VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Deriving concept hierarchies from text
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
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
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Automatic construction of a hypernym-labeled noun hierarchy from text
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Proceedings of the 15th international conference on World Wide Web
Extracting Concept Hierarchy Knowledge from the Web Based on Property Inheritance and Aggregation
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Mining the web for hyponymy relations based on property inheritance
APWeb'08 Proceedings of the 10th Asia-Pacific web conference on Progress in WWW research and development
Mining the web for appearance description
DEXA'07 Proceedings of the 18th international conference on Database and Expert Systems Applications
| Hi-index | 0.00 |
When a user searches the Web for information about a target object by submitting a keyword-based query to such a conventional Web search engine as Google, the precision and recall of the search results depend a great deal on whether or not s/he has known exactly the concrete name of the target object. However, the user does not always know the concrete name of any target object that s/he has encountered in the real world and wanted information about. In this paper, we propose an application system of Object-Name Search that helps her/him to identify the concrete name of the target object by such ambiguous features as its class-name, visual appearance and spatio-temporal information. When the user inputs a class-name, visual appearance and/or real-world context descriptions, our system returns not only concrete object-names ranked by her/his specification but also their typical images, visual appearance and spatio-temporal descriptions. And then the user can also modify her/his original specification repeatedly by using their typical features as a useful reference.