Addressing the New User Cold-Start Problem in Recommender Systems Using Ordered Weighted Averaging Operator
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 propose...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Iran Telecom Research Center
2010-12-01
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| Series: | International Journal of Information and Communication Technology Research |
| Subjects: | |
| Online Access: | http://ijict.itrc.ac.ir/article-1-251-en.html |
| _version_ | 1811169281461714944 |
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| author | Javad Basiri Azadeh Shakery Behzad Moshiri Morteza Zihayat |
| author_facet | Javad Basiri Azadeh Shakery Behzad Moshiri Morteza Zihayat |
| author_sort | Javad Basiri |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-10T16:40:51Z |
| format | Article |
| id | doaj.art-2f131638ade842aaab55876c6cb736ab |
| institution | Directory Open Access Journal |
| issn | 2251-6107 2783-4425 |
| language | English |
| last_indexed | 2024-04-10T16:40:51Z |
| publishDate | 2010-12-01 |
| publisher | Iran Telecom Research Center |
| record_format | Article |
| series | International Journal of Information and Communication Technology Research |
| spelling | doaj.art-2f131638ade842aaab55876c6cb736ab2023-02-08T07:30:01ZengIran Telecom Research CenterInternational Journal of Information and Communication Technology Research2251-61072783-44252010-12-01247987Addressing the New User Cold-Start Problem in Recommender Systems Using Ordered Weighted Averaging OperatorJavad Basiri0Azadeh Shakery1Behzad Moshiri2Morteza Zihayat3 School of Electrical and Computer Engineering College of Engineering University of Tehran, Tehran, Iran School of Electrical and Computer Engineering University of Tehran Tehran, Iran Control & Intelligent Processing Center of Excellence, School of ECE University of Tehran Tehran, Iran School of Electrical and Computer Engineering University of Tehran Tehran, Iran 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.http://ijict.itrc.ac.ir/article-1-251-en.htmlowahybrid approachdemographic- informationcontent-based filteringcollaborative filteringrecommender system |
| spellingShingle | Javad Basiri Azadeh Shakery Behzad Moshiri Morteza Zihayat Addressing the New User Cold-Start Problem in Recommender Systems Using Ordered Weighted Averaging Operator International Journal of Information and Communication Technology Research owa hybrid approach demographic- information content-based filtering collaborative filtering recommender system |
| title | Addressing the New User Cold-Start Problem in Recommender Systems Using Ordered Weighted Averaging Operator |
| title_full | Addressing the New User Cold-Start Problem in Recommender Systems Using Ordered Weighted Averaging Operator |
| title_fullStr | Addressing the New User Cold-Start Problem in Recommender Systems Using Ordered Weighted Averaging Operator |
| title_full_unstemmed | Addressing the New User Cold-Start Problem in Recommender Systems Using Ordered Weighted Averaging Operator |
| title_short | Addressing the New User Cold-Start Problem in Recommender Systems Using Ordered Weighted Averaging Operator |
| title_sort | addressing the new user cold start problem in recommender systems using ordered weighted averaging operator |
| topic | owa hybrid approach demographic- information content-based filtering collaborative filtering recommender system |
| url | http://ijict.itrc.ac.ir/article-1-251-en.html |
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