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.

Understanding Linked Open Data through Keyword Searching: the KEYRY approach

Velegrakis, Ioannis
2011

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.
Proceedings of the 1st international workshop on linked web data management
AA. VV.
New York, USA
ACM
S., Bergamaschi; F., Guerra; S., Rota; Velegrakis, Ioannis
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11572/89010
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? ND
social impact