Visual Query Posing in Multimedia Web Document Retrieval

In the last few years, the techniques implemented to satisfy users' information needs are changing due to the heterogeneity of web contents, which are getting more wealthy of multimedia contents. The search engines adapt at information needs of users and provides a multi-modal search interface...

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Bibliographic Details
Published in2021 IEEE 15th International Conference on Semantic Computing (ICSC) pp. 415 - 420
Main Authors Rinaldi, Antonio M., Russo, Cristiano, Tommasino, Cristian
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.01.2021
Subjects
Content based image retrieval
deep features
Deep learning
Image retrieval
Multimedia computing
multimedia document retrieval
Ontologies
Search engines
Semantic information retrieval
Semantics
Visualization
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DOI10.1109/ICSC50631.2021.00086

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Summary:In the last few years, the techniques implemented to satisfy users' information needs are changing due to the heterogeneity of web contents, which are getting more wealthy of multimedia contents. The search engines adapt at information needs of users and provides a multi-modal search interface that allows the users to specify the image and text predominantly. Nevertheless, it is not easy to find systems that integrate visual and textual query with reasonable accuracy. Over the years, many authors proposed several frameworks that develop and improve search engines. Moreover, the use of ontology in semantic research had good results and, in an image retrieval system, the deep learning obtained excellent outcomes. In this paper, we present a novel approach for visual query posing to perform a visual and textual query using only images.
DOI:10.1109/ICSC50631.2021.00086