کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
395454 665981 2008 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A new similarity measure for collaborative filtering to alleviate the new user cold-starting problem
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
A new similarity measure for collaborative filtering to alleviate the new user cold-starting problem
چکیده انگلیسی

Collaborative filtering is one of the most successful and widely used methods of automated product recommendation in online stores. The most critical component of the method is the mechanism of finding similarities among users using product ratings data so that products can be recommended based on the similarities. The calculation of similarities has relied on traditional distance and vector similarity measures such as Pearson’s correlation and cosine which, however, have been seldom questioned in terms of their effectiveness in the recommendation problem domain. This paper presents a new heuristic similarity measure that focuses on improving recommendation performance under cold-start conditions where only a small number of ratings are available for similarity calculation for each user. Experiments using three different datasets show the superiority of the measure in new user cold-start conditions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Information Sciences - Volume 178, Issue 1, 2 January 2008, Pages 37–51
نویسندگان
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