automatic-tagging-suggestion-for-database-enrichment
https://github.com/kaminarimanu/automatic-tagging-suggestion-for-database-enrichment
Science Score: 44.0%
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○Scientific vocabulary similarity
Low similarity (4.4%) to scientific vocabulary
Repository
Basic Info
- Host: GitHub
- Owner: KaminariManu
- Language: Jupyter Notebook
- Default Branch: main
- Size: 2.34 MB
Statistics
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Automatic-Tagging-Suggestion-for-Database-Enrichment
Code for Hogheschool Utrecht Project "Automatic Tagging Suggestion for Database Enrichment".
Project page: https://www.internationalhu.com/research/projects/automatic-tagging-suggestion-for-database-enrichment
Project overview: We aim to determine the feasibility of creating an automatic image tagging tool capable of effectively handling a growing number of tags. This is important in the context of news and journalism, where new tags need to be added regularly.
FILES DESCRIPTION:
The file "AlexNet.ipynb" addresses the first research question, presenting a comparative analysis between a conventional image classifier and the merged CNN-KNN classifier.
The file "TagName Increase.ipynb" corresponds to the second research question, examining the implications of expanding the tag count in the database.
Lastly, the file "MinimumNumber.ipynb" is designed to address the final research question by exploring different set divisions and their implications for tag insertion.
Owner
- Name: Emanuele Cuono Amoruso
- Login: KaminariManu
- Kind: user
- Repositories: 1
- Profile: https://github.com/KaminariManu
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: Amoruso
given-names: Emanuele Cuono
orcid: https://orcid.org/0009-0008-7302-5862
title: "Automatic Tagging Suggestion for Database Enrichment"