با سلام خدمت کاربران در صورتی که با خطای سیستم پرداخت بانکی مواجه شدید از طریق کارت به کارت (6037997535328901 بانک ملی ناصر خنجری ) مقاله خود را دریافت کنید (تا مشکل رفع گردد).
دسته بندی:
سیستم های توصیه گر - recommender systems
سال انتشار:
2019
عنوان انگلیسی مقاله:
Recommender system based on pairwise association rules
ترجمه فارسی عنوان مقاله:
سیستم تصیه گر مبتنی بر قوانین ارتباط زوج
منبع:
Sciencedirect - Elsevier - Expert Systems With Applications, 115 (2019) 535-542: doi:10:1016/j:eswa:2018:07:077
نویسنده:
Timur Osadchiy a , ∗, Ivan Poliakov a , Patrick Olivier a , Maisie Rowland b , Emma Foster b
چکیده انگلیسی:
Recommender systems based on methods such as collaborative and content-based filtering rely on ex- tensive user profiles and item descriptors as well as on an extensive history of user preferences. Such methods face a number of challenges; including the cold-start problem in systems characterized by ir- regular usage, privacy concerns, and contexts where the range of indicators representing user interests is limited. We describe a recommender algorithm that builds a model of collective preferences indepen- dently of personal user interests and does not require a complex system of ratings. The performance of the algorithm is analyzed on a large transactional data set generated by a real-world dietary intake recall system.
Keywords: Association rules | Cold-start problem | Data mining | Ontologies | Recommender systems
قیمت: رایگان
توضیحات اضافی:
تعداد نظرات : 0