Bridging the gap between tagging and querying vocabularies: Analyses and applications for enhancing multimedia IR

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.