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ORCIDAndrew Yates
Andrew C. Yates
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- affiliation: University of Amsterdam, The Netherlands
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2020 – today
- 2023
[j10]Maurits J. R. Bleeker, Andrew Yates, Maarten de Rijke:
Reducing Predictive Feature Suppression in Resource-Constrained Contrastive Image-Caption Retrieval. Trans. Mach. Learn. Res. 2023 (2023)- [c74]Vaishali Pal, Andrew Yates, Evangelos Kanoulas, Maarten de Rijke
:
MultiTabQA: Generating Tabular Answers for Multi-Table Question Answering. ACL (1) 2023: 6322-6334 - [c73]Yibin Lei, Liang Ding, Yu Cao, Changtong Zan, Andrew Yates, Dacheng Tao:
Unsupervised Dense Retrieval with Relevance-Aware Contrastive Pre-Training. ACL (Findings) 2023: 10932-10940 - [c72]Thong Nguyen, Sean MacAvaney, Andrew Yates:
A Unified Framework for Learned Sparse Retrieval. ECIR (3) 2023: 101-116 - [c71]Lila Boualili, Andrew Yates:
A Study of Term-Topic Embeddings for Ranking. ECIR (2) 2023: 359-366 - [c70]Clara Rus, Maarten de Rijke, Andrew Yates:
Counterfactual Representations for Intersectional Fair Ranking in Recruitment. HR@RecSys 2023 - [c69]Ming Li, Mozhdeh Ariannezhad, Andrew Yates, Maarten de Rijke:
Masked and Swapped Sequence Modeling for Next Novel Basket Recommendation in Grocery Shopping. RecSys 2023: 35-46 - [c68]Thong Nguyen, Sean MacAvaney, Andrew Yates:
Adapting Learned Sparse Retrieval for Long Documents. SIGIR 2023: 1781-1785 - [c67]Ming Li, Ali Vardasbi, Andrew Yates, Maarten de Rijke:
Repetition and Exploration in Sequential Recommendation. SIGIR 2023: 2532-2541 - [c66]Ghazaleh Haratinezhad Torbati, Gerhard Weikum, Andrew Yates:
Search-based Recommendation: the Case for Difficult Predictions. WWW (Companion Volume) 2023: 318-321 - [i38]Thong Nguyen, Sean MacAvaney, Andrew Yates:
A Unified Framework for Learned Sparse Retrieval. CoRR abs/2303.13416 (2023) - [i37]Vaishali Pal, Andrew Yates, Evangelos Kanoulas, Maarten de Rijke:
MultiTabQA: Generating Tabular Answers for Multi-Table Question Answering. CoRR abs/2305.12820 (2023) - [i36]Thong Nguyen, Sean MacAvaney, Andrew Yates:
Adapting Learned Sparse Retrieval for Long Documents. CoRR abs/2305.18494 (2023) - [i35]Yibin Lei, Liang Ding, Yu Cao, Changtong Zan, Andrew Yates, Dacheng Tao:
Unsupervised Dense Retrieval with Relevance-Aware Contrastive Pre-Training. CoRR abs/2306.03166 (2023) - [i34]Thong Nguyen, Andrew Yates:
Generative Retrieval as Dense Retrieval. CoRR abs/2306.11397 (2023) - [i33]Ming Li, Mozhdeh Ariannezhad, Andrew Yates, Maarten de Rijke:
Masked and Swapped Sequence Modeling for Next Novel Basket Recommendation in Grocery Shopping. CoRR abs/2308.01308 (2023) - [i32]Michael Unterkalmsteiner, Andrew Yates:
Expert-sourcing Domain-specific Knowledge: The Case of Synonym Validation. CoRR abs/2309.16798 (2023) - [i31]Andrew Yates, Michael Unterkalmsteiner:
Replicating Relevance-Ranked Synonym Discovery in a New Language and Domain. CoRR abs/2310.01507 (2023) - [i30]Ghazaleh Haratinezhad Torbati, Anna Tigunova, Andrew Yates, Gerhard Weikum:
Recommendations by Concise User Profiles from Review Text. CoRR abs/2311.01314 (2023) - 2022
- [j9]Shahrzad Naseri, Jeffrey Dalton, Andrew Yates, James Allan:
CEQE to SQET: A study of contextualized embeddings for query expansion. Inf. Retr. J. 25(2): 184-208 (2022) - [c65]Thong Nguyen, Andrew Yates, Ayah Zirikly, Bart Desmet, Arman Cohan:
Improving the Generalizability of Depression Detection by Leveraging Clinical Questionnaires. ACL (1) 2022: 8446-8459 - [c64]Hai Dang Tran, Andrew Yates:
Dense Retrieval with Entity Views. CIKM 2022: 1955-1964 - [c63]Ronak Pradeep, Yuqi Liu, Xinyu Zhang, Yilin Li, Andrew Yates, Jimmy Lin:
Squeezing Water from a Stone: A Bag of Tricks for Further Improving Cross-Encoder Effectiveness for Reranking. ECIR (1) 2022: 655-670 - [c62]Antonios Minas Krasakis, Andrew Yates, Evangelos Kanoulas:
Zero-shot Query Contextualization for Conversational Search. SIGIR 2022: 1880-1884 - [c61]Pooya Khandel, Ilya Markov, Andrew Yates, Ana Lucia Varbanescu:
ParClick: A Scalable Algorithm for EM-based Click Models. WWW 2022: 392-400 - [i29]Thong Nguyen, Andrew Yates, Ayah Zirikly, Bart Desmet, Arman Cohan:
Improving the Generalizability of Depression Detection by Leveraging Clinical Questionnaires. CoRR abs/2204.10432 (2022) - [i28]Antonios Minas Krasakis, Andrew Yates, Evangelos Kanoulas:
Zero-shot Query Contextualization for Conversational Search. CoRR abs/2204.10613 (2022) - [i27]Maurits J. R. Bleeker, Andrew Yates, Maarten de Rijke:
Keep the Caption Information: Preventing Shortcut Learning in Contrastive Image-Caption Retrieval. CoRR abs/2204.13382 (2022) - 2021
- [b1]Jimmy Lin, Rodrigo Frassetto Nogueira, Andrew Yates:
Pretrained Transformers for Text Ranking: BERT and Beyond. Synthesis Lectures on Human Language Technologies, Morgan & Claypool Publishers 2021, ISBN 978-3-031-01053-8, pp. 1-325 - [j8]Zhi Zheng, Kai Hui, Ben He, Xianpei Han, Le Sun, Andrew Yates:
Contextualized query expansion via unsupervised chunk selection for text retrieval. Inf. Process. Manag. 58(5): 102672 (2021) - [c60]Xinyu Zhang, Andrew Yates, Jimmy Lin:
Comparing Score Aggregation Approaches for Document Retrieval with Pretrained Transformers. ECIR (2) 2021: 150-163 - [c59]Ghazaleh H. Torbati, Andrew Yates, Gerhard Weikum:
You Get What You Chat: Using Conversations to Personalize Search-Based Recommendations. ECIR (1) 2021: 207-223 - [c58]Shahrzad Naseri, Jeff Dalton, Andrew Yates, James Allan:
CEQE: Contextualized Embeddings for Query Expansion. ECIR (1) 2021: 467-482 - [c57]Anna Tigunova, Paramita Mirza, Andrew Yates, Gerhard Weikum:
PRIDE: Predicting Relationships in Conversations. EMNLP (1) 2021: 4636-4650 - [c56]Iain Mackie, Jeffrey Dalton, Andrew Yates:
How Deep is your Learning: the DL-HARD Annotated Deep Learning Dataset. SIGIR 2021: 2335-2341 - [c55]Sean MacAvaney, Andrew Yates, Sergey Feldman, Doug Downey, Arman Cohan, Nazli Goharian:
Simplified Data Wrangling with ir_datasets. SIGIR 2021: 2429-2436 - [c54]Kevin Martin Jose, Thong Nguyen, Sean MacAvaney, Jeffrey Dalton, Andrew Yates:
DiffIR: Exploring Differences in Ranking Models' Behavior. SIGIR 2021: 2595-2599 - [c53]Andrew Yates, Rodrigo Frassetto Nogueira, Jimmy Lin:
Pretrained Transformers for Text Ranking: BERT and Beyond. SIGIR 2021: 2666-2668 - [c52]Anna Tigunova, Paramita Mirza, Andrew Yates, Gerhard Weikum:
Exploring Personal Knowledge Extraction from Conversations with CHARM. WSDM 2021: 1077-1080 - [c51]Andrew Yates, Rodrigo Frassetto Nogueira, Jimmy Lin:
Pretrained Transformers for Text Ranking: BERT and Beyond. WSDM 2021: 1154-1156 - [i26]Sean MacAvaney, Andrew Yates, Sergey Feldman, Doug Downey, Arman Cohan, Nazli Goharian:
Simplified Data Wrangling with ir_datasets. CoRR abs/2103.02280 (2021) - [i25]Shahrzad Naseri, Jeffrey Dalton, Andrew Yates, James Allan:
CEQE: Contextualized Embeddings for Query Expansion. CoRR abs/2103.05256 (2021) - [i24]Iain Mackie, Jeff Dalton, Andrew Yates:
How Deep is your Learning: the DL-HARD Annotated Deep Learning Dataset. CoRR abs/2105.07975 (2021) - [i23]Ghazaleh Haratinezhad Torbati, Andrew Yates, Gerhard Weikum:
Personalized Entity Search by Sparse and Scrutable User Profiles. CoRR abs/2109.04713 (2021) - [i22]Ghazaleh Haratinezhad Torbati, Andrew Yates, Gerhard Weikum:
You Get What You Chat: Using Conversations to Personalize Search-based Recommendations. CoRR abs/2109.04716 (2021) - [i21]Simon Razniewski, Andrew Yates, Nora Kassner, Gerhard Weikum:
Language Models As or For Knowledge Bases. CoRR abs/2110.04888 (2021) - 2020
- [c50]Ghazaleh H. Torbati, Andrew Yates, Gerhard Weikum:
Personalized Entity Search by Sparse and Scrutable User Profiles. CHIIR 2020: 427-431 - [c49]Andrew Yates, Kevin Martin Jose, Xinyu Zhang, Jimmy Lin:
Flexible IR Pipelines with Capreolus. CIKM 2020: 3181-3188 - [c48]Xinyu Zhang, Andrew Yates, Jimmy Lin:
A Little Bit Is Worse Than None: Ranking with Limited Training Data. SustaiNLP@EMNLP 2020: 107-112 - [c47]Zhi Zheng, Kai Hui, Ben He, Xianpei Han, Le Sun, Andrew Yates:
BERT-QE: Contextualized Query Expansion for Document Re-ranking. EMNLP (Findings) 2020: 4718-4728 - [c46]Anna Tigunova, Andrew Yates, Paramita Mirza, Gerhard Weikum:
CHARM: Inferring Personal Attributes from Conversations. EMNLP (1) 2020: 5391-5404 - [c45]Anna Tigunova, Paramita Mirza, Andrew Yates, Gerhard Weikum:
RedDust: a Large Reusable Dataset of Reddit User Traits. LREC 2020: 6118-6126 - [c44]Canjia Li, Andrew Yates:
MPII at the TREC 2020 Deep Learning Track. TREC 2020 - [c43]Andrew Yates, Siddhant Arora, Xinyu Zhang, Wei Yang, Kevin Martin Jose, Jimmy Lin:
Capreolus: A Toolkit for End-to-End Neural Ad Hoc Retrieval. WSDM 2020: 861-864 - [i20]Canjia Li, Andrew Yates, Sean MacAvaney, Ben He, Yingfei Sun:
PARADE: Passage Representation Aggregation for Document Reranking. CoRR abs/2008.09093 (2020) - [i19]Zhi Zheng, Kai Hui, Ben He, Xianpei Han, Le Sun, Andrew Yates:
BERT-QE: Contextualized Query Expansion for Document Re-ranking. CoRR abs/2009.07258 (2020) - [i18]Jimmy Lin, Rodrigo Frassetto Nogueira, Andrew Yates:
Pretrained Transformers for Text Ranking: BERT and Beyond. CoRR abs/2010.06467 (2020)
2010 – 2019
- 2019
- [j7]Sean MacAvaney, Andrew Yates, Arman Cohan, Luca Soldaini, Kai Hui, Nazli Goharian, Ophir Frieder:
Overcoming low-utility facets for complex answer retrieval. Inf. Retr. J. 22(3-4): 395-418 (2019) - [c42]Siddhant Arora, Andrew Yates:
Investigating Retrieval Method Selection with Axiomatic Features. AMIR@ECIR 2019: 18-31 - [c41]Andrew Yates, Michael Unterkalmsteiner:
Replicating Relevance-Ranked Synonym Discovery in a New Language and Domain. ECIR (1) 2019: 429-442 - [c40]Kashyap Popat, Subhabrata Mukherjee, Andrew Yates, Gerhard Weikum:
STANCY: Stance Classification Based on Consistency Cues. EMNLP/IJCNLP (1) 2019: 6412-6417 - [c39]Michael A. Hedderich, Andrew Yates, Dietrich Klakow, Gerard de Melo:
Using Multi-Sense Vector Embeddings for Reverse Dictionaries. IWCS (1) 2019: 247-258 - [c38]Michael Unterkalmsteiner, Andrew Yates:
Expert-sourcing Domain-specific Knowledge: The Case of Synonym Validation. REFSQ Workshops 2019 - [c37]Sean MacAvaney, Andrew Yates, Kai Hui, Ophir Frieder:
Content-Based Weak Supervision for Ad-Hoc Re-Ranking. SIGIR 2019: 993-996 - [c36]Sean MacAvaney, Andrew Yates, Arman Cohan, Nazli Goharian:
CEDR: Contextualized Embeddings for Document Ranking. SIGIR 2019: 1101-1104 - [c35]Samarth Mehrotra, Andrew Yates:
MPII at TREC CAsT 2019: Incoporating Query Context into a BERT Re-ranker. TREC 2019 - [c34]Anna Tigunova, Andrew Yates, Paramita Mirza, Gerhard Weikum:
Listening between the Lines: Learning Personal Attributes from Conversations. WWW 2019: 1818-1828 - [i17]Michael A. Hedderich, Andrew Yates, Dietrich Klakow, Gerard de Melo:
Using Multi-Sense Vector Embeddings for Reverse Dictionaries. CoRR abs/1904.01451 (2019) - [i16]Siddhant Arora, Andrew Yates:
Investigating Retrieval Method Selection with Axiomatic Features. CoRR abs/1904.05737 (2019) - [i15]Sean MacAvaney, Andrew Yates, Arman Cohan, Nazli Goharian:
CEDR: Contextualized Embeddings for Document Ranking. CoRR abs/1904.07094 (2019) - [i14]Anna Tigunova, Andrew Yates, Paramita Mirza, Gerhard Weikum:
Listening between the Lines: Learning Personal Attributes from Conversations. CoRR abs/1904.10887 (2019) - [i13]Kashyap Popat, Subhabrata Mukherjee, Andrew Yates, Gerhard Weikum:
STANCY: Stance Classification Based on Consistency Cues. CoRR abs/1910.06048 (2019) - 2018
- [c33]Sean MacAvaney, Bart Desmet, Arman Cohan, Luca Soldaini, Andrew Yates, Ayah Zirikly, Nazli Goharian:
RSDD-Time: Temporal Annotation of Self-Reported Mental Health Diagnoses. CLPsych@NAACL-HTL 2018: 168-173 - [c32]Arman Cohan, Bart Desmet, Andrew Yates, Luca Soldaini, Sean MacAvaney, Nazli Goharian:
SMHD: a Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions. COLING 2018: 1485-1497 - [c31]Kashyap Popat, Subhabrata Mukherjee, Andrew Yates, Gerhard Weikum:
DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learning. EMNLP 2018: 22-32 - [c30]Canjia Li, Yingfei Sun, Ben He, Le Wang, Kai Hui, Andrew Yates, Le Sun, Jungang Xu:
NPRF: A Neural Pseudo Relevance Feedback Framework for Ad-hoc Information Retrieval. EMNLP 2018: 4482-4491 - [c29]Sean MacAvaney, Andrew Yates, Arman Cohan, Luca Soldaini, Kai Hui, Nazli Goharian, Ophir Frieder:
Overcoming Low-Utility Facets for Complex Answer Retrieval. ProfS/KG4IR/Data:Search@SIGIR 2018: 46-47 - [c28]Sean MacAvaney, Andrew Yates, Arman Cohan, Luca Soldaini, Kai Hui, Nazli Goharian, Ophir Frieder:
Characterizing Question Facets for Complex Answer Retrieval. SIGIR 2018: 1205-1208 - [c27]Sean MacAvaney, Nazli Goharian, Ophir Frieder, Andrew Yates:
PACRR Gated Expansion for TREC CAR 2018. TREC 2018 - [c26]Kai Hui, Andrew Yates, Klaus Berberich, Gerard de Melo:
Co-PACRR: A Context-Aware Neural IR Model for Ad-hoc Retrieval. WSDM 2018: 279-287 - [i12]Sean MacAvaney, Andrew Yates, Arman Cohan, Luca Soldaini, Kai Hui, Nazli Goharian, Ophir Frieder:
Characterizing Question Facets for Complex Answer Retrieval. CoRR abs/1805.00791 (2018) - [i11]Arman Cohan, Bart Desmet, Andrew Yates, Luca Soldaini, Sean MacAvaney, Nazli Goharian:
SMHD: A Large-Scale Resource for Exploring Online Language Usage for Multiple Mental Health Conditions. CoRR abs/1806.05258 (2018) - [i10]Sean MacAvaney, Bart Desmet, Arman Cohan, Luca Soldaini, Andrew Yates, Ayah Zirikly, Nazli Goharian:
RSDD-Time: Temporal Annotation of Self-Reported Mental Health Diagnoses. CoRR abs/1806.07916 (2018) - [i9]Kashyap Popat, Subhabrata Mukherjee, Andrew Yates, Gerhard Weikum:
DeClarE: Debunking Fake News and False Claims using Evidence-Aware Deep Learning. CoRR abs/1809.06416 (2018) - [i8]Canjia Li, Yingfei Sun, Ben He, Le Wang, Kai Hui, Andrew Yates, Le Sun, Jungang Xu:
NPRF: A Neural Pseudo Relevance Feedback Framework for Ad-hoc Information Retrieval. CoRR abs/1810.12936 (2018) - [i7]Sean MacAvaney, Andrew Yates, Arman Cohan, Luca Soldaini, Kai Hui, Nazli Goharian, Ophir Frieder:
Overcoming low-utility facets for complex answer retrieval. CoRR abs/1811.08772 (2018) - 2017
- [j6]Luca Soldaini, Andrew Yates, Nazli Goharian:
Learning to reformulate long queries for clinical decision support. J. Assoc. Inf. Sci. Technol. 68(11): 2602-2619 (2017) - [j5]Arman Cohan, Sydney Young, Andrew Yates, Nazli Goharian:
Triaging content severity in online mental health forums. J. Assoc. Inf. Sci. Technol. 68(11): 2675-2689 (2017) - [c25]Luca Soldaini, Andrew Yates, Nazli Goharian:
Denoising Clinical Notes for Medical Literature Retrieval with Convolutional Neural Model. CIKM 2017: 2307-2310 - [c24]Kai Hui, Andrew Yates, Klaus Berberich, Gerard de Melo:
PACRR: A Position-Aware Neural IR Model for Relevance Matching. EMNLP 2017: 1049-1058 - [c23]Andrew Yates, Arman Cohan, Nazli Goharian:
Depression and Self-Harm Risk Assessment in Online Forums. EMNLP 2017: 2968-2978 - [c22]Sean MacAvaney, Andrew Yates, Kai Hui:
Contextualized PACRR for Complex Answer Retrieval. TREC 2017 - [c21]Kai Hui, Andrew Yates, Klaus Berberich, Gerard de Melo:
Position-Aware Representations for Relevance Matching in Neural Information Retrieval. WWW (Companion Volume) 2017: 799-800 - [i6]Arman Cohan, Sydney Young, Andrew Yates, Nazli Goharian:
Triaging Content Severity in Online Mental Health Forums. CoRR abs/1702.06875 (2017) - [i5]Kai Hui, Andrew Yates, Klaus Berberich, Gerard de Melo:
A Position-Aware Deep Model for Relevance Matching in Information Retrieval. CoRR abs/1704.03940 (2017) - [i4]Andrew Yates, Kai Hui:
DE-PACRR: Exploring Layers Inside the PACRR Model. CoRR abs/1706.08746 (2017) - [i3]Kai Hui, Andrew Yates, Klaus Berberich, Gerard de Melo:
RE-PACRR: A Context and Density-Aware Neural Information Retrieval Model. CoRR abs/1706.10192 (2017) - [i2]Sean MacAvaney, Kai Hui, Andrew Yates:
An Approach for Weakly-Supervised Deep Information Retrieval. CoRR abs/1707.00189 (2017) - [i1]Andrew Yates, Arman Cohan, Nazli Goharian:
Depression and Self-Harm Risk Assessment in Online Forums. CoRR abs/1709.01848 (2017) - 2016
- [j4]Luca Soldaini, Andrew Yates, Elad Yom-Tov, Ophir Frieder, Nazli Goharian:
Enhancing web search in the medical domain via query clarification. Inf. Retr. J. 19(1-2): 149-173 (2016) - [c20]Andrew Yates, Jonah Joselow, Nazli Goharian:
The News Cycle's Influence on Social Media Activity. ICWSM 2016: 735-738 - [c19]Andrew Yates, Nazli Goharian, Ophir Frieder:
Learning the Relationships between Drug, Symptom, and Medical Condition Mentions in Social Media. ICWSM 2016: 739-742 - [c18]Andrew Yates, Alek Kolcz, Nazli Goharian, Ophir Frieder:
Effects of Sampling on Twitter Trend Detection. LREC 2016 - 2015
- [j3]Jon Parker, Andrew Yates, Nazli Goharian, Ophir Frieder:
Health-related hypothesis generation using social media data. Soc. Netw. Anal. Min. 5(1): 7:1-7:15 (2015) - [c17]Andrew Yates, Nazli Goharian, Ophir Frieder:
Extracting Adverse Drug Reactions from Social Media. AAAI 2015: 2460-2467 - [c16]Luca Soldaini, Arman Cohan, Andrew Yates, Nazli Goharian, Ophir Frieder:
Retrieving Medical Literature for Clinical Decision Support. ECIR 2015: 538-549 - 2014
- [c15]Arman Cohan, Luca Soldaini, Andrew Yates, Nazli Goharian, Ophir Frieder:
On clinical decision support. BCB 2014: 651-652 - [c14]Andrew Yates, Nazli Goharian, Ophir Frieder:
Relevance-Ranked Domain-Specific Synonym Discovery. ECIR 2014: 124-135 - [c13]Michael Wang, Andrew Yates, Igor L. Markov:
SuperPUF: integrating heterogeneous physically unclonable functions. ICCAD 2014: 454-461 - [c12]Andrew Yates, Jon Parker, Nazli Goharian, Ophir Frieder:
A Framework for Public Health Surveillance. LREC 2014: 475-482 - [c11]Luca Soldaini, Arman Cohan, Andrew Yates, Nazli Goharian, Ophir Frieder:
Query Reformulation for Clinical Decision Support Search. TREC 2014 - 2013
- [c10]Jordan Wilberding, Andrew Yates, Micah Sherr, Wenchao Zhou:
Validating web content with senser. ACSAC 2013: 339-348 - [c9]Andrew Yates, Nazli Goharian, Wai Gen Yee:
Semi-supervised probabilistic sentiment analysis: Merging labeled sentences with unlabeled reviews to identify sentiment. ASIST 2013: 1-10 - [c8]Jon Parker, Yifang Wei, Andrew Yates, Ophir Frieder, Nazli Goharian:
A framework for detecting public health trends with Twitter. ASONAM 2013: 556-563 - [c7]Andrew Yates, Nazli Goharian:
ADRTrace: Detecting Expected and Unexpected Adverse Drug Reactions from User Reviews on Social Media Sites. ECIR 2013: 816-819 - [c6]Eric William Burger, Howard J. Federoff, Massimo S. Fiandaca, Ophir Frieder, Nazli Goharian, Andrew Yates:
Social media communications networks and pharmacovigilance: SequelAE-2.0. Healthcom 2013: 1-3 - [c5]Andrew Yates, Nazli Goharian, Ophir Frieder:
Graded relevance ranking for synonym discovery. WWW (Companion Volume) 2013: 139-140 - 2012
- [c4]Jon Parker, Andrew Yates, Nazli Goharian, Wai Gen Yee:
Efficient estimation of aspect weights. SIGIR 2012: 1057-1058 - [c3]Andrew Yates, Dave DeBoer, Hui Yang, Nazli Goharian, Steve Kunath, Ophir Frieder:
(Not Too) Personalized Learning to Rank for Contextual Suggestion. TREC 2012 - 2010
- [c2]Wai Gen Yee, Andrew Yates, Ophir Frieder, Armin Moehrle:
eduKEN: a tool for fine-grained video comment collection and analysis. WWW 2010: 1325-1328
2000 – 2009
- 2009
- [c1]Wai Gen Yee, Andrew Yates, Shizhu Liu, Ophir Frieder:
Are Web User Comments Useful for Search? LSDS-IR@SIGIR 2009 - 2007
- [j2]Andrew Yates, Cliburn Chan, Jessica Strid, Simon Moon, Robin Callard, Andrew J. T. George, Jaroslav Stark:
Reconstruction of cell population dynamics using CFSE. BMC Bioinform. 8 (2007) - 2001
- [j1]Andrew Yates, C. C. W. Chan, R. E. Callard, Andrew J. T. George, Jaroslav Stark:
An Approach to Modelling in Immunology. Briefings Bioinform. 2(3): 245-257 (2001)