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International Journal of Information and Communication Technology Research (IJICT، جلد ۲، شماره ۴، صفحات ۷۹-۸۷
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| عنوان فارسی |
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| چکیده فارسی مقاله |
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| کلیدواژه‌های فارسی مقاله |
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| عنوان انگلیسی |
Addressing the New User Cold-Start Problem in Recommender Systems Using Ordered Weighted Averaging Operator |
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| چکیده انگلیسی مقاله |
Recommender systems have become significant tools in electronic commerce, proposing effectively those items that best meet the preferences of users. A variety of techniques have been proposed for the recommender systems such as, collaborative filtering and content-based filtering. This study proposes a new hybrid recommender system that focuses on improving the performance under the "new user cold-start" condition where existence of users with no ratings or with only a small number of ratings is probable. In this method, the optimistic exponential type of ordered weighted averaging (OWA) operator is applied to fuse the output of five recommender system strategies. Experiments using MovieLens dataset show the superiority of the proposed hybrid approach in the cold-start conditions. |
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| کلیدواژه‌های انگلیسی مقاله |
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| نویسندگان مقاله |
| Javad Basiri
School of Electrical and Computer Engineering College of Engineering University of Tehran, Tehran, Iran
| Azadeh Shakery
School of Electrical and Computer Engineering University of Tehran Tehran, Iran
| Behzad Moshiri
Control & Intelligent Processing Center of Excellence, School of ECE University of Tehran Tehran, Iran
| Morteza Zihayat
School of Electrical and Computer Engineering University of Tehran Tehran, Iran
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| نشانی اینترنتی |
http://ijict.itrc.ac.ir/browse.php?a_code=A-10-27-221&slc_lang=en&sid=1 |
| فایل مقاله |
اشکال در دسترسی به فایل - ./files/site1/rds_journals/417/article-417-1212509.pdf |
| کد مقاله (doi) |
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| زبان مقاله منتشر شده |
en |
| موضوعات مقاله منتشر شده |
فناوری اطلاعات |
| نوع مقاله منتشر شده |
پژوهشی |
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