This application discloses a method and
system for reviewing government documents based on historical
case analysis, belonging to the field of
smart government platform technology. The method includes: acquiring archived historical case data and target government documents to be reviewed from the government approval
system; performing structured modeling on the historical case data to form a case
database containing content features, review conclusions, and business categories, thus achieving a computable representation of experience data; extracting multi-dimensional features from the target documents, combining the reliability weight of the business category obtained from clustering, the similarity weight between the target documents and historical cases, and the
importance weight of each review dimension; employing a multi-layered weighted voting mechanism to generate a comprehensive review
score for the documents through the fusion calculation of the three weights, and automatically outputting the
machine review conclusion based on the
score threshold. This achieves a transformation from manual experience to data-driven decision-making, effectively improving the accuracy, consistency, and intelligence level of government document review.