کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6856376 | 1437955 | 2018 | 36 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Personalized restaurant recommendation method combining group correlations and customer preferences
ترجمه فارسی عنوان
روش توصیه شخصی رستوران ترکیبی از همبستگی های گروهی و ترجیحات مشتری
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
The increasing practicality of the group identification approach has led to many studies of restaurant recommendations. The success of group identification depends on how to fully aggregate the customer preferences in a group. However, the aggregation approaches towards customer preferences still pose many challenges to current research. For example, aggregation approaches can cause the group as a whole to report high satisfaction, while the satisfaction reported by individuals is low. Therefore, this paper proposes a novel personalized restaurant recommendation approach that combines group correlations and customer preferences. Our model employs the unsupervised means and probabilistic linguistic term set (PLTS) to conduct the group correlations between customer group and restaurant group. The recommendation list is provided by looking for the most similar group that the target customer belongs to. To validate the model, a case study of TripAdvisor.com is implemented. Our results confirm that the proposed restaurant recommendation approach outperforms the other three benchmark models.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volumes 454â455, July 2018, Pages 128-143
Journal: Information Sciences - Volumes 454â455, July 2018, Pages 128-143
نویسندگان
Chenbin Zhang, Hongyu Zhang, Jianqiang Wang,