Affiliation recommendation using auxiliary networks

RecSys'10 - Proceedings of the 4th ACM Conference on Recommender Systems

Volumn , Issue , 2010, Pages 103-110

  Vasuki, Vishvas ^a   Natarajan, Nagarajan ^a   Lu, Zhengdong ^a   Dhillon, Inderjit ^a  

^a University of Texas at Austin   (United States)

Author keywords

Algorithms; Experimentation

Indexed keywords

AUXILIARY NETWORK; EVALUATION STRATEGIES; EXPERIMENTATION; LATENT FACTOR; LINK PREDICTION; REAL-WORLD NETWORKS; RECOMMENDATION ALGORITHMS; SOCIAL NETWORK ANALYSIS; SOCIAL NETWORKS; YOUTUBE;

ALGORITHMS; ELECTRIC NETWORK ANALYSIS;

MATHEMATICAL MODELS;

EID: 78649965057     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1864708.1864731     Document Type: Conference Paper

References (13)

1. Lars Backstrom, Dan Huttenlocher, Jon Kleinberg, and Xiangyang Lan. Group formation in large social networks: membership, growth, and evolution. In KDD '06: Proceedings of the 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 44-54, New York, NY, USA, 2006. ACM.
2. Brett W. Bader and Peter A. Chew. Enhancing multilingual latent semantic analysis with term alignment information. In COLING '08: Proceedings of the 22nd International Conference on Computational Linguistics, pages 49-56, Morristown, NJ, USA, 2008. Association for Computational Linguistics.
3. Wei Chen, Yajun Wang, and Siyu Yang. Efficient influence maximization in social networks. In KDD '09: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 199-208, New York, NY, USA, 2009. ACM.
4. Wen-Yen Chen, Jon-Chyuan Chu, Junyi Luan, Hongjie Bai, Yi Wang, and Edward Y. Chang. Collaborative filtering for orkut communities: discovery of user latent behavior. In WWW '09: Proceedings of the 18th International Conference on World wide web, pages 681-690, New York, NY, USA, 2009. ACM.
5. Wen-Yen Chen, Dong Zhang, and Edward Y. Chang. Combinational collaborative filtering for personalized community recommendation. In KDD '08: Proceeding of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 115-123, New York, NY, USA, 2008. ACM.
6. Thomas Hofmann. Probabilistic latent semantic indexing. In SIGIR '99: Proceedings of the 22nd annual International ACM SIGIR Conference on Research and development in Information Retrieval, pages 50-57, New York, NY, USA, 1999. ACM.
7. David Kempe, Jon Kleinberg, and Éva Tardos. Maximizing the spread of influence through a social network. In KDD '03: Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 137-146, New York, NY, USA, 2003. ACM.
8. David Liben-Nowell and Jon Kleinberg. The link prediction problem for social networks. In CIKM '03: Proceedings of the Twelfth International Conference on Information and Knowledge Management, pages 556-559, New York, NY, USA, 2003. ACM.
9. Alan Mislove, Massimiliano Marcon, Krishna P. Gummadi, Peter Druschel, and Bobby Bhattacharjee. Measurement and analysis of online social networks. In IMC '07: Proceedings of the 7th ACM SIGCOMM Conference on Internet Measurement, pages 29-42, New York, NY, USA, 2007. ACM.
10. B. Savas and I. S. Dhillon. Fast and accurate low rank approximation of massive graphs. Technical report TR-10-18, Department of Computer Science, The University of Texas at Austin, 2010.
11. Ajit P. Singh and Geoffrey J. Gordon. Relational learning via collective matrix factorization. In KDD '08: Proceeding of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 650-658, New York, NY, USA, 2008. ACM.
12. Wei Tang, Zhengdong Lu, and Inderjit S. Dhillon. Clustering with multiple graphs. In ICDM '09: Proceedings of the 2009 Ninth IEEE International Conference on Data Mining, pages 1016-1021, Washington, DC, USA, 2009. IEEE Computer Society.
13. Elena Zheleva, Hossam Sharara, and Lise Getoor. Co-evolution of social and affiliation networks. In KDD '09: Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 1007-1016, New York, NY, USA, 2009. ACM.