Abstract
We propose the demonstration of KEYRY, a tool for translating keyword queries over structured data sources into queries in the native language of the data source. KEYRY does not assume any prior knowledge of the source contents. This allows it to be used in situations where traditional keyword search techniques over structured data that require such a knowledge cannot be applied, i.e., sources on the hidden web or those behind wrappers in integration systems. In KEYRY the search process is modeled as a Hidden Markov Model and the List Viterbi algorithm is applied to computing the top-k queries that better represent the intended meaning of a user keyword query. We demonstrate the tool’s capabilities, and we show how the tool is able to improve its behavior over time by exploiting implicit user feedback provided through the selection among the top-k solutions generated.
This work was partially supported by project “Searching for a needle in mountains of data” http://www.dbgroup.unimo.it/keymantic.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bergamaschi, S., Domnori, E., Guerra, F., Lado, R.T., Velegrakis, Y.: Keyword search over relational databases: a metadata approach. In: Sellis, T.K., Miller, R.J., Kementsietsidis, A., Velegrakis, Y. (eds.) SIGMOD Conference, pp. 565–576. ACM, New York (2011)
Bergamaschi, S., Guerra, F., Rota, S., Velegrakis, Y.: A Hidden Markov Model Approach to Keyword-based Search over Relational Databases. In: De Troyer, O., et al. (eds.) ER 2011 Workshops. LNCS, vol. 6999, pp. 328–331. Springer, Heidelberg (2011)
Bourgeois, F., Lassalle, J.-C.: An extension of the Munkres algorithm for the assignment problem to rectangular matrices. Communications of ACM 14(12), 802–804 (1971)
Li, L., Shang, Y., Shi, H., Zhang, W.: Performance evaluation of hits-based algorithms. In: Hamza, M.H. (ed.) Communications, Internet, and Information Technology, pp. 171–176. IASTED/ACTA Press (2002)
Seshadri, N., Sundberg, C.-E.: List Viterbi decoding algorithms with applications. IEEE Transactions on Communications 42(234), 313–323 (1994)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bergamaschi, S., Guerra, F., Rota, S., Velegrakis, Y. (2011). KEYRY: A Keyword-Based Search Engine over Relational Databases Based on a Hidden Markov Model. In: De Troyer, O., Bauzer Medeiros, C., Billen, R., Hallot, P., Simitsis, A., Van Mingroot, H. (eds) Advances in Conceptual Modeling. Recent Developments and New Directions. ER 2011. Lecture Notes in Computer Science, vol 6999. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24574-9_42
Download citation
DOI: https://doi.org/10.1007/978-3-642-24574-9_42
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24573-2
Online ISBN: 978-3-642-24574-9
eBook Packages: Computer ScienceComputer Science (R0)