Comparison of different ontology-based query expansion algorithms for effective image retrieval
|Comparison of different ontology-based query expansion algorithms for effective image retrieval|
|Author(s)||Leung C.H.C., Li Y.|
|Published in||Communications in Computer and Information Science|
|Keyword(s)||concept distance, Image retrieval, ontology, query expansion (Extra: concept distance, Concept similarity, Concept-based, Expansion methods, Image search, Ontology-based, Ontology-based query, Query expansion, Re-ranking, Semantic distance, Wikipedia, Algorithms, Expansion, Image processing, Information technology, Internet protocols, Ontology, Pattern recognition, Semantics, Image retrieval)|
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Comparison of different ontology-based query expansion algorithms for effective image retrieval is a 2011 conference paper written in English by Leung C.H.C., Li Y. and published in Communications in Computer and Information Science.
We study several semantic concept-based query expansion and re-ranking scheme and compare different ontology-based expansion methods in image search and retrieval. In particular, we exploit the two concept similarities of different concept expansion ontology-WordNet Similarity, Wikipedia Similarity. Furthermore, we compare the keywords semantic distance with the precision of image search results with query expansion according to different concept expansion algorithms. We also compare the image retrieval precision of searching with the expanded query and original plain query. Preliminary experiments have been able to demonstrate that the two proposed retrieval mechanism has the potential to outperform unaided approaches.
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