کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4945817 | 1438953 | 2017 | 39 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
What and who with: A social approach to double-sided recommendation
ترجمه فارسی عنوان
چه کسی و چه کسی: رویکرد اجتماعی به توصیه دو طرفه
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کلمات کلیدی
سیستم توصیهگر، توصیه گروهی، شبکه اجتماعی، مدل کاربر توصیه محتوا، توصیه های دو طرفه،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
چکیده انگلیسی
Our data show that users consider double-sided recommendations more useful than traditional recommendations which provide equivalent information. It was observed that our “social” DSR algorithm performs better in the event recommendation domain than a content-based one which has already been recognised as providing a good performance, in terms of precision, recall, accuracy and F1. This result is strengthened by our demonstrating that the good performance DSRs provide also depends on their peculiar structure and not only on the fact that they include “social” information. The item-recommendation part also performed better than a user-based collaborative filtering algorithm. Lastly, we found that users' scores for recommended item-group packages can be better predicted by considering only the system scores for the recommended groups, at least in the domain of social and cultural events.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Human-Computer Studies - Volume 101, May 2017, Pages 62-75
Journal: International Journal of Human-Computer Studies - Volume 101, May 2017, Pages 62-75
نویسندگان
Ilaria Lombardi, Fabiana Vernero,