CN110309379A - Products Show method, apparatus, equipment and computer readable storage medium - Google Patents
Products Show method, apparatus, equipment and computer readable storage medium Download PDFInfo
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Abstract
The present invention relates to data analysis fields, a kind of Products Show method, apparatus, equipment and computer readable storage medium are provided, this method comprises: when receiving shared scale acquisition and the user's physique data sent, corresponding terminal bind request is sent to the shared scale, so that the shared scale shows the terminal bind request；If receiving the terminal binding instruction that user terminal is sent based on the terminal bind request within a preset time, the user terminal and user's physique data are bound；The sample physique data of default sample population are extracted, and clustering is carried out to user's physique data and the sample physique data based on default clustering rule, to determine target group；The corresponding high frequency product information of the target group is obtained, and the high frequency product information is pushed into the user terminal.The present invention realizes personalized information push, is conducive to improve the suitability between recommended products and user's individual attribute.
Description
Technical field
The present invention relates to data analysis field more particularly to a kind of Products Show method, apparatus, equipment and computer-readable
Storage medium.
Background technique
With the continuous development of society, start a kind of shared scale occur on the market, these shared scales are by businessman
The public domains such as pharmacy, market, hotel are placed on, with for users to use.When user needs to share scale detection by this certainly
When oneself weight, it can be obtained after upper scale mobile scanning terminal two dimensional code or by way of binding social account, cell-phone number
Get weight testing result；Meanwhile the relevant advertisements information (such as health insurance product information) of oneself can be pushed to user by businessman
Mobile terminal, realize business promotion information push.However this " extensively casting net " formula publicity popularization behavior is to all use
Family pushes opposing product information, and the suitability between the product information recommended and user's individual attribute is poor, the effect of recommendation
It is very unsatisfactory.
Summary of the invention
The main purpose of the present invention is to provide a kind of Products Show method, apparatus, equipment and computer-readable storage mediums
Matter, it is intended to solve the technical problem of product and user's individual attribute suitability difference in existing product recommendation process.
To achieve the above object, the embodiment of the present invention provides a kind of Products Show method, and the Products Show method includes:
When receiving the acquisition of shared scale and the user's physique data sent, according to user's physique data to institute
It states shared scale and sends corresponding terminal bind request, so that the shared scale shows the terminal bind request；
If receiving the terminal binding instruction that user terminal is sent based on the terminal bind request within a preset time,
The user terminal and user's physique data are bound according to terminal binding instruction；
Extract the sample physique data of default sample population, and based on default clustering rule to user's physique data with
The sample physique data carry out clustering, to determine target group in the default sample population based on the analysis results；
The corresponding high frequency product information of the target group is obtained, and the high frequency product information is pushed into the user
Terminal.
In addition, to achieve the above object, the embodiment of the present invention also provides a kind of Products Show device, the Products Show dress
It sets and includes:
Request sending module, for when receiving the acquisition of shared scale and the user's physique data sent, according to institute
It states user's physique data and sends corresponding terminal bind request to the shared scale, so that the shared scale shows institute
State terminal bind request；
Data binding module, if being sent for receiving user terminal within a preset time based on the terminal bind request
Terminal bind instruction, then the user terminal and user's physique data tied up according to terminal binding instruction
It is fixed；
Cluster Analysis module, for extracting the sample physique data of default sample population, and based on default clustering rule pair
User's physique data and the sample physique data carry out clustering, based on the analysis results in the default sample people
Target group is determined in group；
Info push module, for obtaining the corresponding high frequency product information of the target group, and by the high frequency product
Information pushes to the user terminal.
In addition, to achieve the above object, the embodiment of the present invention also provides a kind of Products Show equipment, the Products Show is set
It is standby to include processor, memory and be stored in the Products Show program that executed on the memory and by the processor,
When wherein the Products Show program is executed by the processor, realize such as the step of above-mentioned Products Show method.
In addition, to achieve the above object, the embodiment of the present invention also provides a kind of computer readable storage medium, the calculating
Products Show program is stored on machine readable storage medium storing program for executing, wherein realizing such as when the Products Show program is executed by processor
The step of above-mentioned Products Show method.
The present invention provides a kind of Products Show method, apparatus, equipment and computer readable storage medium, passes through shared weight
Scale obtains the physique data of user, then using user's physique data as starting point, analyzes and determines target group belonging to user, and
Feature is bought according to the corresponding product of target group and recommends corresponding product information to user, is realized personalized information and is pushed away
It send, is conducive to improve the suitability between recommended products and user's individual attribute, and then improve product promotion effect, while also rich
The new client of rich business personnel obtains visiting field scape, and the new client for solving business is helped to obtain objective demand.
Detailed description of the invention
Fig. 1 is the hardware structural diagram of Products Show equipment involved in the embodiment of the present invention；
Fig. 2 is the flow diagram of product of the present invention recommended method first embodiment；
Fig. 3 is the flow diagram of product of the present invention recommended method second embodiment；
Fig. 4 is the functional block diagram of product of the present invention recommendation apparatus first embodiment.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
The present embodiments relate to Products Show method be mainly used in Products Show equipment, which can
It is set with being that server, personal computer (personal computer, PC), laptop etc. are having data processing function
It is standby.
Referring to Fig.1, Fig. 1 is the hardware structural diagram of Products Show equipment involved in the embodiment of the present invention.This
In inventive embodiments, which may include (such as the central processing unit Central of processor 1001
Processing Unit, CPU), communication bus 1002, user interface 1003, network interface 1004, memory 1005.Wherein,
Communication bus 1002 is for realizing the connection communication between these components；User interface 1003 may include display screen
(Display), input unit such as keyboard (Keyboard)；Network interface 1004 optionally may include that the wired of standard connects
Mouth, wireless interface (such as Wireless Fidelity WIreless-FIdelity, WI-FI interface)；Memory 1005 can be high speed and deposit at random
Access to memory (random access memory, RAM), is also possible to stable memory (non-volatile memory),
Such as magnetic disk storage, memory 1005 optionally can also be the storage device independently of aforementioned processor 1001.This field
Technical staff is appreciated that hardware configuration shown in Fig. 1 and does not constitute a limitation of the invention, and may include more than illustrating
Or less component, perhaps combine certain components or different component layouts.
With continued reference to Fig. 1, the memory 1005 in Fig. 1 as a kind of computer readable storage medium may include operation system
System, network communication module and Products Show program.In Fig. 1, network communication module can be used for connecting database, with database
Carry out data communication；And processor 1001 can call the Products Show program stored in memory 1005, and execute the present invention
The Products Show method that embodiment provides.
The embodiment of the invention provides a kind of Products Show methods.
It is the flow diagram of product of the present invention recommended method first embodiment referring to Fig. 2, Fig. 2.
In the present embodiment, the Products Show method the following steps are included:
Step S10, when receiving shared scale acquisition and the user's physique data sent, according to user's physique
Data send corresponding terminal bind request to the shared scale, so that the shared scale shows the terminal binding
Request；
With the continuous development of society, start a kind of shared scale occur on the market, these shared scales are by businessman
The public domains such as pharmacy, market, hotel are placed on, with for users to use.When user needs to share scale detection by this certainly
When oneself weight, it can be obtained after upper scale mobile scanning terminal two dimensional code or by way of binding social account, cell-phone number
Get weight testing result；Meanwhile the relevant advertisements information (such as health insurance product information) of oneself can be pushed to user by businessman
Mobile terminal, realize business promotion information push.However this " extensively casting net " formula publicity popularization behavior is to all use
Family pushes opposing product information, and the suitability between the product information recommended and user's individual attribute is poor, the effect of recommendation
It is very unsatisfactory.In this regard, this method is illustrated the present embodiment provides a kind of Products Show method with the recommendation of health insurance product:
When user is using shared scale, when obtaining the physique data of user by sharing scale, and according to the physique number of user
Target health population belonging to the user is determined according to analyzing, and the target health population according to belonging to user is pushed to user and corresponded to
Health insurance product information, so that the use of shared scale be combined with the popularization process of health insurance product, and according to
The physique data at family realize personalized information push, are conducive to improve product promotion effect, while also enriching business personnel's
New client obtains visiting field scape, and the new client for solving business is helped to obtain objective demand.
Products Show method in the present embodiment is realized by Products Show equipment, and the Products Show equipment is to recommend to take
It is illustrated for business device.Recommendation server and shared scale in the present embodiment are connected to the network, and data can be achieved in the two
Interaction；And scale is shared for this, then it is pre-placed in public domains such as pharmacy, market, hotels.When a certain user needs to survey
When measuring the physique data of itself, it can stand to the detection zone for sharing scale；When shared scale detects the detection
When there is user's standing in region, it will acquire user's physique data of the user, the data type of user's physique data include but
It is not limited to weight, body fat rate, fat weight, skeletal muscle mass, muscle rate etc.；When user's physique data, which acquire, to be completed, share
User's physique data can be sent to recommendation server by scale.Certainly, in practice, recommendation server may be simultaneously with two
It is more than platform (herein " more than " include this number, similarly hereinafter) shared scale be connected to the network, in order to show user's physique number
According to source, share scale to recommendation server send user's physique data when, will also send the equipment mark of itself together
Know (mailing address, hardware number, the current location information of such as shared weighing apparatus).Recommendation server is receiving shared scale
When acquisition and the user's physique data sent, in order to show user's physique data to user and carry out subsequent Products Show
Operation, recommendation server can send corresponding terminal bind request to shared scale according to user's physique data first, with
The terminal bind request is shown for the shared scale.The form that can be two dimensional code for the terminal bind request, when
When user scans the two dimensional code by user terminal (equipment such as mobile phone or tablet computer), i.e., it is believed that user agrees to the user
Physique data and the user terminal of itself are bound, and are sent corresponding identity to recommendation server by the user terminal and tied up
Fixed instruction；The terminal bind request can also be the form of identifying code, when the identifying code is sent to by user by user terminal
When a certain number, i.e., it is believed that user agrees to bind user's physique data and the user terminal of itself, and by being somebody's turn to do
User terminal sends corresponding identity binding instruction to recommendation server；Certain terminal bind request can also be other shapes
Formula.
Step S20 is tied up if receiving the terminal that user terminal is sent based on the terminal bind request within a preset time
Fixed instruction then binds the user terminal and user's physique data according to terminal binding instruction；
In the present embodiment, when recommendation server receives the identity binding that user terminal is sent based on the terminal bind request
When instruction, that is, it can determine that user agrees to bind user's physique data and the user terminal of itself, at this time recommendation server
Can be instructed according to the identity binding and bind user terminal and user's physique data, and using the user terminal as it is subsequent to
User pushes the object of relevant information, so that the new client enriched obtains visiting field scape, helping the new client for solving business to obtain visitor is needed
It asks.And after binding user terminal and user's physique data, recommendation server can also be to user terminal sending step
The resulting user's physique data of S10, so that user understands the physical condition of oneself.
It is worth noting that recommendation server is to be sent to user's physique data to bind based on terminal in the present embodiment
Request the user terminal bound；And in practice, after user has used shared scale, it is possible to will not be by the user of oneself
Terminal carries out related bindings, is bound at this time by third terminal based on the terminal that shared scale is shown if there is the third party
Request carries out bindings, then the third party can obtain user's physique data of a user；The occurrence of in order to avoid this,
The terminal bind request that recommendation server is sent to shared scale has certain timeliness；If namely recommendation server exists
The terminal binding instruction that user terminal is sent based on the terminal bind request is received in preset time, then is bound according to the terminal
User terminal and user's physique data are bound in instruction；When more than a preset time, which fails,
User (or third party) can not carry out bindings by the terminal bind request.For example, when the terminal bind request is two dimension
When code, the effective time of the two dimensional code is 1 minute, if user scanned the two dimensional code using the mobile phone of oneself in 1 minute, the hand
Machine can send corresponding terminal binding instruction to recommendation server, and recommendation server will be bound the mobile phone and be used according to terminal
Family physique data are bound；And after 1 minute, which fails, even if recommendation server receives user terminal base
Instruction is bound in the terminal that the two dimensional code is sent, relevant bindings will not be carried out, to avoid using to a certain extent
The case where physique data at family are obtained by other people is conducive to the safety for protecting user's physique data.
Further, in the present embodiment, if recommendation server does not receive user terminal within a preset time and is based on the end
The terminal for holding bind request to send binds instruction, will also will be deleted user's body lattice data.In this way, it is ensured that clothes
User's physique data will not be stored in business device memory, user's physique data is avoided to reveal in the unwitting situation of user, also
Be conducive to save server memory.
Further, for user's physique data, since it is expanded business city having reacted business personnel to a certain degree
The achievement of field, therefore user's physique data can also be used in business personnel's achievement statistics.For example, business personnel can be with several shares
Weight scale is associated；When shared scale sends user's physique data to recommendation server, the equipment that itself can be sent together
Mark；And when recommendation server successfully binds user and user's physique data, i.e., it is believed that this gets one
Potential user, recommendation server can determine the business personnel of this achievement ownership according to the device identification at this time, and the achievement is returned
Category is recorded as relevant data, to carry out other data clearing (such as wages calculating), in the above manner, being conducive to transfer
Pass through the enthusiasm of scale exhibition industry with raising business personnel.
Step S30 extracts the sample physique data of default sample population, and based on default clustering rule to the user's body
Lattice data and the sample physique data carry out clustering, to determine mesh in the default sample population based on the analysis results
Mark crowd；
In the present embodiment, after by user terminal and the binding of user's physique data, recommendation server will be according to user's
Physique data, which are analyzed, determines target group belonging to the user (i.e. with the crowd of same or similar physique), and according to user institute
The target group of category push corresponding health insurance product information to user.The present embodiment is determining target group's belonging to user
In the process, due to including a plurality of types of data in user's physique data, and the physique data between different health populations may
The mode that clustering can be used with more covert connection, therefore in the present embodiment, in the sample of sample population gathered in advance
The determining target sample data with the same cluster of user's physique data (similar) in this physique data, the target sample data with cluster
Affiliated target group is regarded as belonging to same target group with user.
Optionally, the process of the present embodiment clustering can be and be realized by way of K mean cluster (K-Means)
's.For convenience of explanation, the K in the present embodiment is illustrated for 2.Recommendation server can connect with a presetting database network
It connects, the sample physique data of several sample populations collected in advance is stored in the presetting database, for these sample physique
User's physique data quantization can be corresponding user coordinates group according to default quantizing rule by data and user's physique data, will
The sample physique data quantization is corresponding sample coordinate group；Certain above-mentioned sample group and user coordinates group seat having the same
Dimension is marked, such as can be " (weight, body fat rate, fat weight, skeletal muscle mass, muscle rate) ", and is sat in actually reference
Mark group dimension can also be configured according to the actual situation.When quantifying to complete, push server will be in sample coordinate group and use
Two set of coordinates are randomly choosed in the set of coordinates of family as initial cluster center；The wherein quantity of the initial cluster center, Ye Jiju
The informational cluster quantity (value of K) of class process.When determining initial cluster center, each initial clustering and each non-initial center will be calculated
The initial distance of set of coordinates (distance can be and indicate in several ways, such as Euclidean distance, manhatton distance, cut ratio
Avenge husband's distance etc.).When obtaining the initial distance of each initial cluster center and each non-initial centre coordinate group, each non-initial center
Set of coordinates can using apart from closer initial cluster center as oneself cluster target, so that it is determined that each initial cluster center is corresponding
Initial clustering set of coordinates, each initial cluster center and corresponding initial clustering set of coordinates constitute initial clustering at this time
Cluster, also will all set of coordinates be divided into two classes.When obtaining initial clustering cluster, recommendation server will pass through certain election
Algorithm determines secondary cluster centre in each initial clustering cluster, which can be true by way of coordinate mean value computation
Fixed, the mode for being also possible to weighted mean, which determines, (i.e. on the basis of coordinate mean value, assigns different power for different set of coordinates
Weight values, if the weighted value of user coordinates group is greater than the weighted value of sample coordinate group, to as far as possible determine cluster centre in user
Near set of coordinates).And for secondary cluster centre, slightly different with initial cluster center, i.e., the secondary cluster centre can be
Virtual set of coordinates.When determining secondary cluster centre, each secondary cluster centre and the secondary centre coordinate of Ge Fei will be calculated separately
The secondary range of group (calculating process is similar with initial distance calculating, and the distance uses same way to indicate).?
When to the secondary range, the corresponding secondary cluster set of coordinates of each secondary cluster centre can be determined according to the secondary range, thus
Secondary clustering cluster is obtained, namely all set of coordinates are divided into two classes again.When obtaining secondary clustering cluster, recommendation server meeting
The cluster situation of the secondary clustering cluster is compared with the cluster situation of previous clustering cluster (i.e. initial clustering cluster), is judged
Whether the two is consistent (judging whether double classification situation is consistent).If consistent, it is believed that clustering convergence, i.e. cluster are completed,
The secondary clustering cluster where user coordinates group can be determined as target cluster at this time, the target sample coordinate which includes
Sample population corresponding to group (target sample data) is target group, which is regarded as having to user similar
The crowd of physical condition；And if the two is inconsistent, it is believed that cluster is not converged, needs again to carry out secondary clustering cluster at this time
Iteration cluster, direct clustering convergence (the iteration clustering cluster obtained is consistent with the set of coordinates of preceding clustering cluster classification situation),
And the process of specific iteration cluster is similar with secondary cluster process, details are not described herein again.
Further, in the present embodiment, in step S10 by sharing user's physique data that scale obtains and pre-
If the sample physique data stored in database, data type involved in the two is not necessarily identical, due to sharing doctor's type scale
Function restriction, it includes bone in sample data, such as sample physique data that the data type of user's physique data, which may be less than,
Flesh weight and in user's physique data and do not include skeletal muscle mass；And if in the different situation of the two data type into
Row clustering, it will reduce the accuracy of analysis, or even the case where can not carrying out clustering occur.In order to avoid this is asked
Topic, the present embodiment can also carry out regular and type to the two when quantifying to user's physique data and sample physique data
It is unitized.Specifically, it is corresponding user coordinates group, general that the basis, which presets quantizing rule for user's physique data quantization,
The sample physique data quantization be corresponding sample coordinate group the step of include:
Determine the data type that user's physique data packet includes, and according to the data type to the sample physique number
According to data filtering is carried out, corresponding effective sample data are obtained；
Recommendation server is when carrying out set of coordinates quantization, the data type that will can determine whether that user's body lattice data include first,
Then data filtering operation is carried out to sample physique data according to the data type of user's physique data, i.e., by sample physique data
Middle user's physique data data type not to be covered is rejected；For example, not including skeletal muscle mass in user's physique data and sample
Include skeletal muscle mass in physique data, then the skeletal muscle mass in sample physique data can be filtered out, does not use the item number
According to the subsequent operation of progress, and for filtered sample physique data, it can be described as effective sample data, the effective sample data
Included data type is consistent with user's physique data.Certainly, in practice, can also be by relevant staff or
User specifies the data type for analysis, recommendation server further according to specified data type respectively to user's physique data,
Sample physique data carry out data filtering.
According to predetermined order rule and the data type respectively to user's physique data and the effective sample data into
Row sequence, obtains corresponding user's physique sequence and effective sample sequence；
When obtaining effective sample data, recommendation server also by according to certain ordering rule respectively to user's physique number
Be ranked up according to effective sample data so that the data value in the two be ranked up with certain data type sequence, for example,
The ordering rule be " weight, body fat rate, fat weight, muscle rate ", then recommendation server can by user's physique data and effectively
Respective data value is ranked up in sample data with above-mentioned rule, obtains corresponding user's physique sequence and effective sample sequence
Column, to carry out regular processing to the two.
Corresponding user coordinates group is obtained according to user's physique sequence, is corresponded to according to the effective sample sequence
Sample coordinate group.
When obtaining user's physique sequence and effective sample sequence, corresponding user can be obtained according to user's physique sequence
Set of coordinates obtains corresponding sample coordinate group according to the effective sample sequence, and by the user coordinates group and sample coordinate group
To clustering, target group corresponding to user (user's physique data) is determined.
Step S40 obtains the corresponding high frequency product information of the target group, and the high frequency product information is pushed to
The user terminal.
In the present embodiment, recommendation server will acquire the corresponding high frequency product letter of target group when determining target group
Breath.For example, for the acquisition process of high frequency health insurance product, can be by taking health insurance product as an example and first obtain these target persons
The health insurance purchaser record of each target person in group, then according to determining that purchase number is most in these health insurance purchaser records
Several health insurance products, the most several health insurance products of these purchase numbers are regarded as the corresponding high frequency of target group and produce
Product, the related introduction information of these high frequency products are high frequency product information.When obtaining high frequency product information, recommendation server
These high frequency product informations can be pushed to user terminal, so that user knows the crowd's high frequency for having identical physique with oneself
The health insurance product of purchase.Certainly, in practice, other than health insurance product, recommendation server can also obtain other insurance kinds
High frequency product information, and pushed to user terminal.And for the high frequency product information, it can also be the user with user
Physique data are sent to the user terminal together.In addition, the information of push can also be and is configured by business personnel, example
It such as can be recommendation server and first send relevant information push task to corresponding service terminal, which is passed through by business personnel
The selection of business terminal makes relevant pushed information, pushes the information when selecting/completing, then through recommendation server
To user terminal.
Further, recommendation server can provide data storage in the user's physique data for obtaining user for user
Function passes through user terminal when user checks again and inquires to keep user's physique data；And it is storing
In the process, in order to protect the privacy of user, kept secure function can be also provided for user.In order to improve storage in the present embodiment
Safety, which can be is carried out by way of public private key encryption, specifically, the Products Show method of the present embodiment
Further include:
When receiving the data encryption instruction that the user terminal is sent, extracts in the data encryption instruction and include
Data public key, wherein the corresponding data private key of the data public key is stored by the user terminal；
When user needs that user's physique data of recommendation server are encrypted, can carry out on the subscriber terminal
Operation, so that user terminal generates asymmetric key pair, which includes data public key and data private key, wherein counting
User terminal local is stored according to private key；Then user terminal generates corresponding data encryption according to the data public key and instructs, and
Data encryption instruction is sent to recommendation server.Recommendation server is when receiving data encryption instruction, i.e., extractable
The data public key for including in data encryption instruction.
Public key carries out encryption storage to user's physique data based on the data.
Recommendation server will encrypt user's physique data based on the data public key when obtaining data public key, and
Encrypted user's physique data are stored.At this point, the data private key as needed for user's physique data deciphering is storage
It can not be also decrypted even if third party has got user's physique data of the encryption in user terminal and know it
Truthful data value；To ensure that privacy of user.And if user can pass through user terminal when needing to inquire the physique data of oneself
Data query instruction is sent to recommendation server, recommendation server then instructs to user terminal according to the data query and returns and should add
Close user's physique data；User terminal in the user's physique data for receiving the encryption again by local data private key into
Row decryption oprerations, so that user checks its specific data value.
Further, user's physique data in the present embodiment are collected and are sent by shared scale
It arrives, in this regard, recommendation server can also judge whether this shares the use of scale based on the data transmission frequency of shared scale
There is exception, and then relevant staff is prompted in time when occurring abnormal.Specifically, the product of the present embodiment pushes away
Recommend method further include:
Physique data transmission times of the shared scale in preset period of time is counted, and judges the physique data hair
Send whether number is less than preset flow threshold value；
Recommendation server can be periodically in physique of the statistical time point to shared scale in preset period of time that some is fixed
Data transmission times is counted, such as physique data transmission of the shared scale at upper one week is counted when the morning 9 on every Mondays
Number；Then the physique data transmission times can be compared by recommendation server with a preset flow threshold value, judge the physique
Whether data transmission times is less than preset flow threshold value.
If the physique data transmission times is less than the preset flow threshold value, scale is sent to corresponding management end
Use exception information.
If the physique data transmission times is less than preset flow threshold value, it is believed that the shared scale exists using abnormal
The case where, recommendation server will send scale to corresponding management end and use exception information at this time, to relevant staff
It is prompted and carries out abnormal investigation；And recommendation server to management end send scale use exception information when, the information
In can also include the contents such as address information, the associated services person of abnormal scale.Certainly for shared scale using different
Often might have a variety of situations, for instance it can be possible that there is failure in the software/hardware of shared scale, can not normal use,
May be shared scale access times it is less (i.e. the volume of the flow of passengers is less).
In the present embodiment, when receiving shared scale acquisition and the user's physique data sent, according to the user
Physique data send corresponding terminal bind request to the shared scale, so that the shared scale shows the terminal
Bind request；If receiving the terminal binding instruction that user terminal is sent based on the terminal bind request within a preset time,
Then the user terminal and user's physique data are bound according to terminal binding instruction；Extract default sample people
The sample physique data of group, and user's physique data and the sample physique data are gathered based on default clustering rule
Alanysis, to determine target group in the default sample population based on the analysis results；It is corresponding to obtain the target group
High frequency product information, and the high frequency product information is pushed into the user terminal.In the above manner, the present embodiment passes through
Shared scale obtains the physique data of user, then using user's physique data as starting point, analyzes and determines mesh belonging to user
Group is marked, and feature is bought according to the corresponding product of target group and recommends corresponding product information to user, realizes personalization
Information push, be conducive to improve the suitability between recommended products and user's individual attribute, and then improve product promotion effect,
The new client for also enriching business personnel simultaneously obtains visiting field scape, and the new client for solving business is helped to obtain objective demand.
It is the flow diagram of product of the present invention recommended method second embodiment referring to Fig. 3, Fig. 3.
Based on above-mentioned embodiment illustrated in fig. 2, in the present embodiment, the high frequency product information includes manual service link, institute
After stating step S40, further includes:
Step S50, when receiving the manual service request that the user terminal is received and sent based on the manual service chain,
Corresponding service role is sent according to the corresponding artificial customer side of the high frequency information query, and to the artificial customer side
Information.
In the present embodiment, it is contemplated that user might have query or interest, for convenience after the information for having browsed push
User seeks advice from, and further includes having manual service link in the high frequency product information that recommendation server is pushed；User is passing through
After user terminal has browsed the high frequency product information of push, attendant consultation service if desired is carried out to business personnel, then can pass through user's end
Endpoint hits manual service link, to trigger corresponding manual service request；User terminal then depending on the user's operation should
Manual service request is sent to recommendation server.Recommendation server, first will be according to this when receiving manual service request
The corresponding artificial customer side (or the terminal for the business personnel for being responsible for shared scale) of the source inquiry of user's physique data, and to
Artificial customer side sends corresponding service role information；Wherein the service role information may include user terminal IP address,
Name on account, telephone number etc., so that contact staff can contact quickly through service terminal and user, it is user
Manual service is provided, user is advantageously reduced and requests artificial enquiry the time it takes, promote the service experience of user, simultaneously also
The time that internal carry out task distribution and data transfer can be reduced spends, and improves business processing efficiency.
In addition, the embodiment of the present invention also provides a kind of Products Show device.
It is the functional block diagram of product of the present invention recommendation apparatus first embodiment referring to Fig. 4, Fig. 4.
In the present embodiment, the Products Show device includes:
Request sending module 10, for when receiving the acquisition of shared scale and the user's physique data sent, according to
User's physique data send corresponding terminal bind request to the shared scale, so that the shared scale is shown
The terminal bind request；
Data binding module 20, if being sent out for receiving user terminal within a preset time based on the terminal bind request
The terminal binding instruction sent then ties up the user terminal and user's physique data according to terminal binding instruction
It is fixed；
Cluster Analysis module 30, for extracting the sample physique data of default sample population, and based on default clustering rule
Clustering is carried out to user's physique data and the sample physique data, based on the analysis results in the default sample
Target group is determined in crowd；
Info push module 40 for obtaining the corresponding high frequency product information of the target group, and the high frequency is produced
Product information pushes to the user terminal.
Wherein, each virtual functions module of the said goods recommendation apparatus is stored in the storage of Products Show equipment shown in Fig. 1
It is functional for realizing the institute of Products Show program in device 1005；, it can be achieved that product pushes away when each module is executed by processor 1001
The correlation function recommended.
Further, the Products Show device further include:
Public key extraction module, for extracting the number when receiving the data encryption instruction that the user terminal is sent
According to the data public key for including in encrypted instruction, wherein the corresponding data private key of the data public key is stored by the user terminal；
Data encryption module carries out encryption storage to user's physique data for public key based on the data.
Further, the Cluster Analysis module 20 includes:
Set of coordinates quantifying unit, for being corresponding user according to quantizing rule is preset by user's physique data quantization
Set of coordinates, by the sample physique data quantization be corresponding sample coordinate group；
Center selection unit, for randomly selecting more than two coordinates in the user coordinates group and sample coordinate group
Group is used as initial cluster center, and calculates separately the initial distance of each initial cluster center Yu each non-initial centre coordinate group；
Cluster cell, for being determined according to the initial distance of each initial cluster center and each non-initial centre coordinate group
The corresponding initial clustering set of coordinates of each initial cluster center, and it is corresponding according to each initial cluster center and each initial cluster center
Initial clustering set of coordinates obtains initial clustering cluster；
Unit is elected at center, for determining secondary cluster centre in each initial clustering cluster based on default election algorithm, and
Calculate separately the secondary range of each initial cluster center Yu each non-secondary centre coordinate group；
Secondary cluster cell, for being determined according to the secondary range of each secondary cluster centre and each non-secondary centre coordinate group
The corresponding secondary cluster set of coordinates of each secondary cluster centre, and it is corresponding according to each secondary cluster centre and each secondary cluster centre
Secondary cluster set of coordinates obtains secondary clustering cluster；
Cluster judging unit, for judge each secondary clustering cluster and each initial clustering cluster coordinate group cluster situation whether one
It causes；
Target cluster determination unit, if secondary clustering cluster where the user coordinates group is determined as mesh for consistent
Mark cluster；If inconsistent, cluster is iterated to the secondary clustering cluster, until obtained iteration clustering cluster and preceding primary cluster
The set of coordinates classification situation of cluster is consistent, and the iteration clustering cluster where warrantee's set of coordinates is determined as target cluster；
Crowd's determination unit, for the target sample set of coordinates according to included by the target information cluster in the default sample
Target group is determined in this crowd.
Further, the set of coordinates quantifying unit is specifically used for:
Determine the data type that user's physique data packet includes, and according to the data type to the sample physique number
According to data filtering is carried out, corresponding effective sample data are obtained；
According to predetermined order rule and the data type respectively to user's physique data and the effective sample data into
Row sequence, obtains corresponding user's physique sequence and effective sample sequence；
Corresponding user coordinates group is obtained according to user's physique sequence, is corresponded to according to the effective sample sequence
Sample coordinate group.
Further, the high frequency product information includes manual service link, the Products Show device further include:
Task sending module, in the artificial clothes for receiving the user terminal and being received and sent based on the manual service chain
When business request, according to the corresponding artificial customer side of the high frequency information query, and sends and correspond to the artificial customer side
Service role information.
Further, the Products Show device further include:
Number statistical module, for counting physique data transmission times of the shared scale in preset period of time, and
Judge whether the physique data transmission times is less than preset flow threshold value；
Information sending module, if being less than the preset flow threshold value for the physique data transmission times, to correspondence
Management end send scale use exception information.
Further, the Products Show device further include:
Data removing module, if being asked for not receiving the user terminal within a preset time based on terminal binding
It asks the terminal of transmission to bind instruction, deletes user's physique data.
Wherein, the function of modules is realized and the said goods recommendation apparatus embodiment of the method in the said goods recommendation apparatus
In each step it is corresponding, function and realization process no longer repeat one by one here.
In addition, the embodiment of the present invention also provides a kind of computer readable storage medium.
Products Show program is stored on computer readable storage medium of the present invention, wherein the Products Show program is located
When managing device execution, realize such as the step of above-mentioned Products Show method.
Wherein, Products Show program, which is performed realized method, can refer to each reality of product of the present invention recommended method
Example is applied, details are not described herein again.
It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that the process, method, article or the system that include a series of elements not only include those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or system institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including being somebody's turn to do
There is also other identical elements in the process, method of element, article or system.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art
The part contributed out can be embodied in the form of software products, which is stored in one as described above
In storage medium (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that terminal device (it can be mobile phone,
Computer, server, air conditioner or network equipment etc.) execute method described in each embodiment of the present invention.
The above is only a preferred embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (10)
1. a kind of Products Show method, which is characterized in that the Products Show method includes:
When receiving the acquisition of shared scale and the user's physique data sent, according to user's physique data to described total
It enjoys scale and sends corresponding terminal bind request, so that the shared scale shows the terminal bind request；
If receiving the terminal binding instruction that user terminal is sent based on the terminal bind request within a preset time, basis
The user terminal and user's physique data are bound in the terminal binding instruction；
Extract the sample physique data of default sample population, and based on default clustering rule to user's physique data with it is described
Sample physique data carry out clustering, to determine target group in the default sample population based on the analysis results；
The corresponding high frequency product information of the target group is obtained, and the high frequency product information is pushed into user's end
End.
2. Products Show method as described in claim 1, which is characterized in that the Products Show method further include:
When receiving the data encryption instruction that the user terminal is sent, the data for including in the data encryption instruction are extracted
Public key, wherein the corresponding data private key of the data public key is stored by the user terminal；
Public key carries out encryption storage to user's physique data based on the data.
3. Products Show method as described in claim 1, which is characterized in that described to be based on default clustering rule to the user
Physique data and the sample physique data carry out clustering, to determine in the default sample population based on the analysis results
The step of target group includes:
It by user's physique data quantization is corresponding user coordinates group according to default quantizing rule, by the sample physique number
According to being quantified as corresponding sample coordinate group；
More than two set of coordinates are randomly selected in the user coordinates group and sample coordinate group as initial cluster center, and
Calculate separately the initial distance of each initial cluster center Yu each non-initial centre coordinate group；
Determine that each initial cluster center is corresponding with the initial distance of each non-initial centre coordinate group according to each initial cluster center
Initial clustering set of coordinates, and obtained just according to each initial cluster center and the corresponding initial clustering set of coordinates of each initial cluster center
Beginning clustering cluster；
Secondary cluster centre is determined in each initial clustering cluster based on default election algorithm, and calculates separately each initial cluster center
With the secondary range of each non-secondary centre coordinate group；
Determine that each secondary cluster centre is corresponding with the secondary range of each non-secondary centre coordinate group according to each secondary cluster centre
Secondary cluster set of coordinates, and two are obtained according to the corresponding secondary cluster set of coordinates of each secondary cluster centre and each secondary cluster centre
Secondary clustering cluster；
Judge whether each secondary clustering cluster is consistent with the coordinate group cluster situation of each initial clustering cluster；
If consistent, the secondary clustering cluster where the user coordinates group is determined as target cluster；If inconsistent, to described two
Secondary clustering cluster is iterated cluster, until obtained iteration clustering cluster is consistent with the set of coordinates of preceding clustering cluster classification situation,
And the iteration clustering cluster where warrantee's set of coordinates is determined as target cluster；
Target group is determined in the default sample population according to target sample set of coordinates included by the target information cluster.
4. Products Show method as claimed in claim 3, which is characterized in that the basis presets quantizing rule for the user
The step of physique data quantization is corresponding user coordinates group, by the sample physique data quantization is corresponding sample coordinate group
Include:
Determine the data type that user's physique data packet includes, and according to the data type to the sample physique data into
Row data filtering obtains corresponding effective sample data；
User's physique data and the effective sample data are arranged respectively according to predetermined order rule and the data type
Sequence obtains corresponding user's physique sequence and effective sample sequence；
Corresponding user coordinates group is obtained according to user's physique sequence, corresponding sample is obtained according to the effective sample sequence
This set of coordinates.
5. Products Show method as described in claim 1, which is characterized in that the high frequency product information includes manual service chain
It connects,
It is described to obtain the corresponding high frequency product information of the target group, and the high frequency product information is pushed into the user
After the step of terminal, further includes:
When receiving the manual service request that the user terminal is received and sent based on the manual service chain, according to the high frequency
The corresponding artificial customer side of information query, and corresponding service role information is sent to the artificial customer side.
6. Products Show method as described in claim 1, which is characterized in that the Products Show method further include:
Physique data transmission times of the shared scale in preset period of time is counted, and it is secondary to judge that the physique data are sent
Whether number is less than preset flow threshold value；
If the physique data transmission times is less than the preset flow threshold value, scale is sent to corresponding management end and is used
Exception information.
7. such as Products Show method described in any one of claims 1 to 6, which is characterized in that described to receive shares
It is corresponding to the shared scale transmission according to user's physique data when the acquisition of weight scale and the user's physique data sent
Terminal bind request, after the step of showing the terminal bind request for the shared scale, further includes:
If not receiving the terminal binding instruction that the user terminal is sent based on the terminal bind request within a preset time,
Then delete user's physique data.
8. a kind of Products Show device, which is characterized in that the Products Show device includes:
Request sending module, for when receiving the acquisition of shared scale and the user's physique data sent, according to the use
Family physique data send corresponding terminal bind request to the shared scale, so that the shared scale shows the end
Hold bind request；
Data binding module, if the end sent for receiving user terminal within a preset time based on the terminal bind request
End binding instruction then binds the user terminal and user's physique data according to terminal binding instruction；
Cluster Analysis module, for extracting the sample physique data of default sample population, and based on default clustering rule to described
User's physique data and the sample physique data carry out clustering, with based on the analysis results in the default sample population
Determine target group；
Info push module, for obtaining the corresponding high frequency product information of the target group, and by the high frequency product information
Push to the user terminal.
9. a kind of Products Show equipment, which is characterized in that the Products Show equipment includes processor, memory and storage
On the memory and the Products Show program that can be executed by the processor, wherein the Products Show program is by the place
When managing device and executing, the step of realizing Products Show method as described in any one of claims 1 to 7.
10. a kind of computer readable storage medium, which is characterized in that be stored with construction journey on the computer readable storage medium
Sequence, wherein when the constructor is executed by processor, realizing the test data as described in any one of claims 1 to 7
The step of building method.
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