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From Text to Metadata: Automated Product Tagging with Python and Natural Language Processing.

Authors :
Verma, Aayushi
Khan, Omar Agha
Source :
ITEA Journal of Test & Evaluation; Sep2024, Vol. 45 Issue 3, p1-9, 9p
Publication Year :
2024

Abstract

The Institute for Defense Analyses (IDA) produces a variety of researchdeliverables such as reports, memoranda, slides, and other formats for oursponsors. Summarizing keywords from these products quickly and foreffi cient retrieval of information on given research topics poses achallenge. IDA has numerous initiatives for tagging products with IDA-defi ned taxonomies of research terms, but this is a manual and time-consuming process and must be repeated periodically to tag newerproducts. To address this challenge, we developed a Python-basedautomated tagging pipeline. In this article, we introduce the mechanics ofthis pipeline, highlight current results, and discuss future applications foranalyzing IDA’s research in terms of these tags. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10540229
Volume :
45
Issue :
3
Database :
Supplemental Index
Journal :
ITEA Journal of Test & Evaluation
Publication Type :
Academic Journal
Accession number :
180348572
Full Text :
https://doi.org/10.61278/itea.45.3.1007