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ACM International Conference on Recommender Systems

RecSys

A

CORE rank

CORE rank (raw)

A

Acceptance rate

18.0% (2024 full papers)

Fields of research

Data Management and Data Science

Papers indexed

2,902

2007–2025

Papers per year

2007239 peak2025

RecSys papers

2,902 records sourced from DBLP. Search titles, filter by year, sort by recency.

YearTitleAuthors
2016Representation Learning for Homophilic Preferences.Trong T. Nguyen, Hady Wirawan Lauw
20163rd Workshop on Recommendation Systems for Television and Online Video (RecSysTV 2016).Jan Neumann, John Hannon, Claudio Riefolo, Hassan Sayyadi
2016RecProfile '16: Workshop on Profiling User Preferences for Dynamic, Online, and Real-Time recommendations.Rani Nelken
2016T-RecS: A Framework for a Temporal Semantic Analysis of the ACM Recommender Systems Conference.Fedelucio Narducci, Pierpaolo Basile, Pasquale Lops, Marco de Gemmis, Giovanni Semeraro
2016ExpLOD: A Framework for Explaining Recommendations based on the Linked Open Data Cloud.Cataldo Musto, Fedelucio Narducci, Pasquale Lops, Marco de Gemmis, Giovanni Semeraro
2016Algorithms Aside: Recommendation As The Lens Of Life.Tamas Motajcsek, Jean-Yves Le Moine, Martha A. Larson, Daniel Kohlsdorf, Andreas Lommatzsch, Domonkos Tikk, Omar Alonso, Paolo Cremonesi, Andrew M. Demetriou, Kristaps Dobrajs, Franca Garzotto, Ayse Gker, Frank Hopfgartner, Davide Malagoli, Thuy Ngoc Nguyen, Jasminko Novak, Francesco Ricci, Mario Scriminaci, Marko Tkalcic, Anna Zacchi
2016A Recommender System to tackle Enterprise Collaboration.Gabriel de Souza Pereira Moreira, Gilmar Alves de Souza
2016Multi-Word Generative Query Recommendation Using Topic Modeling.Matthew Mitsui, Chirag Shah
2016A bottom-up approach to job recommendation system.Sonu K. Mishra, Manoj Reddy
2016A Jungian based framework for Artificial Personality Synthesis.David Mascarenas
2016Mood-Sensitive Truth Discovery For Reliable Recommendation Systems in Social Sensing.Jermaine Marshall, Dong Wang
2016"One Size Doesn't Fit All": Helping Users Find Events from Multiple Perspectives.Sean MacLachlan, Nevena Dragovic, Stacey Donohue, Maria Soledad Pera
2016Discovering What You're Known For: A Contextual Poisson Factorization Approach.Haokai Lu, James Caverlee, Wei Niu
2016Efficient Bayesian Methods for Graph-based Recommendation.Ramon Lopes, Renato M. Assuno, Rodrygo L. T. Santos
2016Bayesian Personalized Ranking with Multi-Channel User Feedback.Babak Loni, Roberto Pagano, Martha A. Larson, Alan Hanjalic
2016Feature Selection For Human Recommenders.Katherine A. Livins
2016Temporal learning and sequence modeling for a job recommender system.Kuan Liu, Xing Shi, Anoop Kumar, Linhong Zhu, Prem Natarajan
2016Are You Influenced by Others When Rating?: Improve Rating Prediction by Conformity Modeling.Yiming Liu, Xuezhi Cao, Yong Yu
2016Factorization Meets the Item Embedding: Regularizing Matrix Factorization with Item Co-occurrence.Dawen Liang, Jaan Altosaar, Laurent Charlin, David M. Blei
2016Guided Walk: A Scalable Recommendation Algorithm for Complex Heterogeneous Social Networks.Roy Levin, Hassan Abassi, Uzi Cohen
2016Combining Content-based and Collaborative Filtering for Personalized Sports News Recommendations.Philip Lenhart, Daniel Herzog
2016Job recommendation based on factorization machine and topic modelling.Vasily A. Leksin, Andrey Ostapets
2016News Article Position Recommendation Based on the Analysis of Article's Content - Time Matters.Parisa Lak, Ceni Babaoglu, Ayse Basar Bener, Pawel Pralat
2016Considering Supplier Relations and Monetization in Designing Recommendation Systems.Jan Krasnodebski, John Dines
2016Emotion Elicitation in Socially Intelligent Services: the Intelligent Typing Tutor Study Case.Andrej Kosir, Marko Meza, Janja Kosir, Matija Svetina, Gregor Strle
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