January 2014 (VOL. 26, No. 1) pp. 1-2
/14/$31.00 © 2014 IEEE
Published by the IEEE Computer Society
Published by the IEEE Computer Society
PDFs Require Adobe Acrobat
Happy New Year!
2013 marked a wonderful year for TKDE. While the statistics for November and December 2013 were not available when this editorial was written, TKDE received 822 submissions in the first 10 months of 2013. Among those submissions, 601 received their first round reviews, 20 submissions were invited for minor revision, 150 submissions were invited for major revision, 243 submissions were declined, and 188 were administratively rejected mainly due to topics out of the scope and clear incompetence in technical quality. Final decisions on 458 of those 822 submissions were made, among which 21 were accepted, while there are many other submissions that are still under revision or the second round review. In total, 125 submissions have been accepted in the first 10 months of 2013, including those submitted in 2013 and earlier. The statistics clearly show that TKDE is in a healthy and fruitful state and, at the same time, remains a highly competitive venue for academic publication. I want to thank all authors who submitted to TKDE, and all reviewers and associate editors who helped to run the submission selection process as smoothly as it can be. Your consistent contributions and support make TKDE a fruitful and professional journal.
I want to sincerely thank the four associate editors who finished their terms in the second half of 2013: Drs. Elena Ferrari, Wook-Shin Han, Haixun Wang, and Aidong Zhang. Their significant contributions to the quality and reputation of TKDE have benefited many authors, readers, and reviewers.
At the same time, I want to officially welcome the six associate editors who joined the editorial board in the second half of 2013: Drs. Eamonn Keogh, Feifei Li, Tao Li, Ee-Peng Lim, Stan Matwin, and Myra Spiliopoulou. Particularly, Eamonn Keogh has been kind enough to rejoin the TKDE editorial board after he retired from his first service several years ago. This group of newly appointed associate editors represents our interest and determination in recruiting the most established and active working experts in the wonderful wide spectrum of knowledge and data engineering. Moreover, they are very committed and dedicated to serving the community and handling the review processes, as testified by their rich experience.
As always, on behalf of the TKDE editorial board and the editorial office, I thank all authors and readers for your enthusiastic support. We look forward to continuing to serve you to the best in the future.
Eamonn Keogh’s research areas include machine learning and data mining, specializing in techniques for solving similarity and indexing problems in time-series data sets. He has authored more than 200 papers. He has received best paper awards from ACM SIGMOD, ACM SIGKDD, IEEE ICDM, and SIAM SDM.
Feifei Li received the BS degree in computer engineering from Nanyang Technological University, Singapore, in 2002 (transferred from Tsinghua University, China) and the PhD degree in computer science from Boston University in 2007. He is an associate professor in the School of Computing, University of Utah. His research focuses on the scalability, efficiency, and effectiveness issues, as well as security problems, in database systems and large scale data management. He was a recipient of a US National Science Foundation career award in 2011, two HP IRP awards in 2011 and 2012, respectively, a Google App Engine award, and the IEEE ICDE best paper award in 2004.
Tao Li is currently an associate professor in the School of Computing and Information Sciences at Florida International University (FIU). He joined FIU right after receiving the PhD degree in computer science from the University of Rochester in 2004. His research interests include data mining, information retrieval, and machine learning, studying both the algorithmic and application issues. He has published prolifically, with more than 200 technical papers in refereed venues and is on the editorial board of the ACM Transactions on Knowledge Discovery from Data (ACM TKDD) and Knowledge and Information System (KAIS) Journal. He was a recipient of a US National Science Foundation CAREER Award in 2006 and multiple IBM Faculty Research Awards. In 2009, he received FIU’s Excellence in Research and Creativities Award. In 2010, he received the IBM Scalable Data Analytics Innovation Award.
Ee-Peng Lim received the PhD degree from the University of Minnesota, Minneapolis, in 1994. He is a professor in the School of Information Systems at Singapore Management University (SMU). His research interests include social network and web mining, information integration, and digital libraries. He is a codirector of the Living Analytics Research Center jointly established by SMU and Carnegie Mellon University. Other than the IEEE Transactions on Knowledge and Data Engineering ( TKDE), he is also an associate editor of the ACM Transactions on Information Systems (TOIS), Information Processing and Management (IPM), Social Network Analysis and Mining (SNAM), Journal of Web Engineering (JWE), IEEE Intelligent Systems, and the International Journal of Digital Libraries (IJDL). He was a member of the ACM Publications Board until December 2012. He serves on the steering committee of the International Conference on Asian Digital Libraries (ICADL), Pacific Asia Conference on Knowledge Discovery and Data Mining (PAKDD), and International Conference on Social Informatics (Socinfo).
Stan Matwin is a professor and Canada Research Chair (Tier 1) at Dalhousie University, a Distinguished Professor Emeritus at the University of Ottawa, and a full professor in the Institute for Computer Science at the Polish Academy of Sciences. Dr. Matwin is also the director of the Institute for Big Data Analytics at Dalhousie, He holds the titles of fellow of the European Coordinating Committee on AI, fellow of the Canadian AI Association (CAIAC), and Ontario Champion of Innovation. Internationally recognized for his work in text mining, applications of machine learning, and data privacy, he is a member of the editorial boards of leading journals in machine learning and data mining. Author and coauthor of more than 250 refereed papers and a supervisor of more than 50 graduate students, he has extensive experience and interest in innovation and technology transfer.
Myra Spiliopoulou is a professor of business information systems in the Faculty of Computer Science at the Otto-von-Guericke University Magdeburg, Germany, and has been since March 2003. Her research lab “Knowledge Management & Discovery” (KMD) works on data mining, stream mining, and web mining for dynamic environments, and develops methods for model adaption and model monitoring under drift. Her research on topic monitoring, social network monitoring, and analysis of complex dynamic data has been published in renowned international conferences and journals. She regularly presents tutorials on different aspects of complex data mining at ECML PKDD, and she is involved as (senior) reviewer in major conferences on data mining and knowledge discovery, including the IEEE Conference on Data Mining (ICDM), ECML PKDD, ACM SIGKDD, and CIKM. She is a member of the IEEE Computer Society and of the ACM. In Germany, she is a member of the German Informatics Society and the German Classification Society. She is a member of the jury for the best PhD Award of the German Informatics Society and for the best PhD Award of the ACM SIGKDD..
For information on obtaining reprints of this article, please send e-mail to: email@example.com.