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A preference-based approach for interactive weight learning: learning weights within a logic-based query language

  • David Zellhöfer
  • Ingo Schmitt
Article

Abstract

The result quality of queries incorporating impreciseness can be improved by the specification of user-defined weights. Existing approaches evaluate weighted queries by applying arithmetic evaluations on top of the query’s intrinsic logic. This complicates the usage of logic-based optimization. Therefore, we suggest a weighting approach that is completely embedded in a logic.

In order to facilitate the user interaction with the system, we exploit the intuitively comprehensible concept of preferences. In addition, we use a machine-based learning algorithm to learn weighting values in correspondence to the user’s intended semantics of a posed query. Experiments show the utility of our approach.

Keywords

User preferences Condition weighting Database query language Information retrieval DB&IR Machine-based learning 

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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of Computer ScienceBrandenburg University of Technology CottbusCottbusGermany

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