{"id":54,"date":"2026-01-11T21:33:13","date_gmt":"2026-01-11T21:33:13","guid":{"rendered":"https:\/\/faculty.eng.fau.edu\/xqzhu\/?page_id=54"},"modified":"2026-02-10T16:14:05","modified_gmt":"2026-02-10T16:14:05","slug":"publications","status":"publish","type":"page","link":"https:\/\/faculty.eng.fau.edu\/xqzhu\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"\n<h6 class=\"wp-block-heading\">Selected Publications [Complete List][<a href=\"https:\/\/dblp.uni-trier.de\/pid\/26\/4253.html\" data-type=\"link\" data-id=\"https:\/\/dblp.uni-trier.de\/pid\/26\/4253.html\">DBLP<\/a>][ <a href=\"https:\/\/scholar.google.com\/citations?user=YhKZXtcAAAAJ&amp;hl=en&amp;oi=ao\">Google<\/a>]<\/h6>\n\n\n\n<h2 class=\"wp-block-heading\">Books<\/h2>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Xingquan Zhu, Haicheng Tao, Zhiang Wu, Jie Cao, Kristopher Kalish, and Jeremy Kayne,&nbsp;<em>Fraud Prevention in Online Digital Advertising&nbsp;<\/em>,&nbsp;<a href=\"http:\/\/www.springer.com\/us\/book\/9783319567921\" target=\"_blank\" rel=\"noreferrer noopener\"><em>Springer Briefs in Computer Science&nbsp;<\/em><\/a>, ISBN 978-3-319-56792-1, Springer, 2017.<\/li>\n\n\n\n<li>Xingquan Zhu and Ian Davidson (Edit),&nbsp;<em>Knowledge Discovery and Data Mining: Challenges and Realities&nbsp;<\/em>,&nbsp;<a href=\"https:\/\/www.igi-global.com\/book\/knowledge-discovery-data-mining\/672\" target=\"_blank\" rel=\"noreferrer noopener\"><em>IGI Global&nbsp;<\/em><\/a>, ISBN13: 9781599042527, 2007.<\/li>\n<\/ul>\n\n\n\n<h2 class=\"wp-block-heading\">Journals<\/h2>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Zhabiz Gharibshah and Xingquan Zhu, User Response Prediction in Online Advertising,&nbsp;<a href=\"https:\/\/dl.acm.org\/journal\/csur\" target=\"_blank\" rel=\"noreferrer noopener\"><em>ACM Computing Survey<\/em><\/a>. Accepted. In Press&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/ACS.Zhabiz.advertising.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Daokun Zhang, Jie Yin, Xingquan Zhu, and Chengqi Zhang, Network Representation Learning: A Survey,&nbsp;<a href=\"https:\/\/ieeexplore.ieee.org\/xpl\/RecentIssue.jsp?punumber=6687317\" target=\"_blank\" rel=\"noreferrer noopener\"><em>IEEE Transactions on Big Data<\/em><\/a>. Accepted. In Press&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/NRLSurvey.TBD-1.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Haishuai Wang, Jia Wu, Xingquan Zhu, Yixin Chen, and Chengqi Zhang, Time-Variant Graph Classification,&nbsp;<a href=\"https:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?arnumber=8361785\" target=\"_blank\" rel=\"noreferrer noopener\"><em>IEEE Transactions on Systems, Man, and Cybernetics: Ststems&nbsp;<\/em><\/a>. Accepted. In Press&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/TSMC.Wang_.2018.Variant.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Ting Guo, Shirui Pan, Xingquan Zhu, and Chengqi Zhang, CFOND: Consensus Factorization for Co-Clustering Networked Data,&nbsp;<a href=\"https:\/\/ieeexplore.ieee.org\/document\/8382296\" target=\"_blank\" rel=\"noreferrer noopener\"><em>IEEE Transactions on Knoweldge and Data Engineering&nbsp;<\/em><\/a>, 31(4):706-719, 2019.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/02\/TKDE.Guo_.2019.CFOND_-1.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Youxi Wu, Yao Tong, Xingquan Zhu, and Xindong Wu, NOSEP: Non-Overlapping Sequence Pattern Mining with Gap Constraints,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/xpl\/RecentIssue.jsp?punumber=6221036\" target=\"_blank\" rel=\"noreferrer noopener\"><em>IEEE Transactions on Cybernetics&nbsp;<\/em><\/a>, 48(10):2809-2822, 2018.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TC-nosep-r2.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, and Philip S. Yu, Multiple Structure-View Learning for Graph Classification,&nbsp;<em><a href=\"http:\/\/ieeexplore.ieee.org\/xpl\/RecentIssue.jsp?punumber=5962385\">IEEE Transactions on Neural Networks and Learning Systems<\/a><\/em>, 29(7):3236-3251, 2018.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/02\/TNN.Wu_.2017.Multiview.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>&nbsp;.<\/li>\n\n\n\n<li>Yisen Wang, Shu-Tao Xia, Qingtao Tang, Jia Wu, and Xingquan Zhu, A Novel Consistent Random Forest Framework: Bernoulli Random Forests,&nbsp;<em><a href=\"http:\/\/ieeexplore.ieee.org\/document\/8010895\/\">IEEE Transactions on Neural Networks and Learning Systems<\/a><\/em>, 29(8):3510-3523, 2018.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TNN.Wang.2017.Forest.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Wei Wu, Bin Li, Ling Chen, Xingquan Zhu, and Chengqi Zhang, K-Ary Tree Hashing for Fast Graph Classification,&nbsp;<em><a href=\"https:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?arnumber=8186208\">IEEE Transactions on Knowledge and Data Engineering<\/a><\/em>, 30(5):936-949, 2018.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TKDE.Wu.2018.Kary.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Lianhua Chi, Bin Li, Xingquan Zhu, Shirui Pan, and Ling Chen, Hashing for Adaptive Real-Time Graph Stream Classification With Concept Drifts,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/document\/8016599\/\" target=\"_blank\" rel=\"noreferrer noopener\"><em>IEEE Transactions on Cybernetics&nbsp;<\/em><\/a>, 48(5):1591-1604, 2018.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TC.Chi.2017.Hashing.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, and Xindong Wu, Multi-instance learning with discriminative bag mapping,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/xpl\/RecentIssue.jsp?punumber=69\"><em>IEEE Transactions on Knowledge and Data Engineering&nbsp;<\/em><\/a>, 30(6):1065-1080, 2018.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TKDE.Wu.2017.Multiinstance.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Lianhua Chi and Xingquan Zhu, Hashing Techniques: A Survey and Taxonomy,&nbsp;<em><a href=\"http:\/\/csur.acm.org\/\">ACM Computing Surveys<\/a><\/em>, 50(1), Article No. 11, 2017.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/ACS.Chi.2017.Hashing.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Ting Guo, Jia Wu, Xingquan Zhu, and Chengqi Zhang, Combining Structured Node Content and Topology Information for Networked Graph Clustering,&nbsp;<em><a href=\"http:\/\/tkdd.acm.org\/\">ACM Transactions on Knowledge Discovery from Data&nbsp;<\/a><\/em>, 11(3), Article No. 29, 2017.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TKDD.Guo.2017.Network.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Jia Wu, Shirui Pan, Xingquan Zhu, Chengqi Zhang, and Xindong Wu, Positive and Unlabeled Multi-Graph Learning,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/document\/7439802\/\"><em>IEEE Transactions on Cybernetics<\/em><\/a>, 47(4):818-829, 2017.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TC.Wu.2017.Positive.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Shirui Pan, Jia Wu, Xingquan Zhu, Guodong Long, and Chengqi Zhang, Task Sensitive Feature Exploration and Learning for Multitask Graph Classification,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/document\/7430282\/\"><em>IEEE Transactions on Cybernetics<\/em><\/a>, 47(3):744-758, 2017.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TC.Pan.2017.Task.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Haishuai Wang, Peng Zhang, Xingquan Zhu, Ivor Wai-Hung Tsang, Ling Chen, Chengqi Zhang, and Xindong Wu, Incremental Subgraph Feature Selection for Graph Classification,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/document\/7588124\/\"><em>IEEE Transactions on Knowledge and Data Engineering&nbsp;<\/em><\/a>, 29(1):128-142, 2017.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TKDE.Wang.2017.Graph.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Meng Fang, Jie Yin, and Xingquan Zhu, Supervised Sampling for Networked Data,&nbsp;<a href=\"http:\/\/ac.els-cdn.com\/S0165168415003461\/1-s2.0-S0165168415003461-main.pdf?_tid=46debef0-9241-11e7-8050-00000aacb360&amp;acdnat=1504619652_67596e8d5afc12542d17dc8332378e6c\"><em>Signal Processing<\/em><\/a>, 124:93-102, 2016.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/SP.Fang.2016.Sampling.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Shirui Pan, Jia Wu, Xingquan Zhu, Chengqi Zhang, and Philip S. Yu, Joint Structure Feature Exploration and Regularization for Multi-Task Graph Classification,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?tp=&amp;arnumber=7006795\"><em>IEEE Transactions on Knowledge and Data Engineering&nbsp;<\/em><\/a>, 28(3):715-728, 2016.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TKDE.Pan.2016.Structure.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Meng Fang, Jie Yin, and Xingquan Zhu, Active Exploration for Large Graphs,&nbsp;<a href=\"http:\/\/www.springer.com\/computer\/database+management+%26+information+retrieval\/journal\/10618\"><em>Data Mining and Knowledge Discovery<\/em><\/a>, 30(3):511-549, 2016.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/DMKD.Fang.2016.Active.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Shirui Pan, Jia Wu, and Xingquan Zhu, CogBoost: Boosting for Fast Cost-sensitive Graph Classification,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?tp=&amp;arnumber=7006795\"><em>IEEE Transactions on Knowledge and Data Engineering&nbsp;<\/em><\/a>, 27(11):2933-2946, 2015.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TKDE.Pan.2015.Cogboost.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Bin Li, Xingquan Zhu, Ruijiang Li, and Chengqi Zhang, Rating Knowledge Sharing in Cross-Domain Collaborative Filtering,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?tp=&amp;arnumber=6876146\"><em>IEEE Transactions on Cybernetics<\/em><\/a>, 45(5):1054-1068, May 2015.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TC.Li.2015.Rating.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Shirui Pan, Jia Wu, Xingquan Zhu, and Chengqi Zhang, Graph Ensemble Boosting for Imbalanced Noisy Graph Stream Classification,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?tp=&amp;arnumber=6884853\"><em>IEEE Transactions on Cybernetics<\/em><\/a>, 45(5):940-954, May 2015.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TC.Pan.2015.Graph.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Meng Fang, Jie Yin, Xingquan Zhu, and Chengqi Zhang, TrGraph: Cross-Network Transfer Learning via Common Signature Subgraphs,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?tp=&amp;arnumber=7061528\"><em>IEEE Transactions on Knowledge and Data Engineering&nbsp;<\/em><\/a>, 27(9):2536-2549, 2015.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TKDE.Fang.2015.Trgraph.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Jia Wu, Shirui Pan, Xingquan Zhu, and Zhihua Cai, Boosting for Multi-Graph Classification,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?arnumber=6848779\"><em>IEEE Transactions on Cybernetics<\/em><\/a>, 45(3): 430-443, March 2015.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TC.Wu.2015.Boosting.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Peng Zhang, Chuan Zhou, Peng Wang, Byron J. Gao, Xingquan Zhu, and Li Guo, E-Tree: An Efficient Indexing Structure for Ensemble Models on Data Streams ,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/stamp\/stamp.jsp?tp=&amp;arnumber=6709813\"><em>IEEE Transactions on Knowledge and Data Engineering&nbsp;<\/em><\/a>, 27(2): 461-474, February 2015.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/TKDE.Zhang_.2015.Etree_.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Jia Wu, Xingquan Zhu, Chengqi Zhang, and Philip S. Yu, Bag Constrained Structure Pattern Mining for Multi-Graph Classification,&nbsp;<a href=\"http:\/\/www.computer.org\/portal\/web\/tkde\/\"><em>IEEE Transactions on Knowledge and Data Engineering<\/em><\/a>, 26(10):2382-2396, October, 2014.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/TKDE.Wu_.2014.Bag_compressed.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Meng Fang and Xingquan Zhu, Active Learning with Uncertain Labeling Knowledge,&nbsp;<a href=\"http:\/\/ac.els-cdn.com\/S016786551300384X\/1-s2.0-S016786551300384X-main.pdf?_tid=14de000e-9242-11e7-9dc4-00000aab0f26&amp;acdnat=1504619997_9ed09717f93666918626a04c85d00ac6\"><em>Pattern Recognition Letter<\/em><\/a>, 43:98-108, 2014.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/02\/PRL.Fang_.2014.Active.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Yifan Fu, Bin Li, Xingquan Zhu, and Chengqi Zhang, Active Learning without Knowing Individual Instance Labels: A Pairwise Label Homogeneity Query Approach,&nbsp;<a href=\"http:\/\/www.computer.org\/portal\/web\/tkde\/\"><em>IEEE Transactions on Knowledge and Data Engineering<\/em><\/a>, 26(4):808-822, April, 2014.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/02\/TKDE.Fu_.2014.Active.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Xindong Wu, Xingquan Zhu, Gong-Qing Wu, and Wei Ding, Data Mining with Big Data,&nbsp;<a href=\"http:\/\/www.computer.org\/portal\/web\/tkde\/\"><em>IEEE Transactions on Knowledge and Data Engineering<\/em><\/a>, 26(1):97-107, January, 2014.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/TKDE.Wu_.2014.Big_.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Hanning Yuan, Meng Fang, and Xingquan Zhu, Hierarchical Sampling for Multi-Instance Ensemble Learning,&nbsp;<a href=\"http:\/\/www.computer.org\/portal\/web\/tkde\/\"><em>IEEE Transactions on Knowledge and Data Engineering<\/em><\/a>, 24(12):2900-2905, December 2013.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/TKDE.Yuan_.2013.Multiinstance.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Yifan Fu, Xingquan Zhu, and Ahmed Elmagarmid, Active Learning with Optimal Instance Subset Selection,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/xpl\/RecentIssue.jsp?punumber=3477\"><em>IEEE Transactions on Cybernetics<\/em><\/a>, 43(2):464-475, April, 2013.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/TC.Fu_.2013.Active.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Xindong Wu, Kui Yu, Wei Ding, Hao Wang, and Xingquan Zhu, Online Feature Selection with Streaming Features,&nbsp;<a href=\"http:\/\/www.computer.org\/portal\/web\/tpami\/\"><em>IEEE Transactions on Pattern Analysis and Machine Intelligence<\/em><\/a>, 35(5):1178-1192, May 2013.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/PAMI.Wu_.2013.Feature_compressed.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Yifan Fu, Bin Li, and Xingquan Zhu, A Survey on Instance Selection for Active Learning,&nbsp;<a href=\"https:\/\/link.springer.com\/article\/10.1007\/s10115-012-0507-8\"><em>Knowledge and Information Systems<\/em><\/a>, 35(2):249-283, May 2013.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/KAIS.Fu_.2013.Active.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Xingquan Zhu, Bin Li, Xindong Wu, Dan He, and Chengqi Zhang, CLAP: Collaborative Pattern Mining for Distributed Information Systems&nbsp;<a href=\"http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0167923611001102\"><em>Decision Support Systems<\/em><\/a>, 52(1):40-51, 2011.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/DSS.Zhu_.2011.Clap_.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Xingquan Zhu, Wei Ding, Philip S. Yu, and Chengqi Zhang, One-class learning and concept summarization for data streams&nbsp;<a href=\"https:\/\/link.springer.com\/article\/10.1007\/s10115-010-0331-y\"><em>Knowledge and Information Systems<\/em><\/a>, 28(3):523-553, 2011.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/KAIS.Zhu.2011.Oneclass.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Xingquan Zhu, Cross Domain Semi-Supervised Learning Using Feature Formulation,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/xpl\/RecentIssue.jsp?punumber=3477\"><em>IEEE Transactions on Systems Man and Cybernetics, Part B<\/em><\/a>, 41(6):1727-1638, 2011.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/TC.Zhu_.2011.Domain.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Xingquan Zhu, Peng Zhang, Xiaodong Lin, and Yong Shi, Active Learning from Stream Data Using Optimal Weight Classifier Ensemble,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/xpl\/RecentIssue.jsp?punumber=3477\"><em>IEEE Transactions on Systems Man and Cybernetics, Part B<\/em><\/a>, 40(6):1607-1621, December 2010.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/TC.Zhu_.2010.Stream.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Xingquan Zhu and Ying Yang, A Lazy Bagging Approach to Classification,&nbsp;<a href=\"http:\/\/www.journals.elsevier.com\/pattern-recognition\/\"><em>Pattern Recognition<\/em><\/a>, 41(10): 2980-2992, October, 2008.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/PR.Zhu.2008.Bagging.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[<\/a><a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/PR.Zhu_.2008.Bagging.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">pdf<\/a><a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/PR.Zhu.2008.Bagging.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">]<\/a>.<\/li>\n\n\n\n<li>Xindong Wu and Xingquan Zhu, Mining with Noise Knowledge: Error Awareness Data Mining,&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/xpl\/RecentIssue.jsp?punumber=3468\"><em>IEEE Transactions on Systems Man and Cybernetics, Part A<\/em><\/a>, 38(4): 917-932, July, 2008.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/TCA.Wu_.2008.Noise_.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Xingquan Zhu and Xindong Wu, Class Noise Handling for Effective Cost-Sensitive Learning by Cost-Guided Iterative Classification Filtering,&nbsp;<a href=\"http:\/\/www.computer.org\/portal\/web\/tkde\/\"><em>IEEE Transactions on Knowledge and Data Engineering<\/em><\/a>, 18(10): 1435-1440, November, 2006.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TKDE.Zhu.2006.Cost.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Xingquan Zhu, Xindong Wu, Ahmed Elmagarmid, Zhe Feng, and Lide Wu, Video Data Mining: Semantic Indexing and Event Detection from the Association Perspective,&nbsp;<a href=\"http:\/\/www.computer.org\/portal\/web\/tkde\/\"><em>IEEE Transactions on Knowledge and Data Engineering<\/em><\/a>, 17(5): 665-677, May, 2005.&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TKDE.Zhu.2005.Video.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[<\/a><a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/TKDE.Zhu_.2005.Video_.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">pdf<\/a><a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/papers\/TKDE.Zhu.2005.Video.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">]<\/a>.<\/li>\n\n\n\n<li>Xingquan Zhu and Xindong Wu, Cost-Constrained Data Acquisition for Intelligent Data Preparation,&nbsp;<a href=\"http:\/\/www.computer.org\/portal\/web\/tkde\/\"><em>IEEE Transactions on Knowledge and Data Engineering<\/em><\/a>, 17(11): 1542-1556, November, 2005.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/TKDE.Zhu_.2005.Cost_.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Xingquan Zhu, Ahmed Elmagarmid, Xiangyang Xue, Lide Wu, and Ann Catlin, InsightVide: Towards Hierarchical Video Content Organization for Efficient Browsing, Summarization and Retrieval,\u00a0<a href=\"http:\/\/ieeexplore.ieee.org\/xpl\/RecentIssue.jsp?punumber=6046\"><em>IEEE Transactions on Multimedia<\/em><\/a>, 7(4): 648-666, November, 2005.\u00a0<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/02\/TMM.Zhu_.2005.Insightvideo.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Xingquan Zhu and Xindong Wu, Class Noise vs. Attribute Noise: A Quantitative Study of Their Impacts,&nbsp;<a href=\"http:\/\/www.springer.com\/computer\/ai\/journal\/10462\"><em>Artificial Intelligence Review<\/em><\/a>, 22 (3-4):177-210, November 2004.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/AIR.Zhu_.2004.Noise_.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n\n\n\n<li>Xingquan Zhu, Jianping Fan, Ahmed Elmagarmid, and Xindong Wu, Hierarchical Video Summarization and Content Description Joint Semantic and Visual Similarity,&nbsp;<a href=\"http:\/\/link.springer.com\/journal\/530\"><em>ACM \/ Springer Multimedia System Journal<\/em><\/a>, 9(1):31-53, 2003.&nbsp;<a href=\"http:\/\/faculty.eng.fau.edu\/xqzhu\/files\/2026\/01\/MMS.Zhu_.2003.Video_.pdf\" target=\"_blank\" rel=\"noreferrer noopener\">[pdf]<\/a>.<\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">Conference Proceedings<\/h2>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, and Chengqi Zhang, Multi-Graph-View Learning for Graph Classification,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/icdm2014.sfu.ca\/home.html\">the IEEE 14th International Conference on Data Mining (ICDM &#8217;14)<\/a><\/em>, Shenzhen, China, December 14-17, 2014. (Best Paper Candidate)<\/li>\n\n\n\n<li>Fei Xie, Xindong Wu, and Xingquan Zhu, Document-Specific Keyphrase Extraction Using Sequential Patterns with Wildcards,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/icdm2014.sfu.ca\/home.html\">the IEEE 14th International Conference on Data Mining (ICDM &#8217;14)<\/a><\/em>, Shenzhen, China, December 14-17, 2014.<\/li>\n\n\n\n<li>Ting Guo, Xingquan Zhu, Jian Pei, and Chengqi Zhang, SNOC:Streaming Network Node Classification,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/icdm2014.sfu.ca\/home.html\">the IEEE 14th International Conference on Data Mining (ICDM &#8217;14)<\/a><\/em>, Shenzhen, China, December 14-17, 2014.<\/li>\n\n\n\n<li>Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, Zhihua Cai, and Chengqi Zhang, Exploring Features for Complicated Objects: Cross-View Feature Selection for Multi-Instance Learning,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/cikm2014.fudan.edu.cn\/\">the 23rd ACM International Conference on Conference on Information and Knowledge Management (CIKM &#8217;14)&nbsp;<\/a><\/em>, Nov. 3-7, 2014, Shanghai, China.<\/li>\n\n\n\n<li>Lianhua Chi, Bin Li, and Xingquan Zhu, Context-Preserving Hashing for Fast Text Classification,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.siam.org\/meetings\/sdm14\/\">the 2014 SIAM International Conference on Data Mining (SDM &#8217;14)<\/a><\/em>, April 24-26, 2014, Philadelphia, Pennsylvania, USA.<\/li>\n\n\n\n<li>Jia Wu, Zhibin Hong, Shirui Pan, Xingquan Zhu, and Zhihua Cai, Multi-Graph Learning with Positive and Unlabeled Bags,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.siam.org\/meetings\/sdm14\/\">the 2014 SIAM International Conference on Data Mining (SDM &#8217;14)<\/a><\/em>, April 24-26, 2014, Philadelphia, Pennsylvania, USA.<\/li>\n\n\n\n<li>Lianhua Chi, Bin Li, and Xingquan Zhu, Fast Graph Stream Classification Using Discriminative Clique Hashing,&nbsp;<em>Proceedings of&nbsp;<a href=\"https:\/\/www.cse.fau.edu\/~xqzhu\/index.html\">the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD &#8217;13)<\/a><\/em>, April 14-17, 2013, Brisbane, Australia. (Best Paper Award)<\/li>\n\n\n\n<li>Jia Wu, Xingquan Zhu, Chengqi Zhang, and Zhihua Cai, Multi-Instance Multi-Graph Dual Embedding Learning,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/icdm2013.rutgers.edu\/\">the 13th IEEE International Conference on Data Mining (ICDM &#8217;13)<\/a><\/em>, Dec. 7-10, 2013, Dallas, Texas, USA.<\/li>\n\n\n\n<li>Chun Zhou, Peng Zhang, Jing Guo, Xingquan Zhu and Li Guo, UBLF: An Upper Bound Based Approach to Discover Influential Nodes in Social Networks,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/icdm2013.rutgers.edu\/\">the 13th IEEE International Conference on Data Mining (ICDM &#8217;13)<\/a><\/em>, Dec. 7-10, 2013, Dallas, Texas, USA.<\/li>\n\n\n\n<li>Meng Fang, Jie Yin, and Xingquan Zhu, Transfer Learning across Networks for Collective Classification,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/icdm2013.rutgers.edu\/\">the 13th IEEE International Conference on Data Mining (ICDM &#8217;13)<\/a><\/em>, Dec. 7-10, 2013, Dallas, Texas, USA.<\/li>\n\n\n\n<li>Meng Fang, Jie Yin, Xingquan Zhu, and Chengqi Zhang, Active Class Discovery and Learning for Networked Data,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.siam.org\/meetings\/sdm13\/\">the 13th SIAM International Conference on Data Mining (SDM &#8217;13)<\/a><\/em>, May 2-4, 2013, Austin, Texas, USA.<\/li>\n\n\n\n<li>Shirui Pan, Xingquan Zhu, Chengqi Zhang, and Philip S. Yu, Graph Stream Classification using Labelled and Unlabeled Graphs,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.icde2013.org\/\">the 29th IEEE International Conference on Data Engineering (ICDE &#8217;13)<\/a><\/em>, April 8-11, 2013, Brisbane, Australia.<\/li>\n\n\n\n<li>Meng Fang, Xingquan Zhu, Bin Li, Wei Ding, and Xindong Wu, Self-Taught Active Learning from Crowds,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/icdm2012.ua.ac.be\/\">the 12th IEEE International Conference on Data Mining (ICDM &#8217;12)<\/a><\/em>, December 10-13, 2012, Brussels, Belgium.<\/li>\n\n\n\n<li>Bin Li, Xingquan Zhu, Lianhua Chi, and Chengqi Zhang, Nested Subtree Hash Kernels for Large-scale Graph Classification over Streams,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/icdm2012.ua.ac.be\/\">the 12th IEEE International Conference on Data Mining (ICDM &#8217;12)<\/a><\/em>, December 10-13, 2012, Brussels, Belgium.<\/li>\n\n\n\n<li>Meng Fang and Xingquan Zhu, I Don&#8217;t Know the Label: Active Learning with Blind Knowledge,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/icdm2012.ua.ac.be\/\">the 21st International Conference on Pattern Recognition (ICPR &#8217;12)<\/a><\/em>, November 11-15, 2012, Tsukuba, Japan. (Best Student Paper Award)<\/li>\n\n\n\n<li>Shirui Pan and Xingquan Zhu, CGStream: Continuous Correlated Graph Query for Data Streams,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.cikm2012.org\/index.php\">the 21st ACM Conference on Information and Knowledge Management (CIKM &#8217;12)<\/a><\/em>, Oct. 29 &#8211; Nov. 2, 2012, Hawaii, USA.<\/li>\n\n\n\n<li>Guodong Song, Ling Chen, Xingquan Zhu, and Chengqi Zhang, TCSST: Transfer Classification of Short &amp; Sparse Text Using External Data,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.cikm2012.org\/index.php\">the 21st ACM Conference on Information and Knowledge Management (CIKM &#8217;12)<\/a><\/em>, Oct. 29 &#8211; Nov. 2, 2012, Hawaii, USA.<\/li>\n\n\n\n<li>Dan He, Xingquan Zhu, and D. Stott Parker, How Does Research Evolve? Pattern Mining for Research Meme Cycles,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/icdm2011.cs.ualberta.ca\/\">the 11th IEEE International Conference on Data Mining (ICDM &#8217;11)<\/a><\/em>, Dec. 11-14, 2011, Vancouver, Canada.<\/li>\n\n\n\n<li>Peng Zhang, Byron J. Gao, Xingquan Zhu, and Li Guo, Enabling Fast Lazy Learning for Data Streams,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/icdm2011.cs.ualberta.ca\/\">the 11th IEEE International Conference on Data Mining (ICDM &#8217;11)<\/a><\/em>, Dec. 11-14, 2011, Vancouver, Canada.<\/li>\n\n\n\n<li>Peng Zhang, Jun Li, Peng Wang, Byron J. Gao, Xingquan Zhu, and J. Gao, Enabling Efficient Prediction for Ensemble Models on Data Streams,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.sigkdd.org\/kdd2011\/\">the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD &#8217;11)<\/a><\/em>, San Diego, CA, USA, August 21-24, 2011.<\/li>\n\n\n\n<li>Ruijiang Li, Bin Li, Cheng Jin, Xiangyang Xue, and Xingquan Zhu, Tracking User-Preference Varying Speed in Collaborative Filtering,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.sigkdd.org\/kdd2011\/\">the 25th AAAI Conference on Artificial Intelligence (AAAI &#8217;11)<\/a><\/em>, San Francisco, USA, August 7-11, 2011.<\/li>\n\n\n\n<li>Bin Li, Xingquan Zhu, Ruijiang Li, Chengqi Zhang, Xiangyang Xue, and Xindong Wu, Cross Domain Collaborative Filtering over Time,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.sigkdd.org\/kdd2011\/\">the 22nd International Joint Conference on Artificial Intelligence (IJCAI &#8217;11)<\/a><\/em>, Barcelona, Spain, July 16-22, 2011.<\/li>\n\n\n\n<li>Peng Zhang, Xingquan Zhu, Jianlong Tan, and Li Guo, Classifier and Cluster Ensembling for Mining Concept Drifting Data Streams,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/datamining.it.uts.edu.au\/icdm10\/\">the 10th IEEE International Conference on Data Mining (ICDM &#8217;10)<\/a><\/em>, Dec. 14-17, 2010, Sydney, Australia.<\/li>\n\n\n\n<li>Zhengyu Lu, Xindong Wu, Xingquan Zhu, and Josh Bongard, Ensemble Pruning via Individual Contribution Ordering,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.sigkdd.org\/kdd2010\/\">the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD &#8217;10)<\/a><\/em>, July 25-28, 2010, Washington, DC, USA.<\/li>\n\n\n\n<li>Xingquan Zhu, Xindong Wu, and Chengqi Zhang, Vague One-Class Learning for Data Streams,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.csee.umbc.edu\/conference\/ICDM09\/\">the 9th IEEE International Conference on Data Mining (ICDM &#8217;09)<\/a><\/em>, December 6-9, 2009, Miami, FL, USA.<\/li>\n\n\n\n<li>Peng Zhang, Xingquan Zhu, and Li Guo, Mining Data Streams with Labeled and Unlabeled Training Examples,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.csee.umbc.edu\/conference\/ICDM09\/\">the 9th IEEE International Conference on Data Mining (ICDM &#8217;09)<\/a><\/em>, December 6-9, 2009, Miami, FL, USA.<\/li>\n\n\n\n<li>Xingquan Zhu and Ruoming Jin, Multiple Information Sources Cooperative Learning,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/ijcai.org\/~ijcai09\/\">the 21st International Joint Conference on Artificial Intelligence (IJCAI &#8217;09)<\/a><\/em>, July 11-17, 2009, Pasadena, California, USA.<\/li>\n\n\n\n<li>Xingquan Zhu, Peng Zhang, Xindong Wu, Dan He, Chengqi Zhang, and Yong Shi, Cleansing Noisy Data Streams,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.cs.uvm.edu\/~icdm\/\">the 8th IEEE International Conference on Data Mining (ICDM &#8217;08)<\/a><\/em>, December, 2008, Pisa, Italy.<\/li>\n\n\n\n<li>Peng Zhang, Xingquan Zhu, and Yong Shi, Categorizing and Mining Concept Drifting Data Stream,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.sigkdd.org\/kdd2008\/\">the 14th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD &#8217;08)<\/a><\/em>, August, 2008, Las Vegas, USA.<\/li>\n\n\n\n<li>Xingquan Zhu, Lazy Learning for Classifying Imbalanced Data,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.ist.unomaha.edu\/icdm2007\/\">the 7th IEEE International Conference on Data Mining (ICDM &#8217;07)<\/a><\/em>, October 28-31, 2007, Omaha, USA.<\/li>\n\n\n\n<li>Xingquan Zhu, Peng Zhang, Xiaodong Lin, and Yong Shi, Active Learning from Data Streams,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.ist.unomaha.edu\/icdm2007\/\">the 7th IEEE International Conference on Data Mining (ICDM &#8217;07)<\/a><\/em>, October 28-31, 2007, Omaha, USA.<\/li>\n\n\n\n<li>Xingquan Zhu and Xindong Wu, Discovering Relational Patterns across Multiple Databases,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/ieeexplore.ieee.org\/xpl\/mostRecentIssue.jsp?punumber=4221634\">the 23rd IEEE International Conference on Data Engineering (ICDE &#8217;07)<\/a><\/em>, April 15-20, 2007, Istanbul, Turkey.<\/li>\n\n\n\n<li>Xingquan Zhu, Xindong Wu, Taghi Khoshgoftaar, and Yong Shi, An Empirical Study of the Noise Impact on Cost-Sensitive Learning,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.ijcai-07.org\/\">the 20th International Joint Conference on Artificial Intelligence (IJCAI &#8217;07)<\/a><\/em>, January 6-12, 2007, Hyderabad, India.<\/li>\n\n\n\n<li>Xingquan Zhu and Xindong Wu, Mining Complex Patterns across Sequences with Gap Requirements,&nbsp;<em>Proceedings of&nbsp;<a href=\"http:\/\/www.ijcai-07.org\/\">the 20th International Joint Conference on Artificial Intelligence (IJCAI &#8217;07)<\/a><\/em>, January 6-12, 2007, Hyderabad, India.<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"<p>Selected Publications [Complete List][DBLP][ Google] Books Journals Conference Proceedings<\/p>\n","protected":false},"author":101,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"normal-width-container","site-content-style":"boxed","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center 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