000167844 001__ 167844
000167844 005__ 20260122161100.0
000167844 0247_ $$2doi$$a10.1016/j.ins.2015.09.013
000167844 0248_ $$2sideral$$a93137
000167844 037__ $$aART-2016-93137
000167844 041__ $$aeng
000167844 100__ $$0(orcid)0000-0003-4239-8785$$aBobed, C.$$uUniversidad de Zaragoza
000167844 245__ $$aQueryGen: Semantic interpretation of keyword queries over heterogeneous information systems
000167844 260__ $$c2016
000167844 5060_ $$aAccess copy available to the general public$$fUnrestricted
000167844 5203_ $$aIn the last years, users have become used to keyword-based search interfaces due to their ease of use. By matching input keywords against huge amounts of textual information and labeled multimedia files, current search engines satisfy most of users'' information needs. However, the principal problem of this kind of search is the semantic gap between the input and the real user need, as keywords are a simplification of the query intended by the user. Moreover, different users could use the same set of keywords to search different information; even the same user could do it at different times. The search system, before accessing any data, should discover first the intended semantics behind the user keywords, in order to return only data fulfilling such semantics. The use of formal query languages is not an option for non-expert users, so a semantic keyword-based search based on semantic interpretation of keyword queries could be the solution, i.e., a search that starts discovering the semantics intended for the input user keywords, and then only data relevant to that semantics are returned as answer. In this paper we present a system that performs semantic keyword interpretation on different data repositories. Our system (1) discovers the meaning of the input keywords by consulting a generic pool of ontologies and applying different disambiguation techniques; (2) once the meaning of each keyword has been established, the system combines them in a formal query that captures the semantics intended by the user, considering different formal query languages and possibilities that could arise, but avoiding inconsistent and semantically equivalent queries; and, finally, (3) after the user has validated the generated query that best fits her/his intended meaning, the system routes the query to the appropriate data repositories that will retrieve data according to the semantics of such a query. Experimental results show the semantic interpretation capabilities and the feasibility of our approach.
000167844 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttps://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
000167844 590__ $$a4.832$$b2016
000167844 591__ $$aCOMPUTER SCIENCE, INFORMATION SYSTEMS$$b7 / 146 = 0.048$$c2016$$dQ1$$eT1
000167844 592__ $$a1.78$$b2016
000167844 593__ $$aArtificial Intelligence$$c2016$$dQ1
000167844 593__ $$aComputer Science Applications$$c2016$$dQ1
000167844 593__ $$aTheoretical Computer Science$$c2016$$dQ1
000167844 593__ $$aInformation Systems and Management$$c2016$$dQ1
000167844 593__ $$aSoftware$$c2016$$dQ1
000167844 593__ $$aControl and Systems Engineering$$c2016$$dQ1
000167844 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000167844 700__ $$0(orcid)0000-0002-7462-0080$$aMena, E.$$uUniversidad de Zaragoza
000167844 7102_ $$15007$$2570$$aUniversidad de Zaragoza$$bDpto. Informát.Ingenie.Sistms.$$cÁrea Lenguajes y Sistemas Inf.
000167844 773__ $$g329 (2016), 412-433$$pInf. sci.$$tInformation Sciences$$x0020-0255
000167844 8564_ $$s414644$$uhttps://zaguan.unizar.es/record/167844/files/texto_completo.pdf$$yPostprint
000167844 8564_ $$s2877813$$uhttps://zaguan.unizar.es/record/167844/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000167844 909CO $$ooai:zaguan.unizar.es:167844$$particulos$$pdriver
000167844 951__ $$a2026-01-22-16:09:38
000167844 980__ $$aARTICLE