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A Probabilistic Scheme for Keyword-Based Incremental Query Construction

Published: 01 March 2012 Publication History

Abstract

Databases enable users to precisely express their informational needs using structured queries. However, database query construction is a laborious and error-prone process, which cannot be performed well by most end users. Keyword search alleviates the usability problem at the price of query expressiveness. As keyword search algorithms do not differentiate between the possible informational needs represented by a keyword query, users may not receive adequate results. This paper presents IQ^P—a novel approach to bridge the gap between usability of keyword search and expressiveness of database queries. IQ^P enables a user to start with an arbitrary keyword query and incrementally refine it into a structured query through an interactive interface. The enabling techniques of IQ^P include: 1) a probabilistic framework for incremental query construction; 2) a probabilistic model to assess the possible informational needs represented by a keyword query; 3) an algorithm to obtain the optimal query construction process. This paper presents the detailed design of IQ^P, and demonstrates its effectiveness and scalability through experiments over real-world data and a user study.

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cover image IEEE Transactions on Knowledge and Data Engineering
IEEE Transactions on Knowledge and Data Engineering  Volume 24, Issue 3
March 2012
190 pages

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IEEE Educational Activities Department

United States

Publication History

Published: 01 March 2012

Author Tags

  1. Query formulation
  2. search process.

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  • (2019)An intelligent automatic query generation interface for relational databases using deep learning techniqueInternational Journal of Speech Technology10.1007/s10772-019-09624-722:3(817-825)Online publication date: 1-Sep-2019
  • (2016)SapphireProceedings of the VLDB Endowment10.14778/3007263.30072899:13(1481-1484)Online publication date: 1-Sep-2016
  • (2013)Supporting keyword search in product databaseProceedings of the VLDB Endowment10.14778/2556549.25565626:14(1786-1797)Online publication date: 1-Sep-2013
  • (2013)Efficient query construction for large scale dataProceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval10.1145/2484028.2484078(573-582)Online publication date: 28-Jul-2013
  • (2012)FreeQProceedings of the 21st International Conference on World Wide Web10.1145/2187980.2188040(325-328)Online publication date: 16-Apr-2012

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