Third International Workshop on Ranking in Databases (2009)

In Conjunction with ICDE 2009

March 29th, 2009
Shanghai, China

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Welcome to DBRank 2009

The Third International Workshop on Ranking in Databases (DBRank'09) focuses on the semantics, the modeling and the implementation of ranking and ordering in database systems and applications. In recent years, there has been a great deal of interest in developing effective techniques for ad-hoc search and retrieval in relational databases, document and multimedia databases, scientific information systems, and so on. In particular, a large number of emerging applications require exploratory querying on such databases; examples include users wishing to search databases and catalogs of products such as homes, cars, cameras, restaurants, and photographs. To address the limitations of the traditional Boolean retrieval model in these emerging ad-hoc search and retrieval applications, Top-k queries and ranking query results are gaining increasing importance. In fact, in many of these applications, ranking is an integral part of the semantics, e.g., keyword search, similarity search in multimedia as well as document databases. The increasing importance of ranking is directly derived from the explosion in the volume of data handled by current applications. The sheer amount of data makes it almost impossible to process queries in the traditional compute-then-sort approach. Hence, ranking comes as a great tool for soliciting user preferences and data exploration.

DBRank aims at providing more insight into supporting ranking in database systems and will be an interesting addition to ICDE 2009; the workshop will be a great venue for the many research groups working on ranking worldwide, with a unique opportunity to share their experience in supporting ranking in various database systems, from relational to semi-structures and unstructured data; and on different levels from query formulation and preference modeling to query processing and optimization frameworks. The workshop covers (and is not limited to) the following topics:

• Ranking relational data
• Rank-aware query processing and optimization
• New fundamental developments in top-k algorithms
• Cost-models for top-k algorithms and operators
• User preference specification and query languages
• Ranking in Web and XML databases
• Learning user preferences and ranking functions
• Ranking in distributed and peer-to-peer databases
• Ranking as a data exploration tool
• Ranking queries in data streams and continuous monitoring systems
• Applications of ranking and top-k retrieval from databases
• Ranking multimedia data
• Domain-specific ranking
• Multidimensional data analysis using ranking tools


We welcome original, unpublished manuscripts for 8-pages papers inclusive of all references and figures. Papers should report completed results. Vision papers and descriptions of work-in-progress are also welcomed as short paper submissions (4 pages). Papers must be written in English, and formatted according to ICDE proceeding format. Electronic version of the workshop proceedings will be published by IEEE.

Paper Submission Site

Formatting Instructions


Steering Committee

  • Gautan Das
    Computer Science and Engineering Department
    University of Texas at Arlington
  • Vagelis Hristidis
    School of Computing and Information Sciences
    Florida International University

  • Ihab F. Ilyas
    David R. Cheriton School of Computer Science
    University of Waterloo

Program Co-Chairs

  • Nikos Mamoulis
    Department of Computer Science
    University of Hong Kong
  • Yufei Tao
    Department of Computer Science and Engineering
    Chinese University of Hong Kong

Program Committee

  • Walid Aref, Purdue Univ.
  • Kaushik Chakrabarti, Microsoft
  • Lei Chen, Hong Kong Univ. of Science and Technology
  • Jan Chomicki, Univ. of Buffalo
  • Alfredo Cuzzocrea, Italian National Research Council & University of Calabria
  • Gautam Das, Univ. of Texas at Arlington
  • Ronald Fagin, IBM Almaden
  • Marios Hadjieleftheriou, AT&T
  • Vagelis Hristidis, Florida International Univ.
  • Ihab Ilyas, Univ. of Waterloo
  • HV Jagadish, Univ. of Michigan
  • Werner Kiessling, Univ. of Augsburg
  • Nick Koudas, Univ. of Toronto
  • Xiaofeng Meng, Renmin Univ. of China
  • Themis Palpanas, Univ. of Trento
  • Divesh Srivastava, AT&T
  • Kian-Lee Tan, National Univ. of Singapore
  • Vassilis Tsotras, UC Riverside
  • Haixun Wang, IBM Watson
  • Xiaokui Xiao, Cornell Univ.
  • Jun Yang, Duke Univ.
  • Ke Yi, Hong Kong Univ. of Science and Technology
  • Man Lung Yiu, Aalborg Univ.
  • Aoying Zhou, Fudan Univ.
  • Shuigeng Zhou, Fudan Univ.
  • Xiaofang Zhou, Univ. of Quessland


Divesh Srivastava (AT&T Labs-Research)

Weighted Set Similarity: Queries and Updates.

Consider a universe of items, each of which is associated with a weight, and a database consisting of subsets of these items. Given a query set, a weighted set similarity query identifies either (i) all sets in the database whose cosine similarity to the query set is above a pre-specified threshold, or (ii) the sets in the database with the k highest similarity values to the query set. Weighted set similarity queries are useful in applications like data cleaning and integration for finding approximate matches in the presence of typographical mistakes, multiple formatting conventions, transformation errors, etc. We show that this problem has semantic properties that can be exploited to design index structures that support efficient algorithms for answering queries; these algorithms can achieve arbitrarily stronger pruning than the family of Threshold Algorithms. We describe how these index structures can be efficiently updated using lazy propagation in a way that gives strict guarantees on the quality of subsequent query answers. Finally, we illustrate that our proposed ideas work well in practice for real datasets.

Divesh Srivastava is the head of Database Research at AT&T Labs Research. He received his Ph.D. from the University of Wisconsin, Madison, and his Bachelor of Technology from the Indian Institute of Technology, Bombay, India. His current research interests include data quality, data streams and data privacy.


Important Dates

All deadlines are at 5:00pm
Pacific Standard Time

Paper Submission
November 26, 2008
December 7, 2008

Author Notification
December 26, 2008
January 4, 2009

Camera-Ready Version
January 2, 2009
January 8, 2009



19/11/2008: Submission Site now open

26/1/2009: Program is out! (new)