Pay-as-you-go ranking of schema mappings using query logs

Ruhaila Maskat; Norman W. Paton; Suzanne M. Embury; Olivier Bodenreider; Bastien Rance

doi:10.1007/978-3-642-31040-9_4

Pay-as-you-go ranking of schema mappings using query logs

Ruhaila Maskat, Norman W. Paton, Suzanne M. Embury, Olivier Bodenreider (Editor), Bastien Rance (Editor)

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

Abstract

Data integration systems typically make use of mappings to capture the relationships between the data resources to be integrated and the integrated representations presented to users. Manual development and maintenance of such mappings is time consuming and thus costly. Pay-as-you-go approaches to data integration support automatic construction of initial mappings, which are generally of rather poor quality, for refinement in the light of user feedback. However, automatic approaches that produce these mappings typically lead to the generation of multiple, overlapping candidate mappings. To present the most relevant set of results to user queries, the mappings have to be ranked. We proposed a ranking technique that uses information from query logs to discriminate among candidate mappings. The technique is evaluated in terms of how quickly stable rankings can be produced, and to investigate how the rankings track query patterns that are skewed towards specific sources. © 2012 Springer-Verlag.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)\|Lect. Notes Comput. Sci.
Editors	Olivier Bodenreider, Bastien Rance
Publisher	Springer Nature
Pages	37-52
Number of pages	15
Volume	7348
ISBN (Print)	9783642310393
DOIs	https://doi.org/10.1007/978-3-642-31040-9_4
Publication status	Published - 2012
Event	8th International Conference on Data Integration in the Life Sciences, DILS 2012 - College Park, MD Duration: 1 Jul 2012 → …

Conference

Conference	8th International Conference on Data Integration in the Life Sciences, DILS 2012
City	College Park, MD
Period	1/07/12 → …

Keywords

Dataspaces
Implicit Feedback
Pay-as-you-go Data Integration
Ranking
Schema Mapping

Access to Document

10.1007/978-3-642-31040-9_4

Cite this

Maskat, R., Paton, N. W., Embury, S. M., Bodenreider, O. (Ed.), & Rance, B. (Ed.) (2012). Pay-as-you-go ranking of schema mappings using query logs. In O. Bodenreider, & B. Rance (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci. (Vol. 7348, pp. 37-52). Springer Nature. https://doi.org/10.1007/978-3-642-31040-9_4

Maskat, Ruhaila ; Paton, Norman W. ; Embury, Suzanne M. et al. / Pay-as-you-go ranking of schema mappings using query logs. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.. editor / Olivier Bodenreider ; Bastien Rance. Vol. 7348 Springer Nature, 2012. pp. 37-52

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title = "Pay-as-you-go ranking of schema mappings using query logs",

abstract = "Data integration systems typically make use of mappings to capture the relationships between the data resources to be integrated and the integrated representations presented to users. Manual development and maintenance of such mappings is time consuming and thus costly. Pay-as-you-go approaches to data integration support automatic construction of initial mappings, which are generally of rather poor quality, for refinement in the light of user feedback. However, automatic approaches that produce these mappings typically lead to the generation of multiple, overlapping candidate mappings. To present the most relevant set of results to user queries, the mappings have to be ranked. We proposed a ranking technique that uses information from query logs to discriminate among candidate mappings. The technique is evaluated in terms of how quickly stable rankings can be produced, and to investigate how the rankings track query patterns that are skewed towards specific sources. {\textcopyright} 2012 Springer-Verlag.",

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author = "Ruhaila Maskat and Paton, {Norman W.} and Embury, {Suzanne M.} and Olivier Bodenreider and Bastien Rance",

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Maskat, R, Paton, NW , Embury, SM, Bodenreider, O (ed.) & Rance, B (ed.) 2012, Pay-as-you-go ranking of schema mappings using query logs. in O Bodenreider & B Rance (eds), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.. vol. 7348, Springer Nature, pp. 37-52, 8th International Conference on Data Integration in the Life Sciences, DILS 2012, College Park, MD, 1/07/12. https://doi.org/10.1007/978-3-642-31040-9_4

Pay-as-you-go ranking of schema mappings using query logs. / Maskat, Ruhaila; Paton, Norman W.; Embury, Suzanne M. et al.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.. ed. / Olivier Bodenreider; Bastien Rance. Vol. 7348 Springer Nature, 2012. p. 37-52.

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

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AU - Paton, Norman W.

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AB - Data integration systems typically make use of mappings to capture the relationships between the data resources to be integrated and the integrated representations presented to users. Manual development and maintenance of such mappings is time consuming and thus costly. Pay-as-you-go approaches to data integration support automatic construction of initial mappings, which are generally of rather poor quality, for refinement in the light of user feedback. However, automatic approaches that produce these mappings typically lead to the generation of multiple, overlapping candidate mappings. To present the most relevant set of results to user queries, the mappings have to be ranked. We proposed a ranking technique that uses information from query logs to discriminate among candidate mappings. The technique is evaluated in terms of how quickly stable rankings can be produced, and to investigate how the rankings track query patterns that are skewed towards specific sources. © 2012 Springer-Verlag.

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Maskat R, Paton NW , Embury SM, Bodenreider O, (ed.), Rance B, (ed.). Pay-as-you-go ranking of schema mappings using query logs. In Bodenreider O, Rance B, editors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|Lect. Notes Comput. Sci.. Vol. 7348. Springer Nature. 2012. p. 37-52 doi: 10.1007/978-3-642-31040-9_4

Pay-as-you-go ranking of schema mappings using query logs

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