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arXiv AI By Vladimir Beskorovainyi

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

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The paper presents the AI Appeals Processor, a deep‑learning system deployed in a CPU‑only government environment to classify and route citizen appeals. On a dataset of 10,000 Russian‑language appeals, multilingual BERT achieved 82% accuracy on a three‑way appeal‑type task, outperforming other models such as fastText, Word2Vec+LSTM, and SVM. After deployment, the system reduced end‑to‑end handling time by 53‑56% and, following several retraining cycles, achieved over 95% correct classifications in production, though the high accuracy is not directly comparable to the test‑set result due to taxonomy issues.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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