Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Classification of user image descriptions
International Journal of Human-Computer Studies
RelaxImage: A Cross-Media Meta-Search Engine for Searching Images from Web Based on Query Relaxation
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
HT06, tagging paper, taxonomy, Flickr, academic article, to read
Proceedings of the seventeenth conference on Hypertext and hypermedia
Optimizing web search using social annotations
Proceedings of the 16th international conference on World Wide Web
Can social bookmarking enhance search in the web?
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
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
High-dimensional visual vocabularies for image retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Can social bookmarking improve web search?
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
Evaluating truthfulness of modifiers attached to web entity names
WAIM'10 Proceedings of the 11th international conference on Web-age information management
Estimating content concreteness for finding comprehensible documents
Proceedings of the sixth ACM international conference on Web search and data mining
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Conventional Web image search engines can return reasonably accurate results for queries containing concrete terms, but the results are less accurate for queries containing only abstract terms, such as "spring" or "peace." To improve the recall ratio without drastically degrading the precision ratio, we developed a method that replaces an abstract query term given by a user with a set of concrete terms and that uses these terms in queries input into Web image search engines. Concrete terms are found for a given abstract term by making use of social tagging information extracted from a social photo sharing system, such as Flickr. This information is rich in user impressions about the objects in the images. The extraction and replacement are done by (1) collecting social tags that include the abstract term, (2) clustering the tags in accordance with the term co-occurrence of images, (3) selecting concrete terms from the clusters by using WordNet, and (4) identifying sets of concrete terms that are associated with the target abstract term by using a technique for association rule mining. Experimental results show that our method improves the recall ratio of Web image searches.