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dc.contributorDepartment of Computingen_US
dc.creatorChan, Elvis-
dc.identifier.urihttps://theses.lib.polyu.edu.hk/handle/200/5417-
dc.languageEnglishen_US
dc.publisherHong Kong Polytechnic University-
dc.rightsAll rights reserveden_US
dc.titleMavis : an intelligent way to perform mass property valuation through the application of data mining techniquesen_US
dcterms.abstractThe purpose of this research is to investigate the merits of applying data mining techniques to the problem of residential property valuation. We present MAVIS, a novel framework for developing a model to estimate the value of residential property for massive development transactions. The system elicits the hidden patterns in the training cases, which could estimate the value of the holdout samples. The adoption of the decision tree technique and fuzzy data mining technique makes MAVIS resilient to noises taken place in real life database, such as missing values and inaccuracy in physical measurements. Without providing user-supplied thresholds to the algorithms, our experimental results showed that MAVIS has been successfully adopted in price estimation and assisting human valuers to make their final decision by eliciting the implicit knowledge and re-applying the non-trivial knowledge to the valuation industry.en_US
dcterms.extent129 leaves : ill. ; 30 cm.en_US
dcterms.isPartOfPolyU Electronic Thesesen_US
dcterms.issued2002en_US
dcterms.educationalLevelAll Masteren_US
dcterms.educationalLevelM.Sc.en_US
dcterms.LCSHHong Kong Polytechnic University -- Dissertationsen_US
dcterms.LCSHReal property -- Valuationen_US
dcterms.LCSHData miningen_US
dcterms.LCSHFuzzy logicen_US
dcterms.accessRightsrestricted accessen_US

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