Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/52035
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dc.contributor.authorSha Yong.
dc.date.accessioned2013-04-19T08:38:32Z
dc.date.available2013-04-19T08:38:32Z
dc.date.copyright2013en_US
dc.date.issued2013
dc.identifier.urihttp://hdl.handle.net/10356/52035
dc.description.abstractDue to the increasing use of the Web, there is an increase in the amount of data. Tags which are used to describe a subject it was tagged to, are also being widely used as a result. With a large amount of growing data, it is essential to be able to search efficiently for useful information that the users need. Tag classes become very important for this purpose by quickly filtering out unwanted information and reducing the search space. It is also useful for other purposes such as recommendation of tags to the users. In this project, tags studied were used on images and photos only, and were mainly used in photo sharing websites such as flickr.com. The aim of this project was to implement a Java program to automatically identify the tag class of a tag, and categorize tags into their respective classes. Both rulebased classification methods which used boolean matching on a library of keywords, as well as modelbased classification methods which used machine learning techniques were used to identify different sets of tag classes. The finished program was run and tested against a set of 500 manually classified tags and the results showed that it was able to classify most image tags correctly.en_US
dc.format.extent50 p.en_US
dc.language.isoenen_US
dc.rightsNanyang Technological University
dc.subjectDRNTU::Engineering::Computer science and engineeringen_US
dc.titleImage tag relationship studyen_US
dc.typeFinal Year Project (FYP)en_US
dc.contributor.supervisorSun Aixinen_US
dc.contributor.schoolSchool of Computer Engineeringen_US
dc.description.degreeBachelor of Engineering (Computer Science)en_US
item.grantfulltextrestricted-
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Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)
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