CN113704633A

CN113704633A - Marriage and love pairing method, device, system and medium based on multidimensional three-view data

Info

Publication number: CN113704633A
Application number: CN202110868873.4A
Authority: CN
Inventors: 赖华来
Original assignee: Shenzhen Mirror Play Technology Co ltd
Current assignee: Shenzhen Mirror Play Technology Co ltd
Priority date: 2021-07-29
Filing date: 2021-07-29
Publication date: 2021-11-26

Abstract

The application discloses a marriage and love pairing method, a device, a system and a medium based on multidimensional three-view data, wherein the method comprises the following steps: the method comprises the steps of obtaining first multi-dimensional three-view data of a first user and second multi-dimensional three-view data of a second user, wherein the first multi-dimensional three-view data and the second multi-dimensional three-view data comprise a plurality of subdata; comparing first subdata in the first multi-dimensional three-view data with second subdata in the second multi-dimensional three-view data in a one-to-one correspondence manner to obtain three-view consistent scores corresponding to the subdata; and pairing the first user and the second user based on the three-view consistent score corresponding to each subdata. According to the method and the device, the multidimensional three-view data of the first user and the multidimensional three-view data of the second user are compared with each other, and the comprehensive comparison is carried out on the three-view data of the first user and the three-view data of the second user from multiple dimensions, multiple directions and multiple angles, so that the three-view data between the paired first user and the paired second user are highly similar, and the accuracy of marriage of love and marriage is improved.

Description

Marriage and love pairing method, device, system and medium based on multidimensional three-view data

Technical Field

The application relates to the field of marriage and love pairing, in particular to a method, a device, a system and a medium for marriage and love pairing based on multidimensional three-view data.

Background

Most of the current marriage and love pairing methods are manual pairing methods or positioning pairing methods. The manual pairing method is to manually evaluate the three views of each user, and then pair the users with similar three-view data according to the evaluation result, but in the process of manually evaluating the three views of the users, the subjectivity often affects the evaluation result. The positioning and pairing method is that after the user opens the application program, the user obtains the position information of the user, and then the user is paired with the opposite friends in the preset range of the position information, but the characters, interests and attitudes of the opposite friends paired by the positioning and pairing method are different. Therefore, the pairing accuracy of the conventional marriage and love pairing method is low.

Disclosure of Invention

The application mainly aims to provide a marriage and love pairing method, device, system and medium based on multidimensional three-dimensional data, and aims to improve the accuracy of marriage and love pairing.

In order to achieve the above object, the present application provides a marriage and love pairing method based on multidimensional tri-view data, which includes the following steps:

the method comprises the steps of obtaining first multi-dimensional three-view data of a first user and second multi-dimensional three-view data of a second user, wherein the first multi-dimensional three-view data and the second multi-dimensional three-view data comprise a plurality of subdata;

comparing first subdata in the first multi-dimensional three-view data with second subdata in the second multi-dimensional three-view data in a one-to-one correspondence manner to obtain three-view values corresponding to the subdata;

and pairing the first user and the second user based on the three-view consistent score corresponding to each piece of subdata.

Optionally, the sub-data includes interest sub-data, marital attitude sub-data, and to-be-processed attitude sub-data, and the step of comparing a first sub-data in the first multi-dimensional tri-view data with a second sub-data in the second multi-dimensional tri-view data in a one-to-one correspondence manner to obtain a tri-view value corresponding to each sub-data includes:

comparing first interest taste subdata, first marital attitude subdata and first to-be-processed attitude subdata in the first multi-dimensional three-view data with second interest taste subdata, second marital attitude subdata and second to-be-processed attitude subdata in the second multi-dimensional three-view data in a one-to-one correspondence manner to obtain the similarity degree of the corresponding subdata;

determining a three-view consistent score of the interest taste sub-data based on the similarity degree of the first interest taste sub-data and the second interest taste sub-data;

determining a three-view consistent score of the marital attitude subdata based on the similarity degree of the first marital attitude subdata and the second marital attitude subdata;

and determining the three-view consistent score of the sub-data of the phase to be processed based on the similarity degree of the first sub-data of the phase to be processed and the second sub-data of the phase to be processed.

Optionally, the sub-data includes sub-data to be personally attended, sub-data to be friends and sub-data to be children, and the step of comparing the first sub-data in the first multidimensional tri-view data with the second sub-data in the second multidimensional tri-view data in a one-to-one correspondence manner to obtain the tri-view value corresponding to each sub-data further includes:

comparing first to-be-parent attitude subdata, first to-be-friend attitude subdata and first to-be-child attitude subdata in the first multidimensional tri-view data with second to-be-parent attitude subdata, second to-be-friend attitude subdata and second to-be-child attitude subdata in the second multidimensional tri-view data in a one-to-one correspondence manner to obtain the similarity degree of the corresponding subdata;

determining a three-view consistency score of the sub-data to be personally attended based on the similarity degree of the first sub-data to be personally attended and the second sub-data to be personally attended;

determining a three-view consistency score of the to-be-friend attitude subdata based on the similarity degree of the first to-be-friend attitude subdata and the second to-be-friend attitude subdata;

and determining the three-view consistent score of the to-be-child attitude subdata based on the similarity degree of the first to-be-child attitude subdata and the second to-be-child attitude subdata.

Optionally, the sub-data includes sub-data of an attitude of a neighbor to be approached, sub-data of an attitude of a pet to be approached, and sub-data of an attitude of a money to be approached, and the step of comparing first sub-data in the first multidimensional tri-view data with second sub-data in the second multidimensional tri-view data in a one-to-one correspondence manner to obtain a tri-view value corresponding to each sub-data further includes:

comparing the first to-be-neighbor attitude subdata, the first to-be-pet attitude subdata and the first to-be-money attitude subdata in the first multi-dimensional three-view data with the second to-be-neighbor attitude subdata, the second to-be-pet attitude subdata and the second to-be-money attitude subdata in the second multi-dimensional three-view data in a one-to-one correspondence manner to obtain the similarity degree of the corresponding subdata;

determining a three-view consistent score of the to-be-neighbor attitude subdata based on the similarity degree of the first to-be-neighbor attitude subdata and the second to-be-neighbor attitude subdata;

determining a three-view consistent score of the to-be-pet attitude subdata based on the similarity degree of the first to-be-pet attitude subdata and the second to-be-pet attitude subdata;

and determining the three-view consistent score of the sub-data of the attitude to be paid money based on the similarity of the first sub-data of the attitude to be paid money and the second sub-data of the attitude to be paid money.

Optionally, the sub-data includes cause attitude sub-data, social attitude sub-data, and belief attitude sub-data, and the step of comparing the first sub-data in the first multidimensional tri-view data with the second sub-data in the second multidimensional tri-view data in a one-to-one correspondence manner to obtain the three-view values corresponding to each sub-data further includes:

comparing the first incident attitude subdata, the first social attitude subdata and the first belief attitude subdata in the first multi-dimensional three-view data with the second incident attitude subdata, the second social attitude subdata and the second belief attitude subdata in the second multi-dimensional three-view data in a one-to-one correspondence manner to obtain the similarity degree of the corresponding subdata;

determining a three-view consistent score of the business attitude subdata based on the similarity degree of the first business attitude subdata and the second business attitude subdata;

determining a three-view consistent score of the social attitude subdata based on the similarity degree of the first social attitude subdata and the second social attitude subdata;

and determining the three-view consistent score of the belief attitude subdata based on the similarity degree of the first belief attitude subdata and the second belief attitude subdata.

Optionally, the step of pairing the first user and the second user based on the three-view consistency score corresponding to each of the child data includes:

determining the three-observation consistent score of the interest and hobby subdata, the three-observation consistent score of the marital attitude subdata and the three-observation consistent score of the to-be-mutually-positioned attitude subdata as a first score;

determining the three-view consistent score of the to-be-personally-attitude subdata, the three-view consistent score of the to-be-friend-attitude subdata and the three-view consistent score of the to-be-child-attitude subdata as a second score;

determining the three-view consistent score of the to-be-neighbor attitude subdata, the three-view consistent score of the to-be-pet attitude subdata and the three-view consistent score of the to-be-monetary attitude subdata as a third score;

determining the three-view consistent score of the cause attitude subdata, the three-view consistent score of the social attitude subdata and the three-view consistent score of the belief attitude subdata as a fourth score;

adding the first score, the second score, the third score and the fourth score to obtain corresponding target three-view consistent scores;

and pairing the first user and the second user according to the target three-view consistent score and the preset character complementation degree.

Optionally, if the target three-view matching score is greater than or equal to a preset three-view matching score, the step of pairing the first user and the second user includes:

the step of pairing the first user and the second user according to the target three-view consistency score and the preset character complementation degree comprises the following steps of:

if the target three-view consistent score is larger than or equal to a preset three-view consistent score, calculating according to the target three-view consistent score and the preset character complementation degree, and then sequentially sorting according to a sequence from high to low;

and matching the corresponding second users with the first users in sequence from high to low.

Optionally, the step of obtaining the first multidimensional tri-view data of the first user and obtaining the second multidimensional tri-view data of the second user includes:

acquiring first questionnaire data filled by the first user, and acquiring first multidimensional three-view data corresponding to the first user based on the first questionnaire data;

and acquiring second questionnaire data filled in by the second user, and acquiring second multidimensional three-view data corresponding to the second user based on the second questionnaire data.

In addition, to achieve the above object, the present application further provides a marriage and love pairing device based on multidimensional tri-view data, including:

the system comprises an acquisition module, a storage module and a display module, wherein the acquisition module is used for acquiring first multi-dimensional three-view data of a first user and second multi-dimensional three-view data of a second user, and the first multi-dimensional three-view data and the second multi-dimensional three-view data comprise a plurality of subdata;

a comparison module, configured to compare first subdata in the first multi-dimensional three-view data with second subdata in the second multi-dimensional three-view data in a one-to-one correspondence manner, so as to obtain three-view values corresponding to the subdata;

and the pairing module is used for pairing the first user and the second user based on the three-view consistent score corresponding to each subdata.

In addition, to achieve the above object, the present application further provides a marriage and love pairing system, which includes a memory, a processor, and a marriage and love pairing program stored in the memory and running on the processor, wherein the marriage and love pairing program, when executed by the processor, implements the steps of the multi-dimensional three-view data-based marriage and love pairing method described above.

In addition, to achieve the above object, the present application further provides a medium having a love and marriage pairing program stored thereon, wherein the love and marriage pairing program, when executed by a processor, implements the steps of the love and marriage pairing method based on multidimensional three-dimensional data as described above.

In addition, to achieve the above object, the present application further provides a computer program product, which includes a computer program that, when being executed by the processor, implements the steps of the method for marriage and love pairing based on multidimensional three-dimensional data as described above.

The application provides a marriage and love pairing method, device, system and medium based on multidimensional three-view data, wherein a plurality of subdata are arranged in the first multidimensional three-view data and the second multidimensional three-view data by acquiring the first multidimensional three-view data of a first user and acquiring the second multidimensional three-view data of a second user; comparing first subdata in the first multi-dimensional three-view data with second subdata in the second multi-dimensional three-view data in a one-to-one correspondence manner to obtain three-view values corresponding to the subdata; and pairing the first user and the second user based on the three-view consistent score corresponding to each subdata. Therefore, the multidimensional three-view data of the first user and the multidimensional three-view data of the second user are compared with each other, and the three-view data of the first user and the three-view data of the second user are comprehensively compared from multiple dimensions, multiple directions and multiple angles, so that the three-view data between the paired first user and the paired second user are highly similar, and the marriage and love pairing accuracy is improved.

Drawings

FIG. 1 is a system diagram illustrating a hardware operating environment according to an embodiment of the present disclosure;

FIG. 2 is a schematic flow chart of a first embodiment of a marriage and love pairing method based on multidimensional tri-view data according to the application;

FIG. 3 is a detailed flowchart of step S10 of the first embodiment of the present application of a method for marriage and love pairing based on multidimensional tri-view data;

FIG. 4 is a schematic diagram illustrating interest and hobbies of a marriage and love pairing method based on multidimensional three-dimensional data according to the present application;

FIG. 5 is a schematic diagram illustrating marital attitude representation of a marriage pairing method based on multidimensional three-dimensional data according to the application;

FIG. 6 is a schematic diagram illustrating the attitude degree of love and marriage based on multidimensional three-dimensional data;

FIG. 7 is a schematic diagram illustrating the attitude of relatives in the marriage and love pairing method based on multidimensional three-dimensional data;

FIG. 8 is a schematic diagram illustrating friend attitudes in the method for marriage and love pairing based on multidimensional three-dimensional data according to the present application;

FIG. 9 is a schematic diagram illustrating the attitude of a child in the marriage and love pairing method based on multidimensional three-dimensional data;

FIG. 10 is a schematic diagram illustrating attitude representation of neighbors of the marriage and love pairing method based on multidimensional tri-view data;

FIG. 11 is a schematic diagram illustrating the attitude of pets in the marriage and love pairing method based on multidimensional three-dimensional data according to the present application;

FIG. 12 is a schematic diagram illustrating the attitude representation of money for a love and marriage method based on multidimensional three-dimensional data according to the present application;

FIG. 13 is a schematic diagram illustrating the cause attitude representation of the marriage and love pairing method based on multidimensional three-dimensional data;

FIG. 14 is a social attitude representation diagram of a marriage and love pairing method based on multidimensional three-dimensional data according to the application;

FIG. 15 is a schematic diagram illustrating belief attitudes of a love and marriage method based on multidimensional three-dimensional data according to the present application;

FIG. 16 is a flowchart illustrating a detailed process of step S20 in the first embodiment of the present invention of a marriage and love pairing method based on multidimensional tri-view data;

FIG. 17 is a flowchart illustrating a detailed process of step S20 in the first embodiment of the present invention of a marriage and love pairing method based on multidimensional tri-view data;

FIG. 18 is a flowchart illustrating a detailed process of step S20 in the first embodiment of the present invention of a marriage and love pairing method based on multidimensional tri-view data;

FIG. 19 is a flowchart illustrating a detailed process of step S20 in the first embodiment of the present invention of a marriage and love pairing method based on multidimensional tri-view data;

FIG. 20 is a flowchart illustrating a detailed process of step S30 in the first embodiment of the present invention of a marriage and love pairing method based on multidimensional tri-view data;

FIG. 21 is a schematic diagram illustrating detailed calculation of three-view consistent scores of the marriage and love matching method based on multidimensional three-view data according to the present application;

FIG. 22 is a detailed flowchart of the step S306 of the present invention of a love and marriage pairing method based on multidimensional three-dimensional data;

fig. 23 is a schematic functional block diagram of a preferred marriage and love pairing device based on multidimensional three-dimensional data according to the present application.

The implementation, functional features and advantages of the objectives of the present application will be further explained with reference to the accompanying drawings.

Detailed Description

It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.

The main solution of the embodiment of the application is as follows: the method comprises the steps of obtaining first multi-dimensional three-view data of a first user and second multi-dimensional three-view data of a second user, wherein the first multi-dimensional three-view data and the second multi-dimensional three-view data comprise a plurality of subdata; comparing first subdata in the first multi-dimensional three-view data with second subdata in the second multi-dimensional three-view data in a one-to-one correspondence manner to obtain three-view values corresponding to the subdata; and pairing the first user and the second user based on the three-view consistent score corresponding to each subdata. According to the method and the device, the multidimensional three-view data of the first user and the multidimensional three-view data of the second user are compared with each other, and the comprehensive comparison is carried out on the three-view data of the first user and the three-view data of the second user from multiple dimensions, multiple directions and multiple angles, so that the three-view data between the paired first user and the paired second user are highly similar, and the accuracy of marriage of love and marriage is improved.

Specifically, referring to fig. 1, fig. 1 is a schematic system structure diagram of a hardware operating environment according to an embodiment of the present application.

As shown in fig. 1, the system may be a server or a mobile terminal with data processing, and the system may include: a processor 1001, such as a CPU (Central Processing Unit), a memory 1005, a user interface 1003, a network interface 1004, and a communication bus 1002. A communication bus 1002 is used to enable connection communications between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a keyboard (board), and the user interface 1003 may optionally include a standard wired interface (e.g., a USB (Universal Serial Bus) interface), and a wireless interface (e.g., a bluetooth interface). The network interface 1004 may include a standard wired interface, a Wireless interface (e.g., a WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001. Optionally, the system may further include RF (Radio Frequency) circuitry, sensors, WiFi modules, and the like.

Those skilled in the art will appreciate that the system architecture shown in FIG. 1 is not intended to be limiting of the system, and may include more or fewer components than those shown, or some components may be combined, or an arrangement of different components may be used.

As shown in fig. 1, a memory 1005 serving as a medium (it should be noted that the medium in the embodiment of the present application is a computer-readable storage medium) may include an operating system, a network communication module, a user interface module, and a marriage and love pairing program. The operating system is a program for managing and controlling system hardware and software resources, and supports the operation of a marriage partner program and other software or programs.

In the system shown in fig. 1, the network interface 1004 is mainly used for connecting to a backend server and communicating with the backend server; the user interface 1003 is mainly used for connecting a user terminal and performing data communication with the user terminal; among other things, the processor 1001 may be configured to call a marriage partner program stored in the memory 1005, and perform the following operations:

Further, the processor 1001 may call the marriage partner pairing program stored in the memory 1005, and also perform the following operations:

The application provides a marriage and love pairing method based on multidimensional tri-view data, and referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of the marriage and love pairing method based on multidimensional tri-view data.

The embodiments of the present application provide embodiments of a marriage and love pairing method based on multidimensional tri-view data, and it should be noted that although a logical order is shown in the flowcharts, under some data, the steps shown or described may be performed in an order different from that here.

The method of the embodiment of the present application is exemplified by taking a marriage and love pairing system as an execution subject. The marriage and love pairing method based on the multidimensional three-dimensional data comprises the following steps:

step S10, obtaining a first multi-dimensional three-view data of a first user and obtaining a second multi-dimensional three-view data of a second user, where the first multi-dimensional three-view data and the second multi-dimensional three-view data include a plurality of subdata.

It should be noted that the third view in the embodiment of the present application is not a life view, a value view, and a world view, and the third view in the embodiment of the present application refers to an interest, a marital attitude, a waiting-to-meet attitude, a waiting-to-relatives attitude, a waiting-to-friends attitude, a waiting-to-children attitude, a waiting-to-neighbors attitude, a waiting-to-pets attitude, a waiting-to-money attitude, a cause attitude, a social attitude, and a belief.

Further, when the marriage and love pairing system detects that the user logs in the preset marriage and love application program and determines that the user is a new registered user of the preset marriage and love application program, the questionnaire data to be filled in needs to be sent to the user terminal corresponding to the user. After receiving a completion instruction sent by a user terminal, detecting whether the required item in the questionnaire data to be filled in is completely filled in, and if detecting that the required item in the questionnaire data to be filled in is not completely filled in, prompting the user to supplement by the marriage and love pairing system. If it is detected that all the required items in the questionnaire data to be filled are filled, the marriage and love pairing system acquires the user account information of the user, binds the user account information with the questionnaire data filled by the user, and stores the bound questionnaire data into a database, wherein the user account information is unique, that is, the user account information of each user cannot be repeated. Further, the user may not fill in the questionnaire data to be filled in sent by the marriage and love pairing system, but after the pairing instruction is triggered, the marriage and love pairing system returns an error prompt message, that is, only when the user completes the questionnaire data to be filled in sent by the marriage and love pairing system, the marriage and love pairing system will respond to the pairing instruction for pairing.

After detecting that a user opens a preset marriage application program, the marriage and love pairing system automatically acquires the three-view data corresponding to the user according to the account information of the user. Certainly, the marriage and love pairing system may also obtain the three-view data corresponding to the user according to the account information of the user after detecting the pairing instruction triggered by the user, which is not limited herein. For better understanding, the present embodiment is illustrated with the user manually triggering the pairing instruction. Specifically, after detecting that a pairing instruction is triggered by a user in a preset marriage application program, a marriage and love pairing system acquires first multi-dimensional three-view data of the user, wherein the multi-dimensional three-view data is three-view data composed of a plurality of three-view sub-data, and the user triggering the pairing instruction is the first user. Then, the marriage and love pairing system acquires second multidimensional three-dimensional data of other users in the database, wherein the other users are the second users, namely the second users refer to a plurality of users, but not refer to a certain user.

Step S20, comparing the first subdata in the first multi-dimensional three-view data with the second subdata in the second multi-dimensional three-view data in a one-to-one correspondence manner, to obtain three-view values corresponding to the subdata.

After determining first multi-dimensional three-view data of a first user and second multi-dimensional three-view data of a second user, the marriage and love pairing system compares all first subdata in the first multi-dimensional three-view data with all second subdata in the second multi-dimensional three-view data in a one-to-one correspondence manner to obtain a three-view score corresponding to each three-view subdata in the multi-dimensional three-view data.

Step S30, pairing the first user and the second user based on the three-view consistent score corresponding to each of the child data.

And after the marriage and love pairing system obtains the three-view consistent score corresponding to each three-view child data in the multi-dimensional three-view data, all the three-view consistent scores corresponding to each three-view child data are added to obtain the final three-view consistent score of the multi-dimensional three-view data. And then, the marriage and love pairing system compares the final three-aspect consistent score with a preset value in the marriage and love pairing system, and pairs the first user and the second user according to a comparison result.

In this embodiment, a first multi-dimensional three-view data of a first user is obtained, and a second multi-dimensional three-view data of a second user is obtained, where the first multi-dimensional three-view data and the second multi-dimensional three-view data include a plurality of subdata; comparing first subdata in the first multi-dimensional three-view data with second subdata in the second multi-dimensional three-view data in a one-to-one correspondence manner to obtain three-view values corresponding to the subdata; and pairing the first user and the second user based on the three-view values corresponding to the sub-data. Therefore, in the embodiment, the multidimensional three-view data of the first user and the multidimensional three-view data of the second user are compared with each other, and the three-view data of the first user and the three-view data of the second user are comprehensively compared from multiple dimensions, multiple directions and multiple angles, so that the three-view data of the first user and the third user are highly similar, and the marriage and love pairing accuracy is improved.

Further, referring to fig. 3, fig. 3 is a detailed flowchart of step S10 of the first embodiment of the present invention, which is a marriage and love pairing method based on multidimensional tri-view data. The step S10 includes:

step S101, acquiring first questionnaire data filled by the first user, and acquiring first multidimensional three-view data corresponding to the first user based on the first questionnaire data;

step S102, obtaining second questionnaire data filled by the second user, and obtaining second multidimensional three-dimensional data corresponding to the second user based on the second questionnaire data.

Specifically, the marriage and love pairing system determines first user account information of a first user, acquires first questionnaire data filled in by the first user from a database according to the first user account information, and then performs data analysis on the first questionnaire data to determine each piece of three-watch sub-data in the first questionnaire data. And then all the three-dimensional sub-viewing data are combined to obtain first multi-dimensional three-dimensional data corresponding to the first user. Similarly, the marriage and love pairing system determines second user account information of the second user, acquires second questionnaire data filled in by the second user in the database according to the second user account information, and then performs data analysis on the second questionnaire data to determine each piece of three-watch sub-data in the second questionnaire data. And then all the three-dimensional sub-viewing data are combined to obtain second multi-dimensional three-dimensional data corresponding to the second user.

It should be noted that the first questionnaire data and the second questionnaire data are one form of a three-view data questionnaire library, and for convenience of understanding of the embodiments of the present application, some questions (not all questions) in the three-view data questionnaire library are listed in a table form, as shown in fig. 4 to fig. 15. FIG. 4 is a schematic diagram illustrating interest and hobbies of a marriage and love pairing method based on multidimensional three-dimensional data according to the present application; FIG. 5 is a schematic diagram illustrating marital attitude representation of a marriage pairing method based on multidimensional three-dimensional data according to the application; FIG. 6 is a schematic diagram illustrating the attitude degree of love and marriage based on multidimensional three-dimensional data; FIG. 7 is a schematic diagram illustrating the attitude of relatives in the marriage and love pairing method based on multidimensional three-dimensional data; FIG. 8 is a schematic diagram illustrating friend attitudes in the method for marriage and love pairing based on multidimensional three-dimensional data according to the present application; FIG. 9 is a schematic diagram illustrating the attitude of a child in the marriage and love pairing method based on multidimensional three-dimensional data; FIG. 10 is a schematic diagram illustrating attitude representation of neighbors of the marriage and love pairing method based on multidimensional tri-view data; FIG. 11 is a schematic diagram illustrating the attitude of pets in the marriage and love pairing method based on multidimensional three-dimensional data according to the present application; FIG. 12 is a schematic diagram illustrating the attitude representation of money for a love and marriage method based on multidimensional three-dimensional data according to the present application; FIG. 13 is a schematic diagram illustrating the cause attitude representation of the marriage and love pairing method based on multidimensional three-dimensional data; FIG. 14 is a social attitude representation diagram of a marriage and love pairing method based on multidimensional three-dimensional data according to the application; fig. 15 is a schematic diagram illustrating belief attitudes of a love and marriage method based on multidimensional three-dimensional data according to the present application.

In this embodiment, first multi-dimensional three-view data corresponding to the first user is obtained based on first questionnaire data obtained by the first user; and acquiring second questionnaire data filled in by the second user, and acquiring second multidimensional three-view data corresponding to the second user based on the second questionnaire data. Therefore, in the embodiment, the question bank performs multi-dimensional evaluation on the three-view data of the user in the form of a questionnaire, so that the accuracy of the three-view data of the user is improved.

Further, referring to fig. 16, fig. 16 is a detailed flowchart of step S20 of the first embodiment of the present invention, which is a marriage and love pairing method based on multidimensional tri-view data. The step S20 includes:

step S201, comparing first interest taste subdata, first marital attitude subdata and first to-be-processed attitude subdata in the first multidimensional three-view data with second interest taste subdata, second marital attitude subdata and second to-be-processed attitude subdata in the second multidimensional three-view data in a one-to-one correspondence manner to obtain the similarity degree of the corresponding subdata;

step S202, determining a three-view consistent score of the interest taste sub-data based on the similarity degree of the first interest taste sub-data and the second interest taste sub-data;

step S203, determining a three-view consistent score of the marital attitude subdata based on the similarity degree of the first marital attitude subdata and the second marital attitude subdata;

step S204, determining a three-view consistent score of the phase-to-be-processed attitude subdata based on the similarity of the first phase-to-be-processed attitude subdata and the second phase-to-be-processed attitude subdata.

Specifically, the subdata in the multidimensional tri-view data includes interest subdata, marital attitude subdata, and to-be-processed attitude subdata. Therefore, the first multidimensional tri-view data comprises first interest sub-data, first marital attitude sub-data and first to-be-processed attitude sub-data, and the second multidimensional tri-view data comprises second interest sub-data, second marital attitude sub-data and second to-be-processed attitude sub-data. It should be noted that each sub-data has a corresponding set score, and the set score may be 10 scores or 100 scores, which is not limited in this embodiment.

The marriage and love pairing system compares the first interest and preference sub-data with the second interest and preference sub-data, then determines the similarity degree of the first interest and preference sub-data and the second interest and preference sub-data according to the interest and preference concepts in the first interest and preference sub-data and the second interest and preference sub-data, and then determines the three-view value of the interest and preference sub-data according to the similarity degree of the interest and preference. Meanwhile, the marriage pairing system compares the first marriage attitude subdata with the second marriage attitude subdata, then determines the similarity degree of the first marriage attitude subdata and the second marriage attitude subdata according to the marriage attitude concepts in the first marriage attitude subdata and the second marriage attitude subdata, and then determines the three-aspect consistent score of the marriage attitude subdata according to the similarity degree of the marriage attitudes. Meanwhile, the marriage and love pairing system compares the first phase position subdata with the second phase position subdata, then determines the similarity degree of the first phase position subdata and the second phase position subdata according to the phase position concept in the first phase position subdata and the second phase position subdata, and then determines the three-aspect value of the phase position subdata according to the similarity degree of the phase position subdata.

In this embodiment, for example, the set score of each piece of sub-data is 10, the first interest sub-data is "sports, reading, traveling, movie and gourmet", the second interest sub-data is "sports, quadratic element, game, movie and gourmet", the same number of keywords in the first interest sub-data and the second interest sub-data is 3, and the three-view coincidence score of the interest sub-data obtained by the love pairing system is 6.

It should be noted that, in another possible embodiment, the marriage and love pairing system may further determine that the three-view consensus score is a full score when the first interest taste sub-data and the second interest taste sub-data are all consistent, and otherwise, determine that the three-view consensus score is a zero score.

In this embodiment, the similarity degree of corresponding sub-data is obtained by comparing first interest sub-data, first marital attitude sub-data and first to-be-processed attitude sub-data in first multidimensional tri-view data with second interest sub-data, second marital attitude sub-data and second to-be-processed attitude sub-data in second multidimensional tri-view data in a one-to-one correspondence manner; determining a three-view value of the interest taste sub-data based on the similarity degree of the first interest taste sub-data and the second interest taste sub-data; determining the three-point score of the marital attitude subdata based on the similarity degree of the first marital attitude subdata and the second marital attitude subdata; and determining the three-observation value of the sub-data of the phase to be processed based on the similarity degree of the sub-data of the first phase to be processed and the sub-data of the second phase to be processed. Therefore, according to the embodiment, the pairing relationship among the users is determined according to the three-view scores corresponding to the interest and preference sub-data, the marital attitude sub-data and the to-be-associated attitude sub-data, so that the interest and preference, the marital attitude and the to-be-associated attitude data of the paired users are highly similar, and the healthy, long-term and stable marital and love relationship can be maintained.

Further, referring to fig. 17, fig. 17 is a schematic flowchart illustrating a detailed process of step S20 in the first embodiment of the present invention, based on multidimensional three-dimensional data, of the marriage and love pairing method. The step S20 further includes:

step S205, comparing the first to-be-parent attitude subdata, the first to-be-friend attitude subdata and the first to-be-child attitude subdata in the first multidimensional tri-view data with the second to-be-parent attitude subdata, the second to-be-friend attitude subdata and the second to-be-child attitude subdata in the second multidimensional tri-view data in a one-to-one correspondence manner, and obtaining the similarity degree of the corresponding subdata;

step S206, determining a three-view consistent score of the sub-data to be personally attended based on the similarity degree of the first sub-data to be personally attended and the second sub-data to be personally attended;

step S207, determining a three-view consistency score of the to-be-friend attitude subdata based on the similarity degree of the first to-be-friend attitude subdata and the second to-be-friend attitude subdata;

step S208, determining the three-view consistent score of the to-be-son-girl-status sub-data based on the similarity of the first to-be-son-girl-status sub-data and the second to-be-son-girl-status sub-data.

Specifically, the subdata in the multidimensional three-view data includes the subdata of the to-be-personally-viewed attitude, the subdata of the to-be-friend attitude and the subdata of the to-be-child attitude. Therefore, the first multidimensional tri-view data comprises first to-be-parent attitude subdata, first to-be-friend attitude subdata and first to-be-child attitude subdata, and the second multidimensional tri-view data comprises second to-be-parent attitude subdata, second to-be-friend attitude subdata and second to-be-child attitude subdata.

The marriage and love pairing system compares the first to-be-parent attitude subdata with the second to-be-parent attitude subdata, then determines the similarity of the first to-be-parent attitude subdata and the second to-be-parent attitude subdata according to the to-be-parent attitude concepts in the first to-be-parent attitude subdata and the second to-be-parent attitude subdata, and then determines the three-aspect score of the to-be-parent attitude subdata according to the similarity of the to-be-parent attitudes. Wherein the triscopic value is a numerical value representing the triscopic. Meanwhile, the marriage and love pairing system compares the first to-be-friend attitude subdata with the second to-be-friend attitude subdata, then determines the similarity degree of the first to-be-friend attitude subdata and the second to-be-friend attitude subdata according to the to-be-friend attitude concepts in the first to-be-friend attitude subdata and the second to-be-friend attitude subdata, and then determines the three-aspect value of the to-be-friend attitude subdata according to the similarity degree of the to-be-friend attitude subdata. Meanwhile, the love pairing system compares the first to-be-son-girl attitude sub-data with the second to-be-son-girl attitude sub-data, then determines the similarity degree of the first to-be-son-girl attitude sub-data and the second to-be-son-girl attitude sub-data according to-be-son-girl attitude concepts in the first to-be-son-girl attitude sub-data and the second to-be-girl attitude sub-data, and then determines the three-aspect value of the to-be-son-girl attitude sub-data according to the similarity degree of the to-be-girl attitude.

In the embodiment, the similarity degree of corresponding subdata is obtained by comparing first to-be-parent attitude subdata, first to-be-friend attitude subdata and first to-be-child attitude subdata in first multidimensional tri-view data with second to-be-parent attitude subdata, second to-be-friend attitude subdata and second to-be-child attitude subdata in second multidimensional tri-view data in a one-to-one correspondence manner; determining the three-observation value of the subdata to be personally attended based on the similarity degree of the first subdata to be personally attended and the second subdata to be personally attended; determining the three-view value of the sub-data to be friend attitude based on the similarity degree of the first sub-data to be friend attitude and the second sub-data to be friend attitude; and determining the three-viewpoint value of the sub-data to be sub-gird status based on the similarity degree of the first sub-girl status sub-data and the second sub-girl status sub-data. Therefore, in the embodiment, the pairing relationship among the users is determined by the three-view values corresponding to the data of the to-be-personally-attitude subdata, the data of the to-be-friend-attitude subdata and the data of the to-be-child-attitude subdata, so that the three-view data of the to-be-personally-attitude, the to-be-friend-attitude and the data of the to-be-child-attitude are highly similar, and thus, a healthy, long-term and stable love relationship can be maintained.

Further, referring to fig. 18, fig. 18 is a schematic flowchart of step S20 of the first embodiment of the present invention, which is a marriage and love pairing method based on multidimensional tri-view data. The step S20 further includes:

step S209, comparing the first to-be-neighbor attitude subdata, the first to-be-pet attitude subdata and the first to-be-money attitude subdata in the first multidimensional tri-view data with the second to-be-neighbor attitude subdata, the second to-be-pet attitude subdata and the second to-be-money attitude subdata in the second multidimensional tri-view data in a one-to-one correspondence manner, and obtaining the similarity degree of the corresponding subdata;

step S210, determining a three-view consistent score of the to-be-neighbor attitude subdata based on the similarity degree of the first to-be-neighbor attitude subdata and the second to-be-neighbor attitude subdata;

step S211, determining a three-view consistent score of the to-be-pet attitude subdata based on the similarity degree of the first to-be-pet attitude subdata and the second to-be-pet attitude subdata;

step S212, determining a three-view consistent score of the sub-data of the to-be-paid money attitude based on the similarity of the first sub-data of the to-be-paid money attitude and the second sub-data of the to-be-paid money attitude.

Specifically, the subdata in the multidimensional tri-view data includes the subdata of the attitude of the to-be-neighbor, the subdata of the attitude of the to-be-pet and the subdata of the attitude of the to-be-money. Therefore, the first multidimensional tri-view data comprises the first to-be-neighbor attitude subdata, the first to-be-pet attitude subdata and the first to-be-monetary attitude subdata, and the second multidimensional tri-view data comprises the second to-be-neighbor attitude subdata, the second to-be-pet attitude subdata and the second to-be-monetary attitude subdata.

The marriage and love pairing system compares the first to-be-neighbor attitude subdata with the second to-be-neighbor attitude subdata, then determines the similarity degree of the first to-be-neighbor attitude subdata and the second to-be-neighbor attitude subdata according to the to-be-neighbor attitude concepts in the first to-be-neighbor attitude subdata and the second to-be-neighbor attitude subdata, and then determines the three-view score of the to-be-neighbor attitude subdata according to the similarity degree of the to-be-neighbor attitude. Meanwhile, the marriage and love pairing system compares the first to-be-pet attitude subdata with the second to-be-pet attitude subdata, then determines the similarity degree of the first to-be-pet attitude subdata and the second to-be-pet attitude subdata according to the to-be-pet attitude concepts in the first to-be-pet attitude subdata and the second to-be-pet attitude subdata, and then determines the three-observation value of the to-be-pet attitude subdata according to the similarity degree of the to-be-pet attitude. Meanwhile, the love pairing system compares the first money attitude subdata with the second money attitude subdata, then determines the similarity of the first money attitude subdata and the second money attitude subdata according to the money attitude concepts in the first money attitude subdata and the second money attitude subdata, and then determines the three-observation value of the money attitude subdata according to the similarity of the money attitude.

In the embodiment, the similarity degree of the corresponding subdata is obtained by comparing the first to-be-neighbor attitude subdata, the first to-be-pet attitude subdata and the first to-be-money attitude subdata in the first multi-dimensional three-view data with the second to-be-neighbor attitude subdata, the second to-be-pet attitude subdata and the second to-be-money attitude subdata in the second multi-dimensional three-view data in a one-to-one correspondence manner; determining a three-view value of the subdata of the to-be-neighbor attitude based on the similarity degree of the first to-be-neighbor attitude subdata and the second to-be-neighbor attitude subdata; determining a three-observation value of the to-be-pet attitude subdata based on the similarity degree of the first to-be-pet attitude subdata and the second to-be-pet attitude subdata; and determining the three-view value of the sub-data of the attitude to be paid based on the similarity of the first sub-data of the attitude to be paid and the second sub-data of the attitude to be paid. Therefore, in the embodiment, the pairing relationship among the users is determined according to the three-view consistent scores corresponding to the to-be-neighbor attitude subdata, the to-be-pet attitude subdata and the to-be-monetary attitude subdata, so that the three-view data of the to-be-neighbor attitude, the to-be-pet attitude and the to-be-monetary attitude are highly similar, and the healthy, long-term and stable love and marriage relationship can be maintained.

Further, referring to fig. 19, fig. 19 is a detailed flowchart of step S20 of the first embodiment of the present invention, which is a marriage and love pairing method based on multidimensional tri-view data. The step S20 further includes:

step S213, comparing the first incident attitude subdata, the first social attitude subdata and the first belief attitude subdata in the first multidimensional three-view data with the second incident attitude subdata, the second social attitude subdata and the second belief attitude subdata in the second multidimensional three-view data in a one-to-one correspondence manner to obtain the similarity degree of the corresponding subdata;

step S214, determining the three-view consistent score of the business attitude subdata based on the similarity degree of the first business attitude subdata and the second business attitude subdata;

step S215, determining the three-view consistent score of the social attitude subdata based on the similarity degree of the first social attitude subdata and the second social attitude subdata;

step S216, determining the three-view consistent score of the belief attitude subdata based on the similarity degree of the first belief attitude subdata and the second belief attitude subdata.

Specifically, the subdata in the multidimensional tri-view data includes cause attitude subdata, social attitude subdata and belief attitude subdata. Therefore, the first multi-dimensional three-view data includes the first incident attitude subdata, the first social attitude subdata and the first belief attitude subdata, and the second multi-dimensional three-view data includes the first incident attitude subdata, the first social attitude subdata and the first belief attitude subdata.

The marriage and love pairing system compares the first to-be-relatives attitude subdata with the second to-be-relatives attitude subdata, then determines the similarity degree of the first business attitude subdata and the second business attitude subdata according to the business attitude concepts in the first business attitude subdata and the second business attitude subdata, and then determines the three-aspect consistent score of the business attitude subdata according to the similarity degree of the business attitude. Meanwhile, the marriage and love pairing system compares the first social attitude subdata with the second social attitude subdata, then determines the similarity degree of the first social attitude subdata and the second social attitude subdata according to social attitude concepts in the first social attitude subdata and the second social attitude subdata, and then determines the three-aspect score of the social attitude subdata according to the similarity degree of the social attitudes. Meanwhile, the marriage and love pairing system compares the first belief attitude subdata with the second belief attitude subdata, then determines the similarity degree of the first belief attitude subdata and the second belief attitude subdata according to belief attitude concepts in the first belief attitude subdata and the second belief attitude subdata, and then determines the three-view score of the belief attitude subdata according to the similarity degree of the belief attitude.

In the embodiment, the similarity degree of the corresponding subdata is obtained by correspondingly comparing the first business attitude subdata, the first social attitude subdata and the first belief attitude subdata in the first multidimensional three-view data with the second business attitude subdata, the second social attitude subdata and the second belief attitude subdata in the second multidimensional three-view data one by one; determining the three-aspect value of the business attitude subdata based on the similarity degree of the first business attitude subdata and the second business attitude subdata; determining the three-observation value of the social attitude subdata based on the similarity degree of the first social attitude subdata and the second social attitude subdata; and determining the three-view score of the belief attitude subdata based on the similarity of the first belief attitude subdata and the second belief attitude subdata. Therefore, the pairing relationship among the users is determined according to the three-view consistent scores corresponding to the cause attitude subdata, the social attitude subdata and the belief attitude subdata, so that the three-view data of the cause attitude, the social attitude and the belief attitude are highly similar after pairing, and the healthy, long-term and stable love and marriage relationship can be maintained.

Further, referring to fig. 20, fig. 20 is a detailed flowchart of step S30 of the first embodiment of the present invention, which is a marriage and love pairing method based on multidimensional tri-view data. The step S30 includes:

step S301, determining the three-view consistent score of the interest and hobby subdata, the three-view consistent score of the marital attitude subdata and the three-view consistent score of the to-be-processed attitude subdata as first scores;

step S302, determining the three-view consistent score of the to-be-personally-assigned attitude subdata, the three-view consistent score of the to-be-friend-attitude subdata and the three-view consistent score of the to-be-child-attitude subdata as second scores;

step S303, determining the three-view consistent score of the to-be-neighbor attitude subdata, the three-view consistent score of the to-be-pet attitude subdata and the three-view consistent score of the to-be-monetary attitude subdata as third scores;

step S304, determining the three-view consistent score of the cause attitude subdata, the three-view consistent score of the social attitude subdata and the three-view consistent score of the belief attitude subdata as a fourth score;

step S305, adding the first score, the second score, the third score and the fourth score to obtain corresponding target three-view consistent scores;

step S306, pairing the first user and the second user according to the target three-view consistent score and the preset character complementation degree.

Specifically, after determining the three-view consistent scores corresponding to the sub-data, the love pairing system adds the three-view consistent scores of the interest and preference sub-data, the three-view consistent scores of the marital attitude sub-data and the three-view consistent scores of the to-be-liked attitude sub-data, determines the obtained calculated value as a first score, adds the three-view consistent scores of the to-be-personally-attitude sub-data, the three-view consistent scores of the to-be-friend attitude sub-data and the three-view consistent scores of the to-be-child attitude sub-data, determines the obtained calculated value as a second score, adds the three-view consistent scores of the to-be-neighboring attitude sub-data, the three-view consistent scores of the to-be-personally-attitude sub-data and the three-view consistent scores of the to-be-child attitude sub-data, determines the obtained calculated value as a third score, and adds the three-view consistent scores of the career attitude sub-data, the social attitude sub-data and the three-view consistent scores of the to-attitude sub-attitude data, the resulting calculation is determined as the fourth score. Then, the marriage and love pairing system adds the first score, the second score, the third score and the fourth score to obtain a corresponding calculated value, the calculated value is that the first user and the second user compare through the multi-dimensional three-view data to obtain a target three-view consistent score, and the target three-view consistent score is used for determining the similarity degree of the three-view data of the first user and the second user. It can be further understood that the higher the objective three-view consistency score is, the higher the similarity degree of the three-view data of the first user and the second user is, and the higher the matching probability of the first user and the second user is. Therefore, the marriage and love pairing system needs to further compare the target three-view consistent score with the preset three-view consistent score, and if the target three-view consistent score is determined to be greater than or equal to the preset three-view consistent score, the marriage and love pairing system determines that the first user and the second user meet the pairing conditions, pairs the first user and the second user, that is, recommends the first user to the second user, and recommends the second user to the first user. And if the target three-aspect consistent score is smaller than the preset three-aspect consistent score, the marriage and love pairing system determines that the first user and the second user do not accord with the pairing conditions, and the pairing process is not executed. The preset three-view consistent score is set by a technician, and the embodiment is not limited.

It should be noted that, in this embodiment, in addition to obtaining the target three-view uniform score by summing all the first score, the second score, the third score, and the fourth score, any one of the first score, the second score, the third score, and the fourth score may be used as the target three-view uniform score. Meanwhile, any two values of the first value, the second value, the third value and the fourth value can be added and summed to obtain the target three-view consistent value. And adding and summing any three values of the first value, the second value, the third value and the fourth value to obtain the target three-view consistent value.

Fig. 21 is a schematic diagram illustrating detailed calculation of three-view consistent scores of the dating and dating method based on multidimensional three-view data according to the present application, and in fig. 21, for simplicity, three views 1, 2,. are used to show interests, marital attitudes, and waiting attitudes; representing options in interest, marital attitude, and to-be-processed attitude with sub-data 1 and sub-data 2 (as shown in fig. 4-15); user 1 represents a first user and user 2 represents a second user. Specifically, the three views of the user 1 and the user 2 are respectively three views 1, three views 2, and. The calculation process for the three-view 1 is as follows: comparing the subdata 1 of the user 1 with the subdata 1 of the user 2 to obtain a comparison score A1 of the subdata 1 of the user 1 and the subdata 1 of the user 2, then comparing the subdata 2 of the user 1 with the subdata 2 of the user 2 to obtain a comparison score B1 of the subdata 2 of the user 1 and the user 2, and until the comparison scores of all the subdata in the three-view 1 are obtained, and finally obtaining the score of the three-view 1 as A1 a% + B1 a%. The calculation process of the third view 2 is as follows: comparing the subdata 1 of the user 1 with the subdata 1 of the user 2 to obtain a comparison score A2 of the subdata 1 of the user 1 and the subdata 1 of the user 2, then comparing the subdata 2 of the user 1 with the subdata 2 of the user 2 to obtain a comparison score B2 of the subdata 2 of the user 1 and the user 2, until obtaining comparison scores of all the subdata in the three views 2, and finally obtaining the score of the three views 2 as A2B% + B2B%. Similarly, the calculation process of other three-view data is the same. The three-dimensional consensus score obtained by the final calculation is a1 a% + B1 a% + a 2B% + B2B% +, which may also be expressed as (a1+ B1 +). a% + (a2+ B2+. B% +.

Determining the three-observation consistent score of the interest and hobby subdata, the three-observation consistent score of the marital attitude subdata and the three-observation consistent score of the to-be-mutually-positioned attitude subdata as a first score; determining the three-view consistent score of the to-be-personally-attitude subdata, the three-view consistent score of the to-be-friend-attitude subdata and the three-view consistent score of the to-be-child-attitude subdata as a second score; determining the three-view consistent score of the to-be-neighbor attitude subdata, the three-view consistent score of the to-be-pet attitude subdata and the three-view consistent score of the to-be-monetary attitude subdata as a third score; determining the three-view consistent score of the cause attitude subdata, the three-view consistent score of the social attitude subdata and the three-view consistent score of the belief attitude subdata as a fourth score; adding the first score, the second score, the third score and the fourth score to obtain corresponding target three-view consistent scores; and pairing the first user and the second user according to the target three-view consistent score and the preset character complementation degree. Therefore, in the embodiment, by calculating the three-view consistent score of each subdata and comparing the obtained target three-view consistent score with the preset three-view consistent score, whether the first user and the second user are paired is determined, multiple pairing verification is set, high similarity of the three-view data among the users is guaranteed, and the pairing accuracy is improved while a healthy, long-term and stable marriage relationship among the paired users can be maintained.

Further, referring to fig. 22, fig. 22 is a detailed flowchart of step S306 of the marriage and love pairing method based on multidimensional three-dimensional data according to the present application. The step S306 includes:

step S3061, if the target three-view consistent score is larger than or equal to a preset three-view consistent score, calculating the target three-view consistent score and the preset character complementation degree, and then sequentially sorting the target three-view consistent score and the preset character complementation degree from high to low;

step S3062, matching the corresponding second users with the first user in sequence from high to low.

Specifically, if the target three-aspect consistent score is greater than or equal to the preset three-aspect consistent score, the marriage and love pairing system sorts all the target three-aspect consistent scores in sequence from high to low according to the scores. And then, the marriage and love pairing system sequentially matches the second users corresponding to the sorted target three-aspect consistent scores with the first users according to the order of the scores from high to low.

In this embodiment, for example, the target three-view coincidence scores include 8.5, 8.3, 8.7, 8.2, and 9.2, the preset three-view coincidence score is 8.0, and the preset character complementation degree is also 8.0, then the marriage and love pairing system calculates the corresponding scores of 8.5, 8.3, 8.7, 8.0, and 9.2 according to the formula "preset character complementation degree M% + target three-view coincidence score N%" (where M and N are set by a technician independently based on different actual applications, but not limited in this embodiment), and then sorts the scores in order from high to low, and finally, matches the scores sorted from high to low with the corresponding second user a, second user B, second user C, second user D, and second user E in order from the first user a.

In this embodiment, if the target three-view consistent score is greater than or equal to the preset three-view consistent score, the scores obtained by calculating the complementary degree of the target three-view consistent score and the preset characters are sequentially sorted from high to low; and matching the second users corresponding to the sorted scores with the first users in sequence from high scores to low scores. Therefore, the first user and the second user are sequentially matched according to the preset score of the three-view consistent score, so that the matching degree between the first user and the second user is higher, the matching accuracy is improved, and the paired users can maintain healthy, long-term and stable marriage and love relationships.

Further, another embodiment is provided in the present application, specifically, the marriage and love pairing system obtains first multidimensional three-view data of a first user, performs data analysis on the first multidimensional three-view data, determines each piece of first subdata in the first multidimensional three-view data, determines, according to each piece of first subdata, a second user corresponding to second subdata highly similar to each piece of first subdata in a database, and recommends the second user to the first user. In this embodiment, for example, the first multidimensional tri-view data of the first user is "cause strong, social responsibility strong, self-esteem strong", the marriage and love pairing system searches the second multidimensional tri-view data in the database as the second user of "cause strong, social responsibility strong, self-esteem strong" according to the first multidimensional tri-view data, and recommends all the second users to the first user.

Referring to fig. 23, fig. 23 is a schematic functional block diagram of a preferred love and marriage pairing device based on multidimensional three-dimensional data according to the present application. The marriage and love pairing device based on the multidimensional three-dimensional data comprises:

an obtaining module 10, configured to obtain first multidimensional tri-view data of a first user and obtain second multidimensional tri-view data of a second user, where the first multidimensional tri-view data and the second multidimensional tri-view data include a plurality of sub-data;

a comparison module 20, configured to compare first subdata in the first multi-dimensional three-view data with second subdata in the second multi-dimensional three-view data in a one-to-one correspondence manner, so as to obtain three-view values corresponding to the subdata;

a pairing module 30, configured to pair the first user and the second user based on the three-view consistent score corresponding to each piece of the child data.

The specific implementation of the marriage and love pairing device based on the multidimensional tri-view data is basically the same as that of each embodiment of the marriage and love pairing method based on the multidimensional tri-view data, and is not described herein again.

In addition, an embodiment of the present application also provides a medium, in which a marriage and love pairing program is stored, and the marriage and love pairing program, when executed by a processor, implements the steps of the marriage and love pairing method based on multidimensional three-dimensional data as described above.

The specific implementation of the medium of the present application is substantially the same as that of each embodiment of the above-mentioned marriage and love pairing method based on multidimensional three-dimensional data, and details are not repeated here.

Furthermore, an embodiment of the present application also provides a computer program product, which includes a computer program, and when the computer program is executed by the processor, the steps of the method for marriage and love pairing based on multidimensional three-dimensional data as described above are implemented.

The specific implementation of the computer program product of the present application is substantially the same as the embodiments of the aforementioned marriage and love pairing method based on multidimensional tri-view data, and details are not repeated here.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation manner in many cases. Based on this understanding, the technical solutions of the present application may be embodied in the form of software goods stored in a storage medium (e.g., RAM/ROM, optical disc, hardware), and include instructions for enabling a marriage partner system to complete the methods described in the embodiments of the present application.

Claims

1. A marriage and love pairing method based on multidimensional tri-view data is characterized by comprising the following steps:

comparing first subdata in the first multi-dimensional three-view data with second subdata in the second multi-dimensional three-view data in a one-to-one correspondence manner to obtain three-view consistent scores corresponding to the subdata;

2. The method as claimed in claim 1, wherein the sub-data includes interest sub-data, marital attitude sub-data and to-be-liked attitude sub-data, and the step of comparing a first sub-data of the first multi-dimensional three-view data with a second sub-data of the second multi-dimensional three-view data in a one-to-one correspondence manner to obtain three-view consistent scores corresponding to the sub-data includes:

3. The method as claimed in claim 1, wherein the child data includes a to-be-personally-attitude sub-data, a to-be-friends-attitude sub-data and a to-be-children-attitude sub-data, and the step of comparing a first sub-data in the first multi-dimensional three-view data with a second sub-data in the second multi-dimensional three-view data in a one-to-one correspondence manner to obtain three-view consistent scores corresponding to the sub-data further includes:

4. The method as claimed in claim 1, wherein the sub-data includes sub-data to be neighbors, sub-data to be pets, and sub-data to be money, and the step of comparing the first sub-data in the first multi-dimensional three-view data with the second sub-data in the second multi-dimensional three-view data in a one-to-one correspondence manner to obtain the three-view consistent score corresponding to each sub-data further includes:

5. The method as claimed in claim 1, wherein the sub-data includes cause attitude sub-data, social attitude sub-data and belief attitude sub-data, and the step of comparing the first sub-data in the first multi-dimensional tri-view data with the second sub-data in the second multi-dimensional tri-view data in a one-to-one correspondence manner to obtain the corresponding tri-view consistent score of each sub-data further comprises:

6. The marriage and love pairing method based on multi-dimensional tri-view data as claimed in claims 1 to 5, wherein the step of pairing the first user and the second user based on the tri-view coincidence score corresponding to each of the child data comprises:

7. The method for marriage-love based on multi-dimensional tri-view data as claimed in claim 6, wherein said step of pairing said first user and said second user according to said target tri-view coincidence score and a preset character complementation degree comprises:

8. The method for marriage-love pairing based on multi-dimensional tri-view data as claimed in claim 1, wherein the steps of obtaining the first multi-dimensional tri-view data of the first user and obtaining the second multi-dimensional tri-view data of the second user comprise:

9. A marriage and love pairing device based on multidimensional tri-view data is characterized by comprising:

10. A marriage pairing system comprising a memory, a processor and a marriage pairing program stored on the memory and running on the processor, wherein the marriage pairing program when executed by the processor implements the steps of the multidimensional three-view data based marriage pairing method of any one of claims 1 to 8.

11. A medium having a marriage and love pairing program stored thereon, wherein the marriage and love pairing program when executed by a processor implements the steps of the multi-dimensional tri-view data based marriage and love pairing method according to any one of claims 1-8.