recsys | ACM Conference on Recommender Systems (RecSys)

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Proceedings of the 10th ACM Conference on Recommender Systems, Boston, MA, USA, September 15-19, 2016.
Automated Machine Learning in the Wild.

Claudia Perlich

Personalization for Google Now: User Understanding and Application to Information Recommendation and Exploration.

Shashi Thakur

Recommendations with a Purpose.

Dietmar Jannach, Gediminas Adomavicius

Recommender Systems for Self-Actualization.

Bart P. Knijnenburg, Saadhika Sivakumar, Daricia Wilkinson

A Coverage-Based Approach to Recommendation Diversity On Similarity Graph.

Shameem Puthiya Parambath, Nicolas Usunier, Yves Grandvalet

A Scalable Approach for Periodical Personalized Recommendations.

Zhen Qin, Ish Rishabh, John Carnahan

Multi-Word Generative Query Recommendation Using Topic Modeling.

Matthew Mitsui, Chirag Shah

Contrasting Offline and Online Results when Evaluating Recommendation Algorithms.

Marco Rossetti, Fabio Stella, Markus Zanker

Adaptive, Personalized Diversity for Visual Discovery.

Choon Hui Teo, Houssam Nassif, Daniel N. Hill, Sriram Srinivasan, Mitchell Goodman, Vijai Mohan, S. V. N. Vishwanathan

Intent-Aware Diversification Using a Constrained PLSA.

Jacek Wasilewski, Neil Hurley

Field-aware Factorization Machines for CTR Prediction.

Yu-Chin Juan, Yong Zhuang, Wei-Sheng Chin, Chih-Jen Lin

Learning Hierarchical Feature Influence for Recommendation by Recursive Regularization.

Jie Yang, Zhu Sun, Alessandro Bozzon, Jie Zhang

Factorization Meets the Item Embedding: Regularizing Matrix Factorization with Item Co-occurrence.

Dawen Liang, Jaan Altosaar, Laurent Charlin, David M. Blei

Local Item-Item Models For Top-N Recommendation.

Evangelia Christakopoulou, George Karypis

Asynchronous Distributed Matrix Factorization with Similar User and Item Based Regularization.

Bikash Joshi, Franck Iutzeler, Massih-Reza Amini

Query-based Music Recommendations via Preference Embedding.

Chih-Ming Chen, Ming-Feng Tsai, Yu-Ching Lin, Yi-Hsuan Yang

Joint User Modeling across Aligned Heterogeneous Sites.

Xuezhi Cao, Yong Yu

Fifty Shades of Ratings: How to Benefit from a Negative Feedback in Top-N Recommendations Tasks.

Evgeny Frolov, Ivan V. Oseledets

Latent Factor Representations for Cold-Start Video Recommendation.

Sujoy Roy, Sharath Chandra Guntuku

Ask the GRU: Multi-task Learning for Deep Text Recommendations.

Trapit Bansal, David Belanger, Andrew McCallum

Addressing Cold Start for Next-song Recommendation.

Szu-Yu Chou, Yi-Hsuan Yang, Jyh-Shing Roger Jang, Yu-Ching Lin

Accuracy and Diversity in Cross-domain Recommendations for Cold-start Users with Positive-only Feedback.

Ignacio Fernández-Tobías, Paolo Tomeo, Iván Cantador, Tommaso Di Noia, Eugenio Di Sciascio

HCI for Recommender Systems: the Past, the Present and the Future.

André Calero Valdez, Martina Ziefle, Katrien Verbert

Human-Recommender Systems: From Benchmark Data to Benchmark Cognitive Models.

Patrick Shafto, Olfa Nasraoui

Gaze Prediction for Recommender Systems.

Qian Zhao, Shuo Chang, F. Maxwell Harper, Joseph A. Konstan

Exploring the Value of Personality in Predicting Rating Behaviors: A Study of Category Preferences on MovieLens.

Raghav Pavan Karumur, Tien T. Nguyen, Joseph A. Konstan

Pairwise Preferences Based Matrix Factorization and Nearest Neighbor Recommendation Techniques.

Saikishore Kalloori, Francesco Ricci, Marko Tkalcic

Observing Group Decision Making Processes.

Amra Delic, Julia Neidhardt, Thuy Ngoc Nguyen, Francesco Ricci, Laurens Rook, Hannes Werthner, Markus Zanker

ExpLOD: A Framework for Explaining Recommendations based on the Linked Open Data Cloud.

Cataldo Musto, Fedelucio Narducci, Pasquale Lops, Marco de Gemmis, Giovanni Semeraro

The Value of Online Customer Reviews.

Georgios Askalidis, Edward C. Malthouse

Mechanism Design for Personalized Recommender Systems.

Qingpeng Cai, Aris Filos-Ratsikas, Chang Liu, Pingzhong Tang

Mood-Sensitive Truth Discovery For Reliable Recommendation Systems in Social Sensing.

Jermaine Marshall, Dong Wang

Crowd-Based Personalized Natural Language Explanations for Recommendations.

Shuo Chang, F. Maxwell Harper, Loren Gilbert Terveen

Domain-Aware Grade Prediction and Top-n Course Recommendation.

Asmaa Elbadrawy, George Karypis

Deep Neural Networks for YouTube Recommendations.

Paul Covington, Jay Adams, Emre Sargin

Optimizing Similar Item Recommendations in a Semi-structured Marketplace to Maximize Conversion.

Yuri M. Brovman, Marie Jacob, Natraj Srinivasan, Stephen Neola, Daniel Galron, Ryan Snyder, Paul Wang

A Package Recommendation Framework for Trip Planning Activities.

Idir Benouaret, Dominique Lenne

Recommender Systems with Personality.

Amos Azaria, Jason Hong

Past, Present, and Future of Recommender Systems: An Industry Perspective.

Xavier Amatriain, Justin Basilico

Algorithms Aside: Recommendation As The Lens Of Life.

Tamas Motajcsek, Jean-Yves Le Moine, Martha Larson, Daniel Kohlsdorf, Andreas Lommatzsch, Domonkos Tikk, Omar Alonso, Paolo Cremonesi, Andrew Demetriou, Kristaps Dobrajs, Franca Garzotto, Ayse Göker, Frank Hopfgartner, Davide Malagoli, Thuy Ngoc Nguyen, Jasminko Novak, Francesco Ricci, Mario Scriminaci, Marko Tkalcic, Anna Zacchi

Behaviorism is Not Enough: Better Recommendations through Listening to Users.

Michael D. Ekstrand, Martijn C. Willemsen

Meta-Prod2Vec: Product Embeddings Using Side-Information for Recommendation.

Flavian Vasile, Elena Smirnova, Alexis Conneau

Convolutional Matrix Factorization for Document Context-Aware Recommendation.

Dong Hyun Kim, Chanyoung Park, Jinoh Oh, Sungyoung Lee, Hwanjo Yu

Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations.

Balázs Hidasi, Massimo Quadrana, Alexandros Karatzoglou, Domonkos Tikk

The Contextual Turn: from Context-Aware to Context-Driven Recommender Systems.

Roberto Pagano, Paolo Cremonesi, Martha Larson, Balázs Hidasi, Domonkos Tikk, Alexandros Karatzoglou, Massimo Quadrana

Discovering What You're Known For: A Contextual Poisson Factorization Approach.

Haokai Lu, James Caverlee, Wei Niu

TAPER: A Contextual Tensor-Based Approach for Personalized Expert Recommendation.

Hancheng Ge, James Caverlee, Haokai Lu

Are You Influenced by Others When Rating?: Improve Rating Prediction by Conformity Modeling.

Yiming Liu, Xuezhi Cao, Yong Yu

Modelling Contextual Information in Session-Aware Recommender Systems with Neural Networks.

Bartlomiej Twardowski

Getting the Timing Right: Leveraging Category Inter-purchase Times to Improve Recommender Systems.

Denis Vuckovac, Julia Wamsler, Alexander Ilic, Martin Natter

MAPS: A Multi Aspect Personalized POI Recommender System.

Ramesh Baral, Tao Li

Recommending New Items to Ephemeral Groups Using Contextual User Influence.

Elisa Quintarelli, Emanuele Rabosio, Letizia Tanca

Guided Walk: A Scalable Recommendation Algorithm for Complex Heterogeneous Social Networks.

Roy Levin, Hassan Abassi, Uzi Cohen

STAR: Semiring Trust Inference for Trust-Aware Social Recommenders.

Peixin Gao, Hui Miao, John S. Baras, Jennifer Golbeck

Vista: A Visually, Socially, and Temporally-aware Model for Artistic Recommendation.

Ruining He, Chen Fang, Zhaowen Wang, Julian McAuley

Representation Learning for Homophilic Preferences.

Trong T. Nguyen, Hady Wirawan Lauw

Personalized Recommendations using Knowledge Graphs: A Probabilistic Logic Programming Approach.

Rose Catherine, William W. Cohen

Efficient Bayesian Methods for Graph-based Recommendation.

Ramon Lopes, Renato Assunção, Rodrygo L. T. Santos

Using Navigation to Improve Recommendations in Real-Time.

Chao-Yuan Wu, Christopher V. Alvino, Alexander J. Smola, Justin Basilico

Bayesian Low-Rank Determinantal Point Processes.

Mike Gartrell, Ulrich Paquet, Noam Koenigstein

Recommending Repeat Purchases using Product Segment Statistics.

Suvodip Dey, Pabitra Mitra, Kratika Gupta

Bayesian Personalized Ranking with Multi-Channel User Feedback.

Babak Loni, Roberto Pagano, Martha Larson, Alan Hanjalic

Mendeley: Recommendations for Researchers.

Saúl Vargas, Maya Hristakeva, Kris Jack

When Recommendation Systems Go Bad.

Evan Estola

News Recommendations at scale at Bloomberg Media: Challenges and Approaches.

Dhaval Shah, Pramod Koneru, Parth Shah, Rohit Parimi

Marsbot: Building a Personal Assistant.

Max Sklar

Music Personalization at Spotify.

Kurt Jacobson, Vidhya Murali, Edward Newett, Brian Whitman, Romain Yon

Recommending for the World.

Justin Basilico, Yves Raimond

The Exploit-Explore Dilemma in Music Recommendation.

Òscar Celma

Feature Selection For Human Recommenders.

Katherine A. Livins

Considering Supplier Relations and Monetization in Designing Recommendation Systems.

Jan Krasnodebski, John Dines

A Cross-Industry Machine Learning Framework with Explicit Representations.

Denise Ichinco, Sahil Zubair, Jana Eggers, Nathan Wilson

Leveraging a Graph-Powered, Real-Time Recommendation Engine to Create Rapid Business Value.

Adam Anthony, Yu-Keng Shih, Ruoming Jin, Yang Xiang

Hypothesis Testing: How to Eliminate Ideas as Soon as Possible.

Roman Zykov

Recommending the World's Knowledge: Application of Recommender Systems at Quora.

Lei Yang, Xavier Amatriain

Multi-corpus Personalized Recommendations on Google Play.

Levent Koc, Cyrus Master

Item-to-item Recommendations at Pinterest.

Stephanie Kaye Rogers

A Recommender System to tackle Enterprise Collaboration.

Gabriel de Souza Pereira Moreira, Gilmar Alves de Souza

Conversational Recommendation System with Unsupervised Learning.

Yueming Sun, Yi Zhang, Yunfei Chen, Roger Jin

Powering Content Discovery through Scalable, Realtime Profiling of Users' Content Preferences.

Ido Tamir, Roy Bass, Guy Kobrinsky, Baruch Brutman, Ronny Lempel, Yoram Dayagi

RecExp: A Semantic Recommender System with Explanation Based on Heterogeneous Information Network.

Jiawei Hu, Zhiqiang Zhang, Jian Liu, Chuan Shi, Philip S. Yu, Bai Wang

Topical Semantic Recommendations for Auteur Films.

Christian Rakow, Andreas Lommatzsch, Till Plumbaum

T-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

4th Workshop on Emotions and Personality in Personalized Systems (EMPIRE).

Marko Tkalcic, Berardina De Carolis, Marco de Gemmis, Andrej Kosir

Engendering Health with Recommender Systems.

David Elsweiler, Bernd Ludwig, Alan Said, Hanna Schäfer, Christoph Trattner

RecProfile '16: Workshop on Profiling User Preferences for Dynamic, Online, and Real-Time recommendations.

Rani Nelken

RecSys'16 Joint Workshop on Interfaces and Human Decision Making for Recommender Systems.

Peter Brusilovsky, Alexander Felfernig, Pasquale Lops, John O'Donovan, Giovanni Semeraro, Nava Tintarev, Martijn C. Willemsen

RecSys'16 Workshop on Deep Learning for Recommender Systems (DLRS).

Alexandros Karatzoglou, Balázs Hidasi, Domonkos Tikk, Oren Sar Shalom, Haggai Roitman, Bracha Shapira, Lior Rokach

RecTour 2016: Workshop on Recommenders in Tourism.

Daniel R. Fesenmaier, Tsvi Kuflik, Julia Neidhardt

Third Workshop on New Trends in Content-based Recommender Systems (CBRecSys 2016).

Toine Bogers, Marijn Koolen, Cataldo Musto, Pasquale Lops, Giovanni Semeraro

LSRS'16: Workshop on Large-Scale Recommender Systems.

Tao Ye, Danny Bickson, Denis Parra

3rd Workshop on Recommendation Systems for Television and Online Video (RecSysTV 2016).

Jan Neumann, John Hannon, Claudio Riefolo, Hassan Sayyadi

RecSys Challenge 2016: Job Recommendations.

Fabian Abel, András A. Benczúr, Daniel Kohlsdorf, Martha Larson, Róbert Pálovics

Group Recommender Systems.

Ludovico Boratto

Matrix and Tensor Decomposition in Recommender Systems.

Panagiotis Symeonidis

People Recommendation Tutorial.

Ido Guy, Luiz Augusto Pizzato

Tutorial: Lessons Learned from Building Real-life Recommender Systems.

Xavier Amatriain, Deepak Agarwal

Context-Based IDE Command Recommender System.

Marko Gasparic

Generating Pseudotransactions for Improving Sparse Matrix Factorization.

Agung Toto Wibowo

Gray Sheep, Influential Users, User Modeling and Recommender System Adoption by Startups.

Abhishek Srivastava

Increasing the Trustworthiness of Recommendations by Exploiting Social Media Sources.

Catalin-Mihai Barbu

Mining Information for the Cold-Item Problem.

Fatemeh Pourgholamali

Personalized Support for Healthy Nutrition Decisions.

Hanna Schäfer

Proactive Recommendation Delivery.

Adem Sabic

Recommender Systems from an Industrial and Ethical Perspective.

Dimitris Paraschakis