Design of intelligent query systems for large databases

  • Bharat Bhargava
Part of the Lecture Notes in Computer Science book series (LNCS, volume 80)


In this chapter, we present techniques that allow a query system to play an active (or intelligent) role in communicating knowledge in large databases to the user via meaningful and efficient feedback during query execution. Our approach is to dynamically create temporary files and access paths for information relevant to present query and inform the user of the existence of such information (if security is not compromised). Our research and experience shows that such information can be made accessible at a very low cost when the system is obtaining the data that has been requested and can be presented (if user shows interest) to the user without much effort. Four types of semantics (database semantics, database organization semantics, usage semantics, and real-world semantics) have been identified, their sources, appropriate data structures for their representation, and applicability have been presented with examples from medical and pictorial databases. Our hypothesis for this research is that most users cannot be expected to know all necessary information available in a large database and the query system must play an intelligent role and provide hints to the users.


Query Execution Access Path Medical Information System Query System Suggested Action 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1980

Authors and Affiliations

  • Bharat Bhargava
    • 1
  1. 1.Computer Science DepartmentUniversity of PittsburghPittsburgh

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