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dc.contributor.authorTorre-Bastida, A.I.
dc.contributor.authorVillar-Rodriguez, Esther
dc.contributor.authorGil-Lopez, S.
dc.contributor.authorDel Ser, Javier
dc.date.accessioned2016-06-13T11:07:08Z
dc.date.available2016-06-13T11:07:08Z
dc.date.issued2015
dc.identifier.citationJOURNAL OF UNIVERSAL COMPUTER SCIENCE, Vol.21, Issue 6, (2015), pp. 757-776en
dc.identifier.issn0948-695Xen
dc.identifier.urihttp://hdl.handle.net/11556/245
dc.description.abstractThe amount of open information available on-line from heterogeneous sources and domains is growing at an extremely fast pace, and constitutes an important knowledge base for the consideration of industries and companies. In this context, two relevant data providers can be highlighted: the "Linked Open Data" (LOD) and "Social Media" (SM) paradigms. The fusion of these data sources - structured the former, and raw data the latter -, along with the information contained in structured corporate databases within the organizations themselves, may unveil significant business opportunities and competitive advantage to those who are able to understand and leverage their value. In this paper, we present two complementary use cases, illustrating the potential of using the open data in the business domain. The first represents the creation of an existing and potential customer knowledge base, exploiting social and linked open data based on which any given organization might infer valuable information as a support for decision making. The second focuses on the classification of organizations and enterprises aiming at detecting potential competitors and/or allies via the analysis of the conceptual similarity between their participated projects. To this end, a solution based on the synergy of Big Data and semantic technologies will be designed and developed. The first will be used to implement the tasks of collection, data fusion and classification supported by natural language processing (NLP) techniques, whereas the latter will deal with semantic aggregation, persistence, reasoning and information retrieval, as well as with the triggering of alerts based on the semantized information.en
dc.language.isoengen
dc.publisherGRAZ UNIV TECHNOLGOY, INST INFORMATION SYSTEMS COMPUTER MEDIA-IICM, INFFELDGASSE 16C, GRAZ, A-8010, AUSTRIAen
dc.titleDesign and Implementation of an Extended Corporate CRM Database System with Big Data Analytical Functionalitiesen
dc.typejournal articleen
dc.isiYesen
dc.rights.accessRightsembargoed accessen
dc.subject.keywordsBig Dataen
dc.subject.keywordsSocial Mediaen
dc.subject.keywordsLinked Open Dataen
dc.subject.keywordsbusiness intelligenceen
dc.subject.keywordsinformation fusionen
dc.subject.keywordsontology managementen
dc.subject.keywordsinformation modellingen


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