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dc.contributor.authorGuerra, Francesco
dc.contributor.authorVelegrakis, Yannis
dc.contributor.authorCardoso, Jorge
dc.contributor.authorBreslin, John G.
dc.date.accessioned2018-03-16T12:36:49Z
dc.date.available2018-03-16T12:36:49Z
dc.date.issued2018
dc.identifier.citationGuerra, Francesco , Velegrakis, Yannis , Cardoso, Jorge , & Breslin, John G. . (2018). The KEYSTONE IC1302 COST Action. In Julian Szymański & Yannis Velegrakis (Eds.), Semantic Keyword-Based Search on Structured Data Sources, Third International KEYSTONE Conference, IKC 2017, Gdańsk, Poland, September 11-12, 2017, Revised Selected Papers and COST Action IC1302 Reports: Springer International Publishing.en_IE
dc.identifier.isbn978-3-319-74496-4
dc.identifier.isbn978-3-319-74497-1
dc.identifier.urihttp://hdl.handle.net/10379/7202
dc.description.abstractAs more and more data becomes available on the Web, as its complexity increases and as the Web’s user base shifts towards a more general non-technical population, keyword searching is becoming a valuable alternative to traditional SQL queries, mainly due to its simplicity and the lower effort/expertise it requires. Existing approaches suffer from a number of limitations when applied to multi-source scenarios requiring some form of query planning, without direct access to database instances, and with frequent updates precluding any effective implementation of data indexes. Typical scenarios include Deep Web databases, virtual data integration systems and data on the Web. Therefore, building effective keyword searching techniques can have an extensive impact since it allows non-professional users to access large amounts of information stored in structured repositories through simple keyword-based query interfaces. This revolutionises the paradigm of searching for data since users are offered access to structured data in a similar manner to the one they already use for documents. To build a successful, unified and effective solution, the action “semantic KEYword-based Search on sTructured data sOurcEs” (KEYSTONE) promoted synergies across several disciplines, such as semantic data management, the Semantic Web, information retrieval, artificial intelligence, machine learning, user interaction, interface design, and natural language processing. This paper describes the main achievements of this COST Action.en_IE
dc.description.sponsorshipThis paper was supported by COST (European Cooperation in Science and Technology) under Action IC1302 (KEYSTONE), and Science Foundation Ireland under Grant Number SFI/12/RC/2289 (INSIGHT).en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherSpringer International Publishingen_IE
dc.relation.ispartofSemantic Keyword-Based Search on Structured Data Sourcesen
dc.subjectKEYSTONEen_IE
dc.subjectKeywordsen_IE
dc.subjectSearchingen_IE
dc.subjectSemanticen_IE
dc.subjectKeyword-based searchen_IE
dc.subjectStructured data sourcesen_IE
dc.titleThe KEYSTONE IC1302 COST Actionen_IE
dc.typeBook chapteren_IE
dc.date.updated2018-03-08T12:40:15Z
dc.local.publishedsourcehttps://www.springerprofessional.de/en/the-keystone-ic1302-cost-action/15444352en_IE
dc.description.peer-reviewedNot peer reviewed
dc.contributor.funderScience Foundation Irelanden_IE
dc.contributor.funderEuropean Cooperation in Science and Technologyen_IE
dc.internal.rssid13996002
dc.local.contactJohn Breslin, Electrical & Electronic Eng, Room 3047, Engineering Building, Nui Galway. 2622 Email: john.breslin@nuigalway.ie
dc.local.copyrightcheckedNo
dc.local.versionPUBLISHED
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/
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