CN109657133A - Friend-making object recommendation method, apparatus, equipment and storage medium - Google Patents
Friend-making object recommendation method, apparatus, equipment and storage medium Download PDFInfo
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- CN109657133A CN109657133A CN201811290662.1A CN201811290662A CN109657133A CN 109657133 A CN109657133 A CN 109657133A CN 201811290662 A CN201811290662 A CN 201811290662A CN 109657133 A CN109657133 A CN 109657133A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/01—Social networking
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
Abstract
The present invention provides a kind of friend-making object recommendation method, apparatus, equipment and storage medium.This method comprises: obtaining the face characteristic of the facial image of multiple first users；According to the face characteristic of the face characteristic of the second user and the multiple first user, the human face similarity degree of each first user in the second user and the multiple first user is determined respectively；According to the human face similarity degree of the second user and each first user, target user to be recommended is determined, and recommend the second user.The efficiency and success rate that the embodiment of the present invention is recommended are higher.
Description
Technical field
The present invention relates to field of artificial intelligence more particularly to a kind of friend-making object recommendation method, apparatus, equipment and deposit
Storage media.
Background technique
With the development of internet, Internet user is more and more.Therefore many singles admire in order to find
Object can find friend-making object by some friend-making sites.The number of users of general friend-making sites is more, how efficiently to find
Suitable friend-making object is more difficult.
In the related technology, it will usually which, according to the hobby of user, the object for selecting essential information to meet user preferences is pushed away
It recommends, essential information for example, the information such as age, constellation, height, weight, educational background, income, occupation.But above scheme pushes away
It is lower to recommend efficiency.
Summary of the invention
The present invention provides a kind of friend-making object recommendation method, apparatus, equipment and storage medium, recommends efficiency higher.
In a first aspect, the present invention provides a kind of friend-making object recommendation method, comprising:
Obtain the face characteristic of the facial image of multiple first users；
According to the face characteristic of the face characteristic of the second user and the multiple first user, described is determined respectively
The human face similarity degree of two users and each first user in the multiple first user；
According to the human face similarity degree of the second user and each first user, target user to be recommended is determined,
And recommend the second user.
Optionally, the human face similarity degree according to the second user and each first user, determines to be recommended
Target user, comprising:
Human face similarity degree is greater than corresponding first user of preset threshold, as the target user to be recommended.
Optionally, the human face similarity degree according to the second user and each first user, determines to be recommended
Target user, comprising:
According to the human face similarity degree of the second user and each first user, each first user is carried out
Descending arrangement, obtains ranking results；
By the first user of top n in the ranking results, as the target user to be recommended；N is whole greater than 1
Number.
Optionally, it is described recommend the second user before, further includes:
Obtain the representation data of the target user to be recommended；
According to the hobby condition of the second user, filtered out from the target user to be recommended and the hobby item
The matched target user of part；
Correspondingly, described recommend the second user, comprising:
The second user will be recommended with the matched target user of hobby condition.
Optionally, the representation data, include at least one of the following: the age, constellation, height, weight, residence, educational background,
Income, occupation, fixed assets, personality and values.
Optionally, the face characteristic of the face characteristic according to the second user and the multiple first user, point
It does not determine in the second user and the multiple first user before the human face similarity degree of each first user, further includes:
The facial image of the second user is obtained, and extracts the face characteristic of the facial image of the second user；With
And
According to the gender and orientation information of the second user and first user, obtain the multiple first user's
Facial image, and extract the face characteristic of the facial image of the multiple first user.
Second aspect, the present invention provide a kind of friend-making object recommendation device, comprising:
Obtain module, the face characteristic of the facial image for obtaining multiple first users；
Determining module, for the face characteristic according to the face characteristic of the second user and the multiple first user,
The human face similarity degree of each first user in the second user and the multiple first user is determined respectively；
Recommending module is determined for the human face similarity degree according to the second user and each first user wait push away
The target user recommended, and recommend the second user.
Optionally, the recommending module, is specifically used for:
Human face similarity degree is greater than corresponding first user of preset threshold, as the target user to be recommended.
Optionally, the recommending module, is specifically used for:
According to the human face similarity degree of the second user and each first user, each first user is carried out
Descending arrangement, obtains ranking results；
By the first user of top n in the ranking results, as the target user to be recommended；N is whole greater than 1
Number.
Optionally, the recommending module, is specifically used for:
Obtain the representation data of the target user to be recommended；
According to the hobby condition of the second user, filtered out from the target user to be recommended and the hobby item
The matched target user of part；
The second user will be recommended with the matched target user of hobby condition.
Optionally, the representation data, include at least one of the following: the age, constellation, height, weight, residence, educational background,
Income, occupation, fixed assets, personality and values.
The third aspect, the embodiment of the present invention provide a kind of computer readable storage medium, are stored thereon with computer program,
Method described in any one of first aspect is realized when the computer program is executed by processor.
Fourth aspect, the embodiment of the present invention provide a kind of electronic equipment, comprising:
Processor；And
Memory, for storing the executable instruction of the processor；
Wherein, the processor is configured to execute described in any one of first aspect via the executable instruction is executed
Method.
Friend-making object recommendation method, apparatus, equipment and storage medium provided in an embodiment of the present invention obtain multiple first and use
The face characteristic of the facial image at family；It is special according to the face characteristic of the second user and the face of the multiple first user
Sign determines the human face similarity degree of each first user in the second user and the multiple first user respectively；Further root
According to the human face similarity degree of the second user and each first user, target user to be recommended is determined, and recommend institute
Second user is stated, above by the face characteristic extracted from facial image, human face similarity degree is determined and then recommends target user, push away
It is more intuitive and efficient to recommend effect.
Detailed description of the invention
The drawings herein are incorporated into the specification and forms part of this specification, and shows the implementation for meeting the disclosure
Example, and together with specification for explaining the principles of this disclosure.
Fig. 1 is the schematic diagram of a scenario of one embodiment of friend-making object recommendation method provided in an embodiment of the present invention；
Fig. 2 is the schematic diagram of a scenario of another embodiment of friend-making object recommendation method provided in an embodiment of the present invention
Fig. 3 is the flow diagram of one embodiment of friend-making object recommendation method provided by the invention；
Fig. 4 is the structural schematic diagram of one embodiment of friend-making object recommendation device provided by the invention；
Fig. 5 is the structural schematic diagram of electronic equipment embodiment provided by the invention.
Through the above attached drawings, it has been shown that the specific embodiment of the disclosure will be hereinafter described in more detail.These attached drawings
It is not intended to limit the scope of this disclosure concept by any means with verbal description, but is by referring to specific embodiments
Those skilled in the art illustrate the concept of the disclosure.
Specific embodiment
Example embodiments are described in detail here, and the example is illustrated in the accompanying drawings.Following description is related to
When attached drawing, unless otherwise indicated, the same numbers in different drawings indicate the same or similar elements.Following exemplary embodiment
Described in embodiment do not represent all implementations consistent with this disclosure.On the contrary, they be only with it is such as appended
The example of the consistent device and method of some aspects be described in detail in claims, the disclosure.
Term " includes " in description and claims of this specification and the attached drawing and " having " and they appoint
What is deformed, it is intended that is covered and non-exclusive is included.Such as contain the process, method, system, production of a series of steps or units
Product or equipment are not limited to listed step or unit, but optionally further comprising the step of not listing or unit, or
Optionally further comprising the other step or units intrinsic for these process, methods, product or equipment.
Application scenarios according to the present invention are introduced first:
Friend-making object recommendation method provided in an embodiment of the present invention, can be applied to the marriage-seeking platform of network, and network is marriage-seeking flat
Platform generally has a large amount of registration user, and user can fill in partial personal information and the basic demand condition to friend-making object, such as
Age, occupation, income etc..The existing marriage-seeking platform of network according to user to the basic demand condition of friend-making object, from data
Qualified friend-making object is filtered out in library, and is recommended to user.With increasing for platform registration user, in database
The quantity of the friend-making object of storage sharply increases, and the workload of qualified friend-making object is gone out according to basic demand conditional filtering
Huge and time-consuming, the qualified friend-making object number further filtered out is also very big, cause user can not quickly from
Determining and oneself well matched friend-making object in the friend-making object of magnanimity.
The method of the embodiment of the present invention, by comparing the human face similarity degree of second user and the first user, so that it is determined that going out
The target user recommended to the second user, efficiency is higher, and second user is easier to get to know the friend-making well matched with oneself
Object.
The method of the embodiment of the present invention, applied to being equipped in the user equipment of the marriage-seeking platform of network.The embodiment of the present invention
In user equipment can be smart phone, tablet computer, wearable device, computer equipment etc..In the embodiment of the present invention
The marriage-seeking platform of network refers to the application program that may be implemented to recommend friend-making object to user.
Friend-making object recommendation method provided in an embodiment of the present invention, specifically, it is marriage-seeking by network to can be applied to user
In the system of platform selecting friend-making object.Fig. 1 is application scenarios schematic diagram provided in an embodiment of the present invention, as shown in Figure 1, this is
It include server 11, the first user equipment 12 in system；First user equipment 12 can be the user equipment of second user.Into one
Step, as shown in Fig. 2, the system can also include second user equipment 13.In Fig. 2, the first user equipment 12 may be
The user equipment of the user equipment of first user, second user equipment 13 or second user, the embodiment of the present invention is to this
With no restriction.Wherein, the database of storage user information can be equipped in server 11.
Wherein, the first user equipment 12 and server 11 and second user equipment 13 and server 11 can pass through net
Network connection, such as the communication networks such as 3G, 4G or Wireless Fidelity (Wireless Fidelity, WIFI).
Technical solution of the present invention is described in detail with specific embodiment below.These specific implementations below
Example can be combined with each other, and the same or similar concept or process may be repeated no more in some embodiments.
Fig. 3 is the flow diagram of one embodiment of friend-making object recommendation method provided by the invention.As shown in figure 3, this reality
The method that example offer is provided, comprising:
Step 301, obtain multiple first users facial image face characteristic.
Step 302, face characteristic and the face characteristic of the multiple first user according to the second user, it is true respectively
The human face similarity degree of the fixed second user and each first user in the multiple first user.
Specifically, when recommending friend-making object to second user, such as can be second user and trigger on a user device
Recommendation request, the recommendation request that user equipment can trigger the second user issue server, and server gets first
The facial image of two users, and the face characteristic of the facial image of the second user is extracted, multiple first users are then extracted again
Facial image face characteristic.The face characteristic of second user is compared with the face characteristic of each first user, really
Make human face similarity degree.According to human face similarity degree, it can be determined that whether there is " man and wife's phase ".Such as human face similarity degree is greater than a certain
Corresponding first user of threshold value has " man and wife's phase " with the second user.
It should be understood that the present embodiment can refer to the prior art to the specific implementation process that face characteristic extracts, herein
It does not repeat them here.
Step 303, according to the human face similarity degree of the second user and each first user, determine mesh to be recommended
User is marked, and recommends the second user.
Specifically, the human face similarity degree of the second user determined and each first user can be sent to by server
User equipment is determined target user to be recommended by user equipment, and recommends second user or server according to determining
Second user and each first user human face similarity degree, determine the target user that recommends to second user, such as by face
Similarity is greater than corresponding first user of a certain threshold value and recommends to second user.
Wherein it is possible to obtain the people of multiple first users according to the gender and orientation information of second user and the first user
Face image, and extract the face characteristic of the facial image of multiple first users.
Specifically, can be selected according to second user and the gender and orientation information of the first user, i.e. gender and sexual orientation
Multiple first users are selected, and obtain the facial image of multiple first users, and extract the people of the facial image of multiple first users
Face feature.
Illustratively, the marriage-seeking platform of second user A logging in network, i.e. after certain APP, triggering friend-making object recommendation request should
May include the essential information of the second user in recommendation request, the facial image for example including second user A, then extract this
Then the face characteristic of the facial image of two users extracts the face characteristic of the facial image of multiple first users again.By second
The face characteristic of user is compared with the face characteristic of each first user, determines human face similarity degree.Such as first user 1
Human face similarity degree with second user A is 80%, and the human face similarity degree of the first user 2 and second user A is 78%, the first user
The human face similarity degree of 3 and second user A is 30%, then according to human face similarity degree, it is biggish to can choose wherein human face similarity degree
First user 1 and the first user 2 recommend to second user A.
In the embodiment of the present invention, it is contemplated that the heavy workload for extracting face characteristic from image recognition is recommended to second user
When there may be delays, then can extract face characteristic in advance, be saved in database, it is straight when to recommend to second user
Calling is connect, the efficiency of recommendation is improved.
The method of the present embodiment obtains the facial image of multiple first users different from the gender of second user, extracts
The face characteristic of the facial image of the multiple first user；According to the face characteristic of the second user and the multiple first
The face characteristic of user determines that the second user is similar to the face of each first user in the multiple first user respectively
Degree；Further according to the human face similarity degree of the second user and each first user, target user to be recommended is determined,
And the second user is recommended, above by the face characteristic extracted from facial image, determines human face similarity degree and then recommend
Target user, recommendation effect are more intuitive and efficient.
On the basis of the above embodiments, further in embodiment illustrated in fig. 3 step 303 according to the second user with
The human face similarity degree of each first user determines that the specific implementation of target user to be recommended carries out specifically
It is bright.
Optionally, as a kind of enforceable mode, according to the face of the second user and each first user
Similarity determines target user to be recommended, can specifically realize in the following way:
Human face similarity degree is greater than corresponding first user of preset threshold, as target user to be recommended.
Specifically, determining the human face similarity degree between second user and multiple first users, face is then therefrom selected
Similarity is greater than corresponding first user of preset threshold, as target user to be recommended.
The preset threshold can be by the human face similarity degree of multiple training samples and the second user, and training obtains.
Optionally, as another enforceable mode, according to the people of the second user and each first user
Face similarity degree determines target user to be recommended, can specifically realize in the following way:
According to the human face similarity degree of second user and each first user, descending arrangement is carried out to each first user, is obtained
To ranking results；
By the first user of top n in ranking results, as target user to be recommended；N is the integer greater than 1.
Specifically, being carried out according to the human face similarity degree between second user and multiple first users to those the first users
Descending arrangement, obtains ranking results；From the ranking results select biggish the first user of top n of human face similarity degree, as to
The target user of recommendation.
In the present embodiment, since the quantity of the first user is more, it is suitable quickly to be selected by above two mode
The first user to second user recommend.
On the basis of the above embodiments, further, it in order to improve the accuracy rate of recommendation, i.e., further improves and makes friends
The success rate of object recommendation in the present embodiment, before recommending second user, can also proceed as follows:
Obtain the representation data of the target user to be recommended；
According to the hobby condition of the second user, filtered out from the target user to be recommended and the hobby item
The matched target user of part；
Correspondingly, described recommend the second user, comprising:
The second user will be recommended with the matched target user of hobby condition.
Wherein, the representation data includes at least one of the following: age, constellation, height, weight, residence, educational background, receipts
Enter, occupation, fixed assets, personality and values.
Specifically, further target user to be recommended can be screened before recommending second user, according to
The hobby condition of second user filters out the matched target user of hobby condition with second user.
Illustratively, the marriage-seeking platform of second user A logging in network, i.e. after certain APP, triggering friend-making object recommendation request should
It may include the essential information of the second user in recommendation request, and hobby condition such as 175 or more height, residence north
Capital；Server can obtain the facial image of second user A according to the essential information of second user and extract face characteristic, then
The face characteristic of the facial image of multiple first users is extracted again.By the people of the face characteristic of second user and each first user
Face feature is compared, and determines human face similarity degree.According to human face similarity degree, the first user of some of them is selected.Such as first
The human face similarity degree of user 1 and second user A are 80%, and the human face similarity degree of the first user 2 and second user A is 78%, the
The human face similarity degree of one user 3 and second user A is 75%, the first user, and the human face similarity degree of 4 and second user A is 30%,
Then according to human face similarity degree, biggish first user 1 of wherein human face similarity degree, the first user 2 and the first user 3 can choose,
And further screened according to hobby condition, such as the first user 1, the first user 2 meet above-mentioned hobby condition, and first uses
Family 3 is unsatisfactory for above-mentioned hobby condition, then the first user 1 and the first user 2 after finally screening recommend to second user A.
In the present embodiment, further determining target user to be recommended is sieved according to the hobby condition of second user
Choosing, improves the accuracy of recommendation.
Further, in order to improve the experience of user, it can further inquire that user's is true before recommending to user
It is intended to, for example, can be mentioned in the operation interface of the application program of user equipment, display after determining target user to be recommended
Show information, such as prompts the user on how to show target user to be recommended.
Illustratively, according to human face similarity degree, M target user to be recommended is determined, according to the finger for receiving user
Show information, carries out descending arrangement according to the height of M target user, and show.
Illustratively, according to human face similarity degree, M target user to be recommended is determined, according to the finger for receiving user
Show information, carries out ascending order arrangement according to the friend-making number of M target user, and show.
Further, when showing the target user recommended to user, the facial image and picture of other side can be shown simultaneously
As data.
Fig. 4 is the structure chart of one embodiment of friend-making object recommendation device provided by the invention, as shown in figure 4, the present embodiment
Friend-making object recommendation device, comprising:
Obtain module 401, the face characteristic of the facial image for obtaining multiple first users；
Determining module 402, for special according to the face characteristic of the second user and the face of the multiple first user
Sign determines the human face similarity degree of each first user in the second user and the multiple first user respectively；
Recommending module 403, for the human face similarity degree according to the second user and each first user, determine to
The target user of recommendation, and recommend the second user.
Optionally, the recommending module 403, is specifically used for:
Human face similarity degree is greater than corresponding first user of preset threshold, as the target user to be recommended.
Optionally, the recommending module 403, is specifically used for:
According to the human face similarity degree of the second user and each first user, each first user is carried out
Descending arrangement, obtains ranking results；
By the first user of top n in the ranking results, as the target user to be recommended；N is whole greater than 1
Number.
Optionally, the recommending module 403, is specifically used for:
Obtain the representation data of the target user to be recommended；
According to the hobby condition of the second user, filtered out from the target user to be recommended and the hobby item
The matched target user of part；
The second user will be recommended with the matched target user of hobby condition.
Optionally, the representation data, include at least one of the following: the age, constellation, height, weight, residence, educational background,
Income, occupation, fixed assets, personality and values.
Optionally, module 401 is obtained, is also used to:
The facial image of the second user is obtained, and extracts the face characteristic of the facial image of the second user；With
And
According to the gender and orientation information of the second user and first user, obtain the multiple first user's
Facial image, and extract the face characteristic of the facial image of the multiple first user.
The device of the present embodiment can be used for executing the technical solution of above method embodiment, realization principle and technology
Effect is similar, and details are not described herein again.
Fig. 5 is the structure chart of electronic equipment embodiment provided by the invention, as shown in figure 5, the electronic equipment includes:
Processor 501, and, the memory 502 of the executable instruction for storage processor 501.
It optionally, can also include communication interface 503, for being communicated with other equipment.
Above-mentioned component can be communicated by one or more bus.
Wherein, processor 501 is configured to execute via the executable instruction is executed corresponding in preceding method embodiment
Method, specific implementation process may refer to preceding method embodiment, and details are not described herein again.
A kind of computer readable storage medium is also provided in the embodiment of the present invention, is stored thereon with computer program, it is described
Realize that corresponding method in preceding method embodiment, specific implementation process may refer to when computer program is executed by processor
Preceding method embodiment, it is similar that the realization principle and technical effect are similar, and details are not described herein again.
The embodiment of the present application also provides a kind of computer program product, and the computer program product includes computer program
Code, when the computer program code is run on computers, so that computer is executed as electronics is set in above-described embodiment
Standby performed method.
Those skilled in the art after considering the specification and implementing the invention disclosed here, will readily occur to its of the disclosure
Its embodiment.The present invention is directed to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes or
Person's adaptive change follows the general principles of this disclosure and including the undocumented common knowledge in the art of the disclosure
Or conventional techniques.The description and examples are only to be considered as illustrative, and the true scope and spirit of the disclosure are by following
Claims are pointed out.
It should be understood that the present disclosure is not limited to the precise structures that have been described above and shown in the drawings, and
And various modifications and changes may be made without departing from the scope thereof.The scope of the present disclosure is only limited by appended claims
System.
Claims (12)
1. a kind of friend-making object recommendation method characterized by comprising
Obtain the face characteristic of the facial image of multiple first users；
According to the face characteristic of the face characteristic of second user and first user, determine respectively the second user with it is described
The human face similarity degree of each first user in multiple first users；
According to the human face similarity degree of the second user and each first user, target user to be recommended is determined, and push away
It recommends to the second user.
2. the method according to claim 1, wherein described use according to the second user with described each first
The human face similarity degree at family determines target user to be recommended, comprising:
Human face similarity degree is greater than corresponding first user of preset threshold, as the target user to be recommended.
3. the method according to claim 1, wherein described use according to the second user with described each first
The human face similarity degree at family determines target user to be recommended, comprising:
According to the human face similarity degree of the second user and each first user, descending is carried out to each first user
Arrangement, obtains ranking results；
By the first user of top n in the ranking results, as the target user to be recommended；N is the integer greater than 1.
4. method according to claim 1-3, which is characterized in that it is described recommend the second user before,
Further include:
Obtain the representation data of the target user to be recommended；
According to the hobby condition of the second user, filtered out from the target user to be recommended and the hobby condition
The target user matched；
Correspondingly, described recommend the second user, comprising:
The second user will be recommended with the matched target user of hobby condition.
5. according to the method described in claim 4, it is characterized in that, the representation data, include at least one of the following: the age,
Constellation, height, weight, residence, educational background, income, occupation, fixed assets, personality and values.
6. method according to claim 1-3, which is characterized in that the face characteristic according to second user with
The face characteristic of first user determines each first user in the second user and the multiple first user respectively
Before human face similarity degree, further includes:
The facial image of the second user is obtained, and extracts the face characteristic of the facial image of the second user；And
According to the gender and orientation information of the second user and first user, the face of the multiple first user is obtained
Image, and extract the face characteristic of the facial image of the multiple first user.
7. a kind of friend-making object recommendation device characterized by comprising
Obtain module, the face characteristic of the facial image for obtaining multiple first users different from the gender of second user；
Determining module, for according to the face characteristic of the second user and the face characteristic of the multiple first user, difference
Determine the human face similarity degree of each first user in the second user and the multiple first user；
Recommending module determines to be recommended for the human face similarity degree according to the second user and each first user
First user, and recommend the second user.
8. device according to claim 7, which is characterized in that the recommending module is specifically used for:
Human face similarity degree is greater than corresponding first user of preset threshold, as first user to be recommended.
9. device according to claim 7, which is characterized in that the recommending module is specifically used for:
According to the human face similarity degree of the second user and each first user, descending is carried out to each first user
Arrangement, obtains ranking results；
By the first user of top n in the ranking results, as first user to be recommended；N is the integer greater than 1.
10. according to the described in any item devices of claim 7-9, which is characterized in that the recommending module is specifically used for:
Obtain the representation data of first user to be recommended；
According to the hobby condition of the second user, filtered out from first user to be recommended and the hobby condition
The first user matched；
The second user will be recommended with matched first user of the hobby condition.
11. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the computer program
Method described in any one of claims 1-6 is realized when being executed by processor.
12. a kind of electronic equipment characterized by comprising
Processor；And
Memory, for storing the executable instruction of the processor；
Wherein, the processor is configured to require 1-6 described in any item via executing the executable instruction and carry out perform claim
Method.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201811290662.1A CN109657133A (en) | 2018-10-31 | 2018-10-31 | Friend-making object recommendation method, apparatus, equipment and storage medium |
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| CN201811290662.1A CN109657133A (en) | 2018-10-31 | 2018-10-31 | Friend-making object recommendation method, apparatus, equipment and storage medium |
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| CN201811290662.1A Pending CN109657133A (en) | 2018-10-31 | 2018-10-31 | Friend-making object recommendation method, apparatus, equipment and storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111178124A (en) * | 2019-09-26 | 2020-05-19 | 重庆市链盟联智能科技有限责任公司 | Marriage and love dating system and data processing method thereof |
| CN111949813A (en) * | 2019-04-30 | 2020-11-17 | 北京百度网讯科技有限公司 | Friend-making request method, friend-making request device, computer equipment and storage medium |
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Application publication date: 20190419 |