A hidden Markov model approach to keyword-based search over relational databases

Sonia Bergamaschi; Francesco Guerra; Silvia Rota; Yannis Velegrakis

doi:10.1007/978-3-642-24606-7_31

A hidden Markov model approach to keyword-based search over relational databases

Sonia Bergamaschi^*, Francesco Guerra, Silvia Rota, Yannis Velegrakis

^*Corresponding author for this work

Sub Data Intensive Systems

University of Modena and Reggio Emilia

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

We present a novel method for translating keyword queries over relational databases into SQL queries with the same intended semantic meaning. In contrast to the majority of the existing keyword-based techniques, our approach does not require any a-priori knowledge of the data instance. It follows a probabilistic approach based on a Hidden Markov Model for computing the top-K best mappings of the query keywords into the database terms, i.e., tables, attributes and values. The mappings are then used to generate the SQL queries that are executed to produce the answer to the keyword query. The method has been implemented into a system called KEYRY (from KEYword to queRY).

Original language	English
Title of host publication	Conceptual Modeling, ER 2011 - 30th International Conference, Proceedings
Pages	411-420
Number of pages	10
DOIs	https://doi.org/10.1007/978-3-642-24606-7_31
Publication status	Published - 9 Nov 2011
Event	30th International Conference on Conceptual Modeling, ER 2011 - Brussels, Belgium Duration: 31 Oct 2011 → 3 Nov 2011

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	6998 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	30th International Conference on Conceptual Modeling, ER 2011
Country/Territory	Belgium
City	Brussels
Period	31/10/11 → 3/11/11

Access to Document

10.1007/978-3-642-24606-7_31

Cite this

Bergamaschi, S., Guerra, F., Rota, S., & Velegrakis, Y. (2011). A hidden Markov model approach to keyword-based search over relational databases. In Conceptual Modeling, ER 2011 - 30th International Conference, Proceedings (pp. 411-420). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6998 LNCS). https://doi.org/10.1007/978-3-642-24606-7_31

Bergamaschi, Sonia ; Guerra, Francesco ; Rota, Silvia et al. / A hidden Markov model approach to keyword-based search over relational databases. Conceptual Modeling, ER 2011 - 30th International Conference, Proceedings. 2011. pp. 411-420 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "A hidden Markov model approach to keyword-based search over relational databases",

abstract = "We present a novel method for translating keyword queries over relational databases into SQL queries with the same intended semantic meaning. In contrast to the majority of the existing keyword-based techniques, our approach does not require any a-priori knowledge of the data instance. It follows a probabilistic approach based on a Hidden Markov Model for computing the top-K best mappings of the query keywords into the database terms, i.e., tables, attributes and values. The mappings are then used to generate the SQL queries that are executed to produce the answer to the keyword query. The method has been implemented into a system called KEYRY (from KEYword to queRY).",

author = "Sonia Bergamaschi and Francesco Guerra and Silvia Rota and Yannis Velegrakis",

year = "2011",

month = nov,

day = "9",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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note = "30th International Conference on Conceptual Modeling, ER 2011 ; Conference date: 31-10-2011 Through 03-11-2011",

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Bergamaschi, S, Guerra, F, Rota, S & Velegrakis, Y 2011, A hidden Markov model approach to keyword-based search over relational databases. in Conceptual Modeling, ER 2011 - 30th International Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6998 LNCS, pp. 411-420, 30th International Conference on Conceptual Modeling, ER 2011, Brussels, Belgium, 31/10/11. https://doi.org/10.1007/978-3-642-24606-7_31

A hidden Markov model approach to keyword-based search over relational databases. / Bergamaschi, Sonia; Guerra, Francesco; Rota, Silvia et al.
Conceptual Modeling, ER 2011 - 30th International Conference, Proceedings. 2011. p. 411-420 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6998 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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N2 - We present a novel method for translating keyword queries over relational databases into SQL queries with the same intended semantic meaning. In contrast to the majority of the existing keyword-based techniques, our approach does not require any a-priori knowledge of the data instance. It follows a probabilistic approach based on a Hidden Markov Model for computing the top-K best mappings of the query keywords into the database terms, i.e., tables, attributes and values. The mappings are then used to generate the SQL queries that are executed to produce the answer to the keyword query. The method has been implemented into a system called KEYRY (from KEYword to queRY).

AB - We present a novel method for translating keyword queries over relational databases into SQL queries with the same intended semantic meaning. In contrast to the majority of the existing keyword-based techniques, our approach does not require any a-priori knowledge of the data instance. It follows a probabilistic approach based on a Hidden Markov Model for computing the top-K best mappings of the query keywords into the database terms, i.e., tables, attributes and values. The mappings are then used to generate the SQL queries that are executed to produce the answer to the keyword query. The method has been implemented into a system called KEYRY (from KEYword to queRY).

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Bergamaschi S, Guerra F, Rota S, Velegrakis Y. A hidden Markov model approach to keyword-based search over relational databases. In Conceptual Modeling, ER 2011 - 30th International Conference, Proceedings. 2011. p. 411-420. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-24606-7_31

A hidden Markov model approach to keyword-based search over relational databases

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