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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| Tác giả chính: | |
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| Định dạng: | Bài viết |
| Ngôn ngữ: | English |
| Được phát hành: |
Trường Đại học Đà Lạt
2014
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| Những chủ đề: | |
| Truy cập trực tuyến: | https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/37525 |
| Các nhãn: |
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| Thư viện lưu trữ: | Thư viện Trường Đại học Đà Lạt |
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| Tóm tắt: | 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. |
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