تقرير
An Adaptive Framework of Geographical Group-Specific Network on O2O Recommendation
| العنوان: | An Adaptive Framework of Geographical Group-Specific Network on O2O Recommendation |
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| المؤلفون: | Ji, Luo, Mao, Jiayu, Shi, Hailong, Li, Qian, Chu, Yunfei, Yang, Hongxia |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Information Retrieval, Computer Science - Machine Learning |
| الوصف: | Online to offline recommendation strongly correlates with the user and service's spatiotemporal information, therefore calling for a higher degree of model personalization. The traditional methodology is based on a uniform model structure trained by collected centralized data, which is unlikely to capture all user patterns over different geographical areas or time periods. To tackle this challenge, we propose a geographical group-specific modeling method called GeoGrouse, which simultaneously studies the common knowledge as well as group-specific knowledge of user preferences. An automatic grouping paradigm is employed and verified based on users' geographical grouping indicators. Offline and online experiments are conducted to verify the effectiveness of our approach, and substantial business improvement is achieved. Comment: 7 pages, 4 figures, Accepted by ECIR 2024 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2312.17072 |
| رقم الأكسشن: | edsarx.2312.17072 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |