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2020 – today
- 2025
[j46]Aleksandr V. Petrov
, Craig Macdonald:
RSS: Effective and Efficient Training for Sequential Recommendation Using Recency Sampling. Trans. Recomm. Syst. 3(1): 1:1-1:32 (2025)- [c259]Fangzheng Tian, Debasis Ganguly, Craig Macdonald:
Is Relevance Propagated from Retriever to Generator in RAG? ECIR (1) 2025: 32-48 - [c258]Jack McKechnie, Graham McDonald, Craig Macdonald:
Context Example Selection for LLM Generated Relevance Assessments. ECIR (1) 2025: 293-309 - [c257]Ariane Mueller, Craig Macdonald:
Semantically Proportioned nDCG for Explaining ColBERT's Learning Process. ECIR (1) 2025: 341-356 - [e19]Claudia Hauff, Craig Macdonald, Dietmar Jannach, Gabriella Kazai, Franco Maria Nardini, Fabio Pinelli, Fabrizio Silvestri, Nicola Tonellotto:
Advances in Information Retrieval - 47th European Conference on Information Retrieval, ECIR 2025, Lucca, Italy, April 6-10, 2025, Proceedings, Part I. Lecture Notes in Computer Science 15572, Springer 2025, ISBN 978-3-031-88707-9 [contents] - [e18]Claudia Hauff, Craig Macdonald, Dietmar Jannach, Gabriella Kazai, Franco Maria Nardini, Fabio Pinelli, Fabrizio Silvestri, Nicola Tonellotto:
Advances in Information Retrieval - 47th European Conference on Information Retrieval, ECIR 2025, Lucca, Italy, April 6-10, 2025, Proceedings, Part II. Lecture Notes in Computer Science 15573, Springer 2025, ISBN 978-3-031-88710-9 [contents] - [e17]Claudia Hauff, Craig Macdonald, Dietmar Jannach, Gabriella Kazai, Franco Maria Nardini, Fabio Pinelli, Fabrizio Silvestri, Nicola Tonellotto:
Advances in Information Retrieval - 47th European Conference on Information Retrieval, ECIR 2025, Lucca, Italy, April 6-10, 2025, Proceedings, Part III. Lecture Notes in Computer Science 15574, Springer 2025, ISBN 978-3-031-88713-0 [contents] - [e16]Claudia Hauff, Craig Macdonald, Dietmar Jannach, Gabriella Kazai, Franco Maria Nardini, Fabio Pinelli, Fabrizio Silvestri, Nicola Tonellotto:
Advances in Information Retrieval - 47th European Conference on Information Retrieval, ECIR 2025, Lucca, Italy, April 6-10, 2025, Proceedings, Part IV. Lecture Notes in Computer Science 15575, Springer 2025, ISBN 978-3-031-88716-1 [contents] - [e15]Claudia Hauff, Craig Macdonald, Dietmar Jannach, Gabriella Kazai, Franco Maria Nardini, Fabio Pinelli, Fabrizio Silvestri, Nicola Tonellotto:
Advances in Information Retrieval - 47th European Conference on Information Retrieval, ECIR 2025, Lucca, Italy, April 6-10, 2025, Proceedings, Part V. Lecture Notes in Computer Science 15576, Springer 2025, ISBN 978-3-031-88719-2 [contents] - [i46]Fangzheng Tian, Debasis Ganguly, Craig Macdonald:
Is Relevance Propagated from Retriever to Generator in RAG? CoRR abs/2502.15025 (2025) - [i45]Jinyuan Fang, Zaiqiao Meng, Craig Macdonald:
KiRAG: Knowledge-Driven Iterative Retriever for Enhancing Retrieval-Augmented Generation. CoRR abs/2502.18397 (2025) - 2024
- [j45]Siwei Liu, Xi Wang, Craig Macdonald, Iadh Ounis:
A Social-aware Gaussian Pre-trained model for effective cold-start recommendation. Inf. Process. Manag. 61(2): 103601 (2024) - [j44]Graham McDonald, Craig Macdonald, Iadh Ounis:
Report on the 46th European Conference on Information Retrieval (ECIR 2024). SIGIR Forum 58(1): 1-18 (2024) - [j43]Zixuan Yi, Iadh Ounis, Craig MacDonald:
Contrastive Graph Prompt-tuning for Cross-domain Recommendation. ACM Trans. Inf. Syst. 42(2): 60:1-60:28 (2024) - [j42]Yaxiong Wu, Craig Macdonald, Iadh Ounis:
Personalised Multi-modal Interactive Recommendation with Hierarchical State Representations. Trans. Recomm. Syst. 2(3): 21:1-21:25 (2024) - [c256]Jinyuan Fang, Zaiqiao Meng, Craig MacDonald:
REANO: Optimising Retrieval-Augmented Reader Models through Knowledge Graph Generation. ACL (1) 2024: 2094-2112 - [c255]Zeyuan Meng, Iadh Ounis, Craig Macdonald, Zixuan Yi:
Knowledge Graph Cross-View Contrastive Learning for Recommendation. ECIR (3) 2024: 3-18 - [c254]Erlend Frayling, Sean MacAvaney, Craig Macdonald, Iadh Ounis:
Effective Adhoc Retrieval Through Traversal of a Query-Document Graph. ECIR (3) 2024: 89-104 - [c253]Aleksandr V. Petrov, Sean MacAvaney, Craig Macdonald:
Shallow Cross-Encoders for Low-Latency Retrieval. ECIR (3) 2024: 151-166 - [c252]Aleksandr V. Petrov, Craig Macdonald:
Transformers for Sequential Recommendation. ECIR (5) 2024: 369-374 - [c251]Jinyuan Fang, Zaiqiao Meng, Craig MacDonald:
TRACE the Evidence: Constructing Knowledge-Grounded Reasoning Chains for Retrieval-Augmented Generation. EMNLP (Findings) 2024: 8472-8494 - [c250]Maria Vlachou, Craig Macdonald:
Coherence-based Query Performance Measures for Dense Retrieval. ICTIR 2024: 15-24 - [c249]Aleksandr V. Petrov, Craig Macdonald:
gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling (Extended Abstract). IJCAI 2024: 8447-8449 - [c248]Aleksandr Vladimirovich Petrov, Craig Macdonald, Nicola Tonellotto:
Efficient Inference of Sub-Item Id-based Sequential Recommendation Models with Millions of Items. RecSys 2024: 912-917 - [c247]Davide Abbattista, Vito Walter Anelli, Tommaso Di Noia, Craig MacDonald, Aleksandr Vladimirovich Petrov:
Enhancing Sequential Music Recommendation with Personalized Popularity Awareness. RecSys 2024: 1168-1173 - [c246]Xuejun Chang, Debabrata Mishra, Craig Macdonald, Sean MacAvaney:
Neural Passage Quality Estimation for Static Pruning. SIGIR 2024: 174-185 - [c245]Jack McKechnie, Graham McDonald, Craig Macdonald:
Bi-Objective Negative Sampling for Sensitivity-Aware Search. SIGIR 2024: 2296-2300 - [c244]Aleksandr V. Petrov, Craig Macdonald:
RecJPQ: Training Large-Catalogue Sequential Recommenders. WSDM 2024: 538-547 - [e14]Nazli Goharian, Nicola Tonellotto, Yulan He, Aldo Lipani, Graham McDonald, Craig Macdonald, Iadh Ounis:
Advances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part I. Lecture Notes in Computer Science 14608, Springer 2024, ISBN 978-3-031-56026-2 [contents] - [e13]Nazli Goharian, Nicola Tonellotto, Yulan He, Aldo Lipani, Graham McDonald, Craig Macdonald, Iadh Ounis:
Advances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part II. Lecture Notes in Computer Science 14609, Springer 2024, ISBN 978-3-031-56059-0 [contents] - [e12]Nazli Goharian, Nicola Tonellotto, Yulan He, Aldo Lipani, Graham McDonald, Craig Macdonald, Iadh Ounis:
Advances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part III. Lecture Notes in Computer Science 14610, Springer 2024, ISBN 978-3-031-56062-0 [contents] - [e11]Nazli Goharian, Nicola Tonellotto, Yulan He, Aldo Lipani, Graham McDonald, Craig Macdonald, Iadh Ounis:
Advances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part IV. Lecture Notes in Computer Science 14611, Springer 2024, ISBN 978-3-031-56065-1 [contents] - [e10]Nazli Goharian, Nicola Tonellotto, Yulan He, Aldo Lipani, Graham McDonald, Craig Macdonald, Iadh Ounis:
Advances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part V. Lecture Notes in Computer Science 14612, Springer 2024, ISBN 978-3-031-56068-2 [contents] - [e9]Nazli Goharian, Nicola Tonellotto, Yulan He, Aldo Lipani, Graham McDonald, Craig Macdonald, Iadh Ounis:
Advances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part VI. Lecture Notes in Computer Science 14613, Springer 2024, ISBN 978-3-031-56071-2 [contents] - [i44]Maria Vlachou, Craig Macdonald:
What Else Would I Like? A User Simulator using Alternatives for Improved Evaluation of Fashion Conversational Recommendation Systems. CoRR abs/2401.05783 (2024) - [i43]Aleksandr V. Petrov, Craig Macdonald:
Aligning GPTRec with Beyond-Accuracy Goals with Reinforcement Learning. CoRR abs/2403.04875 (2024) - [i42]Aleksandr V. Petrov, Sean MacAvaney, Craig Macdonald:
Shallow Cross-Encoders for Low-Latency Retrieval. CoRR abs/2403.20222 (2024) - [i41]Jinyuan Fang, Zaiqiao Meng, Craig Macdonald:
TRACE the Evidence: Constructing Knowledge-Grounded Reasoning Chains for Retrieval-Augmented Generation. CoRR abs/2406.11460 (2024) - [i40]Xuejun Chang, Debabrata Mishra, Craig Macdonald, Sean MacAvaney:
Neural Passage Quality Estimation for Static Pruning. CoRR abs/2407.12170 (2024) - [i39]Aleksandr V. Petrov, Craig Macdonald, Nicola Tonellotto:
Efficient Inference of Sub-Item Id-based Sequential Recommendation Models with Millions of Items. CoRR abs/2408.09992 (2024) - [i38]Davide Abbattista, Vito Walter Anelli, Tommaso Di Noia, Craig Macdonald, Aleksandr Vladimirovich Petrov:
Enhancing Sequential Music Recommendation with Personalized Popularity Awareness. CoRR abs/2409.04329 (2024) - [i37]Jorge Gabín, Javier Parapar, Craig Macdonald:
Beyond Questions: Leveraging ColBERT for Keyphrase Search. CoRR abs/2412.03193 (2024) - 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) - [c243]Xiao Wang, Sean MacAvaney, Craig Macdonald, Iadh Ounis:
Effective Contrastive Weighting for Dense Query Expansion. ACL (1) 2023: 12688-12704 - [c242]Jinyuan Fang, Zaiqiao Meng, Craig Macdonald:
KGPR: Knowledge Graph Enhanced Passage Ranking. CIKM 2023: 3880-3885 - [c241]Antonio Acquavia, Craig Macdonald, Nicola Tonellotto:
Static Pruning for Multi-Representation Dense Retrieval. DocEng 2023: 7:1-7:10 - [c240]Zixuan Yi, Iadh Ounis, Craig Macdonald:
Graph Contrastive Learning with Positional Representation for Recommendation. ECIR (2) 2023: 288-303 - [c239]Mitko Gospodinov, Sean MacAvaney, Craig Macdonald:
Doc2Query-: When Less is More. ECIR (2) 2023: 414-422 - [c238]Sarawoot Kongyoung, Craig MacDonald, Iadh Ounis:
Multi-Task Learning of Query Generation and Classification for Generative Conversational Question Rewriting. EMNLP (Findings) 2023: 13667-13678 - [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 - [i36]Mitko Gospodinov, Sean MacAvaney, Craig Macdonald:
Doc2Query-: When Less is More. CoRR abs/2301.03266 (2023) - [i35]Aleksandr V. Petrov, Craig Macdonald:
Generative Sequential Recommendation with GPTRec. CoRR abs/2306.11114 (2023) - [i34]Xiao Wang, Sean MacAvaney, Craig Macdonald, Iadh Ounis:
Generative Query Reformulation for Effective Adhoc Search. CoRR abs/2308.00415 (2023) - [i33]Aleksandr V. Petrov, Craig Macdonald:
gSASRec: Reducing Overconfidence in Sequential Recommendation Trained with Negative Sampling. CoRR abs/2308.07192 (2023) - [i32]Zixuan Yi, Iadh Ounis, Craig Macdonald:
Contrastive Graph Prompt-tuning for Cross-domain Recommendation. CoRR abs/2308.10685 (2023) - [i31]Maria Vlachou, Craig Macdonald:
On Coherence-based Predictors for Dense Query Performance Prediction. CoRR abs/2310.11405 (2023) - [i30]Zixuan Yi, Zijun Long, Iadh Ounis, Craig Macdonald, Richard McCreadie:
Large Multi-modal Encoders for Recommendation. CoRR abs/2310.20343 (2023) - [i29]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) - [i28]Aleksandr V. Petrov, Craig Macdonald:
RecJPQ: Training Large-Catalogue Sequential Recommenders. CoRR abs/2312.06165 (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) - no results
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, Craig Macdonald, Falk Scholer, J. Shane Culpepper:
On the Cost of Negation for Dynamic Pruning. ECIR 2018: 544-549 - [c176]Graham McDonald, Craig Macdonald, Iadh Ounis:
Towards Maximising Openness in Digital Sensitivity Review Using Reviewing Time Predictions. ECIR 2018: 699-706 - [c175]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 - [c174]Jarana Manotumruksa, Craig Macdonald, Iadh Ounis:
A Contextual Attention Recurrent Architecture for Context-Aware Venue Recommendation. SIGIR 2018: 555-564 - [c173]Richard McCreadie, Craig Macdonald, Iadh Ounis:
Automatic Ground Truth Expansion for Timeline Evaluation. SIGIR 2018: 685-694 - [c172]Craig Macdonald:
Combining Terrier with Apache Spark to create Agile Experimental Information Retrieval Pipelines. SIGIR 2018: 1309-1312 - [c171]Nicola Tonellotto, Craig Macdonald:
Efficient Query Processing Infrastructures: A half-day tutorial at SIGIR 2018. SIGIR 2018: 1403-1406 - [r2]Craig MacDonald, Iadh Ounis:
WEB Information Retrieval Models. Encyclopedia of Database Systems (2nd ed.) 2018 - 2017
- [j21]Leif Azzopardi, Craig Macdonald, Iadh Ounis, Martin Halvey:
Report on the Information Retrieval Festival (IRFest2017). SIGIR Forum 51(1): 12-28 (2017) - [c170]Karin Sim Smith, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Analyzing Disproportionate Reaction via Comparative Multilingual Targeted Sentiment in Twitter. ASONAM 2017: 317-320 - [c169]Xiao Yang, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Transfer Learning for Multi-language Twitter Election Classification. ASONAM 2017: 341-348 - [c168]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 - [c167]Jarana Manotumruksa, Craig Macdonald, Iadh Ounis:
A Deep Recurrent Collaborative Filtering Framework for Venue Recommendation. CIKM 2017: 1429-1438 - [c166]Jarana Manotumruksa, Craig Macdonald, Iadh Ounis:
A Personalised Ranking Framework with Multiple Sampling Criteria for Venue Recommendation. CIKM 2017: 1469-1478 - [c165]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 - [c164]Graham McDonald, Craig Macdonald, Iadh Ounis:
Enhancing Sensitivity Classification with Semantic Features Using Word Embeddings. ECIR 2017: 450-463 - [c163]Jarana Manotumruksa, Craig Macdonald, Iadh Ounis:
Matrix Factorisation with Word Embeddings for Rating Prediction on Location-Based Social Networks. ECIR 2017: 647-654 - [c162]Mehmet Akcay, Ismail Sengor Altingovde, Craig Macdonald, Iadh Ounis:
On the Additivity and Weak Baselines for Search Result Diversification Research. ICTIR 2017: 109-116 - [c161]Craig Macdonald, Nicola Tonellotto:
Upper Bound Approximation for BlockMaxWand. ICTIR 2017: 273-276 - [c160]Craig MacDonald, Nicola Tonellotto, Iadh Ounis:
Efficient & Effective Selective Query Rewriting with Efficiency Predictions. SIGIR 2017: 495-504 - [c159]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
- [c158]Jarana Manotumruksa, Craig MacDonald, Iadh Ounis:
Regularising Factorised Models for Venue Recommendation using Friends and their Comments. CIKM 2016: 1981-1984 - [c157]Jarana Manotumruksa, Craig MacDonald, Iadh Ounis:
Predicting Contextually Appropriate Venues in Location-Based Social Networks. CLEF 2016: 96-109 - [c156]Jimmy Lin, Matt Crane, Andrew Trotman, Jamie Callan, Ishan Chattopadhyaya, John Foley, Grant Ingersoll, Craig MacDonald, Sebastiano Vigna:
Toward Reproducible Baselines: The Open-Source IR Reproducibility Challenge. ECIR 2016: 408-420 - [c155]Stuart Mackie, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Experiments in Newswire Summarisation. ECIR 2016: 421-435 - [c154]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 - [c153]Saul Vargas, Richard McCreadie, Craig MacDonald, Iadh Ounis:
Comparing Overall and Targeted Sentiments in Social Media during Crises. ICWSM 2016: 695-698 - [c152]Bekir Taner Dinçer, Craig Macdonald, Iadh Ounis:
Risk-Sensitive Evaluation and Learning to Rank using Multiple Baselines. SIGIR 2016: 483-492 - [c151]Sean Moran, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Enhancing First Story Detection using Word Embeddings. SIGIR 2016: 821-824 - [c150]Anjie Fang, Craig Macdonald, Iadh Ounis, Philip Habel:
Examining the Coherence of the Top Ranked Tweet Topics. SIGIR 2016: 825-828 - [c149]Anjie Fang, Craig Macdonald, Iadh Ounis, Philip Habel:
Using Word Embedding to Evaluate the Coherence of Topics from Twitter Data. SIGIR 2016: 1057-1060 - [c148]Richard McCreadie, Craig Macdonald, Iadh Ounis:
EAIMS: Emergency Analysis Identification and Management System. SIGIR 2016: 1101-1104 - [c147]Jarana Manotumruksa, Craig MacDonald, Iadh Ounis:
University of Glasgow Terrier Team at TREC 2016: Experiments in Contextual Suggestions. TREC 2016 - [e5]Krisztian Balog, Linda Cappellato, Nicola Ferro, Craig Macdonald:
Working Notes of CLEF 2016 - Conference and Labs of the Evaluation forum, Évora, Portugal, 5-8 September, 2016. CEUR Workshop Proceedings 1609, CEUR-WS.org 2016 [contents] - [e4]Norbert Fuhr, Paulo Quaresma, Teresa Gonçalves, Birger Larsen, Krisztian Balog, Craig Macdonald, Linda Cappellato, Nicola Ferro:
Experimental IR Meets Multilinguality, Multimodality, and Interaction - 7th International Conference of the CLEF Association, CLEF 2016, Évora, Portugal, September 5-8, 2016, Proceedings. Lecture Notes in Computer Science 9822, Springer 2016, ISBN 978-3-319-44563-2 [contents] - [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
- [j20]Rodrygo L. T. Santos, Craig MacDonald, Iadh Ounis:
Search Result Diversification. Found. Trends Inf. Retr. 9(1): 1-90 (2015) - [j19]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) - [c146]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 - [c145]Eugene Kharitonov, Craig Macdonald, Pavel Serdyukov, Iadh Ounis:
Generalized Team Draft Interleaving. CIKM 2015: 773-782 - [c144]Giacomo Berardi, Andrea Esuli, Craig Macdonald, Iadh Ounis, Fabrizio Sebastiani:
Semi-Automated Text Classification for Sensitivity Identification. CIKM 2015: 1711-1714 - [c143]Nut Limsopatham, Craig Macdonald, Iadh Ounis:
Modelling the Usefulness of Document Collections for Query Expansion in Patient Search. CIKM 2015: 1739-1742 - [c142]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 - [c141]Thibaut Thonet, Romain Deveaud, Iadh Ounis, Craig Macdonald:
Suggestion contextuelle composite. CORIA 2015: 89-104 - [c140]Craig Macdonald, Ciaran McCreesh, Alice Miller, Patrick Prosser:
Constructing Sailing Match Race Schedules: Round-Robin Pairing Lists. CP 2015: 671-686 - [c139]Anjie Fang, Iadh Ounis, Philip Habel, Craig MacDonald, Nut Limsopatham:
Topic-centric Classification of Twitter User's Political Orientation. FDIA 2015 - [c138]Craig Macdonald, Bekir Taner Dinçer, Iadh Ounis:
Transferring Learning To Rank Models for Web Search. ICTIR 2015: 41-50 - [c137]Graham McDonald, Craig Macdonald, Iadh Ounis:
Using Part-of-Speech N-grams for Sensitive-Text Classification. ICTIR 2015: 381-384 - [c136]Graham McDonald, Romain Deveaud, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Tweet Enrichment for Effective Dimensions Classification in Online Reputation Management. ICWSM 2015: 654-657 - [c135]Saúl Vargas, Craig Macdonald, Iadh Ounis:
Analysing Compression Techniques for In-Memory Collaborative Filtering. RecSys Posters 2015 - [c134]Eugene Kharitonov, Craig Macdonald, Pavel Serdyukov, Iadh Ounis:
Optimised Scheduling of Online Experiments. SIGIR 2015: 453-462 - [c133]Eugene Kharitonov, Aleksandr Vorobev, Craig Macdonald, Pavel Serdyukov, Iadh Ounis:
Sequential Testing for Early Stopping of Online Experiments. SIGIR 2015: 473-482 - [c132]M-Dyaa Albakour, Craig Macdonald, Iadh Ounis:
Using Sensor Metadata Streams to Identify Topics of Local Events in the City. SIGIR 2015: 711-714 - [c131]Matteo Catena, Craig Macdonald, Nicola Tonellotto:
Load-sensitive CPU Power Management for Web Search Engines. SIGIR 2015: 751-754 - [c130]Giovanni Di Santo, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Comparing Approaches for Query Autocompletion. SIGIR 2015: 775-778 - [c129]Anjie Fang, Iadh Ounis, Philip Habel, Craig Macdonald, Nut Limsopatham:
Topic-centric Classification of Twitter User's Political Orientation. SIGIR 2015: 791-794 - [c128]Richard McCreadie, Saul Vargas, Craig MacDonald, Iadh Ounis, Stuart Mackie, Jarana Manotumruksa, Graham McDonald:
University of Glasgow at TREC 2015: Experiments with Terrier in Contextual Suggestion, Temporal Summarisation and Dynamic Domain Tracks. TREC 2015 - [c127]Richard McCreadie, Craig Macdonald, Iadh Ounis:
Crowdsourced Rumour Identification During Emergencies. WWW (Companion Volume) 2015: 965-970 - [c126]Richard McCreadie, Karolin Kappler, Andreas Kaltenbrunner, Magdalini Kardara, Craig Macdonald, John Soldatos, Iadh Ounis:
SUPER: Towards the use of Social Sensors for Security Assessments and Proactive Management of Emergencies. WWW (Companion Volume) 2015: 1217-1220 - [e3]Yashar Moshfeghi, Iadh Ounis, Craig Macdonald, Joemon M. Jose, Peter Triantafillou, Mark Livingston, Piyushimita Thakuriah:
Proceedings of the ACM First International Workshop on Understanding the City with Urban Informatics, UCUI 2015, Melbourne, Australia, October 19, 2015. ACM 2015, ISBN 978-1-4503-3786-1 [contents] - 2014
- [j18]M-Dyaa Albakour, Craig Macdonald, Iadh Ounis, Charles L. A. Clarke, Veli Bicer:
Report on the 1st International Workshop on Information Access in Smart Cities (i-ASC 2014). SIGIR Forum 48(2): 96-104 (2014) - [c125]Miles Osborne, Sean Moran, Richard McCreadie, Alexander von Lünen, Martin D. Sykora, Amparo Elizabeth Cano, Neil Ireson, Craig Macdonald, Iadh Ounis, Yulan He, Tom Jackson, Fabio Ciravegna, Ann O'Brien:
Real-Time Detection, Tracking, and Monitoring of Automatically Discovered Events in Social Media. ACL (System Demonstrations) 2014: 37-42 - [c124]Richard McCreadie, Craig Macdonald, Iadh Ounis:
Incremental Update Summarization: Adaptive Sentence Selection based on Prevalence and Novelty. CIKM 2014: 301-310 - [c123]Nut Limsopatham, Craig Macdonald, Iadh Ounis:
Modelling Relevance towards Multiple Inclusion Criteria when Ranking Patients. CIKM 2014: 1639-1648 - [c122]Romain Deveaud, M-Dyaa Albakour, Craig Macdonald, Iadh Ounis:
On the Importance of Venue-Dependent Features for Learning to Rank Contextual Suggestions. CIKM 2014: 1827-1830 - [c121]Romain Deveaud, M-Dyaa Albakour, Jarana Manotumruksa, Craig Macdonald, Iadh Ounis:
SmartVenues: Recommending Popular and Personalised Venues in a City. CIKM 2014: 2078-2080 - [c120]Richard McCreadie, Craig Macdonald, Iadh Ounis, Jon Brassey:
A Study of Personalised Medical Literature Search. CLEF 2014: 74-85 - [c119]Stuart Mackie, Richard McCreadie, Craig Macdonald, Iadh Ounis:
Comparing Algorithms for Microblog Summarisation. CLEF 2014: 153-159 - [c118]Graham McDonald, Romain Deveaud, Richard McCreadie, Timothy Gollins, Craig Macdonald, Iadh Ounis:
University of Glasgow Terrier Team / Project Abacá at RepLab 2014: Reputation Dimensions Task. CLEF (Working Notes) 2014: 1500-1504 - [c117]Bekir Taner Dinçer, Iadh Ounis, Craig Macdonald:
Tackling Biased Baselines in the Risk-Sensitive Evaluation of Retrieval Systems. ECIR 2014: 26-38 - [c116]Matteo Catena, Craig Macdonald, Iadh Ounis:
On Inverted Index Compression for Search Engine Efficiency. ECIR 2014: 359-371 - [c115]Graham McDonald, Craig Macdonald, Iadh Ounis, Timothy Gollins:
Towards a Classifier for Digital Sensitivity Review. ECIR 2014: 500-506 - [c114]M-Dyaa Albakour, Craig Macdonald, Iadh Ounis, Charles L. A. Clarke, Veli Bicer:
Information Access in Smart Cities (i-ASC). ECIR 2014: 810-814 - [c113]Stuart Mackie, Richard McCreadie, Craig Macdonald, Iadh Ounis:
On choosing an effective automatic evaluation metric for microblog summarisation. IIiX 2014: 115-124 - [c112]M-Dyaa Albakour, Romain Deveaud, Craig Macdonald, Iadh Ounis:
Diversifying contextual suggestions from location-based social networks. IIiX 2014: 125-134 - [c111]Bekir Taner Dinçer, Craig Macdonald, Iadh Ounis:
Hypothesis testing for the risk-sensitive evaluation of retrieval systems. SIGIR 2014: 23-32 - [c110]Timothy Gollins, Graham McDonald, Craig Macdonald, Iadh Ounis:
On Using Information Retrieval for the Selection and Sensitivity Review of Digital Public Records. PIR@SIGIR 2014: 39-40 - [c109]Kevyn Collins-Thompson, Craig Macdonald, Paul N. Bennett, Fernando Diaz, Ellen M. Voorhees:
TREC 2014 Web Track Overview. TREC 2014 - [c108]Richard McCreadie, Romain Deveaud, M-Dyaa Albakour, Stuart Mackie, Nut Limsopatham, Craig Macdonald, Iadh Ounis, Thibaut Thonet, Bekir Taner Dinçer:
University of Glasgow at TREC 2014: Experiments with Terrier in Contextual Suggestion, Temporal Summarisation and Web Tracks. TREC 2014 - [c107]Ana Freire, Craig Macdonald, Nicola Tonellotto, Iadh Ounis, Fidel Cacheda:
A self-adapting latency/power tradeoff model for replicated search engines. WSDM 2014: 13-22 - [c106]Ismail Sengör Altingövde, Berkant Barla Cambazoglu, Craig Macdonald, Nicola Tonellotto:
Workshop on large-scale and distributed systems for information retrieval (LSDS-IR 2014). WSDM 2014: 691-692 - 2013
- [j17]Richard McCreadie, Craig Macdonald, Iadh Ounis:
Identifying top news using crowdsourcing. Inf. Retr. 16(2): 179-209 (2013) - [j16]Tetsuya Sakai, Noriko Kando, Craig Macdonald, Ian Soboroff:
Introduction to the special issue on search intents and diversification. Inf. Retr. 16(4): 427-428 (2013) - [j15]Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Learning to rank query suggestions for adhoc and diversity search. Inf. Retr. 16(4): 429-451 (2013) - [j14]Craig Macdonald, Rodrygo L. T. Santos, Iadh Ounis:
The whens and hows of learning to rank for web search. Inf. Retr. 16(5): 584-628 (2013) - [j13]Veronica Gil-Costa, Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Modelling efficient novelty-based search result diversification in metric spaces. J. Discrete Algorithms 18: 75-88 (2013) - [j12]Craig Macdonald, Rodrygo L. T. Santos, Iadh Ounis, Ben He:
About learning models with multiple query-dependent features. ACM Trans. Inf. Syst. 31(3): 11 (2013) - [c105]Richard McCreadie, Craig Macdonald, Iadh Ounis, Miles Osborne, Sasa Petrovic:
Scalable distributed event detection for Twitter. IEEE BigData 2013: 543-549 - [c104]Daniele Broccolo, Craig Macdonald, Salvatore Orlando, Iadh Ounis, Raffaele Perego, Fabrizio Silvestri, Nicola Tonellotto:
Load-sensitive selective pruning for distributed search. CIKM 2013: 379-388 - [c103]M-Dyaa Albakour, Craig Macdonald, Iadh Ounis:
On sparsity and drift for effective real-time filtering in microblogs. CIKM 2013: 419-428 - [c102]Eugene Kharitonov, Craig Macdonald, Pavel Serdyukov, Iadh Ounis:
Using historical click data to increase interleaving sensitivity. CIKM 2013: 679-688 - [c101]Nut Limsopatham, Craig Macdonald, Iadh Ounis:
Learning to handle negated language in medical records search. CIKM 2013: 1431-1440 - [c100]Nut Limsopatham, Craig Macdonald, Iadh Ounis:
Learning to selectively rank patients' medical history. CIKM 2013: 1833-1836 - [c99]Eugene Kharitonov, Craig Macdonald, Pavel Serdyukov, Iadh Ounis:
Intent models for contextualising and diversifying query suggestions. CIKM 2013: 2303-2308 - [c98]Nut Limsopatham, Craig Macdonald, Iadh Ounis:
University of Glasgow at CLEF 2013: Experiments in eHealth Task 3 with Terrier. CLEF (Working Notes) 2013 - [c97]Nut Limsopatham, Craig Macdonald, Iadh Ounis:
Aggregating Evidence from Hospital Departments to Improve Medical Records Search. ECIR 2013: 279-291 - [c96]Ana Freire, Craig Macdonald, Nicola Tonellotto, Iadh Ounis, Fidel Cacheda:
Hybrid Query Scheduling for a Replicated Search Engine. ECIR 2013: 435-446 - [c95]Nut Limsopatham, Craig Macdonald, Iadh Ounis:
A Task-Specific Query and Document Representation for Medical Records Search. ECIR 2013: 747-751 - [c94]Sasa Petrovic, Miles Osborne, Richard McCreadie, Craig Macdonald, Iadh Ounis, Luke Shrimpton:
Can Twitter Replace Newswire for Breaking News? ICWSM 2013 - [c93]Nut Limsopatham, Craig Macdonald, Iadh Ounis:
Inferring conceptual relationships to improve medical records search. OAIR 2013: 1-8 - [c92]Saul Vargas, Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Selecting effective expansion terms for diversity. OAIR 2013: 69-76 - [c91]M-Dyaa Albakour, Craig Macdonald, Iadh Ounis:
Identifying local events by using microblogs as social sensors. OAIR 2013: 173-180 - [c90]Richard McCreadie, Craig Macdonald:
Relevance in microblogs: enhancing tweet retrieval using hyperlinked documents. OAIR 2013: 189-196 - [c89]Richard McCreadie, Craig Macdonald, Iadh Ounis:
News vertical search: when and what to display to users. SIGIR 2013: 253-262 - [c88]Eugene Kharitonov, Craig Macdonald, Pavel Serdyukov, Iadh Ounis:
User model-based metrics for offline query suggestion evaluation. SIGIR 2013: 633-642 - [c87]Nut Limsopatham, Craig Macdonald, Iadh Ounis:
Learning to combine representations for medical records search. SIGIR 2013: 833-836 - [c86]Daniele Broccolo, Craig Macdonald, Salvatore Orlando, Iadh Ounis, Raffaele Perego, Fabrizio Silvestri, Nicola Tonellotto:
Query Processing in Highly-Loaded Search Engines. SPIRE 2013: 49-55 - [c85]Richard McCreadie, M-Dyaa Albakour, Stuart Mackie, Nut Limsopatham, Craig Macdonald, Iadh Ounis, Bekir Taner Dinçer:
University of Glasgow at TREC 2013: Experiments with Terrier in Contextual Suggestion, Temporal Summarisation and Web Tracks. TREC 2013 - [c84]Nicola Tonellotto, Craig Macdonald, Iadh Ounis:
Efficient and effective retrieval using selective pruning. WSDM 2013: 63-72 - [c83]Nicola Tonellotto, Craig Macdonald, Ismail Sengör Altingövde:
Workshop on large-scale and distributed systems for information retrieval (LSDS-IR 2013). WSDM 2013: 791-792 - [i1]Eugene Kharitonov, Craig Macdonald, Pavel Serdyukov, Iadh Ounis:
Intent Models for Contextualising and Diversifying Query Suggestions. CoRR abs/1312.1611 (2013) - 2012
- [j11]Rodrygo L. T. Santos, Craig Macdonald, Richard McCreadie, Iadh Ounis, Ian Soboroff:
Information Retrieval on the Blogosphere. Found. Trends Inf. Retr. 6(1): 1-125 (2012) - [j10]Richard McCreadie, Craig Macdonald, Iadh Ounis:
MapReduce indexing strategies: Studying scalability and efficiency. Inf. Process. Manag. 48(5): 873-888 (2012) - [j9]Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
On the role of novelty for search result diversification. Inf. Retr. 15(5): 478-502 (2012) - [c82]Richard McCreadie, Craig Macdonald, Iadh Ounis, Jim Giles, Ferris Jabr:
An examination of content farms in web search using crowdsourcing. CIKM 2012: 2551-2554 - [c81]Craig Macdonald, Rodrygo L. T. Santos, Iadh Ounis:
On the usefulness of query features for learning to rank. CIKM 2012: 2559-2562 - [c80]Dean McCullough, Jimmy Lin, Craig Macdonald, Iadh Ounis, Richard McCreadie:
Evaluating Real-Time Search over Tweets. ICWSM 2012 - [c79]M-Dyaa Albakour, Craig Macdonald, Iadh Ounis, Aristodemos Pnevmatikakis, John Soldatos:
SMART: An Open Source Framework for Searching the Physical World. OSIR@SIGIR 2012: 48-51 - [c78]Craig Macdonald, Richard McCreadie, Rodrygo L. T. Santos, Iadh Ounis:
From Puppy to Maturity: Experiences in Developing Terrier. OSIR@SIGIR 2012: 60-63 - [c77]Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
Learning to predict response times for online query scheduling. SIGIR 2012: 621-630 - [c76]Richard McCreadie, Craig Macdonald, Iadh Ounis:
CrowdTerrier: automatic crowdsourced relevance assessments with terrier. SIGIR 2012: 1005 - [c75]Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
Effect of dynamic pruning safety on learning to rank effectiveness. SIGIR 2012: 1051-1052 - [c74]Nut Limsopatham, Craig Macdonald, Richard McCreadie, Iadh Ounis:
Exploiting term dependence while handling negation in medical search. SIGIR 2012: 1065-1066 - [c73]Richard McCreadie, Ian Soboroff, Jimmy Lin, Craig Macdonald, Iadh Ounis, Dean McCullough:
On building a reusable Twitter corpus. SIGIR 2012: 1113-1114 - [c72]Ana Freire, Craig Macdonald, Nicola Tonellotto, Iadh Ounis, Fidel Cacheda:
Scheduling queries across replicas. SIGIR 2012: 1139-1140 - [c71]Nut Limsopatham, Richard McCreadie, M-Dyaa Albakour, Craig Macdonald, Rodrygo L. T. Santos, Iadh Ounis:
University of Glasgow at TREC 2012: Experiments with Terrier in Medical Records, Microblog, and Web Tracks. TREC 2012 - [c70]Ian Soboroff, Iadh Ounis, Craig Macdonald, Jimmy Lin:
Overview of the TREC-2012 Microblog Track. TREC 2012 - [c69]Craig Macdonald, Jun Wang, Charles L. A. Clarke:
2nd international workshop on diversity in document retrieval (DDR 2012). WSDM 2012: 769-770 - [c68]John Soldatos, Moez Draief, Craig Macdonald, Iadh Ounis:
Multimedia search over integrated social and sensor networks. WWW (Companion Volume) 2012: 283-286 - 2011
- [j8]Craig Macdonald, Iadh Ounis:
The influence of the document ranking in expert search. Inf. Process. Manag. 47(3): 376-390 (2011) - [j7]Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Mimicking Web search engines for expert search. Inf. Process. Manag. 47(4): 467-481 (2011) - [j6]Craig Macdonald, Charles L. A. Clarke, Jun Wang:
The 1st international workshop on diversity in document retrieval. SIGIR Forum 45(2): 87-93 (2011) - [j5]Craig Macdonald, Iadh Ounis, Nicola Tonellotto:
Upper-bound approximations for dynamic pruning. ACM Trans. Inf. Syst. 29(4): 17:1-17:28 (2011) - [c67]Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Effectiveness beyond the first crawl tier. CIKM 2011: 1937-1940 - [c66]Craig Macdonald, Iadh Ounis:
Learning Models for Ranking Aggregates. ECIR 2011: 517-529 - [c65]Matt-Mouley Bouamrane, Craig Macdonald, Iadh Ounis, Frances S. Mair:
Protocol-Driven Searches for Medical and Health-Sciences Systematic Reviews. ICTIR 2011: 188-200 - [c64]Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Aggregated Search Result Diversification. ICTIR 2011: 250-261 - [c63]Craig Macdonald, Nicola Tonellotto, Iadh Ounis:
On Upper Bounds for Dynamic Pruning. ICTIR 2011: 313-317 - [c62]F. Javier Ortega, Craig Macdonald, José A. Troyano, Fermín L. Cruz, Fernando Enríquez:
Combining Textual Content and Hyperlinks in Web Spam Detection. NLDB 2011: 266-269 - [c61]Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
University of Glasgow at the NTCIR-9 Intent task: Experiments with Terrier on Subtopic Mining and Document Ranking. NTCIR 2011 - [c60]Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Intent-aware search result diversification. SIGIR 2011: 595-604 - [c59]Nicola Tonellotto, Craig Macdonald, Iadh Ounis:
Effect of different docid orderings on dynamic pruning retrieval strategies. SIGIR 2011: 1179-1180 - [c58]Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
On the suitability of diversity metrics for learning-to-rank for diversity. SIGIR 2011: 1185-1186 - [c57]Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
How diverse are web search results? SIGIR 2011: 1187-1188 - [c56]Nut Limsopatham, Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Disambiguating biomedical acronyms using EMIM. SIGIR 2011: 1213-1214 - [c55]Richard McCreadie, Craig Macdonald, Iadh Ounis:
A Learned Approach for Ranking News in Real-Time Using the Blogosphere. SPIRE 2011: 104-116 - [c54]Veronica Gil-Costa, Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Sparse Spatial Selection for Novelty-Based Search Result Diversification. SPIRE 2011: 344-355 - [c53]Nut Limsopatham, Craig Macdonald, Iadh Ounis, Graham McDonald, Matt-Mouley Bouamrane:
University of Glasgow at Medical Records Track: Experiments with Terrier. TREC 2011 - [c52]Richard McCreadie, Craig Macdonald, Rodrygo L. T. Santos, Iadh Ounis:
University of Glasgow at TREC 2011: Experiments with Terrier in Crowdsourcing, Microblog, and Web Tracks. TREC 2011 - [c51]Iadh Ounis, Craig Macdonald, Jimmy Lin, Ian Soboroff:
Overview of the TREC 2011 Microblog Track. TREC 2011 - [e2]Craig Macdonald, Iadh Ounis, Ian Ruthven:
Proceedings of the 20th ACM Conference on Information and Knowledge Management, CIKM 2011, Glasgow, United Kingdom, October 24-28, 2011. ACM 2011, ISBN 978-1-4503-0717-8 [contents] - 2010
- [j4]Craig Macdonald, Rodrygo L. T. Santos, Iadh Ounis, Ian Soboroff:
Blog track research at TREC. SIGIR Forum 44(1): 58-75 (2010) - [c50]F. Javier Ortega, Craig Macdonald, José A. Troyano, Fermín L. Cruz:
Spam detection with a content-based random-walk algorithm. SMUC@CIKM 2010: 45-52 - [c49]Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Selectively diversifying web search results. CIKM 2010: 1179-1188 - [c48]Rodrygo L. T. Santos, Jie Peng, Craig Macdonald, Iadh Ounis:
Explicit Search Result Diversification through Sub-queries. ECIR 2010: 87-99 - [c47]Jie Peng, Craig Macdonald, Iadh Ounis:
Learning to Select a Ranking Function. ECIR 2010: 114-126 - [c46]Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Voting for related entities. RIAO 2010: 1-8 - [c45]Richard McCreadie, Craig Macdonald, Iadh Ounis:
News article ranking: leveraging the wisdom of bloggers. RIAO 2010: 40-48 - [c44]Nicola Tonellotto, Craig Macdonald, Iadh Ounis:
Efficient Dynamic Pruning with Proximity Support. LSDS-IR@SIGIR 2010: 31-35 - [c43]Rodrygo L. T. Santos, Richard McCreadie, Craig Macdonald, Iadh Ounis:
University of Glasgow at TREC 2010: Experiments with Terrier in Blog and Web Tracks. TREC 2010 - [c42]Rodrygo L. T. Santos, Craig Macdonald, Iadh Ounis:
Exploiting query reformulations for web search result diversification. WWW 2010: 881-890 - no results
2000 – 2009
- 2009
- [b1]Craig Macdonald:
The voting model for people search. University of Glasgow, UK, 2009 - [j3]Craig Macdonald, Iadh Ounis:
Searching for Expertise: Experiments with the Voting Model. Comput. J. 52(7): 729-748 (2009) - [j2]Craig Macdonald:
The voting model for people search. SIGIR Forum 43(1): 73 (2009) - [c41]Craig Macdonald, Iadh Ounis:
The influence of the document ranking in expert search. CIKM 2009: 1983-1986 - [c40]Jie Peng, Craig Macdonald, Ben He, Iadh Ounis:
A study of selective collection enrichment for enterprise search. CIKM 2009: 1999-2002 - [c39]Rodrygo L. T. Santos, Ben He, Craig Macdonald, Iadh Ounis:
Integrating Proximity to Subjective Sentences for Blog Opinion Retrieval. ECIR 2009: 325-336 - [c38]Craig Macdonald, Iadh Ounis, Ian Soboroff:
Is spam an issue for opinionated blog post search? SIGIR 2009: 710-711 - [c37]Craig Macdonald, Iadh Ounis:
On perfect document rankings for expert search. SIGIR 2009: 740-741 - [c36]Richard McCreadie, Craig Macdonald, Iadh Ounis:
On single-pass indexing with MapReduce. SIGIR 2009: 742-743 - [c35]Craig Macdonald, Ryen W. White:
Usefulness of click-through data in expert search. SIGIR 2009: 816-817 - [c34]Richard McCreadie, Craig Macdonald, Iadh Ounis:
Comparing Distributed Indexing: To MapReduce or Not? LSDS-IR@SIGIR 2009 - [c33]Duncan McDougall, Craig Macdonald:
Expertise search in academia using facets. SIGIR 2009: 834 - [c32]Craig Macdonald, Iadh Ounis, Ian Soboroff:
Overview of the TREC 2009 Blog Track. TREC 2009 - [c31]Richard McCreadie, Craig Macdonald, Iadh Ounis, Jie Peng, Rodrygo L. T. Santos:
University of Glasgow at TREC 2009: Experiments with Terrier. TREC 2009 - [c30]Craig Macdonald, Iadh Ounis:
Usefulness of quality click-through data for training. WSCD@WSDM 2009: 75-79 - [r1]Craig Macdonald, Iadh Ounis:
WEB Information Retrieval Models. Encyclopedia of Database Systems 2009: 3479-3482 - 2008
- [j1]Craig Macdonald, Iadh Ounis:
Voting techniques for expert search. Knowl. Inf. Syst. 16(3): 259-280 (2008) - [c29]Craig Macdonald, Iadh Ounis:
Key blog distillation: ranking aggregates. CIKM 2008: 1043-1052 - [c28]Ben He, Craig Macdonald, Jiyin He, Iadh Ounis:
An effective statistical approach to blog post opinion retrieval. CIKM 2008: 1063-1072 - [c27]Craig Macdonald, David Hannah, Iadh Ounis:
High Quality Expertise Evidence for Expert Search. ECIR 2008: 283-295 - [c26]Craig Macdonald, Iadh Ounis:
Expert Search Evaluation by Supporting Documents. ECIR 2008: 555-563 - [c25]David Hannah, Craig Macdonald, Iadh Ounis:
Analysis of Link Graph Compression Techniques. ECIR 2008: 596-601 - [c24]Iadh Ounis, Craig Macdonald, Ian Soboroff:
On the TREC Blog Track. ICWSM 2008 - [c23]Ben He, Craig Macdonald, Iadh Ounis:
Retrieval sensitivity under training using different measures. SIGIR 2008: 67-74 - [c22]Ben He, Craig Macdonald, Iadh Ounis:
Ranking opinionated blog posts using OpinionFinder. SIGIR 2008: 727-728 - [c21]Craig Macdonald, Ben He, Iadh Ounis, Ian Soboroff:
Limits of opinion-finding baseline systems. SIGIR 2008: 747-748 - [c20]Jie Peng, Craig Macdonald, Iadh Ounis:
Automatic document prior feature selection for web retrieval. SIGIR 2008: 761-762 - [c19]Ben He, Craig Macdonald, Iadh Ounis, Jie Peng, Rodrygo L. T. Santos:
University of Glasgow at TREC 2008: Experiments in Blog, Enterprise, and Relevance Feedback Tracks with Terrier. TREC 2008 - [c18]Iadh Ounis, Craig MacDonald, Ian Soboroff:
Overview of the TREC 2008 Blog Track. TREC 2008 - [e1]Craig Macdonald, Iadh Ounis, Vassilis Plachouras, Ian Ruthven, Ryen W. White:
Advances in Information Retrieval , 30th European Conference on IR Research, ECIR 2008, Glasgow, UK, March 30-April 3, 2008. Proceedings. Lecture Notes in Computer Science 4956, Springer 2008, ISBN 978-3-540-78645-0 [contents] - 2007
- [c17]Craig Macdonald, Iadh Ounis:
Expertise drift and query expansion in expert search. CIKM 2007: 341-350 - [c16]Craig Macdonald, Iadh Ounis:
Using Relevance Feedback in Expert Search. ECIR 2007: 431-443 - [c15]Jie Peng, Craig Macdonald, Ben He, Iadh Ounis:
Combination of Document Priors in Web Information Retrieval. RIAO 2007: 596-611 - [c14]Jie Peng, Craig Macdonald, Ben He, Vassilis Plachouras, Iadh Ounis:
Incorporating term dependency in the dfr framework. SIGIR 2007: 843-844 - [c13]David Hannah, Craig Macdonald, Jie Peng, Ben He, Iadh Ounis:
University of Glasgow at TREC 2007: Experiments in Blog and Enterprise Tracks with Terrier. TREC 2007 - [c12]Craig Macdonald, Iadh Ounis, Ian Soboroff:
Overview of the TREC 2007 Blog Track. TREC 2007 - 2006
- [c11]Craig Macdonald, Iadh Ounis:
Voting for candidates: adapting data fusion techniques for an expert search task. CIKM 2006: 387-396 - [c10]Craig Macdonald, Iadh Ounis:
Combining fields in known-item email search. SIGIR 2006: 675-676 - [c9]Craig Macdonald, Iadh Ounis:
Searching for expertise using the terrier platform. SIGIR 2006: 732 - [c8]Christina Lioma, Craig Macdonald, Vassilis Plachouras, Jie Peng, Ben He, Iadh Ounis:
University of Glasgow at TREC 2006: Experiments in Terabyte and Enterprise Tracks with Terrier. TREC 2006 - [c7]Iadh Ounis, Craig Macdonald, Maarten de Rijke, Gilad Mishne, Ian Soboroff:
Overview of the TREC 2006 Blog Track. TREC 2006 - 2005
- [c6]Christina Lioma, Craig Macdonald, Ben He, Vassilis Plachouras, Iadh Ounis:
Applying Light Natural Language Processing to Ad-Hoc Cross Language Information Retrieval. CLEF 2005: 170-178 - [c5]Christina Lioma, Craig Macdonald, Ben He, Vassilis Plachouras, Iadh Ounis:
Applying Light Natural Language Processing to Ad-Hoc Cross Language Information Retrieval. CLEF (Working Notes) 2005 - [c4]Craig Macdonald, Vassilis Plachouras, Ben He, Christina Lioma, Iadh Ounis:
University of Glasgow at WebCLEF 2005: Experiments in Per-Field Normalisation and Language Specific Stemming. CLEF 2005: 898-907 - [c3]Craig Macdonald, Vassilis Plachouras, Ben He, Christina Lioma, Iadh Ounis:
University of Glasgow at WebCLEF 2005: Experiments in per-field Normalisation and Language Specific Stemming. CLEF (Working Notes) 2005 - [c2]Iadh Ounis, Gianni Amati, Vassilis Plachouras, Ben He, Craig Macdonald, Douglas Johnson:
Terrier Information Retrieval Platform. ECIR 2005: 517-519 - [c1]Craig Macdonald, Ben He, Vassilis Plachouras, Iadh Ounis:
University of Glasgow at TREC 2005: Experiments in Terabyte and Enterprise Tracks with Terrier. TREC 2005 - no results
Coauthor Index
[i30] [p1] [j34] [c202] [c201] [i10] [j26] [i6] [j23] [j22] [c183] [c180] [c179] [c175] [c173] [c170] [c169] [c155] [c153] [c151] [c148] [i2] [c136] [c130] [c128] [c127] [c126] [c125] [c124] [c120] [c119] [c118] [c113] [c108] [j17] [c105] [c94] [c90] [c89] [c85] [j11] [j10] [c82] [c80] [c78] [c76] [c74] [c73] [c71] [c55] [c52] [c45] [c43] [c36] [c34] [c31]
[j45] [j44] [j43] [j42] [c255] [c254] [e14] [e13] [e12] [e11] [e10] [e9] [j41] [j40] [c243] [c240] [c238] [c236] [c234] [i34] [i32] [i30] [i29] [j39] [j38] [j36] [j35] [c231] [c230] [c229] [c228] [c227] [c226] [c223] [c221] [c220] [c219] [c217] [c216] [p1] [i27] [i23] [i22] [j34] [j33] [c213] [c211] [c210] [c209] [c208] [c207] [i21] [i20] [i19] [i18] [i17] [i16] [i13] [j32] [j31] [j30] [j28] [c206] [c205] [c204] [c202] [c201] [c200] [c199] [c198] [c196] [c195] [i11] [i10] [i8] [j27] [j26] [c194] [c193] [c192] [c191] [c190] [c189] [c188] [c186] [c185] [c184] [i7] [i6] [j25] [j24] [j23] [j22] [c182] [c181] [c180] [c179] [c178] [c176] [c175] [c174] [c173] [r2] [j21] [c170] [c169] [c168] [c167] [c166] [c165] [c164] [c163] [c162] [c160] [c159] [i5] [c158] [c157] [c155] [c154] [c153] [c152] [c151] [c150] [c149] [c148] [c147] [i4] [i3] [i2] [j20] [j19] [c146] [c145] [c144] [c143] [c142] [c141] [c139] [c138] [c137] [c136] [c135] [c134] [c133] [c132] [c130] [c129] [c128] [c127] [c126] [e3] [j18] [c125] [c124] [c123] [c122] [c121] [c120] [c119] [c118] [c117] [c116] [c115] [c114] [c113] [c112] [c111] [c110] [c108] [c107] [j17] [j15] [j14] [j13] [j12] [c105] [c104] [c103] [c102] [c101] [c100] [c99] [c98] [c97] [c96] [c95] [c94] [c93] [c92] [c91] [c89] [c88] [c87] [c86] [c85] [c84] [i1] [j11] [j10] [j9] [c82] [c81] [c80] [c79] [c78] [c77] [c76] [c75] [c74] [c73] [c72] [c71] [c70] [c68] [j8] [j7] [j5] [c67] [c66] [c65] [c64] [c63] [c61] [c60] [c59] [c58] [c57] [c56] [c55] [c54] [c53] [c52] [c51] [e2] [j4] [c49] [c48] [c47] [c46] [c45] [c44] [c43] [c42] [j3] [c41] [c40] [c39] [c38] [c37] [c36] [c34] [c32] [c31] [c30] [r1] [j1] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [e1] [c17] [c16] [c15] [c14] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [c6] [c5] [c4] [c3] [c2] [c1]
Aleksandr V. Petrov
aka: Aleksandr Vladimirovich Petrov
aka: Aleksandr Vladimirovich Petrov
[e19] [e18] [e17] [e16] [e15] [c248] [e14] [e13] [e12] [e11] [e10] [e9] [i39] [j40] [c241] [c234] [c233] [c232] [i24] [c215] [c214] [c213] [c212] [c211] [c210] [i19] [i16] [i15] [i14] [j29] [c203] [i9] [j25] [c171] [c161] [c160] [j19] [c131] [c107] [c106] [c104] [c96] [c86] [c84] [c83] [c77] [c75] [c72] [j5] [c63] [c59] [c44]
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