A latent factor model for highly multi-relational data

Advances in Neural Information Processing Systems

Volumn 4, Issue , 2012, Pages 3167-3175

  Jenatton, Rodolphe ^a   Le Roux, Nicolas ^b   Bordes, Antoine ^c   Obozinski, Guillaume ^b  

^a CENTRE DE MATHÉMATIQUES APPLIQUÉES   (France)

^b ECOLE NORMALE SUPÉRIEURE   (France)

^c UNIVERSITÉ DE TECHNOLOGIE DE COMPIÈGNE   (France)

Author keywords

[No Author keywords available]

Indexed keywords

KNOWLEDGE BASIS; LATENT FACTOR; LATENT FACTOR MODELS; SOCIAL NETWORKS; TYPES OF RELATIONS;

EID: 84877742658     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (28)

1. F. Bach, R. Jenatton, J. Mairal, and G. Obozinski. Optimization with sparsity-inducing penalties. Foundations and Trends in Machine Learning, 4(1):1-106, 2011.
2. A. Bordes, X. Glorot, J. Weston, and Y. Bengio. A semantic matching energy function for learning with multi-relational data. Machine Learning, 2012. To appear.
3. L. Bottou and Y. LeCun. Large scale online learning. In Advances in Neural Information Processing Systems, volume 16, pages 217-224, 2004.
4. W. Chu and Z. Ghahramani. Probabilistic models for incomplete multi-dimensional arrays. Journal of Machine Learning Research - Proceedings Track, 5:89-96, 2009.
5. R. Collobert, J. Weston, L. Bottou, M. Karlen, K. Kavukcuoglu, and P. Kuksa. Natural language processing (almost) from scratch. JMLR, 12:2493-2537, 2011.
6. W. Denham. The detection of patterns in Alyawarra nonverbal behavior. PhD thesis, 1973.
7. L. Getoor and B. Taskar. Introduction to Statistical Relational Learning (Adaptive Computation and Machine Learning). The MIT Press, 2007.
8. R. A. Harshman and M. E. Lundy. Parafac: parallel factor analysis. Comput. Stat. Data Anal., 18(1):39-72, Aug. 1994.
9. C. Kemp, J. B. Tenenbaum, T. L. Griffiths, T. Yamada, and N. Ueda. Learning systems of concepts with an infinite relational model. In Proc. of AAAI, pages 381-388, 2006.
10. S. Kok and P. Domingos. Statistical predicate invention. In Proceedings of the 24th international conference on Machine learning, pages 433-440, 2007.
11. A. Korhonen, Y. Krymolowski, and T. Briscoe. A large subcategorization lexicon for natural language processing applications. In Proceedings of LREC, 2006.
12. A. T. McCray. An upper level ontology for the biomedical domain. Comparative and Functional Genomics, 4:80-88, 2003.
13. G. Miller. Word Net: a Lexical Database for English. Communications of the ACM, 38(11):39-41, 1995.
14. K. Miller, T. Griffiths, and M. Jordan. Nonparametric latent feature models for link prediction. In Advances in Neural Information Processing Systems 22, pages 1276-1284. 2009.
15. M. Nickel, V. Tresp, and H.-P. Kriegel. A three-way model for collective learning on multi-relational data. In Proceedings of the 28th Intl Conf. on Mach. Learn., pages 809-816, 2011.
16. M. Nickel, V. Tresp, and H.-P. Kriegel. Factorizing YAGO: scalable machine learning for linked data. In Proc. of the 21st intl conf. on WWW, pages 271-280, 2012.
17. K. Nowicki and T. A. B. Snijders. Estimation and prediction for stochastic block-structures. Journal of the American Statistical Association, 96(455):1077-1087, 2001.
18. A. Paccanaro and G. Hinton. Learning distributed representations of concepts using linear relational embedding. IEEE Trans. on Knowl. and Data Eng., 13:232-244, 2001.
19. T. Pedersen, S. Patwardhan, and J. Michelizzi. Wordnet:: Similarity: measuring the relatedness of concepts. In Demonstration Papers at HLT-NAACL 2004, pages 38-41, 2004.
20. H. Poon and P. Domingos. Unsupervised ontology induction from text. In Proceedings of the 48th Annual Meeting of the Association for Computl Linguistics, pages 296-305, 2010.
21. R. J. Rummel. Dimensionality of nations project: Attributes of nations and behavior of nation dyads. In ICPSR data file, pages 1950-1965. 1999.
22. D. Shen, J.-T. Sun, H. Li, Q. Yang, and Z. Chen. Document summarization using conditional random fields. In Proc. of the 20th Intl Joint Conf. on Artif. Intel., pages 2862-2867, 2007.
23. A. P. Singh and G. J. Gordon. Relational learning via collective matrix factorization. In Proc. of SIGKDD'08, pages 650-658, 2008.
24. I. Sutskever, R. Salakhutdinov, and J. Tenenbaum. Modelling relational data using bayesian clustered tensor factorization. In Adv. in Neur. Inf. Proc. Syst. 22, 2009.
25. L. R. Tucker. Some mathematical notes on three-mode factor analysis. Psychometrika, 31:279-311, 1966.
26. Y. J. Wang and G. Y. Wong. Stochastic blockmodels for directed graphs. Journal of the American Statistical Association, 82(397), 1987.
27. D. Yang and D. M. W. Powers. Verb similarity on the taxonomy of wordnet. Proceedings of GWC-06, pages 121-128, 2006.
28. J. Zhu. Max-margin nonparametric latent feature models for link prediction. In Proceedings of the 29th Intl Conference on Machine Learning, 2012.