کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
384537 | 660848 | 2009 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
An iterative semi-explicit rating method for building collaborative recommender systems
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Collaborative filtering plays the key role in recent recommender systems. It uses a user-item preference matrix rated either explicitly (i.e., explicit rating) or implicitly (i.e., implicit feedback). Despite the explicit rating captures the preferences better, it often results in a severely sparse matrix. The paper presents a novel iterative semi-explicit rating method that extrapolates unrated elements in a semi-supervised manner. Extrapolation is simply an aggregation of neighbor ratings, and iterative extrapolations result in a dense preference matrix. Preliminary simulation results show that the recommendation using the semi-explicit rating data outperforms that of using the pure explicit data only.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 36, Issue 3, Part 2, April 2009, Pages 6181–6186
Journal: Expert Systems with Applications - Volume 36, Issue 3, Part 2, April 2009, Pages 6181–6186
نویسندگان
Buhwan Jeong, Jaewook Lee, Hyunbo Cho,