Real estate app development and recommendation (II)
The growth of the e-commerce market has revolutionised the way real estate is bought and sold, resulting in an increased need for effective social recommendation algorithms that can assist buyers in selecting the best properties based on their needs and preferences. This study reviewed existing comm...
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2023
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sg-ntu-dr.10356-1660712023-04-21T15:38:18Z Real estate app development and recommendation (II) Jiang, Jonathan Zhang Jie School of Computer Science and Engineering ZhangJ@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence The growth of the e-commerce market has revolutionised the way real estate is bought and sold, resulting in an increased need for effective social recommendation algorithms that can assist buyers in selecting the best properties based on their needs and preferences. This study reviewed existing commercial solutions in real estate recommendation, analysing their methodological approaches, challenges, and evaluation procedures. After identifying gaps in current models, we developed a social recommendation app that utilises a multi-modal algorithm to circumvent these challenges. The performance evaluation of the proposed algorithm, using public and proprietary datasets, demonstrated that it performs well as an unsupervised machine learning algorithm, comparable to existing algorithms in speed and explainability of results. This research contributes to the development of effective real estate recommendation algorithms that can enhance the user experience in property acquisition. Bachelor of Engineering (Computer Science) 2023-04-21T00:36:47Z 2023-04-21T00:36:47Z 2023 Final Year Project (FYP) Jiang, J. (2023). Real estate app development and recommendation (II). Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166071 https://hdl.handle.net/10356/166071 en application/pdf Nanyang Technological University |
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Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Jiang, Jonathan Real estate app development and recommendation (II) |
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The growth of the e-commerce market has revolutionised the way real estate is bought and sold, resulting in an increased need for effective social recommendation algorithms that can assist buyers in selecting the best properties based on their needs and preferences. This study reviewed existing commercial solutions in real estate recommendation, analysing their methodological approaches, challenges, and evaluation procedures. After identifying gaps in current models, we developed a social recommendation app that utilises a multi-modal algorithm to circumvent these challenges. The performance evaluation of the proposed algorithm, using public and proprietary datasets, demonstrated that it performs well as an unsupervised machine learning algorithm, comparable to existing algorithms in speed and explainability of results. This research contributes to the development of effective real estate recommendation algorithms that can enhance the user experience in property acquisition. |
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Zhang Jie |
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Zhang Jie Jiang, Jonathan |
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Final Year Project |
author |
Jiang, Jonathan |
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Jiang, Jonathan |
title |
Real estate app development and recommendation (II) |
title_short |
Real estate app development and recommendation (II) |
title_full |
Real estate app development and recommendation (II) |
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Real estate app development and recommendation (II) |
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Real estate app development and recommendation (II) |
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real estate app development and recommendation (ii) |
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Nanyang Technological University |
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2023 |
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https://hdl.handle.net/10356/166071 |
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1764208116132478976 |