A semantics based interactive query formulation technique

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Baer, David ; Groenewoud, Paul ; Kapetanios, Epaminondas ; Keuser, S.

We present an interactive query formulation technique\ud which enables exploitation not only of structural properties\ud of data but also of semantic constraints as posed by the contents of data. The technique aims at the formulation of a semantically consistent or meaningful query by the end-user without any previous knowledge of syntax formalisms and\ud data model semantics. This has been achieved by end-user\ud guidance in that an inference engine suggests semantically\ud rich query terms for further consideration by the end-user.\ud The set of suggested terms at each interaction stage comply\ud with the already considered query terms with respect to\ud structure and contents based semantics. Assignment or selection of operational terms are also allowed, if operational semantics comply with the semantics of data. The interactive query formulation component has been implemented in Java and runs on the client side of a client/server based query answering system architecture.\ud
  • References (35)
    35 references, page 1 of 4

    S . Abiteboul, P. Buneinan, and D. Suciu. Data on the Web: From Relations to semistnrctured Data and XML. Morgan Kaufmann Publishers.,2000.

    S . Abiteboul, D. Quass, J. McHugh, J. Widom, and J. Wiener. The Lore1 Query Language for Semistructured Data. Intemational Joumal on Digital Libraries, 1(1):68- 88,April 1997.

    M. Angelaccio,T.Catarci, and G. Santucci. QBD*: a graphical query language with recursion. IEEE Transactions on Software Engineering, 16(10):1150-1163, 1990.

    E.Bertino and D. Musto. Query Optimization by Using Knowledge about Daia Semantics. IEEE Trans. on Knowledge and Data Engineering, pages 121-155, 1992.

    J. Cardiff, T. Catarci, and G. Santucci. Semanticquery processing in the VEMJS environment. International Journal of Cooperative Injbrmation Systems, 6(2):151-192, June 1997.

    T.Catarci, M. Costabile, S. Levialdi, and C. Batini. Visual query systems for databases: A survey. Joumal of Visual Languages and Computing, 8(2):215-260, April 1997.

    S . Chawathe, H. Garcia-Molina, J. Hammer, K. Ireland, Y. Papakonstantinou. J. Ullman, and J. Widom. The TSIMMIS project: Integration of heterogeneous information sources. In Proc. of Info. Processing Society of Japan, Tokyo, Japan, October 1994.

    W. Chu and Q. Chen. Neighborhood and AssociativeQuery Answering. Intelligent Information Systems, 1(3/4):355- 382, 1992.

    W. Chu and Q. Chen. A Structured Approach for Cooperative Query Answering. IEEE Transactions on Knowledge and Data Engineering, 6(5):738-749, October 1994.

    W. Chu, R.Lei, and Q. Chen. Using 'Qpe Inference and Induced Rules to Provide Intensional Answers. In Proc. of the 7th Intem. Con5 on Data Engineering, April 1991.

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