Digital economy policies are critical for guiding the promotion and regulation of activities within a digital economy. Analyzing these policies quantitatively can significantly support the formulation and enhancement of related strategies. This paper used text mining techniques and the Policy Modeling Consistency index model to construct an evaluation framework comprising 9 primary variables and 35 secondary variables as indicators for quantitatively assessing digital economy policies within Shandong Province. Of the ten selected samples of digital economy policies, researchers rated three as excellent, three as good, three as satisfactory, and one as inadequate. Research findings indicated that digital economy policies in Shandong Province were generally effective, showing a certain degree of scientific rigor. In the future, policy optimization should focus on policy timeliness, scope, and perspectives.

Private information retrieval aims to protect users’ query content and privacy, serving as an important extension of privacy protection in the field of information retrieval. A highly configurable, stateful, single-server private information retrieval scheme was designed based on the concept of cost amortization. Experiments conducted on a database containing 1 million 1 kB elements showed that this method delivered superior performance, being able to respond to client queries in less than 1 s, with the server’s response data being increased by less than 3.6 times. It is noteworthy that the experimental analysis was based on a simple, unoptimized Rust implementation, suggesting that this method is particularly suitable for deployment environments involving a large number of clients. Experimental results indicate that this method holds significant potential in the field of private information retrieval and can provide an efficient and cost-effective solution for handling large-scale retrieval tasks.