Details
| Original language | English |
|---|---|
| Title of host publication | CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops |
| Pages | 189-198 |
| Number of pages | 10 |
| Publication status | Published - 26 Oct 2010 |
| Event | 19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10 - Toronto, ON, Canada Duration: 26 Oct 2010 → 30 Oct 2010 |
Publication series
| Name | International Conference on Information and Knowledge Management, Proceedings |
|---|
Abstract
With the rapidly increasing popularity of Social Media sites, a lot of user generated content has been injected in the Web, thus resulting in a large amount of both multimedia items (music - Last.fm, MySpace.com, pictures - Flickr, Picasa, videos - YouTube) and textual data (tags and other text-based documents). As a consequence, especially for multimedia content it has become more and more difficult to find exactly the objects that best match the users' information needs. The methods we propose in this paper try to alleviate this problem and we focus on the domain of pictures, in particular on a subset of Flickr data. Many of the photos posted by users on Flickr have been shot during events and our methods aim to allow browsing and organization of picture collections in a natural way, by events. The algorithms we introduce in this paper exploit the social information produced by users in form of tags, titles and photo descriptions, for classifying pictures into different event categories. The extensive automated experiments demonstrate that our approach is very effective and opens new possibilities for multimedia retrieval, in particular image search. Moreover, the direct comparison with previous event detection algorithms confirm once more the quality of our methods.
Keywords
- Collaborative tagging, Event classification, Event detection, Machine learning, Metadata enrichment
ASJC Scopus subject areas
- Decision Sciences(all)
- General Decision Sciences
- Business, Management and Accounting(all)
- General Business,Management and Accounting
Cite this
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CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops. 2010. p. 189-198 (International Conference on Information and Knowledge Management, Proceedings).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Bringing Order to Your Photos
T2 - 19th International Conference on Information and Knowledge Management and Co-located Workshops, CIKM'10
AU - Firan, Claudiu S.
AU - Georgescu, Mihai
AU - Nejdl, Wolfgang
AU - Paiu, Raluca
PY - 2010/10/26
Y1 - 2010/10/26
N2 - With the rapidly increasing popularity of Social Media sites, a lot of user generated content has been injected in the Web, thus resulting in a large amount of both multimedia items (music - Last.fm, MySpace.com, pictures - Flickr, Picasa, videos - YouTube) and textual data (tags and other text-based documents). As a consequence, especially for multimedia content it has become more and more difficult to find exactly the objects that best match the users' information needs. The methods we propose in this paper try to alleviate this problem and we focus on the domain of pictures, in particular on a subset of Flickr data. Many of the photos posted by users on Flickr have been shot during events and our methods aim to allow browsing and organization of picture collections in a natural way, by events. The algorithms we introduce in this paper exploit the social information produced by users in form of tags, titles and photo descriptions, for classifying pictures into different event categories. The extensive automated experiments demonstrate that our approach is very effective and opens new possibilities for multimedia retrieval, in particular image search. Moreover, the direct comparison with previous event detection algorithms confirm once more the quality of our methods.
AB - With the rapidly increasing popularity of Social Media sites, a lot of user generated content has been injected in the Web, thus resulting in a large amount of both multimedia items (music - Last.fm, MySpace.com, pictures - Flickr, Picasa, videos - YouTube) and textual data (tags and other text-based documents). As a consequence, especially for multimedia content it has become more and more difficult to find exactly the objects that best match the users' information needs. The methods we propose in this paper try to alleviate this problem and we focus on the domain of pictures, in particular on a subset of Flickr data. Many of the photos posted by users on Flickr have been shot during events and our methods aim to allow browsing and organization of picture collections in a natural way, by events. The algorithms we introduce in this paper exploit the social information produced by users in form of tags, titles and photo descriptions, for classifying pictures into different event categories. The extensive automated experiments demonstrate that our approach is very effective and opens new possibilities for multimedia retrieval, in particular image search. Moreover, the direct comparison with previous event detection algorithms confirm once more the quality of our methods.
KW - Collaborative tagging
KW - Event classification
KW - Event detection
KW - Machine learning
KW - Metadata enrichment
UR - http://www.scopus.com/inward/record.url?scp=78651304752&partnerID=8YFLogxK
U2 - 10.1145/1871437.1871465
DO - 10.1145/1871437.1871465
M3 - Conference contribution
AN - SCOPUS:78651304752
SN - 9781450300995
T3 - International Conference on Information and Knowledge Management, Proceedings
SP - 189
EP - 198
BT - CIKM'10 - Proceedings of the 19th International Conference on Information and Knowledge Management and Co-located Workshops
Y2 - 26 October 2010 through 30 October 2010
ER -