Systems translating keyword queries into SQL queries over relational databases are usually referred to in the literature as schema-based approaches. These techniques exploit the information contained in the database schema to build SQL queries that express the intended meaning of the user query. Besides, typically, they perform a preliminary step that associates keywords in the user query with database elements (names of tables, attributes and domain attributes). In this paper, we present a probabilistic approach based on a Hidden Markov Model to provide such mappings. In contrast to most existing techniques, our proposal does not require any a-priori knowledge of the database extension.

Code 105867 Using a HMM based approach for mapping keyword queries into database terms

Velegrakis, Ioannis
2013-01-01

Abstract

Systems translating keyword queries into SQL queries over relational databases are usually referred to in the literature as schema-based approaches. These techniques exploit the information contained in the database schema to build SQL queries that express the intended meaning of the user query. Besides, typically, they perform a preliminary step that associates keywords in the user query with database elements (names of tables, attributes and domain attributes). In this paper, we present a probabilistic approach based on a Hidden Markov Model to provide such mappings. In contrast to most existing techniques, our proposal does not require any a-priori knowledge of the database extension.
2013
Proceedings of the 21st Italian Symposium on Advanced Database Systems
AA. VV.
Reggio Calabria
Universita Reggio Calabria and Centro di Competenza (ICT-SUD)
9781629939490
S., Bergamaschi; F., Guerra; M., Interlandi; S., Rota; R., Trillo; Velegrakis, Ioannis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/100779
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