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dc.contributor.authorGarcía Moya, Lisette
dc.contributor.authorKudama, Shahad
dc.contributor.authorAramburu Cabo, María José
dc.contributor.authorBerlanga Llavori, Rafael
dc.date.accessioned2015-02-11T10:33:30Z
dc.date.available2015-02-11T10:33:30Z
dc.date.issued2013-07
dc.identifier.issn1387-3326
dc.identifier.urihttp://hdl.handle.net/10234/114279
dc.description.abstractWeb opinion feeds have become one of the most popular information sources users consult before buying products or contracting services. Negative opinions about a product can have a high impact in its sales figures. As a consequence, companies are more and more concerned about how to integrate opinion data in their business intelligence models so that they can predict sales figures or define new strategic goals. After analysing the requirements of this new application, this paper proposes a multidimensional data model to integrate sentiment data extracted from opinion posts in a traditional corporate data warehouse. Then, a new sentiment data extraction method that applies semantic annotation as a means to facilitate the integration of both types of data is presented. In this method, Wikipedia is used as the main knowledge resource, together with some well-known lexicons of opinion words and other corporate data and metadata stores describing the company products like, for example, technical specifications and user manuals. The resulting information system allows users to perform new analysis tasks by using the traditional OLAP-based data warehouse operators. We have developed a case study over a set of real opinions about digital devices which are offered by a wholesale dealer. Over this case study, the quality of the extracted sentiment data is evaluated, and some query examples that illustrate the potential uses of the integrated model are provided.ca_CA
dc.format.extent18 p.ca_CA
dc.format.mimetypeapplication/pdfca_CA
dc.language.isoengca_CA
dc.publisherSpringer USca_CA
dc.relation.isPartOfInformation Systems Frontiers, vol. 15, n. 3, p. 331-349ca_CA
dc.rightsCopyright Springer Science+Business Media New York 2013ca_CA
dc.subjectSentiment analysisca_CA
dc.subjectData warehousesca_CA
dc.subjectOLAPca_CA
dc.subjectText processingca_CA
dc.titleStoring and analysing voice of the market data in the corporate data warehouseca_CA
dc.typeinfo:eu-repo/semantics/articleca_CA
dc.identifier.doihttp://dx.doi.org/10.1007/s10796-012-9400-y
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccessca_CA
dc.relation.publisherVersionhttp://link.springer.com/article/10.1007/s10796-012-9400-yca_CA


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