Application of data mining in designing a recommender system on social networks
محل انتشار: هفتمین کنفرانس ملی مهندسی برق و الکترونیک ایران
سال انتشار: 1394
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 570
فایل این مقاله در 8 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
این مقاله در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
ICEEE07_415
تاریخ نمایه سازی: 19 اردیبهشت 1395
چکیده مقاله:
The prevalence of social networks amongst people has become an inevitable issue. At the same time, social networks have widely been used for commercial purposes. As a result, in order to sell the products, social networks have been equipped with various recommender systems that provide the users with commercial offers that are appropriate for their behavior. The accuracy of the recommender systems in providing offers to the users and the number of offers accepted by the users are crucial issues. In the present study, a recommender system was designed that operates based on the users' behavior on Facebook and in two phases offers the users to buy their favorite products. In the first phase, the users' behavior is investigated and based on their interest they are offered to buy some products. In the second phase, the recommender system uses data mining techniques and provides the users with offers that are relevant to their previous purchase. The data of the study are factual and the results are valid. Moreover, the results indicate that the designed recommender system is highly accurate in providing offers to the users.
کلیدواژه ها:
نویسندگان
Saman Forouzandeh
Department of Computer Engineering Science and Research Branch, Islamic Azad University, Tehran, Iran
Heirsh Soltanpanah
PhD, Department of Industrial Sanandaj Branch, Islamic Azad University, Sanandaj, Iran.
Amir Sheikhahmadi
Department of Computer Engineering Sanandaj Branch, Islamic Azad University, Sanandaj, Iran.
Soran Forouzandeh
Department of Computer Engineering Science and Research Branch, Islamic Azad University, Tehran, Iran.
مراجع و منابع این مقاله:
لیست زیر مراجع و منابع استفاده شده در این مقاله را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود مقاله لینک شده اند :