CN110197402A - User tag analysis method, device, equipment and storage medium based on user group - Google Patents
User tag analysis method, device, equipment and storage medium based on user group Download PDFInfo
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- CN110197402A CN110197402A CN201910487705.3A CN201910487705A CN110197402A CN 110197402 A CN110197402 A CN 110197402A CN 201910487705 A CN201910487705 A CN 201910487705A CN 110197402 A CN110197402 A CN 110197402A
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Abstract
The application provides a kind of user tag analysis method, device, equipment and storage medium based on user group, wherein method includes: the identity information for obtaining at least one user within preset range；According to the identity information, the behavioral data of each user is obtained, wherein the behavioral data includes historical data and operation data；Clustering processing is carried out to the behavioral data of each user, obtains the first label of each user, wherein first label is used to characterize the behavior type of user；Clustering processing is carried out to the first label of each user, obtains the second label of each preset user group, wherein second label is used to characterize the behavior type of user group.The user group label accuracy determined is high, reference value is big, it can be achieved that according to the second label of business hall periphery user group, selects quotient, selection, paving goods, tune the behaviors such as to pull out to provide decision support for business hall.
Description
Technical field
The present invention relates to data analysis technique more particularly to a kind of user tag analysis method based on user group, device,
Equipment and storage medium.
Background technique
With the development of communication technology, user also increasingly carrys out the demand of communication service commodity big.Currently, business hall
The communication service commodity of offer mainly include all kinds of communication set meal commodity and terminal device commodity.
In the prior art, when business hall provides communication service commodity for user, according to pre-set quota, configuration
Various communication service commodity；Then, for the needs of individual consumer, specific communication set meal commodity and/or terminal device are provided
Commodity.
However above-mentioned processing method, communication service commodity can only be provided for individual consumer's demand, face user group
When, can not determine the demand type of different user group, and then can not according to the demand type of user group, determine as
What all kinds of communication service commodity of configuration.
Summary of the invention
The present invention provides a kind of user tag analysis method, device, equipment and storage medium based on user group, to solve
Certainly when facing user group, the problem of can not determining the demand type of different user group.
In a first aspect, the application provides a kind of user tag analysis method based on user group, comprising:
Obtain the identity information of at least one user within preset range；
According to the identity information, the behavioral data of each user is obtained, wherein the behavioral data includes going through
History data and operation data；
Clustering processing is carried out to the behavioral data of each user, obtains the first label of each user,
Wherein, first label is used to characterize the behavior type of user；
Clustering processing is carried out to the first label of each user, obtains the second mark of each preset user group
Label, wherein second label is used to characterize the behavior type of user group.
Further, the identity information for obtaining at least one user within preset range, comprising:
Obtain the identity information for entering the user of business hall；
According to the identity information for each user for entering business hall, the user belonged within the preset range is determined,
To obtain the identity information of at least one user within the preset range；
Wherein, the preset range is that user's inhabitation address is less than pre-determined distance at a distance from business hall, alternatively, described pre-
If range is that user appears in the frequency of business hall higher than the default frequency.
Further, according to the identity information, the behavioral data of each user is obtained, comprising:
According to the identity information, the historical data corresponding with the identity information prestored is obtained；
According to the identity information, the operation data of the user on the terminal device is obtained.
Further, the operation data includes at least one below: the browsing time of commodity, different types of commodity
Browsing time, buying behavior data.
It further, include station address information in the identity information；The first label of each user is gathered
Alanysis processing, obtains the second label of each preset user group, comprising:
According to the station address information of the user, at least one described user is divided at least one described user
Group；
Clustering processing is carried out the first label of the user in each described user group, obtains each described use
The second label of family group.
Further, clustering processing is carried out in the first label to each user, obtains each preset use
After the second label of family group, further includes:
It is determining and each user group according to the corresponding relationship between preset business hall label and the second label
The corresponding business hall label of second label；
Alternatively, handled using second label of the machine learning model each user group, obtain with it is each
The corresponding business hall label of second label of a user group.
Second aspect, the application provide a kind of user tag analytical equipment based on user group, comprising:
First acquisition unit, for obtaining the identity information of at least one user within preset range；
Second acquisition unit, for obtaining the behavioral data of each user according to the identity information, wherein
The behavioral data includes historical data and operation data；
First processing units carry out clustering processing for the behavioral data to each user, obtain each institute
State the first label of user, wherein first label is used to characterize the behavior type of user；
The second processing unit carries out clustering processing for the first label to each user, it is pre- to obtain each
If user group the second label, wherein second label is used to characterize the behavior type of user group.
Further, first acquisition unit, comprising:
First obtains subelement, for obtaining the identity information for entering the user of business hall；
First processing subelement determines described in belonging to for the identity information according to each user for entering business hall
User within preset range, to obtain the identity information of at least one user within the preset range；
Wherein, the preset range is that user's inhabitation address is less than pre-determined distance at a distance from business hall, alternatively, described pre-
If range is that user appears in the frequency of business hall higher than the default frequency.
Further, second acquisition unit, comprising:
First obtains subelement, for according to the identity information, obtains prestore corresponding with the identity information and goes through
History data；
Second obtains subelement, for obtaining the operand of the user on the terminal device according to the identity information
According to.
Further, the operation data includes at least one below: the browsing time of commodity, different types of commodity
Browsing time, buying behavior data.
Further, the second processing unit, comprising:
First processing subelement divides at least one described user for the station address information according to the user
For user group described at least one；
Second processing subelement carries out at clustering for the first label the user in each described user group
Reason, obtains the second label of each user group.
Further, the second processing unit, further includes:
Third handles subelement, for determining according to the corresponding relationship between preset business hall label and the second label
Business hall label corresponding with the second label of user group described in each；
Alternatively, fourth process subelement, for the second label using machine learning model each user group
It is handled, obtains business hall label corresponding with the second label of user group described in each.
The third aspect, the application provide a kind of user tag analytical equipment based on user group, comprising: include: processor,
Memory and computer program；
Wherein, computer program stores in memory, and is configured as being executed by processor to realize as above any one
Method.
Fourth aspect, the application provide a kind of computer readable storage medium, deposit in the computer readable storage medium
Computer executed instructions are contained, for realizing the side any one of as above when the computer executed instructions are executed by processor
Method.
The application provides a kind of user tag analysis method, device, equipment and storage medium based on user group, wherein
Method includes the identity information for obtaining at least one user within preset range；According to the identity information, each is obtained
The behavioral data of the user, wherein the behavioral data includes historical data and operation data；Behavior to each user
Data carry out clustering processing, obtain the first label of each user, wherein first label is used for characterizing
The behavior type at family；Clustering processing is carried out to the first label of each user, obtains each preset user group
Second label, wherein second label is used to characterize the behavior type of user group.The user group label accuracy determined
High, reference value is big, it can be achieved that according to the second label of business hall periphery user group, for business hall select quotient, selection, paving goods,
The behaviors such as tune pulls out provide decision support.
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 a kind of flow diagram of user tag analysis method provided by the embodiments of the present application；
Fig. 2 is the flow diagram of another user tag analysis method provided by the embodiments of the present application；
Fig. 3 is a kind of structural schematic diagram of user tag analytical equipment provided by the embodiments of the present application；
Fig. 4 is the structural schematic diagram of another user tag analytical equipment provided by the embodiments of the present application；
Fig. 5 is a kind of structural schematic diagram of user tag analytical equipment provided by the embodiments of the present application.
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.
Noun according to the present invention is explained first:
Clustering: referring to the set by physical object or abstract object, is grouped into the multiple classes being made of similar object
Analytic process, target is to collect data on the basis of similar and classify.
Above-mentioned terminal device can be wireless terminal and be also possible to catv terminal.Wireless terminal can be directed to user's offer
The equipment of voice and/or other business datum connectivity has the handheld device of wireless connecting function or is connected to wireless tune
Other processing equipments of modulator-demodulator.Wireless terminal can be through wireless access network (Radio Access Network, abbreviation RAN)
Communicated with one or more equipments of the core network, wireless terminal can be mobile terminal, as mobile phone (or be " honeycomb "
Phone) and computer with mobile terminal, for example, it may be portable, pocket, hand-held, built-in computer or
Vehicle-mounted mobile device, they exchange language and/or data with wireless access network.For another example wireless terminal can also be personal
Communication service (Personal Communication Service, abbreviation PCS) phone, wireless phone, Session initiation Protocol
(Session Initiation Protocol, abbreviation SIP) phone, wireless local loop (Wireless Local Loop, letter
Claim WLL) it stands, the equipment such as personal digital assistant (Personal Digital Assistant, abbreviation PDA).Optionally, above-mentioned end
End equipment can also be the equipment such as mobile phone, smartwatch, tablet computer.
The specific application scenarios of the present invention: with the development of communication technology, demand of the user for communication service commodity
Increasingly come big.Currently, the communication service commodity that business hall provides, mainly include all kinds of communication set meal commodity and terminal device quotient
Product.In the prior art, it when business hall provides communication service commodity for user, according to pre-set quota, configures various
Communication service commodity；Then, for the needs of individual consumer, specific communication set meal commodity and/or terminal device commodity are provided.
However above-mentioned processing method, communication service commodity can only be provided for individual consumer's demand, face user group
When, it can not determine the demand type of different user group, and then can not determine according to the demand type of user group
How all kinds of communication service commodity are configured.
User tag analysis method, device, equipment and storage medium provided by the invention based on user group, it is intended to solve
The technical problem as above of the prior art.
How to be solved with technical solution of the specifically embodiment to technical solution of the present invention and the application below above-mentioned
Technical problem is described in detail.These specific embodiments can be combined with each other below, for the same or similar concept
Or process may repeat no more in certain embodiments.Below in conjunction with attached drawing, the embodiment of the present invention is described.
Fig. 1 is a kind of flow diagram of user tag analysis method provided by the embodiments of the present application, as shown in Figure 1, should
Method includes:
The identity information of at least one user within step 101, acquisition preset range.
In the present embodiment, specifically, the executing subject of the present embodiment is terminal or controller or other can be with
Execute the device or equipment of the present embodiment.The present embodiment is illustrated by terminal of executing subject, can be arranged in the terminal and be answered
With software, then, terminal control application software executes method provided in this embodiment.
Since the daily routines range of people is limited, obtain using business hall as the body of the user within the preset range of center
Part information, determines the demand type and consumption habit of the user within preset range, this configures communication service for business hall
For commodity, there is reference value and with directive significance.Subscriber identity information is obtained, is to obtain user's other information
Premise, for example, being disappeared after getting the identity information of user according to station address information, the history that identity information obtains user
Take data.
Step 102, according to identity information, obtain the behavioral data of each user, wherein behavioral data includes history number
According to and operation data.
In the present embodiment, specifically, according to the identity information of the user got, row corresponding to the identity information is obtained
For data, behavioral data includes the historical data of the consumer behavior of user, specifically includes the communication that user bought in business hall
The information for the communication set meal commodity that the historical record and user of set meal commodity and terminal device commodity are being currently used.Row
For the operation note that data further include after user enters business hall, on the terminal device of business hall, wherein terminal device is business
What the Room provided understands equipment with communication service commodity are bought for user, and in some alternative embodiments, terminal device can be with
It is self-service to choose instrument, self-service choose plate, self-service terminating machine etc..Obtain the operation note of user on the terminal device, packet
Include obtain user browsed in operator control panel commodity time, inhomogeneity commodity region residence time, user final purchase
Behavioral data etc..
Step 103 carries out clustering processing to the behavioral data of each user, obtains the first label of each user,
Wherein, the first label is used to characterize the behavior type of user.
In the present embodiment, specifically, the historical data and operation data of the user got are discrete without rule
Data, the behavior type of the user can not be determined from these data.Historical data and behaviour to each user got
Make data, carry out clustering processing, obtain the first label of each user, the first label describes the preference letter of user
Breath, consuming capacity information, purchase intention information etc., for characterizing the behavior type of user.Wherein, clustering processing can be used
Existing analysis method realizes that this will not be repeated here.
Step 104 carries out clustering processing to the first label of each user, obtains the of each preset user group
Two labels, wherein the behavior type of the second tagging user characterization user group.
In the present embodiment, specifically, according to the distance of user's inhabitation address to business hall, user is divided into different
User group.The first label of all users is discrete random data in user group, can not be determined from these data
The behavior type of the user group out.After marking off user group range, the first of all users counted in preset time period is obtained
Label, or the first label of the user of preset quantity is obtained, clustering is carried out to the first label of all users of acquisition
Processing, obtains the second label of user group, and the second tagging user characterizes the behavior type of user group.Wherein, clustering is handled
Existing analysis method can be used and realize that this will not be repeated here.
The identity information that the present embodiment passes through at least one user within acquisition preset range；According to identity information, obtain
Take the behavioral data of each user, wherein behavioral data includes historical data and operation data；To the behavioral data of each user
Clustering processing is carried out, the first label of each user is obtained, wherein the first label is used to characterize the behavior class of user
Type；Clustering processing is carried out to the first label of each user, obtains the second label of each preset user group, wherein
The behavior type of second tagging user characterization user group.By obtaining the behavioral data of business hall periphery user, user is determined
The first label, behavioral data not only includes operation data of the user in business hall, further include storage with user identity believe
Corresponding historical data is ceased, depending on the user's operation data and historical data, the first Tag reference value of the user determined
Greatly, objectivity is strong；After marking off user group, according to the first label of users all in user group, determine that business hall periphery is used
The second label of family group, the second label accuracy is high, reference value is big, it can be achieved that according to the second of business hall periphery user group the mark
Label select quotient, selection, paving goods, tune the behaviors such as to pull out and provide decision support for business hall.
Fig. 2 is a kind of flow diagram of user tag analysis method provided by the embodiments of the present application, as shown in Fig. 2, should
Method includes:
Step 201, acquisition enter the identity information of the user of business hall.
In the present embodiment, specifically, by face recognition technology, obtaining the identity of user after user enters business hall
Information.
Step 202, basis enter the identity information of each user of business hall, determine the use belonged within preset range
Family, to obtain the identity information of at least one user within preset range.
In the present embodiment, specifically, according to the identity information of the user got, use corresponding to the identity information is obtained
Family address information.According to station address information, judge whether user's inhabitation address is less than set distance at a distance from business hall, is
Judge the user then for business hall periphery user, the demand type of the user has reference significance for business hall.With
The demand type at family is usually determined by factors such as the preference information of user, consuming capacity, purchase intentions.Judge that user belongs to business
After user within the preset range of the Room, the identity information of the user got is the identity letter of the user within preset range
Breath.When the station address information of user can not be obtained, according to subscriber identity information, the historical behavior data of user is obtained, are sentenced
Whether the frequency that disconnected user appears in business hall is higher than setting value, is to judge the user for business hall periphery user.If with
Family is new user, and can not obtain the station address information of the user, directly judges the user for non-business hall periphery user.
Step 203, according to identity information, obtain the behavioral data of each user, wherein behavioral data includes history number
According to and operation data.
In the present embodiment, it specifically, according to the identity information of the user got, obtains and the subscriber identity information pair
The behavioral data answered, specifically includes: according to identity information, obtaining the historical data corresponding to the identity information prestored；And basis
Identity information obtains the operation data of user on the terminal device.According to identity information, obtain prestore it is corresponding with identity information
Historical data, including according to identity information, obtain the communication service commodity purchaser record of the user prestored, specifically include use
The purchaser record of the subscription record and terminal device commodity of the communication set meal commodity at family, and to obtain the user currently in use logical
Believe set meal data information.According to identity information, the operation data of user on the terminal device is obtained, operation data includes below
It is at least one: the browsing time of commodity, the browsing time of different types of commodity, buying behavior data.Terminal device is business
The equipment for understanding for user and buying communication service commodity that the Room provides, when user operates on the terminal device, eventually
End equipment can acquire the face information of user in real time, and the identity information of user is obtained by face recognition technology, and realization will be used
The identity information at family is mapped with the operation information of user on the terminal device.Even if user has left business hall, it still is able to
According to identity information, historical operation information of the user on the terminal device of business hall is obtained.
Step 204 carries out clustering processing to the behavioral data of each user, obtains the first label of each user,
Wherein, the first label is used to characterize the behavior type of user.
In the present embodiment, it specifically, the behavioral data to each user got carries out clustering processing, obtains
To the first label of each user, the first label describes the preference information of the user, consuming capacity information, purchase intention letter
The contents such as breath.The behavioral data for the user for not having classification to refer to itself is analyzed in clustering processing, according to behavioral data
Itself, excavates behavioral data object and its relation information, and behavioral data is divided into different groups, the behavior in each grouping
Data be it is similar, the object between group is incoherent, the corresponding data label of each grouping, the data mark of all groupings
Label constitute the first label.K mean algorithm, hierarchical clustering algorithm, BRICH algorithm, CURE algorithm can be used in clustering processing
It is realized etc. existing algorithm, here, the application does not repeat them here.
Step 205, the station address information according to user, are divided at least one user group at least one user.
In the present embodiment, specifically, after getting the identity information of user, according to identity information, obtain user's
Station address information.According to station address information, the business hall periphery user under different preset conditions is divided at least one
User group.In some alternative embodiments, respectively by station address to business hall distance be 3km, 5km, 10km within battalion
Industry Room periphery user is divided into three different user groups.The first label of different users be it is discrete irregular, according to
At least one user is divided at least one user group, it can be achieved that according to the station address of user by the station address information at family
Information carries out conclusion division to the first label of different user.
Step 206 carries out clustering processing to the first label of the user in each user group, obtains each use
The second label of family group, wherein the second label is used to characterize the behavior type of user group.
In the present embodiment, it specifically, after marking off user group, obtains in the user group counted in preset time period and owns
The first label of user, or the first label of the user of preset quantity in user group is obtained, the first label of acquisition is carried out
Secondary clustering processing, obtains the second label of each user group, wherein the second label is used to characterize the behavior of user group
Type.Clustering handling principle can refer to step 204, and this will not be repeated here.
Clustering processing is carried out in the first label to each user, obtains the second label of each preset user group
Later, further includes: determining and each user group according to the corresponding relationship between preset business hall label and the second label
The corresponding business hall label of second label；Alternatively, using machine learning model to the second label of each user group at
Reason, obtains business hall label corresponding with the second label of each user group.According to the business hall label determined, for business
Quotient is selected, selection, paving goods, adjusts and the behaviors such as pulls out decision support is provided in the Room.
The present embodiment enters the identity information of the user of business hall by obtaining；According to each use for entering business hall
The identity information at family determines the user belonged within preset range, to obtain the body of at least one user within preset range
Part information；According to identity information, the behavioral data of each user is obtained, wherein behavioral data includes historical data and operation
Data；Clustering processing is carried out to the behavioral data of each user, obtains the first label of each user, wherein the first mark
Sign the behavior type for characterizing user；According to the station address information of user, at least one user is divided at least one
User group；Clustering processing is carried out to the first label of the user in each user group, obtains the of each user group
Two labels, wherein the second label is used to characterize the behavior type of user group.By the behavior number for obtaining business hall periphery user
According to, determine that the first label of user, behavioral data not only include operation data of the user in business hall, further include storage
Historical data corresponding with subscriber identity information, data and historical data depending on the user's operation, the first of the user determined
Label accuracy is high；It according to station address information, determines using business hall as the user within the preset range of center, is business hall week
The first Tag reference value of side user, the business hall periphery user determined are big, and it is controllable that user tag analyzes workload；According to
Business hall periphery user is divided into different user groups by preset condition, according to the first label of users all in user group, really
The second label for making user group, the second label accuracy determined is high, reference value is big, because of the division item of different user group
Part is clear, and therefore, the corresponding division condition of the second label is clear, is applicable in that scene is clear, can for business hall select quotient, selection,
Paving goods is adjusted and the behaviors such as pulls out and provide effective decision support.
Fig. 3 is a kind of structural schematic diagram of user tag analytical equipment provided by the embodiments of the present application, as shown in figure 3, should
Device includes:
First acquisition unit 1, for obtaining the identity information of at least one user within preset range；
Second acquisition unit 2, for obtaining the behavioral data of each user, wherein behavioral data according to identity information
Including historical data and operation data；
First processing units 3 carry out clustering processing for the behavioral data to each user, obtain each user's
First label, wherein the first label is used to characterize the behavior type of user；
The second processing unit 4 carries out clustering processing for the first label to each user, it is preset to obtain each
Second label of user group, wherein the second label is used to characterize the behavior type of user group.
The identity information that the present embodiment passes through at least one user within acquisition preset range；According to identity information, obtain
Take the behavioral data of each user, wherein behavioral data includes historical data and operation data；To the behavioral data of each user
Clustering processing is carried out, the first label of each user is obtained, wherein the first label is used to characterize the behavior class of user
Type；Clustering processing is carried out to the first label of each user, obtains the second label of each preset user group, wherein
The behavior type of second tagging user characterization user group.By obtaining the behavioral data of business hall periphery user, user is determined
The first label, behavioral data not only includes operation data of the user in business hall, further include storage with user identity believe
Corresponding historical data is ceased, depending on the user's operation data and historical data, the first Tag reference value of the user determined
Greatly, objectivity is strong；After marking off user group, according to the first label of users all in user group, determine that business hall periphery is used
The second label of family group, the second label accuracy is high, reference value is big, it can be achieved that according to the second of business hall periphery user group the mark
Label select quotient, selection, paving goods, tune the behaviors such as to pull out and provide decision support for business hall.
Fig. 4 is the structural schematic diagram of another user tag analytical equipment provided by the embodiments of the present application, as shown in Figure 4:
First acquisition unit 1, comprising:
First obtains subelement 11, for obtaining the identity information for entering the user of business hall；
First processing subelement 12, for the identity information according to each user for entering business hall, determination belongs to pre-
User within the scope of if, to obtain the identity information of at least one user within preset range；
Wherein, preset range is that user's inhabitation address is less than pre-determined distance at a distance from business hall, alternatively, preset range is
The frequency that user appears in business hall is higher than the default frequency.
Second acquisition unit 2, comprising:
First obtains subelement 21, for obtaining the historical data corresponding to the identity information prestored according to identity information；
Second obtains subelement 22, for obtaining the operation data of user on the terminal device according to identity information.
Further, operation data includes at least one below: the browsing time of commodity, different types of commodity it is clear
Look at time, buying behavior data.
The second processing unit 4, comprising:
At least one user is divided at least by the first processing subelement 41 for the station address information according to user
One user group；
Second processing subelement 42 carries out at clustering for the first label to the user in each user group
Reason, obtains the second label of each user group.
The second processing unit 4, further includes:
Third handles subelement 43, for according to the corresponding relationship between preset business hall label and the second label, really
Fixed business hall label corresponding with the second label of each user group；
Alternatively, fourth process subelement 44, for using machine learning model to the second label of each user group into
Row processing, obtains business hall label corresponding with the second label of each user group.
The present embodiment enters the identity information of the user of business hall by obtaining；According to each use for entering business hall
The identity information at family determines the user belonged within preset range, to obtain the body of at least one user within preset range
Part information；According to identity information, the behavioral data of each user is obtained, wherein behavioral data includes historical data and operation
Data；Clustering processing is carried out to the behavioral data of each user, obtains the first label of each user, wherein the first mark
Sign the behavior type for characterizing user；According to the station address information of user, at least one user is divided at least one
User group；Clustering processing is carried out to the first label of the user in each user group, obtains the of each user group
Two labels, wherein the second label is used to characterize the behavior type of user group.By the behavior number for obtaining business hall periphery user
According to, determine that the first label of user, behavioral data not only include operation data of the user in business hall, further include storage
Historical data corresponding with subscriber identity information, data and historical data depending on the user's operation, the first of the user determined
Label accuracy is high；It according to station address information, determines using business hall as the user within the preset range of center, is business hall week
The first Tag reference value of side user, the business hall periphery user determined are big, and it is controllable that user tag analyzes workload；According to
Business hall periphery user is divided into different user groups by preset condition, according to the first label of users all in user group, really
The second label for making user group, the second label accuracy determined is high, reference value is big, because of the division item of different user group
Part is clear, and therefore, the corresponding division condition of the second label is clear, is applicable in that scene is clear, can for business hall select quotient, selection,
Paving goods is adjusted and the behaviors such as pulls out and provide effective decision support.
Fig. 5 is a kind of structural schematic diagram of user tag analysis provided by the embodiments of the present application, as shown in figure 5, the application
Embodiment provides a kind of user tag analytical equipment, can be used for executing user tag in Fig. 1-embodiment illustrated in fig. 2 and analyzes
Device action or step, specifically include: processor 501, memory 502 and communication interface 503.
Memory 502, for storing computer program.
Processor 501, for executing the computer program stored in memory 502, to realize Fig. 1-embodiment illustrated in fig. 4
The movement of middle user tag analytical equipment, repeats no more.
Optionally, user tag analytical equipment can also include bus 504.Wherein, processor 501, memory 502 and
Communication interface 503 can be connected with each other by bus 504；Bus 504 can be Peripheral Component Interconnect standard (Peripheral
Component Interconnect, abbreviation PCI) bus or expanding the industrial standard structure (Extended Industry
Standard Architecture, abbreviation EISA) bus etc..Above-mentioned bus 504 can be divided into address bus, data/address bus and
Control bus etc..Only to be indicated with a thick line in Fig. 5, it is not intended that an only bus or a seed type convenient for indicating
Bus.
In the embodiment of the present application, it can mutually be referred to and learnt between the various embodiments described above, same or similar step
And noun no longer repeats one by one.
Alternatively, some or all of above modules can also be embedded in the user tag by way of integrated circuit
It is realized on some chip of analytical equipment.And they can be implemented separately, and also can integrate together.That is the above mould
Block may be configured to implement one or more integrated circuits of above method, such as: one or more specific integrated circuits
(Application Specific Integrated Circuit, abbreviation ASIC), or, one or more microprocessors
(Digital Singnal Processor, abbreviation DSP), or, one or more field programmable gate array (Field
Programmable Gate Array, abbreviation FPGA)
A kind of computer readable storage medium, is stored thereon with computer program, computer program be executed by processor with
Realize above-mentioned processing method.
In the above-described embodiments, can come wholly or partly by software, hardware, firmware or any combination thereof real
It is existing.When implemented in software, it can entirely or partly realize in the form of a computer program product.Computer program product
Including one or more computer instructions.When loading on computers and executing computer program instructions, all or part of real estate
Raw process or function according to the embodiment of the present application.Computer can be general purpose computer, special purpose computer, computer network,
Or other programmable devices.Computer instruction may be stored in a computer readable storage medium, or from a computer
Readable storage medium storing program for executing to another computer readable storage medium transmit, for example, computer instruction can from a web-site,
Computer, user tag analytical equipment or data center are by wired (for example, coaxial cable, optical fiber, Digital Subscriber Line
(digital subscriber line, DSL)) or wireless (for example, infrared, wireless, microwave etc.) mode to another website station
Point, computer, user tag analytical equipment or data center are transmitted.Computer readable storage medium can be computer capacity
Any usable medium that enough accesses or include the integrated user tag analytical equipment of one or more usable mediums, in data
The data storage devices such as the heart.Usable medium can be magnetic medium, (for example, floppy disk, hard disk, tape), optical medium (for example,
) or semiconductor medium (for example, solid state hard disk (solid state disk, SSD)) etc. DVD.
It will be appreciated that in said one or multiple examples, the embodiment of the present application describes those skilled in the art
Function can be realized with hardware, software, firmware or their any combination.It when implemented in software, can be by these
Function storage is in computer-readable medium or as the one or more instructions or code progress on computer-readable medium
Transmission.Computer-readable medium includes computer storage media and communication media, and wherein communication media includes being convenient for from a ground
Any medium of direction another place transmission computer program.Storage medium can be general or specialized computer and can access
Any usable medium.
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 (10)
1. a kind of user tag analysis method based on user group characterized by comprising
Obtain the identity information of at least one user within preset range；
According to the identity information, the behavioral data of each user is obtained, wherein the behavioral data includes history number
According to and operation data；
Clustering processing is carried out to the behavioral data of each user, obtains the first label of each user, wherein
First label is used to characterize the behavior type of user；
Clustering processing is carried out to the first label of each user, obtains the second label of each preset user group,
Wherein, second label is used to characterize the behavior type of user group.
2. the method according to claim 1, wherein described obtain at least one user's within preset range
Identity information, comprising:
Obtain the identity information for entering the user of business hall；
According to the identity information for each user for entering business hall, the user belonged within the preset range is determined, with
The identity information of at least one user within to the preset range；
Wherein, the preset range is that user's inhabitation address is less than pre-determined distance at a distance from business hall, alternatively, the default model
It encloses the frequency for appearing in business hall for user and is higher than the default frequency.
3. the method according to claim 1, wherein obtaining each described user according to the identity information
Behavioral data, comprising:
According to the identity information, the historical data corresponding with the identity information prestored is obtained；
According to the identity information, the operation data of the user on the terminal device is obtained.
4. according to the method described in claim 3, it is characterized in that, the operation data includes at least one below: commodity
Browsing time, the browsing time of different types of commodity, buying behavior data.
5. the method according to claim 1, wherein including station address information in the identity information；To each
The first label of the user carries out clustering processing, obtains the second label of each preset user group, comprising:
According to the station address information of the user, at least one described user is divided at least one described user group；
Clustering processing is carried out the first label of the user in each described user group, obtains each described user group
The second label.
6. method according to claim 1-5, which is characterized in that carried out in the first label to each user
Clustering processing, after obtaining the second label of each preset user group, further includes:
According to the corresponding relationship between preset business hall label and the second label, determining second with each user group
The corresponding business hall label of label；
Alternatively, being handled using second label of the machine learning model each user group, obtain and each institute
State the corresponding business hall label of the second label of user group.
7. a kind of user tag analytical equipment based on user group characterized by comprising
First acquisition unit, for obtaining the identity information of at least one user within preset range；
Second acquisition unit, for obtaining the behavioral data of each user, wherein described according to the identity information
Behavioral data includes historical data and operation data；
First processing units carry out clustering processing for the behavioral data to each user, obtain each described use
First label at family, wherein first label is used to characterize the behavior type of user；
The second processing unit carries out clustering processing for the first label to each user, it is preset to obtain each
Second label of user group, wherein second label is used to characterize the behavior type of user group.
8. device according to claim 7, which is characterized in that first acquisition unit, comprising:
First obtains subelement, for obtaining the identity information for entering the user of business hall；
First processing subelement determines for the identity information according to each user for entering business hall and belongs to described preset
Within the scope of user, to obtain the identity information of at least one user within the preset range；
Wherein, the preset range is that user's inhabitation address is less than pre-determined distance at a distance from business hall, alternatively, the default model
It encloses the frequency for appearing in business hall for user and is higher than the default frequency.
9. a kind of user tag analytical equipment based on user group characterized by comprising include: processor, memory and
Computer program；
Wherein, computer program stores in memory, and is configured as being executed by processor to realize that claim 1-6 such as appoints
One method.
10. a kind of computer readable storage medium, which is characterized in that be stored with computer in the computer readable storage medium
It executes instruction, for realizing the side as described in any one of claim 1 to 6 when the computer executed instructions are executed by processor
Method.
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