Intelligent service recommendation method based on neural network mining model

A technology of business intelligence and neural network, applied in the field of business intelligence recommendation based on neural network mining model, can solve the problems of lack of unified standard for business product recommendation priority, low efficiency of business intelligence recommendation, and one-sided consideration of index dimensions, etc., to achieve Comprehensive coverage, wide range, and improved accuracy effects

Pending Publication Date: 2021-02-26
广州瀚信通信科技股份有限公司
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AI Technical Summary

Problems solved by technology

The traditional business precision marketing recommendation method is aimed at a single business product, the coverage is not comprehensive enough, the index dimension is considered one-sided, too dependent on business experience, and lacks a unified standard for business product recommendation priorities, resulting in low efficiency and passive business intelligent recommendation

Method used

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  • Intelligent service recommendation method based on neural network mining model
  • Intelligent service recommendation method based on neural network mining model
  • Intelligent service recommendation method based on neural network mining model

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Embodiment Construction

[0043]The azimuthal terms such as up, down, left, right, front, back, front, back, top, bottom, etc. mentioned or possibly mentioned in this specification are defined relative to their structure, and they are relative concepts. Therefore, it may change accordingly according to different locations and different usage conditions. Therefore, these or other orientation terms should not be interpreted as restrictive terms.

[0044]The implementation manners described in the following exemplary embodiments do not represent all implementation manners consistent with the present disclosure. Rather, they are merely examples of methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0045]The terms used in the present disclosure are only for the purpose of describing specific embodiments, and are not intended to limit the present disclosure. The singular forms "a", "said" and "the" used in the present disclosure and appended claims are also intended to i...

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Abstract

The invention relates to the technical field of intelligent service pushing, and particularly discloses an intelligent service recommendation method based on a neural network mining model, which comprises the following steps: acquiring user data and preprocessing the user data; taking the preprocessed user data as data source input, and constructing a neural network model in combination with an activation function, training data and adjusting errors; and calculating a utility function of the user according to data output of the constructed neural network model, calculating user similarity anduser interestingness of the user to a service product in combination with a recommendation algorithm, constructing a hybrid service recommendation model, and establishing and displaying a hybrid service recommendation list by the constructed hybrid service recommendation model. According to the service intelligent recommendation method based on the neural network mining model, the coverage serviceproduct range is wider, the same set of model is utilized, the service recommendation standard is unified, and the priority ranking problem of service product recommendation can be solved while the accuracy and timeliness of service product recommendation are met.

Description

Technical field[0001]The invention relates to the technical field of business intelligent push, in particular to a business intelligent recommendation method based on a neural network mining model.Background technique[0002]In recent years, with the rapid development of the mobile Internet market, various new business products have continued to increase, requiring operators to quickly respond to the market’s demand for accurate business recommendations, and continuously improve customer marketing accuracy and timeliness. However, the traditional precision marketing recommendation of mobile market services is to conduct detailed market analysis for specific business products, build a user tag library based on multiple dimensions such as user basic attributes, behavior preferences, and consumption preferences, extract business-related indicators, and build a decision tree , Logistic regression and other data mining model algorithms to calculate the probability of target users to purcha...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9535G06F16/9536G06Q10/06G06Q30/06G06N3/04G06N3/08
CPCG06F16/9535G06F16/9536G06Q10/06393G06Q30/0631G06N3/08G06N3/045
Inventor 苏如春孙少峰练镜锋
Owner 广州瀚信通信科技股份有限公司
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