:1-7:10 - [c239]Zixuan Yi, Iadh Ounis, Craig Macdonald:
Graph Contrastive Learning with Positional Representation for Recommendation. ECIR (2) 2023: 288-303 - [c238]Mitko Gospodinov, Sean MacAvaney, Craig Macdonald:
Doc2Query-: When Less is More. ECIR (2) 2023: 414-422 - [c237]Aleksandr Vladimirovich Petrov, Craig MacDonald:
gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling. RecSys 2023: 116-128 - [c236]Yaxiong Wu, Craig Macdonald, Iadh Ounis:
Goal-Oriented Multi-Modal Interactive Recommendation with Verbal and Non-Verbal Relevance Feedback. RecSys 2023: 362-373 - [c235]Ashutosh Singh, Debasis Ganguly, Suchana Datta, Craig MacDonald:
Unsupervised Query Performance Prediction for Neural Models with Pairwise Rank Preferences. SIGIR 2023: 2486-2490 - [c234]Xiao Wang, Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
Reproducibility, Replicability, and Insights into Dense Multi-Representation Retrieval Models: from ColBERT to Col. SIGIR 2023: 2552-2561 - [i35]Mitko Gospodinov, Sean MacAvaney, Craig Macdonald:
Doc2Query-: When Less is More. CoRR abs/2301.03266 (2023) - [i34]Aleksandr V. Petrov, Craig Macdonald:
Generative Sequential Recommendation with GPTRec. CoRR abs/2306.11114 (2023) - [i33]Xiao Wang, Sean MacAvaney, Craig Macdonald, Iadh Ounis:
Generative Query Reformulation for Effective Adhoc Search. CoRR abs/2308.00415 (2023) - [i32]Aleksandr V. Petrov, Craig Macdonald:
gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling. CoRR abs/2308.07192 (2023) - [i31]Zixuan Yi, Iadh Ounis, Craig Macdonald:
Contrastive Graph Prompt-tuning for Cross-domain Recommendation. CoRR abs/2308.10685 (2023) - [i30]Maria Vlachou, Craig Macdonald:
On Coherence-based Predictors for Dense Query Performance Prediction. CoRR abs/2310.11405 (2023) - [i29]Zixuan Yi, Zijun Long, Iadh Ounis, Craig Macdonald, Richard McCreadie:
Large Multi-modal Encoders for Recommendation. CoRR abs/2310.20343 (2023) - [i28]Siwei Liu, Xi Wang, Craig Macdonald, Iadh Ounis:
A Social-aware Gaussian Pre-trained Model for Effective Cold-start Recommendation. CoRR abs/2311.15790 (2023) - 2022
- [j39]Xiao Wang, Craig Macdonald, Iadh Ounis:
Improving zero-shot retrieval using dense external expansion. Inf. Process. Manag. 59(5): 103026 (2022) - [j38]Graham McDonald, Craig Macdonald, Iadh Ounis:
Search results diversification for effective fair ranking in academic search. Inf. Retr. J. 25(1): 1-26 (2022) - [j37]Alberto Barrón-Cedeño, Giovanni Da San Martino, Mirko Degli Esposti, Guglielmo Faggioli, Nicola Ferro, Allan Hanbury, Craig Macdonald, Gabriella Pasi, Martin Potthast, Fabrizio Sebastiani:
Report on the 13th Conference and Labs of the Evaluation Forum (CLEF 2022): Experimental IR Meets Multilinguality, Multimodality, and Interaction. SIGIR Forum 56(2): 13:1-13:15 (2022) - [j36]Amir Hossein Jadidinejad, Craig Macdonald, Iadh Ounis:
The Simpson's Paradox in the Offline Evaluation of Recommendation Systems. ACM Trans. Inf. Syst. 40(1): 4:1-4:22 (2022) - [j35]Xi Wang, Iadh Ounis, Craig Macdonald:
BanditProp: Bandit Selection of Review Properties for Effective Recommendation. ACM Trans. Web 16(4): 20:1-20:19 (2022) - [c233]Sean MacAvaney, Nicola Tonellotto, Craig Macdonald:
Adaptive Re-Ranking with a Corpus Graph. CIKM 2022: 1491-1500 - [c232]Sean MacAvaney, Nicola Tonellotto, Craig Macdonald:
Adaptive Re-Ranking as an Information-Seeking Agent. CIKM Workshops 2022 - [c231]Erlend Frayling, Craig Macdonald, Graham McDonald, Iadh Ounis:
Using Entities in Knowledge Graph Hierarchies to Classify Sensitive Information. CLEF 2022: 125-132 - [c230]Yaxiong Wu, Craig Macdonald, Iadh Ounis:
Multimodal Conversational Fashion Recommendation with Positive and Negative Natural-Language Feedback. CUI 2022: 6:1-6:10 - [c229]Sean MacAvaney, Craig Macdonald, Iadh Ounis:
Streamlining Evaluation with ir-measures. ECIR (2) 2022: 305-310 - [c228]Xi Wang, Iadh Ounis, Craig Macdonald:
Effective Rating Prediction Using an Attention-Based User Review Sentiment Model. ECIR (1) 2022: 487-501 - [c227]Sean MacAvaney, Craig Macdonald, Iadh Ounis:
Reproducing Personalised Session Search Over the AOL Query Log. ECIR (1) 2022: 627-640 - [c226]Sarawoot Kongyoung, Craig Macdonald, Iadh Ounis:
monoQA: Multi-Task Learning of Reranking and Answer Extraction for Open-Retrieval Conversational Question Answering. EMNLP 2022: 7207-7218 - [c225]Aleksandr V. Petrov, Craig Macdonald:
Effective and Efficient Training for Sequential Recommendation using Recency Sampling. RecSys 2022: 81-91 - [c224]Maria Vlachou, Craig Macdonald:
Performance Predictors for Conversational Fashion Recommendation. KaRS@RecSys 2022: 91-100 - [c223]Yaxiong Wu, Craig Macdonald, Iadh Ounis:
Multi-Modal Dialog State Tracking for Interactive Fashion Recommendation. RecSys 2022: 124-133 - [c222]Aleksandr V. Petrov, Craig Macdonald:
A Systematic Review and Replicability Study of BERT4Rec for Sequential Recommendation. RecSys 2022: 436-447 - [c221]Zixuan Yi, Xi Wang, Iadh Ounis, Craig MacDonald:
Multi-modal Graph Contrastive Learning for Micro-video Recommendation. SIGIR 2022: 1807-1811 - [c220]Siwei Liu, Iadh Ounis, Craig Macdonald:
An MLP-based Algorithm for Efficient Contrastive Graph Recommendations. SIGIR 2022: 2431-2436 - [c219]Xiao Wang, Sean MacAvaney, Craig Macdonald, Iadh Ounis:
An Inspection of the Reproducibility and Replicability of TCT-ColBERT. SIGIR 2022: 2790-2800 - [c218]Sean MacAvaney, Craig Macdonald:
A Python Interface to PISA! SIGIR 2022: 3339-3344 - [c217]Sarawoot Kongyoung, Craig Macdonald, Iadh Ounis:
University of Glasgow Terrier Team at the TREC 2022 Conversational Assistance Track. TREC 2022 - [c216]Xiao Wang, Sean MacAvaney, Craig Macdonald, Iadh Ounis:
Experiments with Adaptive ReRanking and ColBERT-PRF: University of Glasgow Terrier Team at TREC DL 2022. TREC 2022 - [p1]Richard McCreadie, John Soldatos, Jonathan Fürst, Mauricio Fadel Argerich, George Kousiouris, Jean-Didier Totow, Antonio Castillo Nieto, Bernat Quesada Navidad, Dimosthenis Kyriazis, Craig Macdonald, Iadh Ounis:
Leveraging Data-Driven Infrastructure Management to Facilitate AIOps for Big Data Applications and Operations. Technologies and Applications for Big Data Value 2022: 135-158 - [e8]Alberto Barrón-Cedeño, Giovanni Da San Martino, Mirko Degli Esposti, Fabrizio Sebastiani, Craig Macdonald, Gabriella Pasi, Allan Hanbury, Martin Potthast, Guglielmo Faggioli, Nicola Ferro:
Experimental IR Meets Multilinguality, Multimodality, and Interaction - 13th International Conference of the CLEF Association, CLEF 2022, Bologna, Italy, September 5-8, 2022, Proceedings. Lecture Notes in Computer Science 13390, Springer 2022, ISBN 978-3-031-13642-9 [contents] - [e7]Matthias Hagen, Suzan Verberne, Craig Macdonald, Christin Seifert, Krisztian Balog, Kjetil Nørvåg, Vinay Setty:
Advances in Information Retrieval - 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10-14, 2022, Proceedings, Part I. Lecture Notes in Computer Science 13185, Springer 2022, ISBN 978-3-030-99735-9 [contents] - [e6]Matthias Hagen, Suzan Verberne, Craig Macdonald, Christin Seifert, Krisztian Balog, Kjetil Nørvåg, Vinay Setty:
Advances in Information Retrieval - 44th European Conference on IR Research, ECIR 2022, Stavanger, Norway, April 10-14, 2022, Proceedings, Part II. Lecture Notes in Computer Science 13186, Springer 2022, ISBN 978-3-030-99738-0 [contents] - [i27]Sean MacAvaney, Craig Macdonald, Iadh Ounis:
Reproducing Personalised Session Search over the AOL Query Log. CoRR abs/2201.08622 (2022) - [i26]Aleksandr V. Petrov, Craig Macdonald:
Effective and Efficient Training for Sequential Recommendation using Recency Sampling. CoRR abs/2207.02643 (2022) - [i25]Aleksandr V. Petrov, Craig Macdonald:
A Systematic Review and Replicability Study of BERT4Rec for Sequential Recommendation. CoRR abs/2207.07483 (2022) - [i24]Sean MacAvaney, Nicola Tonellotto, Craig Macdonald:
Adaptive Re-Ranking with a Corpus Graph. CoRR abs/2208.08942 (2022) - [i23]Ting Su, Craig Macdonald, Iadh Ounis:
Leveraging Users' Social Network Embeddings for Fake News Detection on Twitter. CoRR abs/2211.10672 (2022) - [i22]Ting Su, Craig Macdonald, Iadh Ounis:
Entity-Assisted Language Models for Identifying Check-worthy Sentences. CoRR abs/2211.10678 (2022) - 2021
- [j34]Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Variational Bayesian representation learning for grocery recommendation. Inf. Retr. J. 24(4-5): 347-369 (2021) - [j33]Sevgi Yigit-Sert, Ismail Sengor Altingovde, Craig Macdonald, Iadh Ounis, Özgür Ulusoy:
Explicit diversification of search results across multiple dimensions for educational search. J. Assoc. Inf. Sci. Technol. 72(3): 315-330 (2021) - [c215]Craig Macdonald, Nicola Tonellotto:
On Approximate Nearest Neighbour Selection for Multi-Stage Dense Retrieval. CIKM 2021: 3318-3322 - [c214]Nicola Tonellotto, Craig Macdonald:
Query Embedding Pruning for Dense Retrieval. CIKM 2021: 3453-3457 - [c213]Craig Macdonald, Nicola Tonellotto, Sean MacAvaney, Iadh Ounis:
PyTerrier: Declarative Experimentation in Python from BM25 to Dense Retrieval. CIKM 2021: 4526-4533 - [c212]Craig Macdonald, Nicola Tonellotto, Sean MacAvaney:
IR From Bag-of-words to BERT and Beyond through Practical Experiments. CIKM 2021: 4861 - [c211]Xiao Wang, Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval. ICTIR 2021: 297-306 - [c210]Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
On Single and Multiple Representations in Dense Passage Retrieval. IIR 2021 - [c209]Yaxiong Wu, Craig Macdonald, Iadh Ounis:
Partially Observable Reinforcement Learning for Dialog-based Interactive Recommendation. RecSys 2021: 241-251 - [c208]Alberto Ueda, Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Structured Fine-Tuning of Contextual Embeddings for Effective Biomedical Retrieval. SIGIR 2021: 2031-2035 - [c207]Xi Wang, Iadh Ounis, Craig Macdonald:
Leveraging Review Properties for Effective Recommendation. WWW 2021: 2209-2219 - [i21]Xi Wang, Iadh Ounis, Craig Macdonald:
Leveraging Review Properties for Effective Recommendation. CoRR abs/2102.03089 (2021) - [i20]Amir Hossein Jadidinejad, Craig Macdonald, Iadh Ounis:
The Simpson's Paradox in the Offline Evaluation of Recommendation Systems. CoRR abs/2104.08912 (2021) - [i19]Xiao Wang, Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval. CoRR abs/2106.11251 (2021) - [i18]Zaiqiao Meng, Siwei Liu, Craig Macdonald, Iadh Ounis:
Graph Neural Pre-training for Enhancing Recommendations using Side Information. CoRR abs/2107.03936 (2021) - [i17]Sean MacAvaney, Craig Macdonald, Roderick Murray-Smith, Iadh Ounis:
IntenT5: Search Result Diversification using Causal Language Models. CoRR abs/2108.04026 (2021) - [i16]Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
On Single and Multiple Representations in Dense Passage Retrieval. CoRR abs/2108.06279 (2021) - [i15]Nicola Tonellotto, Craig Macdonald:
Query Embedding Pruning for Dense Retrieval. CoRR abs/2108.10341 (2021) - [i14]Craig Macdonald, Nicola Tonellotto:
On Approximate Nearest Neighbour Selection for Multi-Stage Dense Retrieval. CoRR abs/2108.11480 (2021) - [i13]Sean MacAvaney, Craig Macdonald, Iadh Ounis:
Streamlining Evaluation with ir-measures. CoRR abs/2111.13466 (2021) - 2020
- [j32]Javier Sanz-Cruzado, Pablo Castells, Craig Macdonald, Iadh Ounis:
Effective contact recommendation in social networks by adaptation of information retrieval models. Inf. Process. Manag. 57(5): 102285 (2020) - [j31]Jarana Manotumruksa, Craig Macdonald, Iadh Ounis:
A Contextual Recurrent Collaborative Filtering framework for modelling sequences of venue checkins. Inf. Process. Manag. 57(6): 102092 (2020) - [j30]Sevgi Yigit-Sert, Ismail Sengor Altingovde, Craig Macdonald, Iadh Ounis, Özgür Ulusoy:
Supervised approaches for explicit search result diversification. Inf. Process. Manag. 57(6): 102356 (2020) - [j29]Nicola Tonellotto, Craig Macdonald:
Using an Inverted Index Synopsis for Query Latency and Performance Prediction. ACM Trans. Inf. Syst. 38(3): 29:1-29:33 (2020) - [j28]Graham McDonald, Craig Macdonald, Iadh Ounis:
How the Accuracy and Confidence of Sensitivity Classification Affects Digital Sensitivity Review. ACM Trans. Inf. Syst. 39(1): 4:1-4:34 (2020) - [c206]Xi Wang, Iadh Ounis, Craig MacDonald:
Negative Confidence-Aware Weakly Supervised Binary Classification for Effective Review Helpfulness Classification. CIKM 2020: 1565-1574 - [c205]Javier Sanz-Cruzado, Craig Macdonald, Iadh Ounis, Pablo Castells:
Axiomatic Analysis of Contact Recommendation Methods in Social Networks: An IR Perspective. ECIR (1) 2020: 175-190 - [c204]Yaxiong Wu, Craig Macdonald, Iadh Ounis:
A Hybrid Conditional Variational Autoencoder Model for Personalised Top-n Recommendation. ICTIR 2020: 89-96 - [c203]Craig Macdonald, Nicola Tonellotto:
Declarative Experimentation in Information Retrieval using PyTerrier. ICTIR 2020: 161-168 - [c202]Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis, Siwei Liu, Yaxiong Wu, Xi Wang, Shangsong Liang, Yucheng Liang, Guangtao Zeng, Junhua Liang, Qiang Zhang:
BETA-Rec: Build, Evaluate and Tune Automated Recommender Systems. RecSys 2020: 588-590 - [c201]Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Exploring Data Splitting Strategies for the Evaluation of Recommendation Models. RecSys 2020: 681-686 - [c200]Amir Hossein Jadidinejad, Craig Macdonald, Iadh Ounis:
Using Exploration to Alleviate Closed Loop Effects in Recommender Systems. SIGIR 2020: 2025-2028 - [c199]Siwei Liu, Iadh Ounis, Craig Macdonald, Zaiqiao Meng:
A Heterogeneous Graph Neural Model for Cold-start Recommendation. SIGIR 2020: 2029-2032 - [c198]Graham McDonald, Craig Macdonald, Iadh Ounis:
Active Learning Stopping Strategies for Technology-Assisted Sensitivity Review. SIGIR 2020: 2053-2056 - [c197]Jimmy Lin, Joel M. Mackenzie, Chris Kamphuis, Craig Macdonald, Antonio Mallia, Michal Siedlaczek, Andrew Trotman, Arjen P. de Vries:
Supporting Interoperability Between Open-Source Search Engines with the Common Index File Format. SIGIR 2020: 2149-2152 - [c196]Alberto Ueda, Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
University of Glasgow Terrier Team and UFMG at the TREC 2020 Precision Medicine Track. TREC 2020 - [c195]Xiao Wang, Yaxiong Wu, Xi Wang, Craig Macdonald, Iadh Ounis:
University of Glasgow Terrier Team at the TREC 2020 Deep Learning Track. TREC 2020 - [i12]Jimmy Lin, Joel M. Mackenzie, Chris Kamphuis, Craig Macdonald, Antonio Mallia, Michal Siedlaczek, Andrew Trotman, Arjen P. de Vries:
Supporting Interoperability Between Open-Source Search Engines with the Common Index File Format. CoRR abs/2003.08276 (2020) - [i11]Xiao Wang, Craig Macdonald, Iadh Ounis:
Deep Reinforced Query Reformulation for Information Retrieval. CoRR abs/2007.07987 (2020) - [i10]Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Exploring Data Splitting Strategies for the Evaluation of Recommendation Models. CoRR abs/2007.13237 (2020) - [i9]Craig Macdonald, Nicola Tonellotto:
Declarative Experimentation in Information Retrieval using PyTerrier. CoRR abs/2007.14271 (2020) - [i8]Xi Wang, Iadh Ounis, Craig Macdonald:
Negative Confidence-Aware Weakly Supervised Binary Classification for Effective Review Helpfulness Classification. CoRR abs/2008.06487 (2020)
2010 – 2019
- 2019
- [j27]Vinicius Monteiro de Lira, Craig Macdonald, Iadh Ounis, Raffaele Perego, Chiara Renso, Valéria Cesário Times:
Event attendance classification in social media. Inf. Process. Manag. 56(3): 687-703 (2019) - [j26]Richard McCreadie, Shahzad Rajput, Ian Soboroff, Craig Macdonald, Iadh Ounis:
On enhancing the robustness of timeline summarization test collections. Inf. Process. Manag. 56(5): 1815-1836 (2019) - [c194]Graham McDonald, Craig Macdonald, Iadh Ounis:
How Sensitivity Classification Effectiveness Impacts Reviewers in Technology-Assisted Sensitivity Review. CHIIR 2019: 337-341 - [c193]Ting Su, Craig Macdonald, Iadh Ounis:
Entity Detection for Check-worthiness Prediction: Glasgow Terrier at CLEF CheckThat! 2019. CLEF (Working Notes) 2019 - [c192]Xi Wang, Iadh Ounis, Craig Macdonald:
Comparison of Sentiment Analysis and User Ratings in Venue Recommendation. ECIR (1) 2019: 215-228 - [c191]Jarana Manotumruksa, Dimitrios Rafailidis, Craig Macdonald, Iadh Ounis:
On Cross-Domain Transfer in Venue Recommendation. ECIR (1) 2019: 443-456 - [c190]Xi Wang, Anjie Fang, Iadh Ounis, Craig Macdonald:
Evaluating Similarity Metrics for Latent Twitter Topics. ECIR (1) 2019: 787-794 - [c189]Siwei Liu, Iadh Ounis, Craig Macdonald:
Social Regularisation in a BPR-based Venue Recommendation System. FDIA@ESSIR 2019: 16-22 - [c188]Amir Hossein Jadidinejad, Craig MacDonald, Iadh Ounis:
Unifying Explicit and Implicit Feedback for Rating Prediction and Ranking Recommendation Tasks. ICTIR 2019: 149-156 - [c187]Arthur Barbosa Câmara, Craig Macdonald:
Dockerising Terrier for The Open-Source IR Replicability Challenge (OSIRRC 2019). OSIRRC@SIGIR 2019: 26-30 - [c186]Ting Su, Craig Macdonald, Iadh Ounis:
Ensembles of Recurrent Networks for Classifying the Relationship of Fake News Titles. SIGIR 2019: 893-896 - [c185]Graham McDonald, Iadh Ounis, Craig Macdonald, Thibaut Thonet, Jean-Michel Renders:
University of Glasgow Terrier Team and Naver Labs Europe at TREC 2019 Fair Ranking Track. TREC 2019 - [c184]Ting Su, Xi Wang, Craig Macdonald, Iadh Ounis:
University of Glasgow Terrier Team at the TREC 2019 Deep Learning Track. TREC 2019 - [i7]Graham McDonald, Craig Macdonald, Iadh Ounis:
The FACTS of Technology-Assisted Sensitivity Review. CoRR abs/1907.02956 (2019) - [i6]Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Variational Bayesian Context-aware Representation for Grocery Recommendation. CoRR abs/1909.07705 (2019) - 2018
- [j25]Nicola Tonellotto, Craig Macdonald, Iadh Ounis:
Efficient Query Processing for Scalable Web Search. Found. Trends Inf. Retr. 12(4-5): 319-500 (2018) - [j24]Xiao Yang, Craig Macdonald, Iadh Ounis:
Using word embeddings in Twitter election classification. Inf. Retr. J. 21(2-3): 183-207 (2018) - [j23]Karin Sim Smith, Richard McCreadie, Craig MacDonald, Iadh Ounis:
Regional Sentiment Bias in Social Media Reporting During Crises. Inf. Syst. Frontiers 20(5): 1013-1025 (2018) - [j22]Richard McCreadie, Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Explicit Diversification of Event Aspects for Temporal Summarization. ACM Trans. Inf. Syst. 36(3): 25:1-25:31 (2018) - [c183]Dimosthenis Kyriazis, Christos Doulkeridis, Panagiotis Gouvas, Ricardo Jiménez-Peris, Ana Juan Ferrer, Leonidas Kallipolitis, Pavlos Kranas, George Kousiouris, Craig Macdonald, Richard McCreadie, Yosef Moatti, Apostolos Papageorgiou, Marta Patiño-Martínez, Stathis Plitsos, Dimitrios Poulopoulos, Antonio Paradell, Amaryllis Raouzaiou, Paula Ta-Shma, Valerio Vianello:
BigDataStack: A Holistic Data-Driven Stack for Big Data Applications and Operations. BigData Congress 2018: 237-241 - [c182]Anjie Fang, Iadh Ounis, Craig MacDonald, Philip Habel, Xiaoyu Xiong, Haitao Yu:
An Effective Approach for Modelling Time Features for Classifying Bursty Topics on Twitter. CIKM 2018: 1547-1550 - [c181]Jorge David Gonzalez Paule, Yashar Moshfeghi, Craig Macdonald, Iadh Ounis:
Learning to Geolocalise Tweets at a Fine-Grained Level. CIKM 2018: 1675-1678 - [c180]Craig Macdonald, Richard McCreadie, Iadh Ounis:
Agile Information Retrieval Experimentation with Terrier Notebooks. DESIRES 2018: 54-61 - [c179]Xiao Yang, Iadh Ounis, Richard McCreadie, Craig Macdonald, Anjie Fang:
On the Reproducibility and Generalisation of the Linear Transformation of Word Embeddings. ECIR 2018: 263-275 - [c178]Graham McDonald, Craig Macdonald, Iadh Ounis:
Active Learning Strategies for Technology Assisted Sensitivity Review. ECIR 2018: 439-453 - [c177]Joel M. Mackenzie,