A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Analyses of multiple evidence combination
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
What Are Ontologies, and Why Do We Need Them?
IEEE Intelligent Systems
Discriminative model fusion for semantic concept detection and annotation in video
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Multimedia semantic indexing using model vectors
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 1
The challenge problem for automated detection of 101 semantic concepts in multimedia
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
An empirical study of inter-concept similarities in multimedia ontologies
Proceedings of the 6th ACM international conference on Image and video retrieval
Towards optimal bag-of-features for object categorization and semantic video retrieval
Proceedings of the 6th ACM international conference on Image and video retrieval
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Although detectors for individual concepts have been widely studied in multimedia search area, the exploration of inter-concept relations among concepts receives relatively less attention, especially when hierarchical concept taxonomy is not manually constructed beforehand. In this paper, we present an ontology-based concept fusion method for building more reliable concept detectors from multiple independent detectors. Specifically, two logical relations among concepts are defined in advance so that an ontology hierarchy can be explicitly built by using a decision rule based on a relation strength function. With the ontology hierarchy built, an effective fusion strategy is then explored to construct an improved detector for each concept. Evaluation on TRECVID'06 test set shows that the proposed method achieves more remarkable and consistent improvement.