Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Computing | en_US |
| dc.creator | Chan, Elvis | - |
| dc.identifier.uri | https://theses.lib.polyu.edu.hk/handle/200/5417 | - |
| dc.language | English | en_US |
| dc.publisher | Hong Kong Polytechnic University | - |
| dc.rights | All rights reserved | en_US |
| dc.title | Mavis : an intelligent way to perform mass property valuation through the application of data mining techniques | en_US |
| dcterms.abstract | The 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.extent | 129 leaves : ill. ; 30 cm. | en_US |
| dcterms.isPartOf | PolyU Electronic Theses | en_US |
| dcterms.issued | 2002 | en_US |
| dcterms.educationalLevel | All Master | en_US |
| dcterms.educationalLevel | M.Sc. | en_US |
| dcterms.LCSH | Hong Kong Polytechnic University -- Dissertations | en_US |
| dcterms.LCSH | Real property -- Valuation | en_US |
| dcterms.LCSH | Data mining | en_US |
| dcterms.LCSH | Fuzzy logic | en_US |
| dcterms.accessRights | restricted access | en_US |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b17523473.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 7.54 MB | Adobe PDF | View/Open |
Copyright Undertaking
As a bona fide Library user, I declare that:
- I will abide by the rules and legal ordinances governing copyright regarding the use of the Database.
- I will use the Database for the purpose of my research or private study only and not for circulation or further reproduction or any other purpose.
- I agree to indemnify and hold the University harmless from and against any loss, damage, cost, liability or expenses arising from copyright infringement or unauthorized usage.
By downloading any item(s) listed above, you acknowledge that you have read and understood the copyright undertaking as stated above, and agree to be bound by all of its terms.
Please use this identifier to cite or link to this item:
https://theses.lib.polyu.edu.hk/handle/200/5417