Rekabsaz, Navid, Bierig, Ralf, Ionescu, Bogdan, Hanbury, Allan and Lupu, Mihai (2015) On the Use of Statistical Semantics for Metadata-Based Social Image Retrieval. 2015 13th International Workshop on Content-Based Multimedia Indexing (CBMI). pp. 1-4. ISSN 1949-3991
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Abstract
We revisit text-based image retrieval for social
media, exploring the opportunities offered by statistical semantics. We assess the performance and limitation of several
complementary corpus-based semantic text similarity methods
in combination with word representations. We compare results
with state-of-the-art text search engines. Our deep learning-based semantic retrieval methods show a statistically significant
improvement in comparison to a best practice Solr search engine,
at the expense of a significant increase in processing time. We
provide a solution for reducing the semantic processing time up
to 48% compared to the standard approach, while achieving the
same performance.
Item Type: | Article |
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Keywords: | Semantics; Image retrieval; Indexing; Context; Encyclopedias; Correlation; |
Academic Unit: | Faculty of Science and Engineering > Computer Science Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
Item ID: | 15205 |
Identification Number: | 10.1109/CBMI.2015.7153634 |
Depositing User: | Ralf Bierig |
Date Deposited: | 10 Jan 2022 13:26 |
Journal or Publication Title: | 2015 13th International Workshop on Content-Based Multimedia Indexing (CBMI) |
Publisher: | IEEE |
Refereed: | Yes |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/15205 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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