CN112927059A - Personalized digital type zero work service recommendation method and system based on deep learning - Google Patents
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Abstract
The invention discloses a personalized digital type zero work service recommendation method and a system based on deep learning, and the technical scheme is as follows: the system comprises an individualized digital service module, wherein a connecting end of the individualized digital service module is provided with a zero-work service module, the connecting end of the zero-work service module is respectively provided with a background management module, a fund management module, an account registration module and a password login module, the connecting end of the account registration module and the password login module is provided with a terminal selection module, and the connecting end of the terminal selection module is respectively provided with a service end module and a demand end module; the connecting end of the server module is respectively provided with a label writing module, a data writing module and an image uploading module, and the invention has the beneficial effects that: the deep learning algorithm is used for analyzing and matching labels and figures of both parties, digital type zero work service matching and recommendation for buyers are achieved, matching and recommendation of personalized digital type zero work service are achieved rapidly and accurately, and working efficiency and user experience are improved.
Description
Technical Field
The invention relates to the field of digital type zero work service, in particular to a personalized digital type zero work service recommendation method and system based on deep learning.
Background
With the development of modern information technology and the formation of network environment, the development and utilization of digital information service become the key of information construction and innovation development of the relational country, the digital information service is based on the international social information environment, on the basis of information users and the analysis of the digital information requirements thereof, the organization of digital information resources facing users, the construction of a digital information service business system, the sharing of digital information resources and the integration of information resources are researched, an information service interaction mechanism based on a user system is disclosed, the organization principle and the method of the digital information service are explained, and the promotion strategy of social, integration and personalized information service is provided in the social development facing knowledge innovation.
The prior art has the following defects: most of the existing retail services can be known and serviced through forums or advertisements, which causes that the retail services are not wide enough, the retail services are not known by the public, many people with skills and talents cannot better develop their own talents, and many people needing services cannot find or cannot find service providers.
Therefore, it is necessary to provide a method and a system for recommending personalized digital class of zero work services based on deep learning.
Disclosure of Invention
Therefore, the invention provides a personalized digital type zero work service recommendation method and system based on deep learning, which realize matching and recommending digital type zero work services for buyers by analyzing and matching labels and figures of both parties by utilizing a deep learning algorithm and solve the problems that the zero work services are not wide enough, the zero work services are not known by the public, a plurality of people with skills and talents cannot better play their own talents, and a plurality of people needing services cannot find out or cannot find out a server easily.
In order to achieve the above purpose, the invention provides the following technical scheme: a personalized digital type of zero work service recommendation method and system based on deep learning comprise a personalized digital service module, wherein a zero work service module is arranged at the connecting end of the personalized digital service module, a background management module, a fund management module, an account registration module and a password login module are respectively arranged at the connecting end of the zero work service module, a terminal selection module is arranged at the connecting end of the account registration module and the password login module, and a service end module and a demand end module are respectively arranged at the connecting end of the terminal selection module;
the server module connecting end is equipped with label write-in module, data write-in module and portrait respectively and uploads the module, the label write-in module connecting end is equipped with label detection module, label detection module connecting end is equipped with label upload module, label upload module connecting end is equipped with label price generation module and label respectively and sums up the module.
Preferably, the data writing module connecting end is provided with a data auditing module, and the data auditing module connecting end is provided with a data uploading module.
Preferably, the demand end module connecting end is provided with an identity data uploading module, and the identity data uploading module connecting end is provided with a privacy protection module.
Preferably, the connecting end of the demand end module is provided with a label matching module, the connecting end of the label matching module is provided with a label selecting module, and the connecting end of the label selecting module is provided with a communication module.
Preferably, the communication module connecting end is respectively provided with a communication monitoring module and a deposit module, the deposit module connecting end is provided with a payment module, and the payment module connecting end is provided with a service comment module.
Preferably, the demand end module connecting end is provided with a demand label writing module, the demand label writing module connecting end is provided with a demand label auditing module, and the demand label auditing module connecting end is provided with a demand label uploading module.
Preferably, the fund management module connecting end is provided with a payment module, the payment module connecting end is provided with a fund transfer-in module, the fund transfer-in module connecting end is provided with a fund management module, the fund management module connecting end is provided with a service confirmation module, and the service confirmation module connecting end is provided with a fund transfer-out module.
Preferably, the connection end of the background management module is provided with a background service module, the connection end of the background service module is provided with a notification sending module, the connection end of the notification sending module is provided with a data checking module, and the connection end of the data checking module is provided with an instruction execution module.
Preferably, the input end of the payment module is connected with a payment module.
Preferably, the specific steps are as follows:
s1, client login: the account number is registered through a mobile phone number, the password is input through short message verification, and the account number and the password can be input for login after the login is successful;
s2, platform operation: entering a zero-work service platform, uploading a personal digital label, personal data and a portrait to the platform according to personal requirements, generating labels and portraits of a zero-work service provider and a service provider by data, acquiring identity data of a service purchaser, generating a requirement label and a portrait by the data, analyzing and matching the labels and the portraits of both parties by the platform by using an LSTM algorithm in a deep learning algorithm, and quickly pushing the requirement label to a demander and the service provider;
s3, platform communication: the demander and the service provider check and communicate according to the label information pushed by the platform, and the platform marks and monitors communication sensitive information in the communication process to avoid illegal operation;
s4, service: after the communication is finished, the demander pays the service deposit to ensure that the service provider is relieved of the service, the payment deposit automatically enters the background for storage, after the service is finished, the demander pays the tail money after confirming that the service reaches the purpose, and the fund is transferred to the account of the service provider after both sides confirm the service;
s5, background management: aiming at service ambiguity, a demander and a server can contact a background, the background sends data viewing information, queries data and communication records of the two parties after agreement is obtained, and enforces a command after one party breaks rules.
The invention has the beneficial effects that:
1. the invention obtains the data of digital type zero work service and service provider, and generates the label and portrait of the zero work service and service provider; the identity data of a service purchaser is obtained, and a demand label and a portrait of the service purchaser are generated by the data, so that the retail service is wider, the retail service is easily known by the public, a plurality of people with skills and talents can better exert the talents of the user, and a plurality of people needing service can easily find a server;
2. the invention realizes the matching and recommendation of the digital type of the zero work service for the buyer by analyzing and matching the labels and the figures of both parties by utilizing the deep learning algorithm, can quickly and accurately realize the matching and recommendation of the personalized digital type of the zero work service, improves the working efficiency and the user experience, simultaneously facilitates the communication between the service person and the demander, and improves the safety of funds.
Drawings
FIG. 1 is a block diagram of the overall system provided by the present invention;
FIG. 2 is a system structure diagram of a server module provided by the present invention;
FIG. 3 is a block diagram of a demand side module system according to the present invention;
FIG. 4 is a block diagram of a fund security module system provided by the present invention;
fig. 5 is a structural diagram of a background management module system provided by the present invention.
In the figure: 1 personalized digital service module, 2 zero-work service module, 3 password login module, 4 fund management module, 5 demand side module, 6 terminal selection module, 7 service side module, 8 background management module, 9 account registration module, 10 data writing module, 11 portrait uploading module, 12 tag detection module, 13 tag writing module, 14 tag price generation module, 15 tag uploading module, 16 tag induction module, 17 data auditing module, 18 data uploading module, 19 privacy protection module, 20 identity data uploading module, 21 communication module, 22 communication monitoring module, 23 fixed amount module, 24 payment module, 25 service review module, 26 tag matching module, 27 tag selection module, 28 demand tag writing module, 29 demand tag auditing module, 30 demand tag uploading module, 31 payment module, 32 fund transferring module, 33 fund management module, 34 service confirmation module, 35 fund transfer-out module, 36 background service module, 37 notification sending module, 38 data viewing module and 39 instruction execution module.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
the link of server module 7 is equipped with label respectively and writes in module 13, data write in module 10 and portrait and upload module 11, the link of module 13 is written in to the label is equipped with label detection module 12, the link of label detection module 12 is equipped with label and uploads module 15, the link of module 15 is uploaded to the label is equipped with label price generation module 14 and label respectively and sums up module 16.
Furthermore, a data auditing module 17 is arranged at the connecting end of the data writing module 10, and a data uploading module 18 is arranged at the connecting end of the data auditing module 17.
Furthermore, the connection end of the demand end module 5 is provided with an identity data uploading module 20, and the connection end of the identity data uploading module 20 is provided with a privacy protection module 19.
Further, a label matching module 26 is arranged at the connecting end of the demand end module 5, a label selecting module 27 is arranged at the connecting end of the label matching module 26, and a communication module 21 is arranged at the connecting end of the label selecting module 27.
Further, a communication monitoring module 22 and a deposit module 23 are respectively arranged at the connecting end of the communication module 21, a payment module 24 is arranged at the connecting end of the deposit module 23, and a service comment module 25 is arranged at the connecting end of the payment module 24.
Further, the connecting end of the demand end module 5 is provided with a demand label writing module 28, the connecting end of the demand label writing module 28 is provided with a demand label auditing module 29, and the connecting end of the demand label auditing module 29 is provided with a demand label uploading module 30.
Further, a payment module 31 is arranged at the connection end of the fund management module 4, a fund transfer-in module 32 is arranged at the connection end of the payment module 31, a fund management module 33 is arranged at the connection end of the fund transfer-in module 32, a service confirmation module 34 is arranged at the connection end of the fund management module 33, and a fund transfer-out module 35 is arranged at the connection end of the service confirmation module 34.
Further, a background service module 36 is arranged at the connection end of the background management module 8, a notification sending module 37 is arranged at the connection end of the background service module 36, a data checking module 38 is arranged at the connection end of the notification sending module 37, and an instruction execution module 39 is arranged at the connection end of the data checking module 38.
Further, the input end of the payment module 31 is connected with the payment module 24.
Further, the specific steps are as follows:
s1, client login: the account number is registered through a mobile phone number, the password is input through short message verification, and the account number and the password can be input for login after the login is successful;
s2, platform operation: entering a zero-work service platform, uploading a personal digital label, personal data and a portrait to the platform according to personal requirements, generating labels and portraits of a zero-work service provider and a service provider by data, acquiring identity data of a service purchaser, generating a requirement label and a portrait by the data, analyzing and matching the labels and the portraits of both parties by the platform by using an LSTM algorithm in a deep learning algorithm, and quickly pushing the requirement label to a demander and the service provider;
s3, platform communication: the demander and the service provider check and communicate according to the label information pushed by the platform, and the platform marks and monitors communication sensitive information in the communication process to avoid illegal operation;
s4, service: after the communication is finished, the demander pays the service deposit to ensure that the service provider is relieved of the service, the payment deposit automatically enters the background for storage, after the service is finished, the demander pays the tail money after confirming that the service reaches the purpose, and the fund is transferred to the account of the service provider after both sides confirm the service;
s5, background management: aiming at service ambiguity, a demander and a server can contact a background, the background sends data viewing information, queries data and communication records of the two parties after agreement is obtained, and enforces a command after one party breaks rules.
The using process of the invention is as follows: when the invention is used, the mobile phone number enters the account registration module 9 and the password login module 3 to perform account registration and login, the password is input through short message verification, the registration can be successful, the account and the password can be input to perform login after the registration is successful, the mobile phone number enters the terminal selection module 6 after the login is completed, and the server module 7 or the demand side module 5 is selected on the terminal selection module 6 according to personal requirements; after entering a zero-work service platform, a server uploads a digital label, personal data and a portrait through a label writing module 13, a data writing module 10 and a portrait uploading module 11, meanwhile, labels are classified through a label induction module 16, prices are produced through a label price generation module 14, a demander uploads labels, portraits and data through an identity data uploading module 20, a label matching module 26 and a demand label writing module 28 to obtain identity data of a service purchaser, and the demand labels and the portraits are generated from the data, the platform analyzes and matches the labels and the portraits of both sides by using a deep learning algorithm, an LSTM algorithm in the deep learning algorithm is a specific form of RNN (Recurrent neural network), the RNN is a general name of a series of neural networks capable of processing sequence data, and the difference between the Recurrent neural network and the Recurrent neural network is required to be paid attention to, generally, RNNs contain three properties:
a. the cyclic neural network can generate an output at each time node, and the connection between the hidden units is cyclic;
b. the cyclic neural network can generate an output at each time node, and the output at the time node is only circularly connected with the hidden unit of the next time node;
c. the recurrent neural network comprises a hidden unit with recurrent connection, and can process sequence data and output single prediction, thereby quickly pushing a demand label to a demander and a service provider, the demander and the service provider can check according to label information pushed by a platform and enter a communication module 21 for communication, a communication monitoring module 22 of the platform marks and monitors communication sensitive information in the communication process to avoid illegal operation, after the communication is completed, the demander pays a service deposit through a deposit module 23 to ensure that the server is relieved of service, the payment deposit automatically enters a background for storage, after the service is completed, the demander confirms the service to reach the purpose and pays a payment tail through a payment module 24, after both sides confirm the service, funds are transferred to an account of the servicer through a fund transfer-out module 35 to generate ambiguity aiming at the service, the demander and the server can contact the background, the background sends data viewing information through the notification sending module 37, the data viewing module 38 queries data and communication records of the demander and the servant after agreement is obtained, and the instruction execution module 39 forcibly executes commands after one party is found to be illegal, so that matching and recommendation of personalized digital type zero-work services are quickly and accurately realized, and the working efficiency and the user experience are improved.
The above description is only a preferred embodiment of the present invention, and any person skilled in the art may modify the present invention or modify it into an equivalent technical solution by using the technical solution described above. Therefore, any simple modifications or equivalent substitutions made in accordance with the technical solution of the present invention are within the scope of the claims of the present invention.
Claims (10)
1. A personalized digital type zero work service recommendation system based on deep learning comprises a personalized digital service module (1) and is characterized in that: the personalized digital service module (1) is provided with a retail service module (2) at a connecting end, the retail service module (2) is provided with a background management module (8), a fund management module (4), an account registration module (9) and a password login module (3) at the connecting end respectively, a terminal selection module (6) is arranged at the connecting end of the account registration module (9) and the password login module (3), and a service end module (7) and a demand end module (5) are arranged at the connecting end of the terminal selection module (6) respectively;
the utility model discloses a label is uploaded module (15), server module (7) link is equipped with label respectively and writes in module (13), data write in module (10) and portrait and uploads module (11), the label writes in module (13) link and is equipped with label detection module (12), label detection module (12) link is equipped with label and uploads module (15), label upload module (15) link is equipped with label price generation module (14) respectively and the label sums up module (16).
2. The deep learning-based personalized digital class-of-the-retail service recommendation method and system according to claim 1, wherein: the data writing module (10) is provided with a data auditing module (17) at the connecting end, and the data auditing module (17) is provided with a data uploading module (18) at the connecting end.
3. The deep learning-based personalized digital class-of-the-retail service recommendation method and system according to claim 1, wherein: the identity data uploading module (20) is arranged at the connecting end of the demand end module (5), and the privacy protection module (19) is arranged at the connecting end of the identity data uploading module (20).
4. The deep learning-based personalized digital class-of-the-retail service recommendation method and system according to claim 1, wherein: the demand end module (5) connecting end is equipped with label matching module (26), label matching module (26) connecting end is equipped with label and selects module (27), the label is selected module (27) connecting end and is equipped with and communicates module (21).
5. The deep learning-based personalized digital class-of-the-retail service recommendation method and system according to claim 4, wherein: the communication module (21) connecting end is equipped with respectively and communicates monitoring module (22) and deposit module (23), deposit module (23) connecting end is equipped with payment module (24), payment module (24) connecting end is equipped with service comment module (25).
6. The deep learning-based personalized digital class-of-the-retail service recommendation method and system according to claim 1, wherein: the demand label writing module is characterized in that a demand label writing module (28) is arranged at the connecting end of the demand end module (5), a demand label auditing module (29) is arranged at the connecting end of the demand label writing module (28), and a demand label uploading module (30) is arranged at the connecting end of the demand label auditing module (29).
7. The deep learning-based personalized digital class-of-the-retail service recommendation method and system according to claim 1, wherein: the fund transfer system is characterized in that a payment module (31) is arranged at the connecting end of the fund management module (4), a fund transfer module (32) is arranged at the connecting end of the payment module (31), a fund management module (33) is arranged at the connecting end of the fund transfer module (32), a service confirmation module (34) is arranged at the connecting end of the fund management module (33), and a fund transfer-out module (35) is arranged at the connecting end of the service confirmation module (34).
8. The deep learning-based personalized digital class-of-the-retail service recommendation method and system according to claim 1, wherein: the system is characterized in that a background service module (36) is arranged at the connecting end of the background management module (8), a notification sending module (37) is arranged at the connecting end of the background service module (36), a data checking module (38) is arranged at the connecting end of the notification sending module (37), and an instruction execution module (39) is arranged at the connecting end of the data checking module (38).
9. The method and system for recommending personalized digital class of zero-work services based on deep learning according to claim 5 or 7, wherein: the input end of the payment module (31) is connected with a payment module (24).
10. The deep learning-based personalized digital class-of-the-retail service recommendation method and system according to claim 1, wherein: the method comprises the following specific steps:
s1, client login: the account number is registered through a mobile phone number, the password is input through short message verification, and the account number and the password can be input for login after the login is successful;
s2, platform operation: entering a zero-work service platform, uploading a personal digital label, personal data and a portrait to the platform according to personal requirements, generating labels and portraits of a zero-work service provider and a service provider by data, acquiring identity data of a service purchaser, generating a requirement label and a portrait by the data, analyzing and matching the labels and the portraits of both parties by the platform by using an LSTM algorithm in a deep learning algorithm, and quickly pushing the requirement label to a demander and the service provider;
s3, platform communication: the demander and the service provider check and communicate according to the label information pushed by the platform, and the platform marks and monitors communication sensitive information in the communication process to avoid illegal operation;
s4, service: after the communication is finished, the demander pays the service deposit to ensure that the service provider is relieved of the service, the payment deposit automatically enters the background for storage, after the service is finished, the demander pays the tail money after confirming that the service reaches the purpose, and the fund is transferred to the account of the service provider after both sides confirm the service;
s5, background management: aiming at service ambiguity, a demander and a server can contact a background, the background sends data viewing information, queries data and communication records of the two parties after agreement is obtained, and enforces a command after one party breaks rules.
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| CN111626784A (en) * | 2020-05-29 | 2020-09-04 | 杭州回星科技有限公司 | Enterprise demand information matching method, device and system |
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