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Interactive Query Relaxation System for Addressing the Empty-Answer Problem

The Interactive Query Relaxation System (IQR) developed by Mottin et al. addresses the empty-answer problem in database querying. This innovative approach utilizes a probabilistic optimization framework to enhance user experience by expanding queries intelligently. By assessing users' prior beliefs about finding answers, their preferences for relaxation, and the associated costs, IQR constructs a relaxation tree that facilitates effective querying. The system efficiently computes both full and approximate relaxation trees, improving response times and increasing the likelihood of user satisfaction with query results.

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Interactive Query Relaxation System for Addressing the Empty-Answer Problem

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  1. IQR: An Interactive Query Relaxation System for the Empty-Answer Problem DavideMottin (U of Trento), A. Marascu (IBM Research - Ireland), S. Basu Roy (U of Washigton Tacoma), G. Das (U of Texas Arligton), T. Palpanas (Paris Descartes U) and Y. Velegrakis (U of Trento) Full technical details in: DavideMottin, A. Marascu, S. Basu Roy, G. Das, T. Palpanas and Y. Velegrakis, "A Probabilistic Optimization Framework for the Empty-Answer Problem", Proceedings of VLDB, 6(14), 2013 A Database The Theory • For a relaxation Q’ of Q • Prior • Belief of the user that an answer will be found in the database • Prefer • The likelihood the user will like the relaxed query answers • Relaxation Preference Function • Probability to reject the a relaxation • Probability to accept the relaxation • Cost for a relaxation A Query Cars with ABS, DSL & Manual Transmission The Answer: None What Users Want The Relaxation Tree The Algorithms The Performance • Full Tree • Precompute the whole Relaxation Tree • Fast Optimal • Start from the root and construct the tree on demand, computing min and max cost bounds • Approximate (CDR) • Approximate the cost of each relaxation

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