DocumentCode :
2003351
Title :
Use of Semantic Enhancements to NLP of Image Captions to Aid Image Retrieval
Author :
Kesorn, Kraisak ; Poslad, Stefan
Author_Institution :
Sch. of Electron. Eng. & Comput. Sci., Queen Mary Univ. of London, London, UK
fYear :
2008
fDate :
15-16 Dec. 2008
Firstpage :
52
Lastpage :
57
Abstract :
This paper proposes a semantic-based create and search technique to enhance visual information retrieval. Our approach includes an ontology-based scheme for the semi-automatic annotation for image retrieval. Latent Semantic Indexing (LSI) is used in order to solve the Natural Language (NL) vagueness problem and to tolerate ontology imperfections. In addition, our framework is able to find indirect relevant concepts in images and to represent image semantics at a higher level. Experiments demonstrate that semantic-based approaches can significantly improve image retrieval.
Keywords :
image representation; image retrieval; natural language processing; ontologies (artificial intelligence); image captions; image retrieval; image semantics representation; latent semantic indexing; natural language processing; natural language vagueness problem; ontology-based scheme; semantic enhancements; semiautomatic annotation; visual information retrieval; Computer science; Frequency; HTML; Image retrieval; Indexing; Information retrieval; Large scale integration; Ontologies; Uncertainty; XML; Image retrieval; Knowledge-based model; Ontology; Semantic model; Semantic retrieval;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Semantic Media Adaptation and Personalization, 2008. SMAP '08. Third International Workshop on
Conference_Location :
Prague
Print_ISBN :
978-0-7695-3444-2
Type :
conf
DOI :
10.1109/SMAP.2008.18
Filename :
4724848
Link To Document :
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