Understanding linked open data through keyword searching: the KEYRY approach

Authors:
Sonia Bergamaschi;Francesco Guerra;Silvia Rota;Yannis Velegrakis
Affiliations:
University of Modena and Reggio, Emilia, Italy;University of Modena and Reggio, Emilia, Italy;University of Modena and Reggio, Emilia, Italy;University of Trento, Italy
Venue:
Proceedings of the 1st International Workshop on Linked Web Data Management
Year:
2011

Citing 3
Cited 1

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Proceedings of the 2011 ACM SIGMOD International Conference on Management of data

dbTrento: the data and information management group at the University of Trento

ACM SIGMOD Record

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Abstract

We introduce KEYRY, a tool for translating keyword queries over structured data sources into queries formulated in their native query language. Since it is not based on analysis of the data source contents, KEYRY finds application in scenarios where sources hold complex and huge schemas, apt to frequent changes, such as sources belonging to the linked open data cloud. KEYRY is based on a probabilistic approach that provides the top-k results that better approximate the intended meaning of the user query.