Issue No. 02 - February (2012 vol. 24)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2012.15
I would like to thank the associate editors who have completed their term during 2011: Elisa Bertino, Nicholas Bruno, Christopher Clifton, Minos Garofalakis, and Maurizio Lenzerini, and would like to formally welcome the new associate editors who joined the editorial board in 2011: Deepak Agarwal, James Bailey, Kaushik Chakrabarti, Lei�Chen, Gautam Das, Aristides Gionis, Panagiotiss Ipeirotis, Zachary Ives, Latifur R. Khan, Yehuda Koren, Anthony T.H. Tung, Jianyong Wang, and Hongyuan Zha. I would also like to thank Jian Pei for agreeing to renew his term as an associate editor-in-chief and for helping me with the recruitment of associate editors and handling submissions. Without their contributions, the reviewing process would not have been possible.
Once again, as could be observed from the list of newly appointed associated editors, we have made conscious efforts to recruit well-established researchers with diverse backgrounds and strengths, and from different regions of the world. We will continue to look for highly qualified editors who are committed and dedicated to handling the review process.
The number of submissions in 2010 was 704, and the number of submissions in 2011 was about 680 (projection that includes submissions for the month of December). As mentioned before, it is our primary goal to improve the quality of the journal, and the number of submissions does not quite reflect the quality of the journal. Rather, the quality and timeliness of the papers are better reflections of the quality of the journal. We have kept the acceptance rate around 17�percent, and the turnaround time to about 2.4 months in 2011. The reviewing process does take up a lot of the associate editors’ and reviewers’ time, so it is important for the journal to attract better quality submissions. We have therefore been more critical with the screening of submissions before assigning them to reviewers. As in the past, many papers that are out of the scope of TKDE and are not ready for review were administratively rejected. I have also spent time randomly checking the submissions using cross-checking software, and have rejected a number of papers where the authors did not declare prior work clearly and that contained material from papers belonging to others.
In 2011, we published three special issues/sections: the best papers of the 26th IEEE ICDE (International Conference of Data Engineering 2010), Cloud Data Management, and Keyword Search on Structured Data, which, respectively, appeared in the August, September, and December 2011 issues. I would like to thank the ICDE best papers special issue editors: Shahram Ghandeharizadeh Jayant Haritsa, and Gerhard; the Cloud Data Management special issue editor,:David Lomet; and the Keyword Search special issue editors: Surajit Chaudhuri, Yi Chen, and Jeffrey Xu Yu for their time and contributions. The issues contained very solid papers that addressed contemporary research issues. I hope the readers found them interesting and useful for their research and development.
In the new year, we shall continue to enhance the editorial board as well as the quality and composition of the papers, and I hope to get your support in this regard, as a good journal will benefit most of us, especially the graduate students.
I am happy to announce that TKDE will be transitioning to the OnlinePlus" publication model in 2013. OnlinePlus" is a hybrid of online only and print where subscribers will receive full archival online access plus four quarterly abstract books. In addition, they will receive interactive disks that contain the complete contents of every issue, including supplemental material, all for a lower price than traditional print. For those subscribers who like having a print copy of an issue, all OnlinePlus titles have a Print on Demand option. Please visit www.computer.org/onlineplus for more information.
I would like to conclude this note by thanking all the associate editors, guest editors, reviewers, and authors for their hard work, understanding, and support. Thanks very much indeed.
Beng Chin Ooi
Deepak Agarwal received the PhD degree in statistics from the University of Connecticut; his thesis advisor was Alan Gelfand. He is currently a principal research scientist at Yahoo! Research. Prior to joining Yahoo!, he was a member of the Statistics Department at AT&T Research. At AT&T, he worked on methods for mining massive graphs, statistical models for social network analysis, anomaly detection using a time series approach, and computational approaches for scaling spatial scan statistic to large data sets. His current research interests at Yahoo! include content optimization, large scale regression for massive, sparse, and noisy data via "feature aggregation," anomaly detection in high-dimensional spaces, explore/exploit, and statistical methods for social network analysis. He won a best research paper award at the Joint Statistical Meetings 2001 for his thesis work, which studied deforestation patterns in Madagascar using a two-stage spatial regression model, the best applications paper award at Siam Data Mining 2004 for his Bayesian modeling work on large sparse social networks via stochastic blockmodels, and more recently, the best research paper award at KDD 2007 for his work that proposed a general class of models for large sparse dyadic data. He regularly serves on program committees of prestigious data mining conferences like KDD, SDM, and has organized several invited sessions at the Joint Statistical Meetings. He is an associate editor of the Journal of the American Statistica Association and Applied Stochastic Models in Business and Industry.
James Bailey received the PhD degree in 1998. He is an Australian Research Council Future Fellow in the Department of Computing and Information Systems at the University of Melbourne and has previously held appointments at King’s College and Birkbeck College, The University of London. His research interests are in the area of data mining and machine learning, with a focus on both fundamental topics such as contrast pattern mining and data clustering, as well as application aspects in areas such as health informatics and bioinformatics. He has been the recipient of two best paper awards and serves on the program committees of many international conferences in data mining. His research has consistently been supported by the Australian Research Council.
Kaushik Chakrabarti received the bachelor’s degree in computer science and engineering from the Indian Institute of Technology, Kharagpur, in 1996, and the MS and PhD degrees in computer science from the University of Illinois at Urbana Champaign in 1999 and 2001, respectively. He is a researcher in the Data Management, Mining, and Exploration group at Microsoft Research. His research interests include database management, information retrieval, and data and web mining. He has published more than 30 research papers in the above areas and holds more than 10 patents. Several of his papers have won best paper awards, including ACM SIGMOD and VLDB best paper awards. He regularly serves on the program committees of prestigious conferences like ACM SIGMOD, ICDE, WWW, ICDM, and ICME as well as a reviewer for several journals like the ACM Transactions on Database Systems and VLDB Journal. He is on the editorial board of several journals, including the reputable Distributed and Parallel Databases journal.
Lei Chen received the BS degree in computer science and engineering from Tianjin University, China, in 1994, the MA degree from the Asian Institute of Technology, Thailand, in 1997, and the PhD degree in computer science from the University of Waterloo, Canada, in 2005. He is now an associate professor in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology. His research interests include uncertain and probabilistic databases, multimedia and time series databases, graph databases, and sensor and peer-to-peer databases. He served as a program committee cochair of the international conferences on Web-Age Information Management (WAIM) and Web Information System Engineering (WISE) in 2010. He has also served as a program committee member for various international conferences, including ACM SIGMOD, VLDB, IEEE ICDE, WWW, ACM SIGMM, and ACM SIGKDD. He has published extensively in prestigious conferences and journals such as ACM SIGMOD, VLDB, IEEE ICDE, IEEE Transactions on Knowledge and Data Engineering, and VLDB Journal. He received the best paper awards of the international conference on Databases Systems for Advanced Applications (DASFAA) in 2009 and 2010. He is a member of the IEEE and the ACM and vice-chairman of the ACM Hong Kong chapter.
Gautam Das receiveed the BTech degree in computer science from IIT Kanpur, India, and the PhD degree in computer science from the University of Wisconsin-Madison. He is a professor in the Computer Science and Engineering Department of the University of Texas at Arlington (UTA). Prior to UTA, he held positions at Microsoft Research, Compaq Corporation, and the University of Memphis, as well as visiting positions at IBM Research. His research interests span data mining, information retrieval, databases, approximate query processing, applied graph and network algorithms, and computational geometry. His research has resulted in numerous papers that have appeared in premier conferences and journals such as SIGMOD, VLDB, ICDE, KDD, ACM Transactions on Database Systems, and IEEE Transactions on Knowledge and Data Engineering, including several best paper awards. Dr. Das served as the general chair of ICIT 2009, program committee vice-chair of ICDM 2011, program chair of COMAD 2008, ICDE DBRank 2007, Best Paper Awards Chair of KDD 2006, Best Papers Awards committee member of DAFSAA 2008, program chair of ICIT 2004, as well as on program committees of premier conferences such as SIGMOD, PODS, WWW, ICDE, KDD, and ICML. His research has been supported by grants from federal and state agencies such as the US National Science Foundation, US Office of Naval Research, Department of Education, Texas Higher Education Coordination Board, as well as industry such as Nokia, Microsoft, Cadence, and Apollo.
Aristides Gionis received the PhD degree from the Computer Science Department of Stanford University in 2003. He is a senior research scientist at Yahoo! Research, Barcelona. Between 2003 and 2006, he was a senior researcher in the Basic Research Unit at the Helsinki Institute of Information Technology, Finland. His research interests include data mining, web mining, and algorithmic data analysis. He is currently serving as an associate editor of Knowledge and Information Systems ( KAIS). He served as program committee cochair of ECML PKDD 2010. He has served on the program committee of most premier conferences in databases and data mining, such as VLDB, SIGMOD, PODS, ICDE, KDD, ICDM, and WWW.
Panos Ipeirotis received the PhD degree in computer science from Columbia University in 2004, with distinction. He is an associate professor in the Department of Information, Operations, and Management Sciences at the Leonard N. Stern School of Business of New York University. His recent research interests focus on crowdsourcing and on mining user-generated content on the Internet. He has received three “Best Paper” awards (IEEE ICDE 2005, ACM SIGMOD 2006, and WWW 2011), two “Best Paper Runner Up” awards (JCDL 2002 and ACM KDD 2008), and is also a recipient of a CAREER award from the US National Science Foundation.
Zachary Ives received the BS degree from Sonoma State University and the PhD degree from the University of Washington. He is an associate professor and the Markowitz Faculty Fellow at the University of Pennsylvania. His research interests include data integration, collaborative data sharing, heterogeneous sensor networks, and information provenance and authoritativeness. He is a recipient of the US National Science Foundation CAREER award, an alumnus of the Defense Advanced Research Projects Agency (DARPA) Computer Science Study Panel, and a member of DARPA’s Information Science and Technology advisory panel. He has been a coprogram chair for the XML Symposium (2006), New Trends in Information Integration (2008 and 2010), and WebDB (2012) workshops. He is a recipient of the Christian R. and Mary F. Lindback Foundation Award for Distinguished Teaching and serves as the undergraduate curriculum chair for Penn’s new Singh Program in Market and Social Systems Engineering. He is a coauthor (with Alon Halevy and AnHai Doan) of the upcoming book Principles of Data Integration, to be available in 2012 from Morgan-Kaufmann.
Latifur R. Khan received the MS and PhD degrees in computer science from the University of Southern California in December of 1996 and August of 2000, respectively. He is currently an associate professor in the Computer Science Department at the University of Texas at Dallas (UTD), where he has been teaching and conducting research since September 2000. Dr. Khan is the director of the state-of-the-art DBL@UTD, UTD Data Mining/Database Laboratory, which is the primary center of research related to data mining, semantic web, and image/video annotation at the University of Texas-Dallas. His research areas cover data mining, multimedia information management, semantic web, cloud computing, and database systems. He has served as a committee member for numerous prestigious conferences, symposiums, and workshops. Dr. Khan has published more 150 papers in prestigious journals and conferences including IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Dependable and Secure Computing, IEEE Systems, Man, and Cybernetics, VLDB Journal, the Journal of Web Semantics, Journal of AI Research, Bioinformatics, ICDM, ECML, ISWC, ACM GIS, ACM SACMAT, ACM Multimedia, AAAI, and IJCAI, among others. His research is supported by grants from NASA, NGA, AFOSR, US NSF, IARPA, Nokia, Raytheon, CISCO, and Tektronix. He is a senior member of the IEEE.
Yehuda Koren received the PhD degree in computer science from The Weizmann Institute. He is senior research scientist at Yahoo! Research. Prior to this, he was a principal staff member of AT&T Labs-Research. His main research interests are recommender systems, data mining, machine learning, and information visualization. He was awarded the best paper award at INFOVIS 2005 for work on directed graph layout through constrained energy minimization, the best research paper award at KDD 2009 for his work on collaborative filtering with temporal dynamics, and more recently, the best paper award at RecSys’11 for an ordinal model for predicting personalized item rating distributions. He led the team that won the two progress awards in the Netflix Prize competition, and was part of the team which won the Netflix Grand Prize. Dr. Koren has more than 50 research publications and several patents to his credit. He is serving as a senior program committee member at conferences like KDD, ICDM, and RecSys and recently co-organized the KDD-Cup'11 contest.
Anthony K. H. Tung received both the BSc and MSc degrees in computer sciences from the National University of Singapore in 1997 and 1998, respectively. In 2001, he received the PhD degree in computer sciences from Simon Fraser University (SFU). He is currently an associate professor in the Department of Computer Science, National University of Singapore (NUS), an affiliated faculty member in the NUS Graduate School for Integrative Sciences and Engineering, and a SINGA supervisor. His research group called iData (Intelligence and Data Management Group) has research interests that span across the whole process of converting data into intelligence. He served as a vice program committee chair for ICDE ’09,and is serving as a vice program committee chair for ICDE ’12, and a track program committee chair for VLDB�’12.
Jianyong Wang received the PhD degree in computer science in 1999 from the Institute of Computing Technology, Chinese Academy of Sciences. He is currently an associate professor in the Department of Computer Science and Technology, Tsinghua University, Beijing, China. He was an assistant professor at Peking University, and visited Simon Fraser University, the University of Illinois at Urbana-Champaign, and the University of Minnesota at Twin Cities before joining Tsinghua University in December 2004. His research interests mainly include data mining and Web information management. He has coauthored more than 50 papers in some leading international conferences such as ACM SIGMOD, ACM SIGKDD, VLDB, IEEE ICDE, IEEE ICDM, SIAM SDM, EDBT, IEEE IPDPS, and ACM CIKM, and some top international journals such as the ACM Transactions on Database Systems, IEEE Transactions on Knowledge and Data Engineering, VLDB Journal, ACM Journal of Data and Information Quality, and Data Mining and Knowledge Discovery. He is serving or has served as a program commitee member for some leading international conferences, such as ACM SIGKDD, VLDB, AAAI, IEEE ICDE, WWW, IEEE ICDM, SIAM SDM, ACM CIKM, ACM WSDM, IEEE IPDPS, and ECML/PKDD, the local demo chair for ACM SIGMOD’07, senior program committee for SIAM SDM 2010 & 2011, vice program committee chair for IEEE ICDM 2010 & 2011, program committee cochair for NDBC’10 and ADMA’11, and an editorial board member of the International Journal on Intelligent Data Analysis. He is a senior member of the IEEE, a member of the ACM, a recipient of the 2009 and 2010 HP Labs Innovation Research award, the 2009 Okawa Foundation Research Grant (Japan), WWW ’08 best posters award, and the Year 2007 Program for New Century Excellent Talents in University, State Education Ministry of China.
Hongyuan Zha received the BS degree in mathematics from Fudan University in Shanghai in 1984, and the PhD degree in scientific computing and computational mathematics from Stanford University in 1993. He is a professor in the School of Computational Science and Engineering, College of Computing, Georgia Institute of Technology, and director of the Computational Science and Engineering graduate program at the Georgia Institute of Technology. He was a faculty member in the Department of Computer Science and Engineering at Pennsylvania State University from 1992 to 2006, and he worked from 1999 to 2001 at Inktomi Corporation. His current research interests include Web search, collaborative filtering, and machine learning and data mining applications.
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