Precomputed Clustering for Movie Recommendation System in Real Time
A recommendation system delivers customized data (articles, news, images, music, movies, etc.) to its users. As the interest of recommendation systems grows, we started working on the movie recommendation systems. Most research efforts in the fields of movie recommendation system are focusing on dis...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Journal of Applied Mathematics |
| Online Access: | http://dx.doi.org/10.1155/2014/742341 |
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| _version_ | 1832556124051603456 |
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| author | Bo Li Yibin Liao Zheng Qin |
| author_facet | Bo Li Yibin Liao Zheng Qin |
| author_sort | Bo Li |
| collection | DOAJ |
| description | A recommendation system delivers customized data (articles, news, images, music, movies, etc.) to its users. As the interest
of recommendation systems grows, we started working on the movie recommendation systems. Most research efforts in the fields of movie recommendation system are focusing on discovering the most relevant features from users, or seeking out users who share same tastes as that of the given user as well as recommending the movies according to the liking of these sought users or seeking out users who share a connection with other people (friends, classmates, colleagues, etc.) and make recommendations based on those related people’s tastes. However, little research has focused on recommending movies based on the movie’s features. In this paper, we present a novel idea that applies machine learning techniques to construct a cluster for the movie by implementing a distance matrix based on the movie features and then make movie recommendation in real time. We implement some different clustering methods and evaluate their performance in a real movie forum website owned by one of our authors. This idea can also be used in other types of recommendation systems such as music, news, and articles. |
| format | Article |
| id | doaj-art-c3a7b3bfce604fa3a5e88af4580cf3f1 |
| institution | Kabale University |
| issn | 1110-757X 1687-0042 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Applied Mathematics |
| spelling | doaj-art-c3a7b3bfce604fa3a5e88af4580cf3f12025-02-03T05:46:20ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/742341742341Precomputed Clustering for Movie Recommendation System in Real TimeBo Li0Yibin Liao1Zheng Qin2Department of Computer Science, University of Georgia, Athens, GA 30602, USADepartment of Computer Science, University of Georgia, Athens, GA 30602, USASchool of Software, Tsinghua University, Beijing 100084, ChinaA recommendation system delivers customized data (articles, news, images, music, movies, etc.) to its users. As the interest of recommendation systems grows, we started working on the movie recommendation systems. Most research efforts in the fields of movie recommendation system are focusing on discovering the most relevant features from users, or seeking out users who share same tastes as that of the given user as well as recommending the movies according to the liking of these sought users or seeking out users who share a connection with other people (friends, classmates, colleagues, etc.) and make recommendations based on those related people’s tastes. However, little research has focused on recommending movies based on the movie’s features. In this paper, we present a novel idea that applies machine learning techniques to construct a cluster for the movie by implementing a distance matrix based on the movie features and then make movie recommendation in real time. We implement some different clustering methods and evaluate their performance in a real movie forum website owned by one of our authors. This idea can also be used in other types of recommendation systems such as music, news, and articles.http://dx.doi.org/10.1155/2014/742341 |
| spellingShingle | Bo Li Yibin Liao Zheng Qin Precomputed Clustering for Movie Recommendation System in Real Time Journal of Applied Mathematics |
| title | Precomputed Clustering for Movie Recommendation System in Real Time |
| title_full | Precomputed Clustering for Movie Recommendation System in Real Time |
| title_fullStr | Precomputed Clustering for Movie Recommendation System in Real Time |
| title_full_unstemmed | Precomputed Clustering for Movie Recommendation System in Real Time |
| title_short | Precomputed Clustering for Movie Recommendation System in Real Time |
| title_sort | precomputed clustering for movie recommendation system in real time |
| url | http://dx.doi.org/10.1155/2014/742341 |
| work_keys_str_mv | AT boli precomputedclusteringformovierecommendationsysteminrealtime AT yibinliao precomputedclusteringformovierecommendationsysteminrealtime AT zhengqin precomputedclusteringformovierecommendationsysteminrealtime |