RecSys2016论文合集

【文件属性】：
文件名称：RecSys2016论文合集
文件大小：32.55MB
文件格式：RAR
更新时间：2019-12-12 03:50:26
推荐系统 RecSys2016论文合集

【文件预览】：
RecSys2016
----Efficient Bayesian Methods for Graph-based Recommendation.pdf(577KB)
----Mechanism Design for Personalized Recommender Systems.pdf(748KB)
----Crowd-Based Personalized Natural Language Explanations for Recommendations.pdf(2.85MB)
----Latent Factor Representations for Cold-Start Video Recommendation.pdf(903KB)
----Deep Neural Networks for YouTube Recommendations.pdf(1.12MB)
----Personalized Recommendations using Knowledge Graphs A Probabilistic Logic Programming Approach.pdf(664KB)
----Bayesian Low-Rank Determinantal Point Processes.pdf(413KB)
----Mood-Sensitive Truth Discovery For Reliable Recommendation Systems in Social Sensing.pdf(894KB)
----Representation Learning for Homophilic Preferences.pdf(1.31MB)
----Joint User Modeling across Aligned Heterogeneous Sites.pdf(694KB)
----Domain-Aware Grade Prediction and Top-n Course Recommendation.pdf(315KB)
----Learning Hierarchical Feature Influence for Recommendation by Recursive Regularization.pdf(1.21MB)
----Parallel Recurrent Neural Network Architectures for Feature-rich Session-based Recommendations.pdf(894KB)
----TAPER A Contextual Tensor-Based Approach for Personalized Expert Recommendation.pdf(992KB)
----Field-aware Factorization Machines for CTR Prediction.pdf(351KB)
----Meta-Prod2Vec – Product Embeddings Using Side-Information for Recommendation.pdf(759KB)
----Guided Walk A Scalable Recommendation Algorithm for Complex Heterogeneous Social Networks.pdf(5.63MB)
----Vista A Visually, Socially, and Temporally-aware Model for Artistic Recommendation.pdf(3.92MB)
----Fifty Shades of Ratings How to Benefit from a Negative Feedback in Top-N Recommendations Tasks.pdf(1.39MB)
----Using Navigation to Improve Recommendations in Real-Time.pdf(772KB)
----A Coverage-Based Approach to Recommendation Diversity On Similarity Graph.pdf(726KB)
----Ask the GRU Multi-task Learning for Deep Text Recommendations.pdf(1007KB)
----Local Item-Item Models For Top-N Recommendation.pdf(673KB)
----Discovering What You’re Known For A Contextual Poisson Factorization Approach.pdf(1.65MB)
----Gaze Prediction for Recommender Systems.pdf(1.64MB)
----Recommending New Items to Ephemeral Groups Using Contextual User Influence.pdf(597KB)
----Factorization Meets the Item Embedding Regularizing Matrix Factorization with Item Co-occurrence.pdf(2.13MB)
----Convolutional Matrix Factorization for Document Context-Aware Recommendation.pdf(778KB)
----STAR Semiring Trust Inference for Trust-Aware Social Recommenders.pdf(661KB)