WWW 2013

The 22nd International World Wide Web Conference (WWW 2013) will be held from May 13 to May 17 in Rio de Janeiro, Brazil. Recommender systems are explicitly mentioned in the call for papers of different tracks: Social Networks and Graph Analysis, Behavioral Analysis and Personalization, Web Mining.

External links

• http://www2013.org/
• http://www2013.org/authors/

Papers

A list of papers that mention Recommender Systems / Collaborative Filtering / Personalization in their title:

• DIGTOBI: A Recommendation System for Digg Articles using Probabilistic Modeling. Younghoon Kim, Yoonjae Park and Kyuseok Shim.

• Diversified Recommendation on Graphs: Pitfalls, Measures, and Algorithms. Onur Kucuktunc, Erik Saule, Kamer Kaya and Umit V. Catalyurek.

• Do Social Explanations Work? – Studying and Modeling the Effects of Social Explanations in Recommender Systems. Amit Sharma and Dan Cosley.

• From Amateurs to Connoisseurs: Modeling the Evolution of User Expertise through Online Reviews. Julian McAuley and Jure Leskovec.

• HeteroMF: Recommendation in Heterogeneous Information Networks using Context Dependent Factor Models. Mohsen Jamali and Laks Lakshmanan.

• Know Your Personalization: Learning Topic-Level Personalization in Online Services. A Majumder and Nisheeth Shrivastava.

• Localized Matrix Factorization for Recommendation based on Matrix Block Diagonal Forms. Yongfeng Zhang, Min Zhang, Yiqun Liu, Shaoping Ma and Shi Feng.

• Measuring Personalization of Web Search. Aniko Hannak, Piotr Sapiezynski, Arash Molavi Kakhki, Balachander Krishnamurthy, David Lazer, Alan Mislove and Christo Wilson.

• Multi-Label Learning with Millions of Labels: Recommending Advertiser Bid Phrases for Web Pages. Rahul Agrawal, Archit Gupta, Yashoteja Prabhu and Manik Varma.

• One-class Collaborative Filtering with Random Graphs. Ulrich Paquet and Noam Koenigstein.

• Personalized Recommendation via Cross-Domain Triadic Factorization. Liang Hu, Jian Cao, Guandong Xu, Longbing Cao, Zhiping Gu and Can Zhu.

• Predicting Positive and Negative Links in Signed Social Networks by Transfer Learning. Jihang Ye, Hong Cheng, Zhe Zhu and Minghua Chen.

• Probabilistic Group Recommendation via Information Matching. Jagadeesh Gorla, Neal Lathia, Stephen Robertson and Jun Wang.

• TopRec: Domain-Specific Recommendation through Community Topic Mining in Social Network. Xi Zhang, Jian Cheng, Ting Yuan, Biao Niu and Hanqing Lu.

• What Is the Added Value of Negative Links in Online Social Networks? Jérôme Kunegis, Julia Preusse and Felix Schwagereit.

• When Relevance is not Enough: Promoting Diversity and Freshness in Personalized Question Recommendation. Idan Szpektor, Yoelle Maarek and Dan Pelleg.

• SoCo: A Social Network Aided Context-Aware Recommender System. Xin Liu and Karl Aberer.

• [Workshop] MSND2013 The 2nd International Workshop on Mining Social Network Dynamics (MSND) (Hakim Hacid, Shengbo Guo and Athena Vakali)

• [Workshop] RAMSS2013 2nd International Workshop on Real-Time Analysis and Mining (Arkaitz Zubiaga, Damiano Spina, Maarten de Rijke and Markus Strohmaier)

• [Workshop] SRS2013 4th International Workshop on Social Recommender Systems (Ido Guy, Li Chen and Michelle Zhou)

• [Workshop] WiC2013 WWW Workshop on Web Intelligence and Communities (Rajendra Akerkar, Pierre Maret and Laurent Vercouter)