Proceedings of the 6th international conference on Intelligent user interfaces
Popular music retrieval by detecting mood
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Usage patterns of collaborative tagging systems
Journal of Information Science
Proceedings of the 15th international conference on World Wide Web
InfoScale '06 Proceedings of the 1st international conference on Scalable information systems
HT06, tagging paper, taxonomy, Flickr, academic article, to read
Proceedings of the seventeenth conference on Hypertext and hypermedia
tagging, communities, vocabulary, evolution
CSCW '06 Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work
Why we tag: motivations for annotation in mobile and online media
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The complex dynamics of collaborative tagging
Proceedings of the 16th international conference on World Wide Web
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
Towards automatic extraction of event and place semantics from flickr tags
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A music search engine built upon audio-based and web-based similarity measures
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
The Benefit of Using Tag-Based Profiles
LA-WEB '07 Proceedings of the 2007 Latin American Web Conference
Can social bookmarking improve web search?
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
Can all tags be used for search?
Proceedings of the 17th ACM conference on Information and knowledge management
MIR '08 Proceedings of the 1st ACM international conference on Multimedia information retrieval
Improving music genre classification using collaborative tagging data
Proceedings of the Second ACM International Conference on Web Search and Data Mining
Deriving music theme annotations from user tags
Proceedings of the 18th international conference on World wide web
How do you feel about "dancing queen"?: deriving mood & theme annotations from user tags
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
Personalized social search based on the user's social network
Proceedings of the 18th ACM conference on Information and knowledge management
Information retrieval in folksonomies: search and ranking
ESWC'06 Proceedings of the 3rd European conference on The Semantic Web: research and applications
A social inverted index for social-tagging-based information retrieval
Journal of Information Science
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Collaborative tagging has become an increasingly popular means for sharing and organizing Web resources, leading to a huge amount of user-generated metadata. These annotations represent quite a few different aspects of the resources they are attached to, but it is not obvious which characteristics of the objects are predominantly described. The usefulness of these tags for finding/re-finding the annotated resources is also not completely clear. Several studies have started to investigate these issues, however only by focusing on a single type of tagging system or resource. We study this problem across multiple domains and resource types and identify the gaps between the tag space and the querying vocabulary. Based on the findings of this analysis, we then try to bridge the identified gaps, focusing in particular on multimedia resources. We focus on the two scenarios of music and picture resources and develop algorithms, which identify usage (theme) and opinion (mood) characteristics of the items. The mood and theme labels our algorithms infer are recommended to the users, in order to support them during the annotation process. The evaluation of the proposed methods against user judgements, as well as against expert ground truth reveal the high quality of our recommended annotations and provide insights into possible extensions for music and picture tagging systems to support retrieval.