Survey of Confidentiality and trust in recommender systems

Message:
Article Type:
Research/Original Article (بدون رتبه معتبر)
Abstract:
Recommender systems has an important role in social networks. With the growth and development ofsocial networks, this issue is becoming more and more important. Recommending systems try to predict the user's interests and then suggest the closest items to the user's tastes. Recommender systems analyze the user’s behavior and suggest the most appropriate items. By collecting user information, the system categorizes and summarizes them, allowing users to access more relevant information in less time. Recommender system is an intelligent system that creates appropriate suggestions for each person by discovering and analyzing user information.In this paper, we will investigate recommending systems in three sections: types of recommendingsystems, information confidentiality and trust in recommender systems. We will refer to the relatedworks in each section, review the challenges of them, and present our results and evaluation on thesemethods
Language:
English
Published:
Journal of Artificial Intelligence in Electrical Engineering, Volume:8 Issue: 30, Summer 2019
Pages:
38 to 43
magiran.com/p2348959  
دانلود و مطالعه متن این مقاله با یکی از روشهای زیر امکان پذیر است:
اشتراک شخصی
با عضویت و پرداخت آنلاین حق اشتراک یک‌ساله به مبلغ 1,390,000ريال می‌توانید 70 عنوان مطلب دانلود کنید!
اشتراک سازمانی
به کتابخانه دانشگاه یا محل کار خود پیشنهاد کنید تا اشتراک سازمانی این پایگاه را برای دسترسی نامحدود همه کاربران به متن مطالب تهیه نمایند!
توجه!
  • حق عضویت دریافتی صرف حمایت از نشریات عضو و نگهداری، تکمیل و توسعه مگیران می‌شود.
  • پرداخت حق اشتراک و دانلود مقالات اجازه بازنشر آن در سایر رسانه‌های چاپی و دیجیتال را به کاربر نمی‌دهد.
In order to view content subscription is required

Personal subscription
Subscribe magiran.com for 70 € euros via PayPal and download 70 articles during a year.
Organization subscription
Please contact us to subscribe your university or library for unlimited access!