Enterprise policy information multiple dynamic intelligent matching recommendation method for digital government affairs

Abstract

The invention provides an enterprise policy information multi-dynamic intelligent matching recommendation method for digital government affairs, which comprises the following steps of: regularly crawling multiple groups of policy data from a webpage, performing text semantic analysis on the crawled data, performing modular disassembly and policy label setting on each group of policy data according to a semantic analysis result, and storing in a policy database; receiving enterprise data input by a user, performing enterprise label setting on different types of content information in the enterprise data, and storing the enterprise labels in an enterprise database; and positioning a data category according to the set policy label and enterprise label, then performing multiple intelligent matching on enterprise data input by a user and multiple groups of policy data in the policy database, performing weight scoring on a matching result of each round, and pushing a policy matching report to the user according to a final weight scoring result.

Description

technical field [0001] The invention relates to the technical field of information processing, in particular to a method for multiple dynamic intelligent matching and recommendation of enterprise policy information for digital government affairs. Background technique [0002] With the rapid development of national science and technology and economy, in order to encourage innovative activities of enterprises and scientific research institutions of universities, various departments of the country will issue many policies every year to support and encourage the development of innovative technologies of enterprises and scientific research institutions of universities. However, due to the fact that the departments, release times, and release sites of the policies are different, the policy information is scattered. Users who want to know the policy information in this industry often have to search a large amount of website information and analyze the obtained policy information to...

AI Technical Summary

Problems solved by technology

However, due to the fact that the department, release time, and release site of the policy are all different, the policy information is scattered.

Users who want to know the policy information in this industry often have to search a large amount of website information and analyze the obtained policy information to judge whether they meet the declaration requirements. Such a cumbersome process takes up a lot of time for enterprises and other users. time

Users often have to analyze a large number of policies one by one to know the policies that they are suitable for reporting, which takes up a lot of manpower time and is inefficient

Enterprises cannot obtain policy information in a timely manner, nor can they judge whether they meet the application requirements and complete the application process in a timely manner, let alone obtain support from government projects in a timely manner, and miss the opportunity to obtain policy assistance, thus hindering the process of national encouragement and support

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