Flickr image tag understanding and recommendation
Image tagging recommendation systems could be used to present potential tag candidates to users to facilitate their tagging process. However, there is still room for improvement for tag recommender systems to recommend tags that may be more applicable to the user. Therefore, the purpose of this proj...
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| Awduron Eraill: | |
| Fformat: | Final Year Project (FYP) |
| Iaith: | English |
| Cyhoeddwyd: |
2015
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| Pynciau: | |
| Mynediad Ar-lein: | http://hdl.handle.net/10356/62805 |
| _version_ | 1826129534175412224 |
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| author | Chen, Alicia Ying Ying |
| author2 | Sun Aixin |
| author_facet | Sun Aixin Chen, Alicia Ying Ying |
| author_sort | Chen, Alicia Ying Ying |
| collection | NTU |
| description | Image tagging recommendation systems could be used to present potential tag candidates to users to facilitate their tagging process. However, there is still room for improvement for tag recommender systems to recommend tags that may be more applicable to the user. Therefore, the purpose of this project is to understand how the list of recommended tags would be different if the temporal and location factors are taken into account. The system implemented also provides other functions which can help users to understand the different tagging trends based on the two factors. This project uses a dataset of over 40 million public Flickr images and videos to base its recommendations on. Through the use of Java programming, the system is able to provide functions for analyzing Flickr tags, such as the number of photos containing a tag, its frequency based on geolocation and date, and the popularity of tags in a given time or location. The key function is producing a list of recommended tags by being able to choose if the time and location should be factored into the recommendation process. Three test cases were used to observe whether the recommended tags would be affected by the geolocation or date, and the results are also analyzed in this report to judge the effectiveness of this method. |
| first_indexed | 2024-10-01T07:42:10Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/62805 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:42:10Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | ntu-10356/628052023-03-03T20:34:55Z Flickr image tag understanding and recommendation Chen, Alicia Ying Ying Sun Aixin School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval Image tagging recommendation systems could be used to present potential tag candidates to users to facilitate their tagging process. However, there is still room for improvement for tag recommender systems to recommend tags that may be more applicable to the user. Therefore, the purpose of this project is to understand how the list of recommended tags would be different if the temporal and location factors are taken into account. The system implemented also provides other functions which can help users to understand the different tagging trends based on the two factors. This project uses a dataset of over 40 million public Flickr images and videos to base its recommendations on. Through the use of Java programming, the system is able to provide functions for analyzing Flickr tags, such as the number of photos containing a tag, its frequency based on geolocation and date, and the popularity of tags in a given time or location. The key function is producing a list of recommended tags by being able to choose if the time and location should be factored into the recommendation process. Three test cases were used to observe whether the recommended tags would be affected by the geolocation or date, and the results are also analyzed in this report to judge the effectiveness of this method. Bachelor of Engineering (Computer Science) 2015-04-29T04:38:16Z 2015-04-29T04:38:16Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/62805 en Nanyang Technological University 57 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval Chen, Alicia Ying Ying Flickr image tag understanding and recommendation |
| title | Flickr image tag understanding and recommendation |
| title_full | Flickr image tag understanding and recommendation |
| title_fullStr | Flickr image tag understanding and recommendation |
| title_full_unstemmed | Flickr image tag understanding and recommendation |
| title_short | Flickr image tag understanding and recommendation |
| title_sort | flickr image tag understanding and recommendation |
| topic | DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval |
| url | http://hdl.handle.net/10356/62805 |
| work_keys_str_mv | AT chenaliciayingying flickrimagetagunderstandingandrecommendation |