Understanding linked open data through keyword searching: The KEYRY approach

Sonia Bergamaschi; Francesco Guerra; Silvia Rota; Yannis Velegrakis

doi:10.1145/1966901.1966912

Understanding linked open data through keyword searching: The KEYRY approach

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 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.

Original language	English
Title of host publication	Proceedings - 1st International Workshop on Linked Web Data Management, LWDM 2011
Pages	34-35
Number of pages	2
DOIs	https://doi.org/10.1145/1966901.1966912
Publication status	Published - 20 May 2011
Event	1st International Workshop on Linked Web Data Management, LWDM 2011 - Uppsala, Sweden Duration: 25 Mar 2011 → 25 Mar 2011

Conference

Conference	1st International Workshop on Linked Web Data Management, LWDM 2011
Country/Territory	Sweden
City	Uppsala
Period	25/03/11 → 25/03/11

Keywords

Intensional knowledge
Semantic keyword-based searching

Access to Document

10.1145/1966901.1966912

Cite this

@inproceedings{85c8a100e76b487a8f57bdca790ede0e,

title = "Understanding linked open data through keyword searching: The KEYRY approach",

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.",

keywords = "Intensional knowledge, Semantic keyword-based searching",

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

year = "2011",

month = may,

day = "20",

doi = "10.1145/1966901.1966912",

language = "English",

isbn = "9781450306089",

pages = "34--35",

booktitle = "Proceedings - 1st International Workshop on Linked Web Data Management, LWDM 2011",

note = "1st International Workshop on Linked Web Data Management, LWDM 2011 ; Conference date: 25-03-2011 Through 25-03-2011",

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T1 - Understanding linked open data through keyword searching

T2 - 1st International Workshop on Linked Web Data Management, LWDM 2011

AU - Bergamaschi, Sonia

AU - Guerra, Francesco

AU - Rota, Silvia

AU - Velegrakis, Yannis

PY - 2011/5/20

Y1 - 2011/5/20

N2 - 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.

AB - 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.

KW - Intensional knowledge

KW - Semantic keyword-based searching

UR - http://www.scopus.com/inward/record.url?scp=79956041488&partnerID=8YFLogxK

U2 - 10.1145/1966901.1966912

DO - 10.1145/1966901.1966912

M3 - Conference contribution

AN - SCOPUS:79956041488

SN - 9781450306089

SP - 34

EP - 35

BT - Proceedings - 1st International Workshop on Linked Web Data Management, LWDM 2011

Y2 - 25 March 2011 through 25 March 2011

ER -

Understanding linked open data through keyword searching: The KEYRY approach

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Keywords

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