@inproceedings{pub6571,
    series = {Lecture Notes in Computer Science, LNCS},
    abstract = {We present a novel approach, called SemI, to semantic indexing of annotated multimedia objects for their efficient retrieval.
The generation of multimedia indexes with SemI relies on the semantic annotation of these objects
with references to concepts formally defined in standard OWL2 and semantic services described in OWL-S.
For scoring the annotated multimedia data in these indexes an appropriate semantic similarity measure
makes use of approximated logical concept abduction in order to alleviate strict logical false negatives.
Efficient query answering over SemI indexes is performed with the use of Fagin's threshold algorithm.
The results of our comparative experimental evaluation reveals that SemI-enabled multimedia retrieval
can significantly outperform representative approaches of LSA- and RDF-based semantic retrieval in this domain
in terms of precision at recall, averaged precision and discounted cumulative gain.},
    year = {2012},
    title = {Semantic Indexing for Efficient Retrieval of Multimedia Data},
    booktitle = {Procedings of the 10th International Workshop on Adaptive Multimedia Retrieval (AMR). International Workshop on Adaptive Multimedia Retrieval (AMR-12), 10th, October 24, Copenhagen, Denmark},
    address = {Birketinget 6 | DK-2300 Copenhagen S},
    publisher = {Springer},
    author = {Xiaoqi Cao and Matthias Klusch},
    keywords = {semantic-based indexing, semantic-based multimedia retrieval},
    organization = {Royal School of Library and Information Science}
}