کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6874328 | 1441158 | 2018 | 33 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Exploring New Vista of intelligent collaborative filtering: A restaurant recommendation paradigm
ترجمه فارسی عنوان
بررسی ویستا جدید از فیلتر شفاف هوشمند: پارادایم توصیه رستوران
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کلمات کلیدی
فیلتراسیون مشترک مبتنی بر مشتری تغییر یافته است، الگوریتم سنجاقک، طبقه بندی مشتری مبتنی بر شخصیت، انعطاف پذیری،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
چکیده انگلیسی
Due to a busy schedule, people highly dependent on various kinds of online recommendations to utilize their precious time. The collaborative filtering is wide as the recommendation tool in the majority of the commercial recommenders. However, the outcome of collaborative filtering is often jeopardized by the sparsity, cold start, and grey sheep problems. To solve these issues in a more efficient way, a novel collaborative filtering algorithm entitled as Altered Client-based Collaborative Filtering (ACCF) for group recommendation is proposed. ACCF employs Dragonfly Algorithm to deal with the sparsity and neighbor selection. Restaurant recommendation system is utilized as a test bed for the validation of ACCF. With the end goal of performance assessment, a comparative study has been incorporated that depicts the proposed algorithm successfully minimizes the sparsity problem. The experimental outcome rendering ACCF provides 37%, 59%, 53% more Coverage, Precision and F-Measure than the user-based collaborative filtering even applicable for a small sample of data.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Computational Science - Volume 27, July 2018, Pages 168-182
Journal: Journal of Computational Science - Volume 27, July 2018, Pages 168-182
نویسندگان
Arup Roy, Soumya Banerjee, Manash Sarkar, Ashraf Darwish, Mohamed Elhoseny, Aboul Ella Hassanien,