RecSys '16- Proceedings of the 10th ACM Conference on Recommender Systems

Full Citation in the ACM Digital Library

SESSION: Invited Keynotes

Automated Machine Learning in the Wild

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

SESSION: Paper Session 1: Beyond Accuracy

Recommendations with a Purpose

Recommender Systems for Self-Actualization

A Coverage-Based Approach to Recommendation Diversity On Similarity Graph

A Scalable Approach for Periodical Personalized Recommendations

Multi-Word Generative Query Recommendation Using Topic Modeling

Contrasting Offline and Online Results when Evaluating Recommendation Algorithms

Adaptive, Personalized Diversity for Visual Discovery

Intent-Aware Diversification Using a Constrained PLSA

SESSION: Paper Session 2: Algorithms I

Field-aware Factorization Machines for CTR Prediction

Learning Hierarchical Feature Influence for Recommendation by Recursive Regularization

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

Local Item-Item Models For Top-N Recommendation

Asynchronous Distributed Matrix Factorization with Similar User and Item Based Regularization

Query-based Music Recommendations via Preference Embedding

SESSION: Paper Session 3: Cold Start and Hybrid Methods

Joint User Modeling across Aligned Heterogeneous Sites

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

Latent Factor Representations for Cold-Start Video Recommendation

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

Addressing Cold Start for Next-song Recommendation

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

SESSION: Paper Session 4: User in the Loop

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

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

Gaze Prediction for Recommender Systems

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

Pairwise Preferences Based Matrix Factorization and Nearest Neighbor Recommendation Techniques

Observing Group Decision Making Processes

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

The Value of Online Customer Reviews

SESSION: Paper Session 5: Trust and Reliability

Mechanism Design for Personalized Recommender Systems

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

Crowd-Based Personalized Natural Language Explanations for Recommendations

SESSION: Paper Session 6: Applications

Domain-Aware Grade Prediction and Top-n Course Recommendation

Deep Neural Networks for YouTube Recommendations

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

A Package Recommendation Framework for Trip Planning Activities

SESSION: Paper Session 7: Past, Present & Future

Recommender Systems with Personality

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

Algorithms Aside: Recommendation As The Lens Of Life

Behaviorism is Not Enough: Better Recommendations through Listening to Users

SESSION: Paper Session 8: Deep Learning

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

Convolutional Matrix Factorization for Document Context-Aware Recommendation

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

SESSION: Paper Session 9: Contextual Challenges

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

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

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

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

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

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

MAPS: A Multi Aspect Personalized POI Recommender System

SESSION: Paper Session 10: Social Perspective

Recommending New Items to Ephemeral Groups Using Contextual User Influence

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

STAR: Semiring Trust Inference for Trust-Aware Social Recommenders

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

Representation Learning for Homophilic Preferences

SESSION: Paper Session 11: Algorithms II

Personalized Recommendations using Knowledge Graphs: A Probabilistic Logic Programming Approach

Efficient Bayesian Methods for Graph-based Recommendation

Using Navigation to Improve Recommendations in Real-Time

Bayesian Low-Rank Determinantal Point Processes

Recommending Repeat Purchases using Product Segment Statistics

Bayesian Personalized Ranking with Multi-Channel User Feedback

SESSION: Industry Session 1

Mendeley: Recommendations for Researchers

When Recommendation Systems Go Bad

News Recommendations at scale at Bloomberg Media: Challenges and Approaches

Marsbot: Building a Personal Assistant

Music Personalization at Spotify

SESSION: Industry Session 2

Recommending for the World

The Exploit-Explore Dilemma in Music Recommendation

Feature Selection For Human Recommenders

Considering Supplier Relations and Monetization in Designing Recommendation Systems

A Cross-Industry Machine Learning Framework with Explicit Representations

SESSION: Industry Session 3

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

Hypothesis Testing: How to Eliminate Ideas as Soon as Possible

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

Multi-corpus Personalized Recommendations on Google Play

Item-to-item Recommendations at Pinterest


A Recommender System to tackle Enterprise Collaboration

Conversational Recommendation System with Unsupervised Learning

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

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

Topical Semantic Recommendations for Auteur Films

T-RecS: A Framework for a Temporal Semantic Analysis of the ACM Recommender Systems Conference

SESSION: Workshops and Challenge

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

Engendering Health with Recommender Systems

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

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

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

RecTour 2016: Workshop on Recommenders in Tourism

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

LSRS'16: Workshop on Large-Scale Recommender Systems

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

RecSys Challenge 2016: Job Recommendations


Group Recommender Systems

Matrix and Tensor Decomposition in Recommender Systems

People Recommendation Tutorial

Tutorial: Lessons Learned from Building Real-life Recommender Systems

SESSION: Doctoral Symposium

Context-Based IDE Command Recommender System

Generating Pseudotransactions for Improving Sparse Matrix Factorization

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

Increasing the Trustworthiness of Recommendations by Exploiting Social Media Sources

Mining Information for the Cold-Item Problem

Personalized Support for Healthy Nutrition Decisions

Proactive Recommendation Delivery

Recommender Systems from an Industrial and Ethical Perspective