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Methods for making high-quality recommendations often rely on learning latent representations from interaction data.
Data sparsity issues in the collaborative filtering framework. In International workshop on knowledge discovery on the web
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IntrospectiveViews: An interface for scrutinizing semantic user models. In UMAP
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Each to His Own: How Different Users Call for Different Interaction Methods in Recommender Systems. In RecSys
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Content-based recommender systems: State of the art and trends
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Collaborative Topic Modeling for Recommending Scientific Articles. In KDD
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Information-seeking behaviors of computer scientists: Challenges for electronic literature search tools
Kumaripaba Athukorala, Eve Hoggan, Anu Lehtiö, Tuukka Ruotsalo, and Giulio Jacucci. 2013 · 2013
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Sinkhorn distances: Lightspeed computation of optimal transport
Marco Cuturi. 2013 · 2013
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Combining content with user preferences for TED lecture recommendation. In 2013 11th International Workshop on Content-Based Multimedia Indexing (CBMI) . IEEE, 47–52
Nikolaos Pappas and Andrei Popescu-Belis. 2013 · 2013
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Collaborative Topic Regression with Social Regularization for Tag Recommendation. In IJCAI
Hao Wang, Binyi Chen, and Wu-Jun Li. 2013 · 2013
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Nonlinear Latent Factorization by Embedding Multiple User Interests. In RecSys
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Searching, Browsing, and Clicking in a Search Session: Changes in User Behavior by Task and over Time. In Proceedings of the 37th International ACM SIGIR Conference on Research Development in Information Retrieval (Gold Coast, Queensland, Australia) (SIGIR ’14) . Association for Computing Machinery, New York, NY, USA, 607–616
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Weakly Supervised User Profile Extraction from Twitter. In ACL
Jiwei Li, Alan Ritter, and Eduard Hovy. 2014 · 2014
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Using Groups of Items for Preference Elicitation in Recommender Systems. In CSCW
Shuo Chang, F. Maxwell Harper, and Loren Terveen. 2015 · 2015
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Putting users in control of their recommendations. In RecSys
F Maxwell Harper, Funing Xu, Harmanpreet Kaur, Kyle Condiff, Shuo Chang, and Loren Terveen. 2015 · 2015
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On Tag Recommendation for Expertise Profiling: A Case Study in the Scientific Domain. In WSDM
Isac S. Ribeiro, Rodrygo L.T. Santos, Marcos A. Gonçalves, and Alberto H.F. Laender. 2015 · 2015
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Building Discriminative User Profiles for Large-Scale Content Recommendation. In KDD
Erheng Zhong, Nathan Liu, Yue Shi, and Suju Rajan. 2015 · 2015
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Ask the GRU: Multi-Task Learning for Deep Text Recommendations. In RecSys
Trapit Bansal, David Belanger, and Andrew McCallum. 2016 · 2016
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User control in recommender systems: Overview and interaction challenges. In International Conference on Electronic Commerce and Web Technologies
Dietmar Jannach, Sidra Naveed, and Michael Jugovac. 2016 · 2016
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What Are You Known For? Learning User Topical Profiles with Implicit and Explicit Footprints. In SIGIR
Cheng Cao, Hancheng Ge, Haokai Lu, Xia Hu, and James Caverlee. 2017 · 2017
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How do different levels of user control affect cognitive load and acceptance of recommendations?. In Workshop on Interfaces and Human Decision Making for Recommender Systems at RecSys
Yucheng Jin, Bruno Cardoso, and Katrien Verbert. 2017 · 2017
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Effects of Personal Characteristics on Music Recommender Systems with Different Levels of Controllability. In RecSys
Yucheng Jin, Nava Tintarev, and Katrien Verbert. 2018 · 2018
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Personal Knowledge Graphs: A Research Agenda. In Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval (Santa Clara, CA, USA) (ICTIR ’19) . Association for Computing Machinery, New York, NY, USA, 217–220
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Transparent, scrutable and explainable user models for personalized recommendation. In SIGIR
Krisztian Balog, Filip Radlinski, and Shushan Arakelyan. 2019 · 2019
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The Impact of More Transparent Interfaces on Behavior in Personalized Recommendation. In SIGIR
Tobias Schnabel, Saleema Amershi, Paul N. Bennett, Peter Bailey, and Thorsten Joachims. 2020 · 2020
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Rationalizing Text Matching: Learning Sparse Alignments via Optimal Transport. In ACL
Kyle Swanson, Lili Yu, and Tao Lei. 2020 · 2020
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Learning a Joint Search and Recommendation Model from User-Item Interactions. In WSDM
Hamed Zamani and W. Bruce Croft. 2020 · 2020
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Fast Multi-Step Critiquing for VAE-Based Recommender Systems. In Proceedings of the 15th ACM Conference on Recommender Systems (Amsterdam, Netherlands) (RecSys ’21) . Association for Computing Machinery, New York, NY, USA, 209–219
Diego Antognini and Boi Faltings. 2021 · 2021
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Interacting with Explanations through Critiquing. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21 , Zhi-Hua Zhou (Ed.). International Joint Conferences on Artificial Intelligence Organization, 515–521
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W. Bruce Croft. 2019 · 2019
Cited alongside, same era.
When People and Algorithms Meet: User-Reported Problems in Intelligent Everyday Applications. In IUI
Malin Eiband, Sarah Theres Völkel, Daniel Buschek, Sophia Cook, and Heinrich Hussmann. 2019 · 2019
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Designing for the Better by Taking Users into Account: A Qualitative Evaluation of User Control Mechanisms in (News) Recommender Systems. In RecSys
Jaron Harambam, Dimitrios Bountouridis, Mykola Makhortykh, and Joris van Hoboken. 2019 · 2019
Cited alongside, same era.
Paper Matching with Local Fairness Constraints. In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (Anchorage, AK, USA) (KDD ’19) . Association for Computing Machinery, New York, NY, USA, 1247–1257
Ari Kobren, Barna Saha, and Andrew McCallum. 2019 · 2019
Cited alongside, same era.
Latent Retrieval for Weakly Supervised Open Domain Question Answering. In ACL
Kenton Lee, Ming-Wei Chang, and Kristina Toutanova. 2019 · 2019
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Interpretability beyond classification output: Semantic bottleneck networks
Max Losch, Mario Fritz, and Bernt Schiele. 2019 · 2019
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Computational optimal transport: With applications to data science
Gabriel Peyré, Marco Cuturi, et al · 2019
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Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks. In EMNLP
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Diego Antognini, Claudiu Musat, and Boi Faltings. 2021 · 2021
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Anchor-Based Collaborative Filtering. In CIKM
Oren Barkan, Roy Hirsch, Ori Katz, Avi Caciularu, and Noam Koenigstein. 2021 · 2021
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Towards a Better Understanding of Query Reformulation Behavior in Web Search. In Proceedings of the Web Conference 2021 (Ljubljana, Slovenia) (WWW ’21) . Association for Computing Machinery, New York, NY, USA, 743–755
Jia Chen, Jiaxin Mao, Yiqun Liu, Fan Zhang, Min Zhang, and Shaoping Ma. 2021 · 2021
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Refocusing on Relevance: Personalization in NLG. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing . Association for Computational Linguistics, Online and Punta Cana, Dominican Republic, 5190–5202
Shiran Dudy, Steven Bedrick, and Bonnie Webber. 2021 · 2021
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POT: Python Optimal Transport
Rémi Flamary, Nicolas Courty, Alexandre Gramfort, Mokhtar Z. Alaya, Aurélie Boisbunon, Stanislas Chambon, Laetitia Chapel, Adrien Corenflos, Kilian Fatras, Nemo Fournier, Léo Gautheron, Nathalie T.H. Gayraud, Hicham Janati, Alain Rakotomamonjy, Ievgen Redko, Antoine Rolet, Antony Schutz, Vivien Seguy, Danica J. Sutherland, Romain Tavenard, Alexander Tong, and Titouan Vayer. 2021 · 2021
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ELIXIR: Learning from User Feedback on Explanations To Improve Recommender Models. In Web Conference
Azin Ghazimatin, Soumajit Pramanik, Rishiraj Saha Roy, and Gerhard Weikum. 2021 · 2021
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Open, scrutable and explainable interest models for transparent recommendation. In IUI Workshops
M Guesmi, M Chatti, Y Sun, S Zumor, F Ji, A Muslim, L Vorgerd, and SA Joarder. 2021 · 2021
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Human-centered recommender systems: Origins, advances, challenges, and opportunities
Joseph Konstan and Loren Terveen. 2021 · 2021
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Disentangling Preference Representations for Recommendation Critiquing with ß-VAE. In CIKM
Preksha Nema, Alexandros Karatzoglou, and Filip Radlinski. 2021 · 2021
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Connecting Students with Research Advisors Through User-Controlled Recommendation. In RecSys
Behnam Rahdari, Peter Brusilovsky, and Alireza Javadian Sabet. 2021 · 2021
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Controllable Gradient Item Retrieval. In Web Conference
Haonan Wang, Chang Zhou, Carl Yang, Hongxia Yang, and Jingrui He. 2021 · 2021
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On the Relation between Sensitivity and Accuracy in In-context Learning
Yanda Chen, Chen Zhao, Zhou Yu, Kathleen McKeown, and He He. 2022 · 2022
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Multi-Vector Models with Textual Guidance for Fine-Grained Scientific Document Similarity
Sheshera Mysore, Arman Cohan, and Tom Hope. 2022 · 2022
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On Natural Language User Profiles for Transparent and Scrutable Recommendation. In SIGIR
Filip Radlinski, Krisztian Balog, Fernando Diaz, Lucas Gill Dixon, and Ben Wedin. 2022 · 2022
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Challenges, Experiments, and Computational Solutions in Peer Review
Nihar B. Shah. 2022 · 2022
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Zero-Shot Recommendation as Language Modeling. In ECIR
Damien Sileo, Wout Vossen, and Robbe Raymaekers. 2022 · 2022
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Memorizing Transformers. In International Conference on Learning Representations
Yuhuai Wu, Markus Norman Rabe, DeLesley Hutchins, and Christian Szegedy. 2022 · 2022
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LaMP: When Large Language Models Meet Personalization
Alireza Salemi, Sheshera Mysore, Michael Bendersky, and Hamed Zamani. 2023 · 2023
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A Gold Standard Dataset for the Reviewer Assignment Problem
Ivan Stelmakh, John Wieting, Graham Neubig, and Nihar B. Shah. 2023 · 2023
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