USING ASSOCIATION RULE MINING TO ENRICH SEMANTIC CONCEPTS FOR VIDEO RETRIEVAL

Nastaran Fatemi, Florian Poulin, Laura E. Raileanu, Alan F. Smeaton

2009

Abstract

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, is 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.

Paper Citation

in Harvard Style

Fatemi N., Poulin F., E. Raileanu L. and F. Smeaton A. (2009). USING ASSOCIATION RULE MINING TO ENRICH SEMANTIC CONCEPTS FOR VIDEO RETRIEVAL . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009) ISBN 978-989-674-011-5, pages 119-126. DOI: 10.5220/0002275701190126

in Bibtex Style

@conference{kdir09,
author={Nastaran Fatemi and Florian Poulin and Laura E. Raileanu and Alan F. Smeaton},
title={USING ASSOCIATION RULE MINING TO ENRICH SEMANTIC CONCEPTS FOR VIDEO RETRIEVAL},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009)},
year={2009},
pages={119-126},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002275701190126},
isbn={978-989-674-011-5},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2009)
TI - USING ASSOCIATION RULE MINING TO ENRICH SEMANTIC CONCEPTS FOR VIDEO RETRIEVAL
SN - 978-989-674-011-5
AU - Fatemi N.
AU - Poulin F.
AU - E. Raileanu L.
AU - F. Smeaton A.
PY - 2009
SP - 119
EP - 126
DO - 10.5220/0002275701190126