An Attention-based Collaboration Framework for Multi-View Network Representation LearningEI
摘要
Learning distributed node representations in networks has been attracting increasing attention recently due to its effectiveness in a variety of applications. Existing approaches usually study networks with a single type of proximity between nodes, which defines a single view of a network. However, in reality there usually exists multiple types of proximities between nodes, yielding networks with multiple views. This paper studies learning node representations for networks with multiple views, which aims to infer robust node represent...更多
- 1Yizhou Sun, Jiawei Han, Xifeng Yan, Philip S. Yu, Tianyi Wu. PathSim: Meta Path-Based Top-K Similarity Search in Heterogeneous Information Networks.PVLDB, pp. 992-1003, 2011.
- 2David E. Rumelhart, Geoffrey E. Hinton, Ronald J. Williams. Learning representations by back-propagating errors.Neurocomputing: foundations of research, pp. 696-699, 1986.
- 3Derek Greene, Pádraig Cunningham. A Matrix Factorization Approach for Integrating Multiple Data Views.ECML/PKDD (1), pp. 423-438, 2009.
- 6Arthur Liberzon, Aravind Subramanian, Reid Pinchback, Helga Thorvaldsdóttir, Pablo Tamayo, Jill P. Mesirov. Molecular signatures database (MSigDB) 3.0.Bioinformatics, pp. 1739-1740, 2011.
- 7Jie Tang, Jing Zhang, Limin Yao, Juanzi Li, Li Zhang, Zhong Su. ArnetMiner: extraction and mining of academic social networks.KDD, pp. 990-998, 2008.
- 8Jun Yu, Yong Rui, Bo Chen. Exploiting Click Constraints and Multi-view Features for Image Re-ranking.IEEE Transactions on Multimedia, pp. 159-168, 2013.
- 9De Domenico M, Lima A, Mougel P, Musolesi M. The anatomy of a scientific rumor.Scientific reports, pp. 2980-2980, 2013.
- 10Avrim Blum, Tom Mitchell. Combining labeled and unlabeled data with co-training.COLT' 98 Proceedings of the eleventh annual conference on Computational learning theory, pp. 92-100, 1998.
- 11Jian Tang, Ming Zhang, Qiaozhu Mei. One theme in all views: modeling consensus topics in multiple contexts.KDD, pp. 5-13, 2013.
- 12Patrick Jaillet, Gao Song, Gang Yu. Airline network design and hub location problems.Location Science, pp. 195-212, 1996.
- 13Andrea Franceschini, Damian Szklarczyk, Sune Frankild, Michael Kuhn, Milan Simonovic, Alexander Roth, Jianyi Lin, Pablo Minguez, Peer Bork, Christian von Mering, Lars Juhl Jensen. STRING v9.1: protein-protein interaction networks, with increased coverage and integration.Nucleic Acids Research, pp. D808-15, 2013.
- 14Ajit P. Singh, Geoffrey J. Gordon. Relational learning via collective matrix factorization.KDD, pp. 650-658, 2008.
- 15Rong-En Fan, Kai-Wei Chang, Cho-Jui Hsieh, Xiang-Rui Wang, Chih-Jen Lin. LIBLINEAR: A Library for Large Linear Classification.Journal of Machine Learning Research, pp. 1871-1874, 2008.
- 17Omer Levy, Yoav Goldberg. Neural Word Embedding as Implicit Matrix Factorization.NIPS, pp. 2177-2185, 2014.
- 18
- 19Dengyong Zhou, Christopher J. C. Burges. Spectral clustering and transductive learning with multiple views.ICML, pp. 1159-1166, 2007.
- 20Kamalika Chaudhuri, Sham M. Kakade, Karen Livescu, Karthik Sridharan. Multi-view clustering via canonical correlation analysis.ICML, pp. 129-136, 2009.
- 21Jian Tang, Meng Qu, Qiaozhu Mei. PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks.ACM Knowledge Discovery and Data Mining, 2015.
- 22Volodymyr Mnih, Nicolas Heess, Alex Graves, Koray Kavukcuoglu. Recurrent Models of Visual Attention.NIPS, pp. 2204-2212, 2014.
- 23David Liben-Nowell, Jon M. Kleinberg. The link-prediction problem for social networks.JASIST, pp. 1019-1031, 2007.
- 24
- 25Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, Jeffrey Dean. Distributed Representations of Words and Phrases and their Compositionality.neural information processing systems, pp. 3111-3119, 2013.
- 26Abhishek Kumar, Piyush Rai, Hal Daumé III. Co-regularized Multi-view Spectral Clustering.NIPS, pp. 1413-1421, 2011.
- 27Bryan Perozzi, Rami Al-Rfou', Steven Skiena. DeepWalk: online learning of social representations.KDD, pp. 701-710, 2014.
- 28Tom Fawcett, An introduction to ROC analysis.Pattern Recognition Letters, pp. 861-874, 2006.
- 29Xufei Wang, Lei Tang, Huan Liu, Lei Wang. Learning with multi-resolution overlapping communities.Knowl. Inf. Syst., pp. 517-535, 2013.
- 30Aditya Grover, Jure Leskovec. node2vec: Scalable Feature Learning for Networks.KDD, pp. 855-864, 2016.
个人信息
CIKM, pp. 1767-1776, 2017.
被引用次数:27|引用|1
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