Difference between revisions of "Daedalus at Imageclef Wikipedia Retrieval 2010: Expanding with Semantic Information from Context"

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'''Daedalus at Imageclef Wikipedia Retrieval 2010: Expanding with Semantic Information from Context''' - scientific work related to Wikipedia quality published in 2010, written by Sara Lana-Serrano, Julio Villena-Román and José Carlos González Cristóbal.
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'''Daedalus at Imageclef Wikipedia Retrieval 2010: Expanding with Semantic Information from Context''' - scientific work related to [[Wikipedia quality]] published in 2010, written by [[Sara Lana-Serrano]], [[Julio Villena-Román]] and [[José Carlos González Cristóbal]].
  
 
== Overview ==
 
== Overview ==
This paper describes the participation of DAEDALUS at the ImageCLEF 2010 Wikipedia Retrieval task. The main focus of experiments is to evaluate the impact in the image retrieval pr ocess of the incorporation of semantic information extracted only from the textua l information provided as metadata of the image itself, as compared to expand ing with contextual information gathered from the document where the image is referred. For the semantic annotation, DBpedia ontology and YAGO classification schema are used. As expected, the obtained results show that, in general, the textual information attached to a given image is not able t o fully represent certain features of the image. Furthermore, the use of sema ntic information in the process of multimedia information extraction poses two hard challenges still to solve: how to automatically extract the high level features associated to a multimedia resource, and, once the resource has bee n semantically tagged, which features must be used in the retrieval proces s to best model the actual and complete meaning of the user query.
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This paper describes the participation of DAEDALUS at the ImageCLEF 2010 [[Wikipedia]] Retrieval task. The main focus of experiments is to evaluate the impact in the image retrieval pr ocess of the incorporation of [[semantic information]] extracted only from the textua l information provided as metadata of the image itself, as compared to expand ing with contextual information gathered from the document where the image is referred. For the semantic annotation, [[DBpedia]] [[ontology]] and YAGO classification schema are used. As expected, the obtained results show that, in general, the textual information attached to a given image is not able t o fully represent certain [[features]] of the image. Furthermore, the use of sema ntic information in the process of multimedia [[information extraction]] poses two hard challenges still to solve: how to automatically extract the high level features associated to a multimedia resource, and, once the resource has bee n semantically tagged, which features must be used in the retrieval proces s to best model the actual and complete meaning of the user query.

Revision as of 09:18, 27 November 2019

Daedalus at Imageclef Wikipedia Retrieval 2010: Expanding with Semantic Information from Context - scientific work related to Wikipedia quality published in 2010, written by Sara Lana-Serrano, Julio Villena-Román and José Carlos González Cristóbal.

Overview

This paper describes the participation of DAEDALUS at the ImageCLEF 2010 Wikipedia Retrieval task. The main focus of experiments is to evaluate the impact in the image retrieval pr ocess of the incorporation of semantic information extracted only from the textua l information provided as metadata of the image itself, as compared to expand ing with contextual information gathered from the document where the image is referred. For the semantic annotation, DBpedia ontology and YAGO classification schema are used. As expected, the obtained results show that, in general, the textual information attached to a given image is not able t o fully represent certain features of the image. Furthermore, the use of sema ntic information in the process of multimedia information extraction poses two hard challenges still to solve: how to automatically extract the high level features associated to a multimedia resource, and, once the resource has bee n semantically tagged, which features must be used in the retrieval proces s to best model the actual and complete meaning of the user query.