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

Vladimir Beskorovainyi

doi:10.5281/zenodo.19393273

January 1, 2025Open Access

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

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Key Points

The aim is to automate the classification of citizen appeals using deep learning techniques.
Developed a microservice-based system for appeal classification.
Combined natural language processing with deep learning.
Utilized Word2Vec and LSTM architecture for analysis.
Evaluated on 10,000 real Russian-language appeals.
Achieved 78% accuracy, surpassing manual processing by 11 percentage points.
Reduced processing time by 54%.

Implication

This system automates classification of citizen appeals in government services, indicating improved efficiency and accuracy.

Abstract

This paper presents AI Appeals Processor, a microservice-based system integrating NLP and deep learning for automated classification of citizen appeals in government services. Evaluated on 10,000 real Russian-language appeals, the Word2Vec+LSTM architecture achieves 78% accuracy (+11pp over manual baseline) while reducing processing time by 54%

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Cite This Study

Vladimir Beskorovainyi (2025) studied this question.

synapsesocial.com/papers/69d1fdf7a79560c99a0a4539 https://doi.org/10.5281/zenodo.19393273

View Full Paper

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

Key Points

Implication

Abstract

Discussion

Cite This Study

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

Key Points

Implication

Abstract

Discussion

Cite This Study

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