Chao Zhang is an Assistant Professor in the School of Computational Science and Engineering, Georgia Institute of Technology. His research area is data mining and machine learning. He is particularly interested in developing label-efficient and robust learning techniques, with applications in text mining and spatiotemporal data mining. Chao has published more than 40 papers in top-tier conferences and journals, such as KDD, WWW, SIGIR, VLDB, and TKDE. He is the recipient of the ECML/PKDD Best Student Paper Runner-up Award (2015), Microsoft Star of Tomorrow Excellence Award (2014), and the Chiang Chen Overseas Graduate Fellowship (2013). His developed technologies have received wide media coverage and been transferred to industrial companies. Before joining Georgia Tech, he obtained his Ph.D. in Computer Science from University of Illinois at Urbana-Champaign in 2018.Jiawei Han is the Abel Bliss Professor in the Department of Computer Science, University of Illinois at Urbana-Champaign. He has been researching into data mining, information network analysis, database systems, and data warehousing, with over 900 journal and conference publications. He has chaired or served on many program committees of international conferences in most data mining and database conferences. He also served as the founding Editor-In-Chief of ACM Transactions on Knowledge Discovery from Data and the Director of Information Network Academic Research Center supported by U.S. Army Research Lab (2009–2016), and is the co-Director of KnowEnG, an NIH funded Center of Excellence in Big Data Computing since 2014. He is a Fellow of ACM, a Fellow of IEEE, and received 2004 ACM SIGKDD Innovations Award, 2005 IEEE Computer Society Technical Achievement Award, and 2009 M. Wallace McDowell Award from IEEE Computer Society. His co-authored book Data Mining: Concepts and Techniques has been adopted as a popular textbook worldwide.

• Introduction.- Topic-Level Taxonomy Generation.- Term-Level Taxonomy Generation.- Weakly Supervised Text Classification.- Weakly Supervised Hierarchical Text Classification.- Multidimensional Summarization.- Cross-Dimension Prediction in Cube Space.- Event Detection in Cube Space.- Conclusions.- Bibliography.- Authors' Biographies.

Chao Zhang is an Assistant Professor in the School of Computational Science and Engineering, Georgia Institute of Technology. His research area is data mining and machine learning. He is particularly interested in developing label-efficient and robust learning techniques, with applications in text mining and spatiotemporal data mining. Chao has published more than 40 papers in top-tier conferences and journals, such as KDD, WWW, SIGIR, VLDB, and TKDE. He is the recipient of the ECML/PKDD Best Student Paper Runner-up Award (2015), Microsoft Star of Tomorrow Excellence Award (2014), and the Chiang Chen Overseas Graduate Fellowship (2013). His developed technologies have received wide media coverage and been transferred to industrial companies. Before joining Georgia Tech, he obtained his Ph.D. in Computer Science from University of Illinois at Urbana-Champaign in 2018.Jiawei Han is the Abel Bliss Professor in the Department of Computer Science, University of Illinois at Urbana-Champaign. He has been researching into data mining, information network analysis, database systems, and data warehousing, with over 900 journal and conference publications. He has chaired or served on many program committees of international conferences in most data mining and database conferences. He also served as the founding Editor-In-Chief of ACM Transactions on Knowledge Discovery from Data and the Director of Information Network Academic Research Center supported by U.S. Army Research Lab (2009–2016), and is the co-Director of KnowEnG, an NIH funded Center of Excellence in Big Data Computing since 2014. He is a Fellow of ACM, a Fellow of IEEE, and received 2004 ACM SIGKDD Innovations Award, 2005 IEEE Computer Society Technical Achievement Award, and 2009 M. Wallace McDowell Award from IEEE Computer Society. His co-authored book Data Mining: Concepts and Techniques has been adopted as a popular textbook worldwide.

• Introduction.- Topic-Level Taxonomy Generation.- Term-Level Taxonomy Generation.- Weakly Supervised Text Classification.- Weakly Supervised Hierarchical Text Classification.- Multidimensional Summarization.- Cross-Dimension Prediction in Cube Space.- Event Detection in Cube Space.- Conclusions.- Bibliography.- Authors' Biographies.