Xiangnan Kong

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Philip S. YuProfessor of Computer Science, University of Illinons at ChicagoVerified email at cs.uic.edu
Elke RundensteinerThe William Smith Dean's Professor, Computer Science; Founding Head, Data Science Program; WorcesterVerified email at wpi.edu
John Boaz LeeResearch Scientist, FacebookVerified email at fb.com
Ryan A. RossiAdobe ResearchVerified email at adobe.com
Charu AggarwalDistinguished Research Staff Member, IBM T. J. Watson Research CenterVerified email at us.ibm.com
Tom HartvigsenAssistant Professor, University of VirginiaVerified email at virginia.edu
Xinyue LiuAmazonVerified email at amazon.com
Chuan ShiBeijing University of Posts and TelecommunicationsVerified email at bupt.edu.cn
Cansu SenCodaMetrixVerified email at codametrix.com
Jiawei ZhangUniversity of California, Davis (UC Davis)Verified email at ucdavis.edu
Bokai CaoMetaVerified email at fb.com
Ann RaginResearch Professor of Radiology, Northwestern UniversityVerified email at Northwestern.edu
Nesreen K. AhmedPrincipal Scientist, Cisco AI Research, Intel Labs, Purdue UniversityVerified email at cisco.com
Sihong XieAssociate Professor at AI Thrust, Information Hub, HKUST-GZVerified email at hkust-gz.edu.cn
Lifang HeAssistant Professor of Computer Science, Lehigh UniversityVerified email at lehigh.edu
Yanhua LiAssociate Professor at Worcester Polytechnic InstituteVerified email at wpi.edu
Ying DingBill & Lewis Suit Professor, School of Information, Dell Med, University of Texas at AustinVerified email at austin.utexas.edu
Zhi-Hua ZhouNanjing UniversityVerified email at nju.edu.cn
Michael Kwok-Po NgAMS, AAIA, SIAM Fellows, Dean of Science, Chair Professor in Mathematics & in Data Science, HKBUVerified email at hkbu.edu.hk
JINGYUAN ZHANGIntuit AIVerified email at intuit.com

Xiangnan Kong

Worcester Polytechnic Institute

Verified email at wpi.edu - Homepage

Data Mining Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Data classification CC Aggarwal, CC Aggarwal Data Mining: The Textbook, 285-344, 2015	3312	2015
Inferring anchor links across multiple heterogeneous social networks X Kong, J Zhang, PS Yu Proceedings of the 22nd ACM international conference on Information …, 2013	438	2013
Graph classification using structural attention JB Lee, R Rossi, X Kong Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	322	2018
Hetesim: A general framework for relevance measure in heterogeneous networks C Shi, X Kong, Y Huang, SY Philip, B Wu IEEE Transactions on Knowledge and Data Engineering 26 (10), 2479-2492, 2014	321	2014
Inferring the impacts of social media on crowdfunding CT Lu, S Xie, X Kong, PS Yu Proceedings of the 7th ACM international conference on Web search and data …, 2014	319	2014
Active learning: A survey CC Aggarwal, X Kong, Q Gu, J Han, SY Philip Data classification, 599-634, 2014	289	2014
Transductive Multi-Label Learning via Label Set Propagation X Kong, M Ng, Z Zhou Knowledge and Data Engineering, IEEE Transactions on, 1-1, 2011	218	2011
Meta path-based collective classification in heterogeneous information networks X Kong, PS Yu, Y Ding, DJ Wild Proceedings of the 21st ACM international conference on Information and …, 2012	172	2012
Semi-supervised feature selection for graph classification X Kong, PS Yu Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010	158	2010
Relevance search in heterogeneous networks C Shi, X Kong, PS Yu, S Xie, B Wu Proceedings of the 15th international conference on extending database …, 2012	150	2012
Transferring heterogeneous links across location-based social networks J Zhang, X Kong, PS Yu Proceedings of the 7th ACM international conference on Web search and data …, 2014	149	2014
Predicting social links for new users across aligned heterogeneous social networks J Zhang, X Kong, SY Philip 2013 IEEE 13th International Conference on Data Mining, 1289-1294, 2013	140	2013
Community detection in incomplete information networks W Lin, X Kong, PS Yu, Q Wu, Y Jia, C Li Proceedings of the 21st international conference on World Wide Web, 341-350, 2012	120	2012
Multi-label classification by mining label and instance correlations from heterogeneous information networks X Kong, B Cao, PS Yu Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013	115	2013
Semi-supervised clustering in attributed heterogeneous information networks X Li, Y Wu, M Ester, B Kao, X Wang, Y Zheng Proceedings of the 26th international conference on world wide web, 1621-1629, 2017	109	2017
Graph convolutional networks with motif-based attention JB Lee, RA Rossi, X Kong, S Kim, E Koh, A Rao Proceedings of the 28th ACM international conference on information and …, 2019	105	2019
Learning role-based graph embeddings NK Ahmed, R Rossi, JB Lee, TL Willke, R Zhou, X Kong, H Eldardiry arXiv preprint arXiv:1802.02896, 2018	100	2018
Deep collective classification in heterogeneous information networks Y Zhang, Y Xiong, X Kong, S Li, J Mi, Y Zhu Proceedings of the 2018 world wide web conference, 399-408, 2018	97	2018
Collective prediction of multiple types of links in heterogeneous information networks B Cao, X Kong, SY Philip 2014 IEEE international conference on data mining, 50-59, 2014	85	2014
Dusk: A dual structure-preserving kernel for supervised tensor learning with applications to neuroimages L He, X Kong, PS Yu, X Yang, AB Ragin, Z Hao Proceedings of the 2014 SIAM International Conference on Data Mining, 127-135, 2014	85	2014

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