Transfer topic modeling with ease and scalability

Proceedings of the 12th SIAM International Conference on Data Mining, SDM 2012

Volumn , Issue , 2012, Pages 564-575

  Kang, Jeon Hyung ^a   Ma, Jun ^a   Liu, Yan ^a  

^a University of Southern California ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

SCALABILITY; SOCIAL NETWORKING (ONLINE); STATISTICS;

LABEL INFORMATION; LABELED DOCUMENTS; LARGE-SCALE APPLICATIONS; LATENT DIRICHLET ALLOCATIONS; MODEL FITTING; TEXT COLLECTION; TOPIC MODELING; TRANSFER LEARNING;

DATA MINING;

EID: 84880235300     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1137/1.9781611972825.49     Document Type: Conference Paper

References (24)

1. A. Arnold, R. Nallapati, and W. Cohen. A comparative study of methods for transductive transfer learning. In ICDM Workshops, 2008.
2. D. Blei, T. Griths, and M. Jordan. The nested chinese restaurant process and bayesian non- parametric inference of topic hierarchies. Journal of the ACM (JACM), 57(2):1-30, 2010.
3. D. Blei, T. Griths, M. Jordan, and J. Tenenbaum. Hierarchical topic models and the nested Chinese restaurant process. Advances in neural information processing systems, 16:106, 2004.
4. D. Blei and J. McAulie. Supervised topic mod- els. Advances in Neural Information Processing Systems, 2008.
5. D. Blei, A. Ng, and M. Jordan. Latent dirich- let allocation. The Journal of Machine Learning Research, 3:993-1022, 2003.
6. D. M. Blei and P. Frazier. Distance dependent chinese restaurant processes.
7. D. Boyd, S. Golder, and G. Lotan. Tweet, tweet, retweet: Conversational aspects of retweeting on twitter. In In Proceedings of the Hawaii Inter- national Conference on System Sciences, 2010.
8. K. R. Canini, M. M. Shashkov, and T. L. Grifths. Modeling transfer learning in human cate- gorization with the hierarchical dirichlet process.
9. A. Celikyilmaz and D. Hakkani-Tur. A hybrid hierarchical model for multi-document summa- rization. In Proceedings of the 48th Annual Meeting of the Association for Computational Lin- guistics, ACL '10, pages 815-824, Stroudsburg, PA, USA, 2010. Association for Computational Linguistics.
10. D. Harman. First text retrieval conference (TREC-1): proceedings. DIANE Publishing, 1993.
11. L. Hong and B. D. Davison. Empirical study of topic modeling in twitter, 2010.
12. S. Lacoste-Julien, F. Sha, and M. Jordan. Dis- cLDA: Discriminative learning for dimensional- ity reduction and classification. NIPS, 2008.
13. H. Lee, A. Battle, R. Raina, and A. Ng. Efficient sparse coding algorithms. NIPS, 2007.
14. D. Lewis, Y. Yang, T. Rose, and F. Li. Rcv1: A new benchmark collection for text categoriza- Tion research. The Journal of Machine Learning Research, 5:361-397, 2004.
15. M. Michelson and S. A. Macskassy. Discovering users' topics of interest on twitter: A first look. In Proceedings of the fourth workshop on Analytics for noisy unstructured text data, AND '10, pages 73-80, New York, NY, USA, Oct. 2010. ACM Press.
16. D. Newman, A. Asuncion, P. Smyth, and M. Welling. Distributed inference for latent dirichlet allocation. Advances in Neural Infor- mation Processing Systems, 20(1081-1088):17-24, 2007.
17. S. Pan and Q. Yang. A survey on transfer learn- ing. TKDE, 2009.
18. K. Puniyani, J. Eisenstein, S. Cohen, and E. Xing. Social links from latent topics in Mi- croblogs. In Proceedings of the NAACL HLT 2010 Workshop on Computational Linguistics in a World of Social Media, pages 19-20. Associa- Tion for Computational Linguistics, 2010.
19. R. Raina, A. Battle, H. Lee, B. Packer, and A. Ng. Self-taught learning: Transfer learning from unlabeled data. In ICML, 2007.
20. D. Ramage, S. Dumais, and D. Liebling. Char- Acterizing microblogs with topic models. In Pro- ceedings of the Fourth International AAAI Con- ference on Weblogs and Social Media. AAAI, 2010.
21. D. Ramage, D. Hall, R. Nallapati, and C. Manning. Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora. In Proceedings of the 2009 Conference on Em- pirical Methods in Natural Language Processing: Volume 1-Volume 1, 2009.
22. A. Ritter, C. Cherry, and B. Dolan. Unsuper- vised modeling of twitter conversations, 2010.
23. Y. Tian, W. Wang, X. Wang, J. Rao, C. Chen, and J. Ma. Topic detection and organization of mobile text messages. In Proceedings of the 19th ACM international conference on Information and knowledge management, CIKM '10, pages 1877-1880, New York, NY, USA, 2010. ACM.
24. H. Wallach, D. Mimno, and A. McCallum. Re- Thinking LDA: Why priors matter. Proceedings of NIPS-09, Vancouver, BC, 2009.