Skip to main content
SQL QueRIE Recommendations
36th Intl. Conference on Very Large Databases (2010)
  • J. Akbarnejad, San Jose State University
  • G. Chatzopoulou, University of California - Riverside
  • Magdalini Eirinaki, San Jose State University
  • S. Koshy, San Jose State University
  • S. Mittal, San Jose State University
  • D. On, San Jose State University
  • N. Polyzotis
  • J. S. Vindhiya Varman, San Jose State University
This demonstration presents QueRIE, a recommender system that supports interactive database exploration. This system aims at assisting non-expert users of scientific databases by tracking their querying behavior and generating personalized query recommendations. The system is supported by two recommendation engines and the underlying recommendation algorithms. The first identifies potentially “interesting” parts of the database related to the corresponding data analysis task by locating those database parts that were accessed by similar users in the past. The second identifies structurally similar queries to the ones posted by the current user. Both approaches result in a recommendation set of SQL queries that is provided to the user to modify, or directly post to the database. The demonstrated system will enable users to query and get real-time recommendations from the SkyServer database, using user traces collected from the SkyServer query log.
Publication Date
September, 2010
Citation Information
J. Akbarnejad, G. Chatzopoulou, Magdalini Eirinaki, S. Koshy, et al.. "SQL QueRIE Recommendations" 36th Intl. Conference on Very Large Databases (2010)
Available at: