Tagged images browsing system
Nowadays, tagging systems have been integrated into many websites, especially for social media websites. By integrating a tagging system with a search engine, the accessing of users to media contents or even documents can be easier. However, retrieving the contents which are most relevant to a tag i...
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| Other Authors: | |
| Format: | Final Year Project (FYP) |
| Language: | English |
| Published: |
2010
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| Online Access: | http://hdl.handle.net/10356/42450 |
| _version_ | 1826119433705226240 |
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| author | Nguyen Tran Nam, Khanh. |
| author2 | Sun Aixin |
| author_facet | Sun Aixin Nguyen Tran Nam, Khanh. |
| author_sort | Nguyen Tran Nam, Khanh. |
| collection | NTU |
| description | Nowadays, tagging systems have been integrated into many websites, especially for social media websites. By integrating a tagging system with a search engine, the accessing of users to media contents or even documents can be easier. However, retrieving the contents which are most relevant to a tag is still challenging and attracting numerous of research effort.
Since the content-related searching is still not scalable, in this paper we propose various methods to improve the purely tag-based search on tagged image system. The proposed methods are: Tf-Idf weight and similarity between tags’ association and tags’ global weight. We also proposed 5 different methods to compute the association of tags and 3 methods to compute tags’ global weight. The above methods are integrated in to the existing image browsing system named TagViz.
After conducting the experiments on the proposed methods, we found out that: generally the method “similarity between tags’ Pointwise KL and tags’ Idf weight” performs the best and can provide good results for searching 25 or 50 images. |
| first_indexed | 2024-10-01T05:00:15Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/42450 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:00:15Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | ntu-10356/424502023-03-03T20:39:53Z Tagged images browsing system Nguyen Tran Nam, Khanh. Sun Aixin School of Computer Engineering Centre for Advanced Information Systems DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval Nowadays, tagging systems have been integrated into many websites, especially for social media websites. By integrating a tagging system with a search engine, the accessing of users to media contents or even documents can be easier. However, retrieving the contents which are most relevant to a tag is still challenging and attracting numerous of research effort. Since the content-related searching is still not scalable, in this paper we propose various methods to improve the purely tag-based search on tagged image system. The proposed methods are: Tf-Idf weight and similarity between tags’ association and tags’ global weight. We also proposed 5 different methods to compute the association of tags and 3 methods to compute tags’ global weight. The above methods are integrated in to the existing image browsing system named TagViz. After conducting the experiments on the proposed methods, we found out that: generally the method “similarity between tags’ Pointwise KL and tags’ Idf weight” performs the best and can provide good results for searching 25 or 50 images. Bachelor of Engineering (Computer Science) 2010-12-07T08:25:26Z 2010-12-07T08:25:26Z 2010 2010 Final Year Project (FYP) http://hdl.handle.net/10356/42450 en Nanyang Technological University 66 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval Nguyen Tran Nam, Khanh. Tagged images browsing system |
| title | Tagged images browsing system |
| title_full | Tagged images browsing system |
| title_fullStr | Tagged images browsing system |
| title_full_unstemmed | Tagged images browsing system |
| title_short | Tagged images browsing system |
| title_sort | tagged images browsing system |
| topic | DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval |
| url | http://hdl.handle.net/10356/42450 |
| work_keys_str_mv | AT nguyentrannamkhanh taggedimagesbrowsingsystem |