An introduction to factorization technique for building recommendation systems
Recommender System (RS) is successfully applied in predicting user preferences. For instance, RS has been used in many areas such as in e-commerce (for online shopping), in entertainments (music/movie/video clip... recommendation), and in education (learning resource recommendation). In Vietnam,...
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Trường Đại học Đà Lạt
2014
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| Truy cập trực tuyến: | https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/37525 |
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oai:scholar.dlu.edu.vn:DLU123456789-375252023-10-27T14:42:17Z An introduction to factorization technique for building recommendation systems Nguyen, Thai Nghe Recommender Systems Rating prediction Matrix factorization Recommender System (RS) is successfully applied in predicting user preferences. For instance, RS has been used in many areas such as in e-commerce (for online shopping), in entertainments (music/movie/video clip... recommendation), and in education (learning resource recommendation). In Vietnam, e-commerce is initially growing, thus, RS may be an interesting and potential research topic in the next years. In this work, we shortly introduce about the RS and thoroughly describe one of the prominent techniques in RS which is Matrix Factorization (MF). We describe the MF in details so that the new reader can understand and implement it easily. In the experiments, we set up and compare the MF with other techniques using three data sets from two different areas which are entertainment and education. Experimental results show that the MF can work well in both entertainment (e-commerce) and education domain. 2014-06-05T08:50:38Z 2014-06-05T08:50:38Z 2013 Article https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/37525 en Tạp chí Khoa học Đại học Đà Lạt, số 6;tr. 44-53 application/pdf Trường Đại học Đà Lạt |
| institution |
Thư viện Trường Đại học Đà Lạt |
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Thư viện số |
| language |
English |
| topic |
Recommender Systems Rating prediction Matrix factorization |
| spellingShingle |
Recommender Systems Rating prediction Matrix factorization Nguyen, Thai Nghe An introduction to factorization technique for building recommendation systems |
| description |
Recommender System (RS) is successfully applied in predicting user preferences.
For instance, RS has been used in many areas such as in e-commerce (for online
shopping), in entertainments (music/movie/video clip... recommendation), and in
education (learning resource recommendation). In Vietnam, e-commerce is initially
growing, thus, RS may be an interesting and potential research topic in the next years. In
this work, we shortly introduce about the RS and thoroughly describe one of the
prominent techniques in RS which is Matrix Factorization (MF). We describe the MF in
details so that the new reader can understand and implement it easily. In the experiments,
we set up and compare the MF with other techniques using three data sets from two
different areas which are entertainment and education. Experimental results show that the
MF can work well in both entertainment (e-commerce) and education domain. |
| format |
Article |
| author |
Nguyen, Thai Nghe |
| author_facet |
Nguyen, Thai Nghe |
| author_sort |
Nguyen, Thai Nghe |
| title |
An introduction to factorization technique for building recommendation systems |
| title_short |
An introduction to factorization technique for building recommendation systems |
| title_full |
An introduction to factorization technique for building recommendation systems |
| title_fullStr |
An introduction to factorization technique for building recommendation systems |
| title_full_unstemmed |
An introduction to factorization technique for building recommendation systems |
| title_sort |
introduction to factorization technique for building recommendation systems |
| publisher |
Trường Đại học Đà Lạt |
| publishDate |
2014 |
| url |
https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/37525 |
| _version_ |
1781719081613787136 |