Interactive recommender system for images and video
With the growth of the internet, e-commerce grew and flourished. With this, there was a need for predicting user’s desire. Recommending items or products to users that they may not have seen or acted upon. A recommender system employs collaborative filtering techniques to predict a user’s liking for...
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| Format: | Final Year Project |
| Language: | English |
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2015
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| Online Access: | http://hdl.handle.net/10356/64673 |
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| Institution: | Nanyang Technological University |
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sg-ntu-dr.10356-646732023-07-07T16:50:37Z Interactive recommender system for images and video Muhammad Ghalib Mohamed Yuan Junsong School of Electrical and Electronic Engineering Graymatics DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision With the growth of the internet, e-commerce grew and flourished. With this, there was a need for predicting user’s desire. Recommending items or products to users that they may not have seen or acted upon. A recommender system employs collaborative filtering techniques to predict a user’s liking for a certain item. In this project, the aim was to develop an interactive system where it would take into account a user’s action on an item and constantly adjust its prediction based on this interactivity. Bachelor of Engineering 2015-05-29T04:10:14Z 2015-05-29T04:10:14Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/64673 en Nanyang Technological University 43 p. application/pdf |
| institution |
Nanyang Technological University |
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NTU Library |
| continent |
Asia |
| country |
Singapore Singapore |
| content_provider |
NTU Library |
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DR-NTU |
| language |
English |
| topic |
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision |
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DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Muhammad Ghalib Mohamed Interactive recommender system for images and video |
| description |
With the growth of the internet, e-commerce grew and flourished. With this, there was a need for predicting user’s desire. Recommending items or products to users that they may not have seen or acted upon. A recommender system employs collaborative filtering techniques to predict a user’s liking for a certain item. In this project, the aim was to develop an interactive system where it would take into account a user’s action on an item and constantly adjust its prediction based on this interactivity. |
| author2 |
Yuan Junsong |
| author_facet |
Yuan Junsong Muhammad Ghalib Mohamed |
| format |
Final Year Project |
| author |
Muhammad Ghalib Mohamed |
| author_sort |
Muhammad Ghalib Mohamed |
| title |
Interactive recommender system for images and video |
| title_short |
Interactive recommender system for images and video |
| title_full |
Interactive recommender system for images and video |
| title_fullStr |
Interactive recommender system for images and video |
| title_full_unstemmed |
Interactive recommender system for images and video |
| title_sort |
interactive recommender system for images and video |
| publishDate |
2015 |
| url |
http://hdl.handle.net/10356/64673 |
| _version_ |
1772825682344148992 |