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Target object matching method based on artificial intelligence and related equipment

A target object, artificial intelligence technology, applied in the field of artificial intelligence, can solve the problems of different order results and performance, poor recommendation effect of recommendation system, inaccurate matching of target objects, etc.

Active Publication Date: 2021-09-21
PING AN TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In the process of implementing the present invention, the inventor found that the existing recommendation system mainly recommends courses based on the user characteristics of insurance agents. However, for two insurance agents with similar user characteristics, such as agents of the same age in the same region , attendance rate, visit frequency, telephone interview frequency, etc. are also similar, but may produce different order results and performance. Therefore, the inaccurate matching of target objects leads to poor recommendation effect of the recommendation system

Method used

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  • Target object matching method based on artificial intelligence and related equipment
  • Target object matching method based on artificial intelligence and related equipment
  • Target object matching method based on artificial intelligence and related equipment

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0060] figure 1 It is a flow chart of the artificial intelligence-based target object matching method provided in Embodiment 1 of the present invention.

[0061] In this embodiment of the present application, target objects can be matched based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results. .

[0062] Artificial intelligence basic technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, and mechatronics. Artificial intelligence software technology mainly includes computer vision technology, robotics technology, biometrics technology, sp...

Embodiment 2

[0139] figure 2 It is a structural diagram of an artificial intelligence-based target object matching device provided in Embodiment 2 of the present invention.

[0140] In some embodiments, the artificial intelligence-based target object matching device 20 may include a plurality of functional modules composed of computer program segments. The computer program of each program segment in the artificial intelligence-based target object matching device 20 can be stored in the memory of the electronic device, and executed by at least one processor to execute (see for details figure 1 Describe) the function of artificial intelligence-based object matching.

[0141] In this embodiment, the artificial intelligence-based target object matching device 20 can be divided into multiple functional modules according to the functions it performs. The functional modules may include: an acquisition module 201 , a training module 202 , an identification module 203 , a pairing module 204 , a ...

Embodiment 3

[0215] This embodiment provides a computer-readable storage medium, and a computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, the steps in the above-mentioned embodiment of the artificial intelligence-based target object matching method are implemented, for example figure 1 S11-S15 shown:

[0216] S11. Obtain multiple positive sample pairs and multiple negative sample pairs, wherein two samples in the positive sample pair are similar samples, and two samples in the negative sample pair are dissimilar samples;

[0217] S12. Obtain the original twin neural network and improve the original twin neural network, and train the improved twin neural network based on the multiple positive sample pairs and the multiple negative sample pairs to obtain a similarity calculation model;

[0218] S13. Obtain target data of multiple objects to be matched, and identify target tags for the corresponding objects to be matched a...

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Abstract

The invention relates to the technical field of artificial intelligence, and provides a target object matching method based on artificial intelligence and related equipment. The method comprises the steps of firstly improving an original twin neural network, and training the improved twin neural network based on similar sample pairs and dissimilar sample pairs to obtain a similarity calculation model with relatively high learning ability and generalization performance; secondly, after a plurality of to-be-matched objects are obtained, marking target labels for the corresponding to-be-matched objects according to target data of the to-be-matched objects, so that the to-be-matched objects marked with different target labels are paired in pairs, and a plurality of to-be-matched object pairs are obtained; and finally, calculating the similarity of each to-be-matched object pair by using a similarity calculation model so as to determine a target to-be-matched object pair in the plurality of to-be-matched object pairs according to the similarity. According to the invention, the target objects can be accurately and quickly paired in batches.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to an artificial intelligence-based target object matching method, device, electronic equipment and storage medium. Background technique [0002] In the insurance industry, the personal characteristics and business behavior characteristics of an insurance agent greatly affect the probability of closing an order and the level of final performance. Enterprises recommend course resources to insurance agents through online learning platforms to improve their order issuance rate. [0003] In the process of implementing the present invention, the inventor found that the existing recommendation system mainly recommends courses based on the user characteristics of insurance agents. However, for two insurance agents with similar user characteristics, such as agents of the same age in the same region , attendance rate, visit frequency, telephone interview frequency, e...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06N3/04G06N3/08G06F16/9535
CPCG06F16/9535G06N3/08G06N3/045G06F18/22
Inventor 袁雅云张莉任杰
Owner PING AN TECH (SHENZHEN) CO LTD
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