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Government affair reservation service recommendation method based on machine learning

A machine learning and service recommendation technology, applied in the field of government appointment service recommendation system, can solve the problems of inability to meet the needs of different users, no personalized recommendation, and no deep mining of the current needs of users, so as to reduce the time of search and query and improve the service efficiency. Efficiency, the effect of enriching data sources

Pending Publication Date: 2022-06-07
厦门市民数据服务股份有限公司
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Such a recommendation method is not well considered on the side of the user, and does not dig deep into the current needs of the user. There is no personalized recommendation for different user groups, and the recommended content seen by the user is the same, which cannot meet the needs of different users.

Method used

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  • Government affair reservation service recommendation method based on machine learning
  • Government affair reservation service recommendation method based on machine learning
  • Government affair reservation service recommendation method based on machine learning

Examples

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Embodiment Construction

[0043] like Figure 1-5 As shown, the present invention discloses a method for recommending government affairs appointment services based on machine learning, recommending to-do items for users based on a specific scenario, and the specific scenario includes one or more of scenario 1, scenario 2 and scenario 3, in:

[0044] Scenario 1: Recommend items to be handled based on data from other government departments

[0045] A1, if figure 1 As shown, the user enters the reservation service module to obtain user identity information, including ID card and name;

[0046] A2. According to the user's identity information, find out whether the user has to-do items in the government affairs database, for example, the user needs to go to the outlet to pay the traffic fine, etc.;

[0047] A3. If yes, recommend corresponding to-do items for users.

[0048] Scenario 2: Recommend services based on the services the user has visited and reservations made

[0049] like figure 2As shown, ...

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Abstract

According to the government affair reservation service recommendation method based on machine learning disclosed by the invention, recommendation is carried out in various scenes, the scene I carries out data linkage, data sources are enriched, and items needing to be handled can be recommended according to personal records of all government affair departments, and the scene II constructs a user portrait and constructs user features in combination with basic information and behavior data of a user, so that the user experience is improved. According to information such as properties of services and appointment items, article features are constructed, article scores are calculated based on an article similarity model and user portraits, users are divided by adopting a clustering mode, and personalized customization and possible affair handling items can be recommended for both new and old users; in the third scene, the geographic position coordinates of the user and the geographic position coordinates of all the to-do sites are utilized, the coordinate positions are classified through a classification algorithm and then weighted calculation is carried out to give a suggested recent service site, item recommendation for different types of users in different scenes is achieved, the user can use the appointment service module more conveniently, and the user experience is improved. And the working efficiency is improved.

Description

technical field [0001] The invention relates to the technical field of a government appointment service recommendation system, in particular to a method for recommending a government appointment service based on machine learning. Background technique [0002] At present, recommended services are set up in the service modules of government affairs apps (such as government affairs service platforms) to guide users to quickly select and make appointments. When the user enters the service appointment page, an area module will appear to display the recommended service list for the user to choose. [0003] Disadvantages of the prior art: [0004] The traditional government service recommendation method does not combine the user's own attributes and needs, but places some services on the recommended special page according to the operator's own understanding and the needs of the service department, or only based on the cumulative number of site-wide user visits. Simply sort, filte...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/02G06Q50/26G06N20/00
CPCG06Q10/02G06Q50/26G06N20/00
Inventor 林佳旻林晨
Owner 厦门市民数据服务股份有限公司
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