CYC: a large-scale investment in knowledge infrastructure
Communications of the ACM
Image searching on the Excite web search engine
Information Processing and Management: an International Journal
Indexing Flower Patent Images Using Domain Knowledge
IEEE Intelligent Systems
An analysis of multimedia searching on AltaVista
MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
Combining the language model and inference network approaches to retrieval
Information Processing and Management: an International Journal - Special issue: Bayesian networks and information retrieval
Flickr tag recommendation based on collective knowledge
Proceedings of the 17th international conference on World Wide Web
Proceedings of the 18th international conference on World wide web
Using large-scale web data to facilitate textual query based retrieval of consumer photos
MM '09 Proceedings of the 17th ACM international conference on Multimedia
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Event classification in personal image collections
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Web query expansion by wordnet
DEXA'05 Proceedings of the 16th international conference on Database and Expert Systems Applications
| Hi-index | 0.00 |
As consumers accumulate more and more personal imagery, searching for specific images has become increasingly difficult. Consumers typically provide little or no annotations, and automated classifiers and concept tagging tools are limited in their scope and vocabulary. This work addresses this sparsity of semantic information by leveraging domain-specific information provided by online photo-sharing communities. Such information enables improved search by allowing user-provided search terms to be expanded into a set of semantically related concepts, using relevant semantic relationships provided by millions of users. Our system first extracts metadata using a modest number of image and event-based semantic classifiers, as well as any meaningful file or folder names. When users pose text-based queries, our system retrieves images from their personal image collections by leveraging Flickr's tag dataset for concept expansion. This approach enables users to search their collections without having to manually annotate their pictures. We compare the retrieval performance of using a Flickr-based concept expander with the performance obtained without concept expansion and with using a WordNet-based concept expander. The results demonstrate that common sense knowledge gleaned from online photo sharing communities can enable meaningful image search on consumer image collections, searches that would be impossible using only the available image metadata.