Using association rule mining to enrich semantic concepts for video retrieval
Fatemi, Nastaran and Poulin, Florian and Raileany, Laura E. and Smeaton, Alan F. (2009) Using association rule mining to enrich semantic concepts for video retrieval. In: KDIR 2009 - International Conference on Knowledge Discovery and Information Retieval, 6-8 October, 2009, Madeira, Portugal.
Full text available as:
In order to achieve true content-based information retrieval on video we should analyse and index video with
high-level semantic concepts in addition to using user-generated tags and structured metadata like title, date,
etc. However the range of such high-level semantic concepts, detected either manually or automatically,
usually limited compared to the richness of information content in video and the potential vocabulary of
available concepts for indexing. Even though there is work to improve the performance of individual concept
classiﬁers, we should strive to make the best use of whatever partial sets of semantic concept occurrences
are available to us. We describe in this paper our method for using association rule mining to automatically
enrich the representation of video content through a set of semantic concepts based on concept co-occurrence
patterns. We describe our experiments on the TRECVid 2005 video corpus annotated with the 449 concepts
of the LSCOM ontology. The evaluation of our results shows the usefulness of our approach.
Archive Staff Only: edit this record