DESIGN OF A PROPERTY PRODUCT RECOMMENDATION SYSTEM USING ASSOCIATION RULE METHOD BASED ON USER INTERACTION PATTERNS
This work creates an association rule-based real estate product recommendation system. Personalizing property suggestions based on user behavior optimises property searches. Data-driven insights enhance dynamic property market user experience. Association rules alter property advice. Data-driven ins...
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| Format: | Article |
| Language: | English |
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Zibeline International
2024-07-01
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| Series: | Acta Informatica Malaysia |
| Subjects: | |
| Online Access: | https://actainformaticamalaysia.com/archives/AIM/2aim2024/2aim2024-69-78.pdf |
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| _version_ | 1832539960035508224 |
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| author | Susi Wagiyati Purtiningruma Yudi Irawan Chandrab Dian Gustinaa Nafisah Yuliania Fahrul Nurzamana Jhonny Z.Aa Agus Wismoa |
| author_facet | Susi Wagiyati Purtiningruma Yudi Irawan Chandrab Dian Gustinaa Nafisah Yuliania Fahrul Nurzamana Jhonny Z.Aa Agus Wismoa |
| author_sort | Susi Wagiyati Purtiningruma |
| collection | DOAJ |
| description | This work creates an association rule-based real estate product recommendation system. Personalizing property suggestions based on user behavior optimises property searches. Data-driven insights enhance dynamic property market user experience. Association rules alter property advice. Data-driven insights and adaptability improve property search by proposing homes depending on user engagement patterns. Strong algorithms establish location, budget, and property associations, and association rule technology and user interaction patterns increase property recommendations. Personalized property discovery uses accurate and adaptive suggestions from continuous learning. Results reveal that user interaction pattern-based association rule techniques improve property suggestion accuracy and personalization. The system’s tailored advice improves property market decisions, confirming its usefulness and adaptability. Insufficient user data might distort suggestions, especially for specific interests. Not enough user diversity can lower system accuracy. User data and privacy must be secured to optimize the recommendation system. Association rule and user engagement patterns can transform property recommendations. This innovative technique can improve property searches, provide personalized ideas, and help consumers make informed decisions in a competitive market. |
| format | Article |
| id | doaj-art-3e52a9428ed343f1aa479117aa527fea |
| institution | Kabale University |
| issn | 2521-0874 2521-0505 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | Zibeline International |
| record_format | Article |
| series | Acta Informatica Malaysia |
| spelling | doaj-art-3e52a9428ed343f1aa479117aa527fea2025-02-05T07:29:55ZengZibeline InternationalActa Informatica Malaysia2521-08742521-05052024-07-0182697810.26480/aim.02.2024.69.78DESIGN OF A PROPERTY PRODUCT RECOMMENDATION SYSTEM USING ASSOCIATION RULE METHOD BASED ON USER INTERACTION PATTERNSSusi Wagiyati Purtiningruma0Yudi Irawan Chandrab1Dian Gustinaa2Nafisah Yuliania3Fahrul Nurzamana4Jhonny Z.Aa5Agus Wismoa6Universitas Persada Indonesia YAI, Jakarta, IndonesiaSekolah Tinggi Manajemen Informatika dan Komputer Jakarta STI&K, Jakarta, Indonesia;Universitas Persada Indonesia YAI, Jakarta, IndonesiaUniversitas Persada Indonesia YAI, Jakarta, IndonesiaUniversitas Persada Indonesia YAI, Jakarta, IndonesiaUniversitas Persada Indonesia YAI, Jakarta, IndonesiaUniversitas Persada Indonesia YAI, Jakarta, IndonesiaThis work creates an association rule-based real estate product recommendation system. Personalizing property suggestions based on user behavior optimises property searches. Data-driven insights enhance dynamic property market user experience. Association rules alter property advice. Data-driven insights and adaptability improve property search by proposing homes depending on user engagement patterns. Strong algorithms establish location, budget, and property associations, and association rule technology and user interaction patterns increase property recommendations. Personalized property discovery uses accurate and adaptive suggestions from continuous learning. Results reveal that user interaction pattern-based association rule techniques improve property suggestion accuracy and personalization. The system’s tailored advice improves property market decisions, confirming its usefulness and adaptability. Insufficient user data might distort suggestions, especially for specific interests. Not enough user diversity can lower system accuracy. User data and privacy must be secured to optimize the recommendation system. Association rule and user engagement patterns can transform property recommendations. This innovative technique can improve property searches, provide personalized ideas, and help consumers make informed decisions in a competitive market.https://actainformaticamalaysia.com/archives/AIM/2aim2024/2aim2024-69-78.pdfproperty recommendation systemassociation rule methoduser interaction patternspersonalized suggestionsreal estate decision-making |
| spellingShingle | Susi Wagiyati Purtiningruma Yudi Irawan Chandrab Dian Gustinaa Nafisah Yuliania Fahrul Nurzamana Jhonny Z.Aa Agus Wismoa DESIGN OF A PROPERTY PRODUCT RECOMMENDATION SYSTEM USING ASSOCIATION RULE METHOD BASED ON USER INTERACTION PATTERNS Acta Informatica Malaysia property recommendation system association rule method user interaction patterns personalized suggestions real estate decision-making |
| title | DESIGN OF A PROPERTY PRODUCT RECOMMENDATION SYSTEM USING ASSOCIATION RULE METHOD BASED ON USER INTERACTION PATTERNS |
| title_full | DESIGN OF A PROPERTY PRODUCT RECOMMENDATION SYSTEM USING ASSOCIATION RULE METHOD BASED ON USER INTERACTION PATTERNS |
| title_fullStr | DESIGN OF A PROPERTY PRODUCT RECOMMENDATION SYSTEM USING ASSOCIATION RULE METHOD BASED ON USER INTERACTION PATTERNS |
| title_full_unstemmed | DESIGN OF A PROPERTY PRODUCT RECOMMENDATION SYSTEM USING ASSOCIATION RULE METHOD BASED ON USER INTERACTION PATTERNS |
| title_short | DESIGN OF A PROPERTY PRODUCT RECOMMENDATION SYSTEM USING ASSOCIATION RULE METHOD BASED ON USER INTERACTION PATTERNS |
| title_sort | design of a property product recommendation system using association rule method based on user interaction patterns |
| topic | property recommendation system association rule method user interaction patterns personalized suggestions real estate decision-making |
| url | https://actainformaticamalaysia.com/archives/AIM/2aim2024/2aim2024-69-78.pdf |
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