Graph regularized transductive classification on heterogeneous information networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6321 LNAI, Issue PART 1, 2010, Pages 570-586

  Ji, Ming ^a   Sun, Yizhou ^a   Danilevsky, Marina ^a   Han, Jiawei ^a   Gao, Jing ^a  

^a University of Illinois at Urbana Champaign ^*  (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARBITRARY NETWORKS; ARBITRARY NUMBER; CLASSIFICATION ACCURACY; COMPUTATIONAL SCHEMES; DATA SETS; GRAPH-BASED; HETEROGENEOUS INFORMATION; HOMOGENEOUS NETWORK; INFORMATION NETWORKS; KNOWLEDGE EXTRACTION; LABEL INFORMATION; LABELED AND UNLABELED DATA; LINK STRUCTURE; NETWORK STRUCTURES; OPTIMIZATION PROBLEMS; REGULARIZATION FRAMEWORK; STATE-OF-THE-ART METHODS;

HETEROGENEOUS NETWORKS; INFORMATION SERVICES; LEARNING SYSTEMS;

CLASSIFICATION (OF INFORMATION);

EID: 78049328752     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15880-3_42     Document Type: Conference Paper

References (22)

1. Banerjee, A., Basu, S., Merugu, S.: Multi-way clustering on relation graphs. In: SDM 2007 (2007)
2. Bekkerman, R., El-Yaniv, R., McCallum, A.: Multi-way distributional clustering via pairwise interactions. In: ICML 2005, pp. 41-48 (2005)
3. Belkin, M., Niyogi, P., Sindhwani, V.: Manifold regularization: A geometric framework for learning from examples. J. Mach. Learn. Res. 7, 2399-2434 (2006)
4. Chakrabarti, S., Dom, B., Indyk, P.: Enhanced hypertext categorization using hyperlinks. In: SIGMOD 1998, pp. 307-318. ACM, New York (1998)
5. Chung, F. R. K.: Spectral Graph Theory. Regional Conference Series in Mathematics, vol. 92. AMS, Providence (1997)
6. Friedman, N., Getoor, L., Koller, D., Pfeffer, A.: Learning probabilistic relational models. In: IJCAI 1999 (1999)
7. Gao, J., Liang, F., Fan, W., Sun, Y., Han, J.: Graph-based consensus maximization among multiple supervised and unsupervised models. In: Advances in Neural Information Processing Systems (NIPS), vol. 22, pp. 585-593 (2009)
8. Long, B., Zhang, Z. M., Wu, X., Yu, P. S.: Spectral clustering for multi-type relational data. In: ICML 2006, pp. 585-592 (2006)
9. Lu, Q., Getoor, L.: Link-based classification. In: ICML 2003 (2003)
10. Macskassy, S. A., Provost, F.: A simple relational classifier. In: Proc. of MRDM-2003 at KDD-2003, pp. 64-76 (2003)
11. Macskassy, S. A., Provost, F.: Classification in networked data: A toolkit and a univariate case study. J. Mach. Learn. Res. 8, 935-983 (2007)
12. Neville, J., Jensen, D.: Relational dependency networks. J. Mach. Learn. Res. 8, 653-692 (2007)
13. Neville, J., Jensen, D., Friedland, L., Hay, M.: Learning relational probability trees. In: KDD 2003, pp. 625-630 (2003)
14. Neville, J., Jensen, D., Gallagher, B.: Simple estimators for relational bayesian classifiers. In: ICDM 2003, p. 609 (2003)
15. Sen, P., Getoor, L.: Link-based classification. Technical Report CS-TR-4858, University of Maryland (Februar 2007)
16. Sun, Y., Yu, Y., Han, J.: Ranking-based clustering of heterogeneous information networks with star network schema. In: KDD 2009, pp. 797-806 (2009)
17. Taskar, B., Abbeel, P., Koller, D.: Discriminative probabilistic models for relational data. In: UAI, pp. 485-492 (2002)
18. Taskar, B., Segal, E., Koller, D.: Probabilistic classification and clustering in relational data. In: IJCAI 2001, pp. 870-876 (2001)
19. Yin, Z., Li, R., Mei, Q., Han, J.: Exploring social tagging graph for web object classification. In: KDD 2009, pp. 957-966 (2009)
20. Zhang, T., Popescul, A., Dom, B.: Linear prediction models with graph regularization for web-page categorization. In: KDD 2006, pp. 821-826 (2006)
21. Zhou, D., Bousquet, O., Lal, T. N., Weston, J., Schölkopf, B.: Learning with local and global consistency. In: NIPS 16 (2003)
22. Zhu, X., Ghahramani, Z., Lafferty, J. D.: Semi-supervised learning using gaussian fields and harmonic functions. In: ICML 2003, pp. 912-919 (2003)