Recommender Systems @ ACM KDD 2012

Looking through the accepted papers at KDD 2012 (Beijing, China). As always, recommendation and personalization is a great application for all sorts of data mining work.. here is a list of titles that caught my eye:

  • Circle-based Recommendation in Online Social Networks
    Author(s): Xiwang Yang*, ECE department, Polytechnic In; Harald Steck, Bell Labs, Alcatel-Lucent Murray Hill, NJ; yong Liu, ECE department, Polytechnic Institute of New York University
  • Cross-domain Collaboration Recommendation
    Author(s): Jie Tang*, Tsinghua University; Sen Wu, Tsinghua University; Jimeng Sun, IBM; Hang Su, Beihang University
  • Incorporating Heterogenous Information for Personalized Tag Recommendation in Social Tagging Systems
    Author(s): Wei Feng*, Tsinghua University; Jianyong Wang, Tsinghua University
  • Learning Binary Codes for Collaborative Filtering
    Author(s): Ke Zhou*, Georgia Tech; Hongyuan Zha, Georgia Tech
  • Learning Personal+Social Latent Factor Model for Social Recommendation
    Author(s): Yelong Sheng*, Kent State University; Ruoming Jin, Kent State University
  • RecMax: Exploiting Recommender Systems for Fun and Profit
    Author(s): Laks Lakshmanan, The University of British Columbia; Amit Goyal*, University of British Columbia
  • Transparent User Models for Personalization
    Author(s): Khalid El-Arini*, Carnegie Mellon University; Ulrich Paquet, Microsoft Research; Ralf Herbrich, Facebook, Inc.; Jurgen Van Gael, Rangespan Ltd.; Blaise Aguera y Arcas, Microsoft Corp.
  • Finding Trending Local Topics in Search Queries for Personalization of a Recommendation System
    Author(s): Ziad Al Bawab; George Mills; Jean-Francois Crespo
  • GetJar Mobile Application Recommendations with Very Sparse Datasets
    Author(s): Kent Shi ; Kamal Ali
  • [Tutorial] Factorization Models for Recommender Systems and Other Applications (slides: link)
    (Lars Schmidt-Thieme, Steffen Rendle)

Happy reading!


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