Matching recommendation method and system based on city specific populations and associated policies

Abstract

The invention relates to a matching recommendation method and system based on city specific populations and associated policies. The method comprises the steps of S1, collecting basic data of the specific populations and requirement and behavior data of the populations for specific areas, and forming a specific population set; S2, performing preprocessing on the collected data to obtain a character feature sequence; S3, performing mining and classification on the specific populations through neural network based clustering analysis, extracting requirement labels of each category of populations, and generating a requirement label set; S4, analyzing according to related policies adopted for the specific populations, and decomposing all of the related policies into a plurality of policy module sets associated with the requirement labels; and S5, generating a three-dimensional space set according to the specific population set, the requirement label set and the policy module sets, performing matching on each policy resource in two dimensions of the specific population set and a policy resource set according to a knowledge based fuzzy label recommendation algorithm, and recommending thematched policy resource to a specific user.

Description

technical field [0001] The invention relates to the technical field of smart cities, in particular to a matching recommendation method and system based on specific urban populations and related policies. Background technique [0002] In most developed and developing countries, people pay more and more attention to people's livelihood and well-being. While the economic take-off of a country or region releases extensive development dividends, it often brings a series of unexpected social and environmental problems. Improving the comprehensive living welfare of the people has become one of the priorities of the local government. The specific groups of people concerned by this patent mainly include the following three types of groups, one is the immigrants in the new resettlement areas produced by large-scale urban construction and the leftover families who have not moved out of the countryside, the other is the urban floating population, and the third is the elderly, weak, sic...

AI Technical Summary

Problems solved by technology

Too often, however, policies are formulated that do not really address the main concerns of specific groups of people or those who really need help are not getting enough help

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