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AI system automates classification of citizen appeals

By PulseAugur Editorial · [1 sources] ·

Researchers have developed an AI Appeals Processor designed to automate the classification and routing of citizen appeals in government services. This deep learning model, utilizing multilingual BERT, achieved 82% accuracy on a Russian-language dataset, significantly outperforming human operators. While deployed with human oversight, the system reduced end-to-end handling time by over 50%, with most remaining errors attributed to the appeal taxonomy itself rather than the model's performance. AI

IMPACT Automates government appeal classification, reducing handling times and potentially improving efficiency in public services.

RANK_REASON The cluster contains a research paper detailing a deep learning approach to a specific problem. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

AI system automates classification of citizen appeals

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The cluster contains a research paper detailing a deep learning approach to a specific problem. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Vladimir Beskorovainyi ·

    AI Appeals Processor: A Deep Learning Approach to Automated Classification of Citizen Appeals in Government Services

    arXiv:2604.03672v2 Announce Type: replace-cross Abstract: Government agencies must register, classify and route every citizen appeal within statutory time limits, and much of this work is still done by hand. We describe AI Appeals Processor, a classification and routing component…

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