A Technology for Automatic Extraction and Portrait Visualization of Document Tags

This paper focuses on the problem of automatic extraction and portrait visualization in industrial enterprises, and deeply studies the advantages of intelligent algorithm application to realize document tagging. To this end, this paper realizes the application of document labels to achieve the purpose of scientific and real-time mining of text information, and carries out industrial data monitoring, so as to reduce the extraction error of the model. The results of this paper show that after upgrading the automatic extraction and portrait visualization technology model, the extraction accuracy is increased to 86.19%, the document processing time is reduced to 279.13s, and the error correction efficiency is increased to 58.11%. Therefore, the final conclusion shows that the application of automatic extraction and portrait visualization technology for document tags can comprehensively improve the operation efficiency and stability of industrial data analysis and processing, and provide feasible solutions for the operation and management of industrial enterprises.

Authors

Publication Details

Published
2025-07-25
DOI
https://doi.org/10.1109/icdsns65743.2025.11168484
Primary Topic
Mathematics, Computing, and Information Processing
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Technology for Automatic Extraction and Portrait Visualization of Document Tags

Yang Zhao
Mathematics, Computing, and Information Processing
article

A Technology for Automatic Extraction and Portrait Visualization of Document Tags

Yang Zhao
article en

Abstract

This paper focuses on the problem of automatic extraction and portrait visualization in industrial enterprises, and deeply studies the advantages of intelligent algorithm application to realize document tagging. To this end, this paper realizes the application of document labels to achieve the purpose of scientific and real-time mining of text information, and carries out industrial data monitoring, so as to reduce the extraction error of the model. The results of this paper show that after upgrading the automatic extraction and portrait visualization technology model, the extraction accuracy is increased to 86.19%, the document processing time is reduced to 279.13s, and the error correction efficiency is increased to 58.11%. Therefore, the final conclusion shows that the application of automatic extraction and portrait visualization technology for document tags can comprehensively improve the operation efficiency and stability of industrial data analysis and processing, and provide feasible solutions for the operation and management of industrial enterprises.

Openalex Percentile: Top 72%
Mathematics, Computing, and Information Processing
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.