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- affiliation: University of Glasgow, UK
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2020 – today
- 2022
[j52]Graham McDonald
, Craig Macdonald, Iadh Ounis:
Search results diversification for effective fair ranking in academic search. Inf. Retr. J. 25(1): 1-26 (2022)- [j51]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) - [c265]Hitarth Narvala, Graham McDonald, Iadh Ounis:
The Role of Latent Semantic Categories and Clustering in Enhancing the Efficiency of Human Sensitivity Review. CHIIR 2022: 56-66 - [c264]Sean MacAvaney, Craig Macdonald, Iadh Ounis:
Streamlining Evaluation with ir-measures. ECIR (2) 2022: 305-310 - [c263]Xi Wang, Iadh Ounis, Craig Macdonald:
Effective Rating Prediction Using an Attention-Based User Review Sentiment Model. ECIR (1) 2022: 487-501 - [c262]Sean MacAvaney, Craig Macdonald, Iadh Ounis:
Reproducing Personalised Session Search Over the AOL Query Log. ECIR (1) 2022: 627-640 - [i19]Sean MacAvaney, Craig Macdonald, Iadh Ounis:
Reproducing Personalised Session Search over the AOL Query Log. CoRR abs/2201.08622 (2022) - 2021
- [j50]Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Variational Bayesian representation learning for grocery recommendation. Inf. Retr. J. 24(4-5): 347-369 (2021) - [j49]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) - [c261]Craig Macdonald, Nicola Tonellotto, Sean MacAvaney, Iadh Ounis:
PyTerrier: Declarative Experimentation in Python from BM25 to Dense Retrieval. CIKM 2021: 4526-4533 - [c260]Hitarth Narvala, Graham McDonald, Iadh Ounis:
RelDiff: Enriching Knowledge Graph Relation Representations for Sensitivity Classification. EMNLP (Findings) 2021: 3671-3681 - [c259]Xiao Wang, Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval. ICTIR 2021: 297-306 - [c258]Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
On Single and Multiple Representations in Dense Passage Retrieval. IIR 2021 - [c257]Yaxiong Wu, Craig Macdonald, Iadh Ounis:
Partially Observable Reinforcement Learning for Dialog-based Interactive Recommendation. RecSys 2021: 241-251 - [c256]Alberto Ueda, Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Structured Fine-Tuning of Contextual Embeddings for Effective Biomedical Retrieval. SIGIR 2021: 2031-2035 - [c255]Xi Wang, Iadh Ounis, Craig Macdonald:
Leveraging Review Properties for Effective Recommendation. WWW 2021: 2209-2219 - [i18]Xi Wang, Iadh Ounis, Craig Macdonald:
Leveraging Review Properties for Effective Recommendation. CoRR abs/2102.03089 (2021) - [i17]Amir Hossein Jadidinejad, Craig Macdonald, Iadh Ounis:
The Simpson's Paradox in the Offline Evaluation of Recommendation Systems. CoRR abs/2104.08912 (2021) - [i16]Xiao Wang, Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
Pseudo-Relevance Feedback for Multiple Representation Dense Retrieval. CoRR abs/2106.11251 (2021) - [i15]Zaiqiao Meng, Siwei Liu, Craig Macdonald, Iadh Ounis:
Graph Neural Pre-training for Enhancing Recommendations using Side Information. CoRR abs/2107.03936 (2021) - [i14]Sean MacAvaney, Craig Macdonald, Roderick Murray-Smith, Iadh Ounis:
IntenT5: Search Result Diversification using Causal Language Models. CoRR abs/2108.04026 (2021) - [i13]Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
On Single and Multiple Representations in Dense Passage Retrieval. CoRR abs/2108.06279 (2021) - [i12]JingMin Huang, Bowei Chen, Lan Luo, Shigang Yue, Iadh Ounis:
DVM-CAR: A large-scale automotive dataset for visual marketing research and applications. CoRR abs/2109.00881 (2021) - [i11]Sean MacAvaney, Craig Macdonald, Iadh Ounis:
Streamlining Evaluation with ir-measures. CoRR abs/2111.13466 (2021) - 2020
- [j48]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) - [j47]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) - [j46]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) - [j45]Zaiqiao Meng, Shangsong Liang, Xiangliang Zhang, Richard McCreadie, Iadh Ounis:
Jointly Learning Representations of Nodes and Attributes for Attributed Networks. ACM Trans. Inf. Syst. 38(2): 16:1-16:32 (2020) - [j44]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) - [c254]Xi Wang, Iadh Ounis, Craig MacDonald:
Negative Confidence-Aware Weakly Supervised Binary Classification for Effective Review Helpfulness Classification. CIKM 2020: 1565-1574 - [c253]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 - [c252]Yaxiong Wu, Craig Macdonald, Iadh Ounis:
A Hybrid Conditional Variational Autoencoder Model for Personalised Top-n Recommendation. ICTIR 2020: 89-96 - [c251]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 - [c250]Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Exploring Data Splitting Strategies for the Evaluation of Recommendation Models. RecSys 2020: 681-686 - [c249]Amir Hossein Jadidinejad, Craig Macdonald, Iadh Ounis:
Using Exploration to Alleviate Closed Loop Effects in Recommender Systems. SIGIR 2020: 2025-2028 - [c248]Siwei Liu, Iadh Ounis, Craig Macdonald, Zaiqiao Meng:
A Heterogeneous Graph Neural Model for Cold-start Recommendation. SIGIR 2020: 2029-2032 - [c247]Graham McDonald, Craig Macdonald, Iadh Ounis:
Active Learning Stopping Strategies for Technology-Assisted Sensitivity Review. SIGIR 2020: 2053-2056 - [c246]Hitarth Narvala, Graham McDonald, Iadh Ounis:
Receptor: A Platform for Exploring Latent Relations in Sensitive Documents. SIGIR 2020: 2161-2164 - [c245]Graham McDonald, Iadh Ounis:
University of Glasgow Terrier Team at the TREC 2020 Fair Ranking Track. TREC 2020 - [c244]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 - [c243]Xiao Wang, Yaxiong Wu, Xi Wang, Craig Macdonald, Iadh Ounis:
University of Glasgow Terrier Team at the TREC 2020 Deep Learning Track. TREC 2020 - [i10]Xiao Wang, Craig Macdonald, Iadh Ounis:
Deep Reinforced Query Reformulation for Information Retrieval. CoRR abs/2007.07987 (2020) - [i9]Zaiqiao Meng, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Exploring Data Splitting Strategies for the Evaluation of Recommendation Models. CoRR abs/2007.13237 (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
- [j43]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) - [j42]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) - [j41]Alexandra Olteanu, Jean Garcia-Gathright, Maarten de Rijke, Michael D. Ekstrand, Adam Roegiest, Aldo Lipani, Alex Beutel, Ana Lucic, Ana-Andreea Stoica, Anubrata Das, Asia Biega, Bart Voorn, Claudia Hauff, Damiano Spina, David D. Lewis, Douglas W. Oard, Emine Yilmaz, Faegheh Hasibi, Gabriella Kazai, Graham McDonald, Hinda Haned, Iadh Ounis, Ilse van der Linden, Joris Baan, Kamuela N. Lau, Krisztian Balog, Mahmoud F. Sayed, Maria Panteli, Mark Sanderson, Matthew Lease, Preethi Lahoti, Toshihiro Kamishima:
FACTS-IR: fairness, accountability, confidentiality, transparency, and safety in information retrieval. SIGIR Forum 53(2): 20-43 (2019) - [c242]Graham McDonald, Craig Macdonald, Iadh Ounis:
How Sensitivity Classification Effectiveness Impacts Reviewers in Technology-Assisted Sensitivity Review. CHIIR 2019: 337-341 - [c241]Ting Su, Craig Macdonald, Iadh Ounis:
Entity Detection for Check-worthiness Prediction: Glasgow Terrier at CLEF CheckThat! 2019. CLEF (Working Notes) 2019 - [c240]Xi Wang, Iadh Ounis, Craig Macdonald:
Comparison of Sentiment Analysis and User Ratings in Venue Recommendation. ECIR (1) 2019: 215-228 - [c239]Jarana Manotumruksa, Dimitrios Rafailidis, Craig Macdonald, Iadh Ounis:
On Cross-Domain Transfer in Venue Recommendation. ECIR (1) 2019: 443-456 - [c238]Xi Wang, Anjie Fang, Iadh Ounis, Craig Macdonald:
Evaluating Similarity Metrics for Latent Twitter Topics. ECIR (1) 2019: 787-794 - [c237]Siwei Liu, Iadh Ounis, Craig Macdonald:
Social Regularisation in a BPR-based Venue Recommendation System. FDIA@ESSIR 2019: 16-22 - [c236]Amir Hossein Jadidinejad, Craig MacDonald, Iadh Ounis:
Unifying Explicit and Implicit Feedback for Rating Prediction and Ranking Recommendation Tasks. ICTIR 2019: 149-156 - [c235]Ting Su, Craig Macdonald, Iadh Ounis:
Ensembles of Recurrent Networks for Classifying the Relationship of Fake News Titles. SIGIR 2019: 893-896 - [c234]Charles Thomas, Richard McCreadie, Iadh Ounis:
Event Tracker: A Text Analytics Platform for Use During Disasters. SIGIR 2019: 1341-1344 - [c233]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 - [c232]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
- [j40]Nicola Tonellotto, Craig Macdonald, Iadh Ounis:
Efficient Query Processing for Scalable Web Search. Found. Trends Inf. Retr. 12(4-5): 319-500 (2018) - [j39]Xiao Yang, Craig Macdonald, Iadh Ounis:
Using word embeddings in Twitter election classification. Inf. Retr. J. 21(2-3): 183-207 (2018) - [j38]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) - [j37]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) - [c231]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 - [c230]Jorge David Gonzalez Paule, Yashar Moshfeghi, Craig Macdonald, Iadh Ounis:
Learning to Geolocalise Tweets at a Fine-Grained Level. CIKM 2018: 1675-1678 - [c229]Craig Macdonald, Richard McCreadie, Iadh Ounis:
Agile Information Retrieval Experimentation with Terrier Notebooks. DESIRES 2018: 54-61 - [c228]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 - [c227]Graham McDonald, Craig Macdonald, Iadh Ounis:
Active Learning Strategies for Technology Assisted Sensitivity Review. ECIR 2018: 439-453 - [c226]Graham McDonald, Craig Macdonald, Iadh Ounis:
Towards Maximising Openness in Digital Sensitivity Review Using Reviewing Time Predictions. ECIR 2018: 699-706 - [c225]Ting Su, Anjie Fang, Richard McCreadie, Craig Macdonald, Iadh Ounis:
On Refining Twitter Lists as Ground Truth Data for Multi-community User Classification. ECIR 2018: 765-772 - [c224]Jarana Manotumruksa, Craig Macdonald, Iadh Ounis:
A Contextual Attention Recurrent Architecture for Context-Aware Venue Recommendation. SIGIR 2018: 555-564 - [c223]Richard McCreadie, Craig Macdonald, Iadh Ounis:
Automatic Ground Truth Expansion for Timeline Evaluation. SIGIR 2018: 685-694 - [r4]Craig MacDonald, Iadh Ounis:
WEB Information Retrieval Models. Encyclopedia of Database Systems (2nd ed.) 2018 - [r3]Iadh Ounis:
Inverse Document Frequency. Encyclopedia of Database Systems (2nd ed.) 2018 - 2017
- [j36]Leif Azzopardi, Craig Macdonald, Iadh Ounis, Martin Halvey:
Report on the Information Retrieval Festival (IRFest2017). SIGIR Forum 51(1): 12-28 (2017) - [c222]Karin Sim Smith, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Analyzing Disproportionate Reaction via Comparative Multilingual Targeted Sentiment in Twitter. ASONAM 2017: 317-320 - [c221]Xiao Yang, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Transfer Learning for Multi-language Twitter Election Classification. ASONAM 2017: 341-348 - [c220]Vinicius Monteiro de Lira, Craig Macdonald, Iadh Ounis, Raffaele Perego, Chiara Renso, Valéria Cesário Times:
Exploring Social Media for Event Attendance. ASONAM 2017: 447-450 - [c219]Jarana Manotumruksa, Craig Macdonald, Iadh Ounis:
A Deep Recurrent Collaborative Filtering Framework for Venue Recommendation. CIKM 2017: 1429-1438 - [c218]Jarana Manotumruksa, Craig Macdonald, Iadh Ounis:
A Personalised Ranking Framework with Multiple Sampling Criteria for Venue Recommendation. CIKM 2017: 1469-1478 - [c217]Anjie Fang, Craig Macdonald, Iadh Ounis, Philip Habel, Xiao Yang:
Exploring Time-Sensitive Variational Bayesian Inference LDA for Social Media Data. ECIR 2017: 252-265 - [c216]Graham McDonald, Craig Macdonald, Iadh Ounis:
Enhancing Sensitivity Classification with Semantic Features Using Word Embeddings. ECIR 2017: 450-463 - [c215]Jarana Manotumruksa, Craig Macdonald, Iadh Ounis:
Matrix Factorisation with Word Embeddings for Rating Prediction on Location-Based Social Networks. ECIR 2017: 647-654 - [c214]Mehmet Akcay, Ismail Sengor Altingovde, Craig Macdonald, Iadh Ounis:
On the Additivity and Weak Baselines for Search Result Diversification Research. ICTIR 2017: 109-116 - [c213]Craig MacDonald, Nicola Tonellotto, Iadh Ounis:
Efficient & Effective Selective Query Rewriting with Efficiency Predictions. SIGIR 2017: 495-504 - [c212]Graham McDonald, Nicolás García-Pedrajas, Craig Macdonald, Iadh Ounis:
A Study of SVM Kernel Functions for Sensitivity Classification Ensembles with POS Sequences. SIGIR 2017: 1097-1100 - [i5]Nut Limsopatham, Craig MacDonald, Iadh Ounis:
Inferring Conceptual Relationships When Ranking Patients. CoRR abs/1702.00171 (2017) - 2016
- [c211]Jarana Manotumruksa, Craig MacDonald, Iadh Ounis:
Regularising Factorised Models for Venue Recommendation using Friends and their Comments. CIKM 2016: 1981-1984 - [c210]Jarana Manotumruksa, Craig MacDonald, Iadh Ounis:
Predicting Contextually Appropriate Venues in Location-Based Social Networks. CLEF 2016: 96-109 - [c209]Stuart Mackie, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Experiments in Newswire Summarisation. ECIR 2016: 421-435 - [c208]Anjie Fang, Craig Macdonald, Iadh Ounis, Philip Habel:
Topics in Tweets: A User Study of Topic Coherence Metrics for Twitter Data. ECIR 2016: 492-504 - [c207]Saul Vargas, Richard McCreadie, Craig MacDonald, Iadh Ounis:
Comparing Overall and Targeted Sentiments in Social Media during Crises. ICWSM 2016: 695-698 - [c206]Richard Zanibbi, Akiko Aizawa, Michael Kohlhase, Iadh Ounis, Goran Topic, Kenny Davila:
NTCIR-12 MathIR Task Overview. NTCIR 2016 - [c205]Bekir Taner Dinçer, Craig Macdonald, Iadh Ounis:
Risk-Sensitive Evaluation and Learning to Rank using Multiple Baselines. SIGIR 2016: 483-492 - [c204]Sean Moran, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Enhancing First Story Detection using Word Embeddings. SIGIR 2016: 821-824 - [c203]Anjie Fang, Craig Macdonald, Iadh Ounis, Philip Habel:
Examining the Coherence of the Top Ranked Tweet Topics. SIGIR 2016: 825-828 - [c202]Anjie Fang, Craig Macdonald, Iadh Ounis, Philip Habel:
Using Word Embedding to Evaluate the Coherence of Topics from Twitter Data. SIGIR 2016: 1057-1060 - [c201]Richard McCreadie, Craig Macdonald, Iadh Ounis:
EAIMS: Emergency Analysis Identification and Management System. SIGIR 2016: 1101-1104 - [c200]Jarana Manotumruksa, Craig MacDonald, Iadh Ounis:
University of Glasgow Terrier Team at TREC 2016: Experiments in Contextual Suggestions. TREC 2016 - [i4]Xiao Yang, Craig MacDonald, Iadh Ounis:
Using Word Embeddings in Twitter Election Classification. CoRR abs/1606.07006 (2016) - [i3]Jarana Manotumruksa, Craig MacDonald, Iadh Ounis:
Modelling User Preferences using Word Embeddings for Context-Aware Venue Recommendation. CoRR abs/1606.07828 (2016) - [i2]Richard McCreadie, Craig MacDonald, Iadh Ounis:
Emergency Identification and Analysis with EAIMS. CoRR abs/1610.04002 (2016) - 2015
- [j35]Rodrygo L. T. Santos, Craig MacDonald, Iadh Ounis:
Search Result Diversification. Found. Trends Inf. Retr. 9(1): 1-90 (2015) - [j34]Ana Freire, Craig Macdonald, Nicola Tonellotto, Iadh Ounis, Fidel Cacheda:
Queuing Theory-based Latency/Power Tradeoff Models for Replicated Search Engines. J. Univers. Comput. Sci. 21(13): 1790-1809 (2015) - [c199]Romain Deveaud, M-Dyaa Albakour, Craig Macdonald, Iadh Ounis:
Experiments with a Venue-Centric Model for Personalisedand Time-Aware Venue Suggestion. CIKM 2015: 53-62 - [c198]Eugene Kharitonov, Craig Macdonald, Pavel Serdyukov, Iadh Ounis:
Generalized Team Draft Interleaving. CIKM 2015: 773-782 - [c197]Giacomo Berardi, Andrea Esuli, Craig Macdonald, Iadh Ounis, Fabrizio Sebastiani:
Semi-Automated Text Classification for Sensitivity Identification. CIKM 2015: 1711-1714 - [c196]Nut Limsopatham, Craig Macdonald, Iadh Ounis:
Modelling the Usefulness of Document Collections for Query Expansion in Patient Search. CIKM 2015: 1739-1742 - [c195]Yashar Moshfeghi, Iadh Ounis, Craig Macdonald, Joemon M. Jose, Peter Triantafillou, Mark Livingston, Piyushimita Thakuriah:
UCUI'15: The 1st International Workshop on Understanding the City with Urban Informatics. CIKM 2015: 1955-1956 - [c194]Thibaut Thonet, Romain Deveaud, Iadh Ounis, Craig Macdonald:
Suggestion contextuelle composite. CORIA 2015: 89-104 - [c193]Anjie Fang, Iadh Ounis, Philip Habel, Craig MacDonald, Nut Limsopatham:
Topic-centric Classification of Twitter User's Political Orientation. FDIA 2015 - [c192]Craig Macdonald, Bekir Taner Dinçer, Iadh Ounis:
Transferring Learning To Rank Models for Web Search. ICTIR 2015: 41-50 - [c191]Graham McDonald, Craig Macdonald, Iadh Ounis:
Using Part-of-Speech N-grams for Sensitive-Text Classification. ICTIR 2015: 381-384 - [c190]Graham McDonald, Romain Deveaud, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Tweet Enrichment for Effective Dimensions Classification in Online Reputation Management. ICWSM 2015: 654-657 - [c189]Saúl Vargas, Craig Macdonald, Iadh Ounis:
Analysing Compression Techniques for In-Memory Collaborative Filtering. RecSys Posters 2015 - [c188]Eugene Kharitonov, Craig Macdonald, Pavel Serdyukov, Iadh Ounis:
Optimised Scheduling of Online Experiments. SIGIR 2015: 453-462 - [c187]Eugene Kharitonov, Aleksandr Vorobev, Craig Macdonald, Pavel Serdyukov, Iadh Ounis:
Sequential Testing for Early Stopping of Online Experiments. SIGIR 2015: 473-482 - [c186]M-Dyaa Albakour, Craig Macdonald, Iadh Ounis:
Using Sensor Metadata Streams to Identify Topics of Local Events in the City. SIGIR 2015: 711-714 - [c185]