Fuzzy Logic Classification in Review Spam Detection

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dc.contributor.advisorRokne, Jon G.
dc.contributor.authorRachdi, Btissam
dc.contributor.committeememberAlhajj, Reda S.
dc.contributor.committeememberMoshirpour, Mohammad
dc.date2019-11
dc.date.accessioned2019-05-30T18:56:58Z
dc.date.available2019-05-30T18:56:58Z
dc.date.issued2019-05-21
dc.description.abstractWith the recent popularity of e-commerce, customers publish reviews about the products or services they purchased or utilized and these reviews in turn serve as the means for the potential customers to make a better choice based on the experiences of others. These pieces of opinion information are not only important for individual users but also benefit the business organizations, as they can monitor the customers’ opinions, and accordingly adjust their business strategies. However, many of the reviewing systems exploit this motivation for some people to enter their fake reviews to promote some products or defame some others. Hence, in recent years, review analysis has gained a lot of importance and by using opinion-mining detection; I could locate and eliminate potential spam reviews. In this thesis, I have introduced fuzzy logic in the review spam detection and combined two others data mining techniques, periodicity of frequent pattern and the outlier detection to study the behavior of the reviewer towards the reviewed product and classify the users using the fuzzy logic classification model. Thus, the proposed analysis have been proposed and examined over a sample of dataset.en_US
dc.identifier.citationRachdi, B. (2019). Fuzzy Logic Classification in Review Spam Detection (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/36607
dc.identifier.urihttp://hdl.handle.net/1880/110448
dc.language.isoengen_US
dc.publisher.facultyScienceen_US
dc.publisher.institutionUniversity of Calgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.en_US
dc.subjectreview spam detection, frequent pattern mining, outlier detectionen_US
dc.subject.classificationComputer Scienceen_US
dc.titleFuzzy Logic Classification in Review Spam Detectionen_US
dc.typemaster thesisen_US
thesis.degree.disciplineComputer Scienceen_US
thesis.degree.grantorUniversity of Calgaryen_US
thesis.degree.nameMaster of Science (MSc)en_US
ucalgary.item.requestcopytrue
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