Text Pre-Processing For The Frequently Mentioned Criteria From Online Community Homebuyer Dataset

Due to the competitive Malaysian residential market with a large number of residential projects that offered almost similar features lead to difficulties of residential purchasing among homebuyers. These days, homebuyers are very selective, careful, and required more time in deciding due to the high...

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Veröffentlicht in:International journal of interactive mobile technologies 2021-03, Vol.15 (6), p.171
Hauptverfasser: Nursal, Ahmad Taufik, Omar, Mohd Faizal, Mohd Nawi, Mohd Nasrun
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container_issue 6
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container_title International journal of interactive mobile technologies
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creator Nursal, Ahmad Taufik
Omar, Mohd Faizal
Mohd Nawi, Mohd Nasrun
description Due to the competitive Malaysian residential market with a large number of residential projects that offered almost similar features lead to difficulties of residential purchasing among homebuyers. These days, homebuyers are very selective, careful, and required more time in deciding due to the high numbers of abundant, and problem residential projects in Malaysia. As a result, a high number of unsold residential projects were reported. Therefore, understanding homebuyer criteria in a residential purchase is crucially important towards successful Malasia residential projects in the long term. This paper identifies and prioritizing homebuyers criteria in mainland Penang, Malaysia from user-generated data in online property forums. 6000 data was extracted through RapidMiner software. Once data were processes, statistic analysis is used to determined and prioritize the homebuyer's criteria. The classification of criteria is made by the real estate experts.  The result of the study provides fresh insight into homebuyers' criteria. The findings should offer developers, government, potential homebuyers, and real estate agents a better understanding of homebuyers criteria in Penang, Malaysia. 
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title Text Pre-Processing For The Frequently Mentioned Criteria From Online Community Homebuyer Dataset
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