COMPARATIVE ANALYSIS OF DOCUMENT CLASSIFICATION ALGORITHMS

Document classification is a critical task in the field of natural language processing (NLP), which involves classifying text documents into predefined classes or topics. Various algorithms have been developed to automate this process, each with its own strengths and limitations. In this article, we provide a comparative analysis of popular document classification algorithms, revealing insights into their methodology, advantages, and challenges.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-08-15
DOI
https://doi.org/10.5281/zenodo.13325063
Primary Topic
Text and Document Classification Technologies
Type
article
Field-Weighted Citation Impact
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article

COMPARATIVE ANALYSIS OF DOCUMENT CLASSIFICATION ALGORITHMS

Zenodo (CERN European Organization for Nuclear Research)
Text and Document Classification Technologies
article

COMPARATIVE ANALYSIS OF DOCUMENT CLASSIFICATION ALGORITHMS

article en

Abstract

Document classification is a critical task in the field of natural language processing (NLP), which involves classifying text documents into predefined classes or topics. Various algorithms have been developed to automate this process, each with its own strengths and limitations. In this article, we provide a comparative analysis of popular document classification algorithms, revealing insights into their methodology, advantages, and challenges.

Zenodo (CERN European Organization for Nuclear Research)
Quality Education
Openalex Percentile: Top 68%
Text and Document Classification Technologies
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COMPARATIVE ANALYSIS OF DOCUMENT CLASSIFICATION ALGORITHMS · Zenodo (CERN European Organization for Nuclear Research) (2024) | TGRS Research Map | TGRS