KDD 2013推荐系统论文

 LCARS: A Location-Content-Aware Recommender System
Authors: Hongzhi Yin, Peking University; Yizhou Sun, ; Bin Cui, Peking University; Zhiting Hu, ; Ling Chen

FISM: Factored Item Similarity Models for Top-N Recommender Systems
Santosh Kabbur, University of Minnesota; George Karypis, University of Minnesota

Making Recommendations from Multiple Domains
Wei Chen, National University of Singapore; Wynne Hsu, National University of Singapore; Mong-Li Lee, National University of Singapore

Combining Latent Factor Model with Location Features for Event-based Group Recommendation
Wei Zhang, Department of Computer Science; Jianyong Wang, Tsinghua University

A New Collaborative Filtering Approach for Increasing the Aggregate Diversity of Recommender Systems
Katja Niemann, Fraunhofer FIT; Martin Wolpers, Fraunhofer Institute for Applied Information Technology

Silence is also evidence: Interpreting dwell time for recommendation from Psychological Perspective
Peifeng Yin, Pennsylvania State University; Ping Luo, HP Lab; Wang-Chien Lee, ; Min Wang, Google Research

 Learning Geographical Preferences for Point-of-Interest Recommendation
Bin Liu, Rutgers Univ; Yanjie Fu, Rutgers University; ZIjun Yao, Rutgers Univ; Hui Xiong, Rutgers, the State University of New Jersey

Collaborative Matrix Factorization with Multiple Similarities for Predictin Drug-Target Interactions
Xiaodong Zheng, Fudan University; Hao Ding, Fudan University; Hiroshi Mamitsuka, Kyoto University; Shanfeng Zhu, Fudan University

有20多篇是有关社会网分析的

Unsupervised Link Prediction Using Aggregative Statistics on Heterogeneous Social Networks
Tsung-Ting Kuo, National Taiwan University; Rui Yan, Peking University; Yu-Yang Huang, National Taiwan University; Perng-Hwa Kung, National Taiwan University; Shou-De Lin, National Taiwan University

 Link Prediction with Social Vector Clocks
Conrad Lee, University College Dublin; Bobo Nick, Konstanz UniversitŠt; Ulrik Brandes, Konstanz UniversitŠt; P‡draig Cunningham, University College Dublin