Collaborative Filtering Recommender System: Overview and Challenges
This paper is to present an overview of Collaborative Filtering (CF) recommender system and show the major CF challenges. In general, the recommendation systems are the best way to help users to overcome the information overload issue. The CF approach is one of the most widely used and most successf...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | en |
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Publishing Technology
2017
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| Online Access: | http://umpir.ump.edu.my/id/eprint/20906/1/Collaborative%20Filtering%20Recommender%20System%20Overview%20and%20Challenges1.pdf http://umpir.ump.edu.my/id/eprint/20906/ https://doi.org/10.1166/asl.2017.10020 |
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| _version_ | 1831525471898042368 |
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| author | Al-Bashiri, Hael Abdulgabber, Mansoor Abdullateef Awanis, Romli Hujainah, Fadhl |
| author_facet | Al-Bashiri, Hael Abdulgabber, Mansoor Abdullateef Awanis, Romli Hujainah, Fadhl |
| author_sort | Al-Bashiri, Hael |
| building | UMPSA Library |
| collection | Institutional Repository |
| content_provider | Universiti Malaysia Pahang Al-Sultan Abdullah |
| content_source | UMPSA Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | This paper is to present an overview of Collaborative Filtering (CF) recommender system and show the major CF challenges. In general, the recommendation systems are the best way to help users to overcome the information overload issue. The CF approach is one of the most widely used and most successful methods in the recommendation system, such as e-commerce. This paper introduced a brief description about recommender’s approaches which are: content-Based, collaborative filtering and hybrid approach. Next, defined the main challenges which have clearly impact on the performance and accuracy of CF recommender system. The major finding of this paper is the CF main problems: Data sparsity, Cold-star, and Scalability. By presenting of these challenges the quality of recommendations can be improved by proposing new methods. The paper ends with conclusion summarizes the limitations of the existing methods and recommendations. |
| format | Article |
| id | my.ump.umpir.20906 |
| institution | Universiti Malaysia Pahang |
| language | en |
| publishDate | 2017 |
| publisher | Publishing Technology |
| record_format | eprints |
| spelling | my.ump.umpir.209062019-10-18T02:32:36Z http://umpir.ump.edu.my/id/eprint/20906/ Collaborative Filtering Recommender System: Overview and Challenges Al-Bashiri, Hael Abdulgabber, Mansoor Abdullateef Awanis, Romli Hujainah, Fadhl QA75 Electronic computers. Computer science This paper is to present an overview of Collaborative Filtering (CF) recommender system and show the major CF challenges. In general, the recommendation systems are the best way to help users to overcome the information overload issue. The CF approach is one of the most widely used and most successful methods in the recommendation system, such as e-commerce. This paper introduced a brief description about recommender’s approaches which are: content-Based, collaborative filtering and hybrid approach. Next, defined the main challenges which have clearly impact on the performance and accuracy of CF recommender system. The major finding of this paper is the CF main problems: Data sparsity, Cold-star, and Scalability. By presenting of these challenges the quality of recommendations can be improved by proposing new methods. The paper ends with conclusion summarizes the limitations of the existing methods and recommendations. Publishing Technology 2017 Article PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/20906/1/Collaborative%20Filtering%20Recommender%20System%20Overview%20and%20Challenges1.pdf Al-Bashiri, Hael and Abdulgabber, Mansoor Abdullateef and Awanis, Romli and Hujainah, Fadhl (2017) Collaborative Filtering Recommender System: Overview and Challenges. Advanced Science Letters, 23 (9). pp. 9045-9049. ISSN 1936-6612. (Published) https://doi.org/10.1166/asl.2017.10020 DOI: 10.1166/asl.2017.10020 |
| spellingShingle | QA75 Electronic computers. Computer science Al-Bashiri, Hael Abdulgabber, Mansoor Abdullateef Awanis, Romli Hujainah, Fadhl Collaborative Filtering Recommender System: Overview and Challenges |
| title | Collaborative Filtering Recommender System: Overview and Challenges |
| title_full | Collaborative Filtering Recommender System: Overview and Challenges |
| title_fullStr | Collaborative Filtering Recommender System: Overview and Challenges |
| title_full_unstemmed | Collaborative Filtering Recommender System: Overview and Challenges |
| title_short | Collaborative Filtering Recommender System: Overview and Challenges |
| title_sort | collaborative filtering recommender system: overview and challenges |
| topic | QA75 Electronic computers. Computer science |
| url | http://umpir.ump.edu.my/id/eprint/20906/1/Collaborative%20Filtering%20Recommender%20System%20Overview%20and%20Challenges1.pdf http://umpir.ump.edu.my/id/eprint/20906/ https://doi.org/10.1166/asl.2017.10020 |
| url_provider | http://umpir.ump.edu.my/ |