Scottsdale, AZ, USA   May 20, 2012


8:45 - 9:00 Opening Remarks

9:00 - 10:00 Keynote Talk

Getting your Acceptance Rate to 80%: A Checklist for Publishing

Eamonn Keogh, University of California Riverside, USA

Abstract: SIGMOD acceptance rates have generally been in the narrow range of between 14 to 18 percent during the past decade. However, for given individuals the range is much wider. Some people have a zero percent acceptance rate, after five or six frustrating unsuccessful attempts they set their sights lower (or, more pessimistically, they fail to get tenure and stop trying). Many people have acceptance rates that reflect the SIGMOD average of about 20%. Are there people that have perfect acceptance rates?

In this talk I argue that while a perfect acceptance rate is essentially impossible to achieve year after year, an 80% acceptance rate is possible for top conferences. I will show how ten simple “tricks” allow you to significantly increase your odds of acceptance. As proof of utility I note that in the last ten years these ideas have allowed me to achieve 80%+ acceptance rates for many competitive conferences, including ICDM (22 papers), SIGKDD (19 papers), SDM (16 papers), VLDB (6) papers etc.

Bio: Eamonn Keogh is a full professor of computer science at the University of California Riverside. His research areas include data mining, machine learning and information retrieval, specializing in techniques for solving similarity and indexing problems in time-series datasets. He has authored more than 180 papers. He received the IEEE ICDM 2007 best paper award, SIGMOD 2001 best paper award, and runner up best paper award in KDD 1997. He has given over two dozen well received tutorials in the premier conferences in data mining and databases.

10:00 - 10:30 Break

10:30 - 12:00 Big Data

Towards an Extensible Efficient Event Processing Kernel, Mohammad Sadoghi (University of Toronto, Canada)
        Mentor: Boon Thau Loo (University of Pennsylvania, USA)

High Performance Spatial Query Processing for Large Scale Scientific Data, Ablimit Aji (Emory University, USA)
        Mentor: Lei Chen (HKUST, Hongkong, China)

Holistic Indexing: Offline, Online and Adaptive Indexing in the same Kernel, Eleni Petraki (CWI, The Netherlands)
        Mentor: Mario Nascimento (Universityof Alberta, Canada)

12:00 - 13:30 Lunch

13:30 - 15:30 Data Integration and Web Data

Data Quality and Integration in Collaborative Environments, Gregor Endler (University of Erlangen-Nuremberg, Germany)
        Mentor: Ashraf Aboulnaga (University of Waterloo, Canada)

Clustering Techniques for Open Relation Extraction, Filipe Mesquita (University of Alberta, Canada)
        Mentor: Hank Korth (Lehigh University, USA)

RecDB: Towards DBMS Support for Online Recommender Systems, Mohamed Sarwat (University of Minnesota, USA)
        Mentor: Cong Yu (Google Research, USA)

Foundations of Regular Expressions in XML Schema Languages and SPARQL, Katja Losemann (Universität Bayreuth, Germany)
        Mentor: Mariano Consens (University of Toronto, Canada)

15:30 - 16:00 Break

16:00 - 17:45 Towards Graduation

Foundational Aspects of Semantic Web Optimization, Sebastian Skritek (Vienna University of Technology, Austria)
        Mentor: Lei Chen (HKUST, Hongkong, China)

Linking Records In Dynamic World, Pei Li (University of Milan - Bicocca, Italy)
        Mentor: M. Tamer Özsu (University of Waterloo, Canada)

An Adaptive Event Stream Processing Environment, Samujjwal Bhandari (Texas Tech University, USA)
        Mentor: Alexandros Labrinidis (University of Pittsburgh, USA)

Dynamic Management of Resources and Workloads for DBMS in Cloud: A Control-theoretic Approach, Pengcheng Xiong (Georgia Institute of Technology, USA)
        Mentor: Hank Korth (Lehigh University, USA)

Efficient Optimization and Processing for Distributed Monitoring and Control Applications, Mengmeng Liu (University of Pennsylvania, USA)
        Mentor: Xin Luna Dong (AT&T Labs-Research, USA)