This item is a Paper in the Rich Media track.
Social tagging provides valuable and crucial information for large-scale web image retrieval. It is ontology-free and easy to obtain; however, irrelevant tags frequently appear, and users typically will not tag all semantic objects in the image, which is also called semantic loss. To avoid noises and compensate for the semantic loss, tag recommendation is proposed in literature. However, current recommendation simply ranks the related tags based on the single modality of tag co-occurrence on the whole dataset, which ignores other modalities, such as visual correlation. This paper proposes a multi-modality recommendation based on both tag and visual correlation, and formulates the tag recommendation as a learning problem. Each modality is used to generate a ranking feature, and Rankboost algorithm is applied to learn an optimal combination of these ranking features from different modalities. Experiments on Flickr data demonstrate the effectiveness of this learning-based multi-modality recommendation strategy.
Fun web stuff for this record
- RKBExplorer (from linked data workshop)
- URI: http://eprints.rkbexplorer.com/id/www2009/eprints-37
Browse the data for this paper at RKBExplorer
- REST Interface
- ORE Resource Map
- ORE was described in the Linked Data Workshop. View Resource Map
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About this site
This website has been set up for WWW2009 by Christopher Gutteridge of the University of Southampton, using our EPrints software.
Add your Slides, Posters, Supporting data, whatnots...
If you are presenting a paper or poster and have slides or supporting material you would like to have permentently made public at this website, please email
email@example.com - Include the file(s), a note to say if they are presentations, supporting material or whatnot, and the URL of the paper/poster from this site. eg. http://www2009.eprints.org/128/
It's impractical to add all the workshops at WWW2009 by hand, but if you can provide me with the metadata in a machine readable way, I'll have a go at importing it. If you are good at slinging XML, my ideal import format is visible at http://www2009.eprints.org/import_example.xml
We (Southampton EPrints Project) intend to preserve the files and HTML pages of this site for many years, however we will turn it into flat files for long term preservation. This means that at some point in the months after the conference the search, metadata-export, JSON interface, OAI etc. will be disabled as we "fossilize" the site. Please plan accordingly. Feel free to ask nicely for us to keep the dynamic site online longer if there's a rally good (or cool) use for it...
- WWW2009 EPrints supports OAI 2.0 with a base URL of http://www2009.eprints.org/cgi/oai2
- The JSON URL is http://www2009.eprints.org/cgi/json?callback=function&eprintid=number
To prevent google killing the server by hammering these tools, the /cgi/ URL's are denied to robots.txt - ask Chris if you want an exception made.
Feel free to contact me (Christopher Gutteridge) with any other queries or suggestions. ...Or if you do something cool with the data which we should link to!
These are not directly related to the EPrints set up, but may be of use to delegates.
- Social tool links
- I've put links in the page header to the WWW2009 stuff on flickr, facebook and to a page which will let you watch the #www2009 tag on Twitter. Not really the right place, but not yet made it onto the main conference homepage. Send me any suggestions for new links.