Entity network prediction using multitype topic models

IEICE Transactions on Information and Systems

Volumn E91-D, Issue 11, 2008, Pages 2589-2598

  Shiozaki, Hitohiro ^a   Eguchi, Koji ^a   Ohkawa, Takenao ^a  

^a KOBE UNIVERSITY   (Japan)

Author keywords

Entity networks; Link prediction; Multitype topic models; Statistical topic models

Indexed keywords

SCALES (WEIGHING INSTRUMENTS);

ARBITRARY NUMBER; LINK PREDICTION; NAMED ENTITIES; NETWORK PREDICTION; SCALE-FREE PROPERTIES; STATISTICAL MODELING; TOPIC MODEL; WEIGHTED NETWORKS;

FORECASTING;

EID: 68749084767     PISSN: 09168532     EISSN: 17451361     Source Type: Journal    
DOI: 10.1093/ietisy/e91-d.11.2589     Document Type: Article

References (14)

1. D. Newman, C. Chemudugunta, P. Smyth, and M. Steyvers, "Statistical entity-topic models," Proc. 12th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.680-686, ACM Press, New York, NY, USA, 2006.
2. D.M. Blei, A.Y. Ng, and M.I. Jordan, "Latent dirichlet allocation," J. Machine Learning Research, vol.3, pp.993-1022, 2003.
3. T. Hofmann, "Probabilistic latent semantic indexing," Proc. 22nd International Conference on Research and Development in Information Retrieval, pp.50-57, Berkeley, California, USA, 1999.
4. N. Ueda and K. Saito, "Parametric mixture models for multi-labeled text," Advances in Neural Information Processing Systems, vol.15, pp.721-728, MIT Press, Cambridge, Massachusetts, USA, 2003.
5. T.L. Griffiths and M. Steyvers, "Finding scientific topics," Proc. National Academy of Sciences of the United States of America, vol.101, pp.5228-5235, 2004.
6. M. Steyvers and T. Griffiths, Handbook of Latent Semantic Analysis, chapter 21, Lawrence Erbaum Associates, Mahwah, New Jersey, London, 2007.
7. Y.W. Teh, D. Newman, and M. Welling, "A collapsed variational Bayesian inference algorithm for latent Dirichlet allocation," Advances in Neural Information Processing Systems, vol.19, pp.1353-1360, MIT Press, Cambridge, Massachusetts, USA, 2006.
8. J. Allan, Topic Detection and Tracking : Event-based Information Organization, chapter 1, Kluwer Academic Publishers, 2002.
9. D.M. Bikel, R.L. Schwartz, and R.M. Weischedel, "An algorithm that learns what's in a name," Mach. Learn., vol.34, pp.211-231, 1999.
10. J.P. Callan, W.B. Croft, and S.M. Harding, "The INQUERY retrieval system," Proc. 3rd International Conference on Database and Expert Systems Applications, pp.78-83, Valencia, Spain, 1992.
11. R. Baeza-Yates and B. Ribeiro-Neto, eds., Modern Information Retrieval, chapter 3, pp.73-97, Addison-Wesley, 1999.
12. S. Robertson, "On gmap: And other transformations," CIKM '06: Proc. 15th ACM International Conference on Information and Knowledge Management, pp.78-83, ACS, New York, NY, USA, 2006.
13. A.-L. Barabási and R. Albert, "Emergence of scaling in random networks," Science, vol.286, no.5439, pp.509-512, 1999.
14. M.E.J. Newman, "The structure and function of complex networks," SIAM Review, vol.45, no.2, pp.167-256, 2003.