An Approach to Integrating Query Refinement in SQL

  • Michael Ortega-Binderberger
  • Kaushik Chakrabarti
  • Sharad Mehrotra
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2287)


With the emergence of applications that require contentbased similarity retrieval, techniques to support such a retrieval paradigm over database systems have emerged as a critical area of research. User subjectivity is an important aspect of such queries, i.e., which objects are relevant to the user and which are not depends on the perception of the user. Query refinement is used to handle user subjectivity in similarity search systems. This paper explores how to enhance database systems with query refinement for content-based (similarity) searches in object-relational databases. Query refinement is achieved through relevance feedback where the user judges individual result tuples and the system adapts and restructures the query to better reflect the users information need. We present a query refinement framework and an array of strategies for refinement that address different aspects of the problem. Our experiments demonstrate the effectiveness of the query refinement techniques proposed in this paper.


Similarity Score Relevance Feedback Query Point Relevance Judgment Similarity Query 
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 2002

Authors and Affiliations

  • Michael Ortega-Binderberger
    • 1
  • Kaushik Chakrabarti
    • 1
  • Sharad Mehrotra
    • 2
  1. 1.University of Illinois, Urbana-ChampaignUrbanaUSA
  2. 2.University of California, IrvineIrvineUSA

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