کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4943043 | 1437619 | 2017 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
FRAIPA: A fast recommendation approach with improved prediction accuracy
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Recommender systems have emerged as a key tool to overcome the negative impact of information overload problem, as well as, help the users seek the relevant information based on their past preferences. Collaborative filtering represents a widely used approach to build recommendation systems. In essence, many methods have been developed to provide high quality results, neverthless, they may incur prohibitive computational costs. In this paper, a novel method called FRAIPA is proposed, which is designed to tackle the sparsity, dynamic data problems, moreover, it improves the prediction accuracy and computation time. Experimental results on two real-world data sets reveal the effectiveness of the proposed method over existing methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 87, 30 November 2017, Pages 90-97
Journal: Expert Systems with Applications - Volume 87, 30 November 2017, Pages 90-97
نویسندگان
Badr Ait Hammou, Ayoub Ait Lahcen,