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EnglishWe 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.
| Titolo: | Understanding Linked Open Data through Keyword Searching: the KEYRY approach |
| Autori Unitn: | |
| Anno di pubblicazione: | 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. |
| Handle: | http://hdl.handle.net/11572/89010 |
| Appare nelle tipologie: | 04.1 Saggio in atti di convegno (Paper in proceedings) |
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