CN109493199A - Products Show method, apparatus, computer equipment and storage medium - Google Patents
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Abstract
This application involves a kind of Products Show method, apparatus, computer equipment and storage medium based on big data is related to user and draws a portrait field.Method includes: to obtain the user identifier of user to be recommended, determine classification belonging to user identifier, obtain the corresponding label sequence of classification, the corresponding user information of acquisition user identifier, and according to the corresponding user's portrait label of each label that user information obtains generic, for the determining recommended products corresponding with each user portrait label of user, according to label sequence, the recommendation order of the recommended products of user is obtained, according to the recommendation order, successively recommends corresponding product to user.Using this method, the recommended products determined for user is no longer single, but different recommended products are determined according to different user's portrait labels, it is based on label sequence again, the recommendation order of recommended products has been determined, can sequentially it recommend from multiple dimensions successively to user's recommended products, so that the contents diversification of recommended products.
Description
Technical field
This application involves Internet technical field, more particularly to a kind of Products Show method, apparatus, computer equipment and
Storage medium.
Background technique
Products Show refers to and recommends Related product for user, such as recommends finance and money management product to user.Traditional recommendation
Method is that user recommends interested product according to user property (such as user interest).But the product that this method is recommended is single.
Summary of the invention
Based on this, it is necessary in view of the above technical problems, provide one kind and can be improved the multifarious product of recommended products and push away
Recommend method, apparatus, computer equipment and storage medium.
A kind of Products Show method, which comprises
Obtain the user identifier of user to be recommended；
Determine classification belonging to the user identifier；
Obtain the corresponding label sequence of the classification；
The corresponding user information of the user identifier is obtained, and corresponding according to each label that user information obtains generic
User draw a portrait label；
For the determining recommended products corresponding with each user's portrait label of user；
According to the label sequence, the recommendation order of the recommended products of user is obtained；
According to the recommendation order, successively recommend corresponding product to user.
In another embodiment, the method also includes:
Obtain the user information of each user identifier；
Clustering is carried out to the user information, obtains cluster class belonging to multiple cluster classifications and each user information
Not；
Establish the corresponding relationship of the user identifier and classification.
In another embodiment, the method also includes:
Obtain feature tag of all categories；
Default label of all categories is obtained according to the feature tag；
The default label of the classification is ranked up according to preset rules, obtains label sequence of all categories；
Establish the corresponding relationship of the classification Yu the label sequence.
In another embodiment, the method also includes:
It obtains preset of all categories；
According to user information, classify to user, obtains classification belonging to each user information；
Establish the corresponding relationship of the user identifier and classification.
In another embodiment, described to obtain the corresponding user information of the user identifier, and obtained according to user information
Take the corresponding user of each label of generic draw a portrait label the step of, comprising:
Obtain the corresponding user information of the user identifier；
Obtain each label of classification belonging to user；
According to user information, user property of each user under each label is extracted；
According to the user property and corresponding label, user's portrait label is obtained.
In another embodiment, the label includes interest tags, according to the user property and corresponding label,
The step of obtaining user's portrait label, comprising:
When user property includes the interest attribute of user, the corresponding use of interest tags is obtained according to the interest attribute of user
Family portrait label；
When user property does not include the interest attribute of user, classification belonging to user is obtained；
Obtain the user interest information of the classification；
The corresponding user's portrait label of interest tags is obtained according to the user interest information of the classification.
A kind of Products Show device, described device include:
User obtains module, for obtaining the user identifier of user to be recommended；
Classification obtains module, for determining classification belonging to the user identifier；
Label acquisition module, for obtaining the corresponding label sequence of the classification；
Portrait label acquisition module, for obtaining the corresponding user information of the user identifier, and is obtained according to user information
Take the corresponding user's portrait label of each label of generic；
Recommended products determining module, for for the determining recommended products corresponding with each user's portrait label of user；
Sequence determining module, for obtaining the recommendation order of the recommended products of user according to the label sequence；
Recommending module, for successively recommending corresponding product to user according to the recommendation order.
In another embodiment, described device further include:
Data obtaining module, for obtaining the user information of each user identifier；
Cluster module obtains multiple cluster classifications and each user letter for carrying out clustering to the user information
Cluster classification belonging to breath；
Class relations establish module, for establishing the corresponding relationship of the user identifier and classification.
A kind of computer equipment, including memory and processor, the memory are stored with computer program, and feature exists
In when the processor executes the computer program the step of any one of realization the various embodiments described above the method.
A kind of computer readable storage medium, is stored thereon with computer program, and the computer program is held by processor
The step of method described in any one of the various embodiments described above is realized when row.
The said goods recommended method, device, computer equipment and storage medium determine classification belonging to user, obtain class
Not corresponding label sequence, the corresponding user tag of each label for obtaining generic according to user information are drawn a portrait, and are that user is true
Fixed recommended products corresponding with each portrait label obtains the sequence of the recommended products of user according to label sequence, suitable according to recommending
Sequence successively recommends corresponding product to user.Using this method, the recommended products determined for user is no longer single, but
Different recommended products are determined according to different user's portrait labels, then are based on label sequence, it is determined that the recommendation of recommended products is suitable
Sequence can sequentially recommend from multiple dimensions successively to user's recommended products, so that the contents diversification of recommended products.
Detailed description of the invention
Fig. 1 is the application scenario diagram of Products Show method in one embodiment；
Fig. 2 is the flow diagram of Products Show method in one embodiment；
The flow diagram for the step of Fig. 3 is the corresponding relationship of determining user identifier and classification in one embodiment；
Fig. 4 is flow diagram the step of determining corresponding label sequence of all categories in another embodiment；
The flow diagram for the step of Fig. 5 is the corresponding relationship of determining user identifier and classification in another embodiment；
Fig. 6 is the structural block diagram of Products Show device in one embodiment；
Fig. 7 is the internal structure chart of computer equipment in one embodiment.
Specific embodiment
It is with reference to the accompanying drawings and embodiments, right in order to which the objects, technical solutions and advantages of the application are more clearly understood
The application is further elaborated.It should be appreciated that specific embodiment described herein is only used to explain the application, not
For limiting the application.
Products Show method provided by the present application, can be applied in application environment as shown in Figure 1.Wherein, first eventually
End 102 is communicated with server 104 by network by network, and second terminal 106 passes through net by network and server 104
Network is communicated.First terminal 102 is the user terminal of Products Show party in request, and Products Show party in request is mentioning for recommended products
Supplier, such as bank, bank provide multiple products, need to recommend different products to different users.Second terminal 106 is to produce
The user terminal of product recommendation recipient.Wherein, first terminal 102 and second terminal 106 can be, but not limited to be various personal meters
Calculation machine, laptop, smart phone, tablet computer and portable wearable device, server 104 can use independent service
The server cluster of device either multiple servers composition is realized.
In one embodiment, as shown in Fig. 2, providing a kind of Products Show method, it is applied in Fig. 1 in this way
It is illustrated for server, comprising the following steps:
S202 obtains the user identifier of user to be recommended.
User to be recommended in the present embodiment can be whole users of platform, or institute, product demand recommendation side
Target user is provided.User identifier is the unique identifier of user, can be user account of the user in platform, or
User's used phone number when platform is registered, or the provided cell-phone number when product demand side handles related service
Code.
S204 determines classification belonging to user identifier.
Specifically, classification refers to the classification to user group, and by certain principle of classification, user is classified as to different classes
Not.Wherein, the setting of classification can be by being manually configured according to the type of product to be recommended, can also be according to whole wait divide
The user's information of analysis user is clustered to obtain.Wherein, user information includes the essential information of user, such as region, year
Age etc. further includes the business datum and user behavior data of user.Wherein business datum can be in platform or product demand
Side handles the data of related service, and by taking product demand side is bank as an example, business datum can be user and handle debit in bank
The business datum of the related services such as card, credit card, loan and financing.User behavior data is user in related application, such as
Mobile banking's program of bank or the operated behavioral data for producing row of the application program of platform, as user browse some page,
Some keyword is searched for, some point is clicked and can have respective record in daily record data.
For example, pre-setting classification includes: consumption-orientation, investment-orientation and credit according to the scope of business of product demand side
Type.According to user information, user is assigned under these three classifications.For example, the user has loan documentation by user information,
The user is then divided into credit type.Wherein, classification can be classified using the method for semi-supervised learning.
In another example carrying out similarity analysis according to user information, the user with same and similar degree is gathered in a classification
In, and obtain cluster labels, the similitude having the same of the user in the same classification, it is different classes of in user have it is higher
Diversity.Cluster labels, that is, tag along sort, e.g., consumption-orientation, investment-orientation and credit type.
S206 obtains the corresponding label sequence of classification.
Wherein, the sequence of the corresponding label of each classification is pre-set.Label is to certain a kind of special group or object
A certain feature carry out abstract classification and summary, value (label value) has can classification.For example, for " people " this monoid
" male ", " female " this category feature can be carried out abstract, be referred to as " gender ", " gender " i.e. label by body.Label sequence be
Refer to multiple label arranged in sequence.The dimension of consideration when tag indicator carries out Products Show to the user of the category.
Label sequence is related to the feature tag of classification, and label sequence determines Products Show sequence.Same category of use
Family similitude having the same, feature tag are the summaries to the similitude of user in classification.For example, the spy of the user of consumption-orientation
Sign is, basis consumption more, no wholesale consumer record high using the frequency of credit card purchase.For consumption-orientation classification, feature mark
Label are consumption, settable label: interest, consumption.In another example the user for investment-orientation is characterized in, have investment record or
Factoring purchaser record has certain ability to pay.For investment-orientation classification, feature tag is investment, then settable label:
Interest, consumption, investment, factoring.
S208 obtains the corresponding user information of user identifier, and each label pair of generic is obtained according to user information
The user's portrait label answered.
User's portrait label, refers to according to label and user information, draws a portrait to user, and what is obtained is used to describe user
The label value of feature.For each label, there is corresponding user's portrait label.Such as this label of gender, according to user information,
Its corresponding user draws a portrait label as boy student.Such as this label of interest, according to user information, corresponding user, which draws a portrait, to be marked
Label are tourism.Such as this label of credit, according to user information, corresponding user's portrait label is that credit rating is high.
S210, for the determining recommended products corresponding with each user portrait label of user.
Specifically, matching user portrait label and recommended products are that user determines matched push away according to user's portrait label
Recommend product.Such as according to a user data, determine that there are the user Financial Demands and short-term consumption to be intended to, hobby is vehicle.
Then when Products Show, the label that can be drawn a portrait according to user recommends the financial product to match, such as vehicle insurance, vehicle mortgage loan etc. for it.It pushes away
Recommending product link can be recommended products content and related link address, the webpage link address borrowed such as vehicle mortgage.
Specifically, the step of recommended products corresponding with each user portrait label determining for user, comprising: obtain to be recommended
Product calculates the matching degree of product to be recommended and user's portrait label, matching degree is greater than to the product to be recommended of threshold value, is determined as
The corresponding recommended products of user portrait label.
Specifically, be user recommend product be with user draw a portrait tag match product, according to user draw a portrait label with
The matching degree of product to be recommended will be determined as the recommended products of user with the matched product of user tag, to improve recommendation
Conversion ratio.Such as, user's portrait tag representation user has Financial Demands and short-term consumption intention, and hobby is vehicle, then produces
When product are recommended, the financial product to match, such as vehicle insurance, vehicle mortgage loan etc. can be recommended according to user tag for it.Recommended products chain
It connects and can be recommended products content and related link address, the webpage link address borrowed such as vehicle mortgage.
S212 obtains the recommendation order of the recommended products of user according to label sequence.
Specifically, user's portrait label is the materialization based on user information to the value of label, is drawn a portrait for each user
Tag match is recommended products, and label has label sequence, is based on label sequence, can determine that the recommendation of recommended products is suitable
Sequence.
Recommendation order refers to that recommended products is by timing recommended to the user.In the present embodiment, produced for the recommendation that user determines
Product are no longer single, but determine different recommended products according to different user's portrait labels, then be based on label sequence, are determined
The recommendation order of recommended products can sequentially recommend successively from multiple dimensions to user's recommended products, so that recommended products
Contents diversification.
S214 successively recommends corresponding product to user according to recommendation order.
Specifically, the time interval of settable each Products Show, according to recommendation order, after reaching the time, to user
Recommend the time corresponding product.For example, the time interval of setting is five days, then there are four the recommended products determined for user
According to recommendation order, recommend recommended products relevant to user interest for user, if cuisines discount coupon was user at the 6th day
Recommend recommended products relevant to consumption, such as credit card recommended recommended products relevant to insurance at the 11st day for user, such as
Accident insurance recommended recommended products relevant to wholesale financing, such as large loan at the 16th day for user.
In actual operation, the way of recommendation can be arranged according to the actual demand of product, for example, primary in user's completion
After the conversion task of recommended products, according to recommendation order, second of Products Show is carried out.
And since the sequence of recommended products is according to the setting of user's acceptable degree, Products Show is carried out according to recommendation order,
User be can be improved to the acceptance of recommended products, further increase the conversion ratio of recommended products.
Above-mentioned Products Show method determines classification belonging to user, the corresponding label sequence of classification is obtained, according to user
The corresponding user tag portrait of each label of acquisition of information generic, determines that recommendation corresponding with each portrait label produces for user
Product obtain the sequence of the recommended products of user according to label sequence, according to recommendation order, successively recommend corresponding production to user
Product.Using this method, the recommended products determined for user is no longer single, but is determined according to different user's portrait labels
Different recommended products, then be based on label sequence, it is determined that the recommendation order of recommended products, can sequentially recommend from multiple dimensions according to
It is secondary to user's recommended products so that the contents diversification of recommended products.
In another embodiment, the step of determining the corresponding relationship of user identifier and classification, as shown in figure 3, include with
Lower step:
S302 obtains the user information of each user identifier.
Wherein, user information includes the essential information of user, such as region, age etc., further include user business datum and
User behavior data.Wherein business datum can be to handle the data of related service in platform or product demand side, with product
Party in request is for bank, business datum can be user and handle debit card, credit card, loan industry related to financing etc. in bank
The business datum of business.User behavior data is user in related application, such as Mobile banking's program of bank or platform
The operated behavioral data for producing row of application program, as user browses some page, searches for some keyword, clicks some point
Can there be respective record in daily record data.
S304 carries out clustering to user information, obtains cluster belonging to multiple cluster classifications and each user information
Classification.
Specifically, clustering is a kind of unsupervised learning, is a kind of disaggregated model under the premise of lacking label.When
After we cluster data and after obtaining cluster, generally individually each cluster can be analysed in depth, to obtain more refinement
The result of cause.Specifically, it can be used K mean value (K-Means), spectral clustering (Spectral Clustering), hierarchical clustering
(Hierarchical Clustering) carries out clustering.User with same and similar degree is gathered in a classification, and
Obtain cluster classification, user's similitude having the same in the same classification, it is different classes of in user's phase with higher
It is anisotropic.
S306 establishes the corresponding relationship of user identifier and classification.
According to clustering as a result, cluster classification belonging to determining user identifier, establishes pair of user identifier and classification
It should be related to.
The step of corresponding relationship of above-mentioned determination user identifier and classification, be the preprocessing process of Products Show, in advance
Clustering is carried out to the user information of whole users, obtains multiple cluster classifications, establishes user identifier pass corresponding with classification
System, when needing to determine recommended products for user, according to this corresponding relationship, that is, can determine classification belonging to user identifier.
In another embodiment, this method further includes the steps that determining corresponding label sequence of all categories.Specifically, such as
Shown in Fig. 4, which includes:
S402 obtains feature tag of all categories.
Specifically, user's similitude having the same in the same classification, it is different classes of in user it is with higher
Diversity, feature tag are the summaries to the similitude of user in classification.For example, in a cluster classification, the similitude of user
It is consumption habit, is consumption-orientation, then the feature tag of the user of the category is consumption.In one cluster classification, the phase of user
It is investment history like property, is investment-orientation, then the feature tag of the user of the category is investment.
S404 obtains default label of all categories according to feature tag.
Default label is to be in advance that each feature tag is arranged, when the user for mark classification carries out Products Show
The dimension of consideration.For each feature tag, label is preset by manually according to the user characteristics of feature tag, considering production to be recommended
The type and feature of product, the dimension for being determined as category user progress Products Show are determined.For consumption-orientation classification, feature
Label is consumption, settable label: interest, consumption., can be from interest then when carrying out Products Show, consuming two dimensions is
User's recommended products.In another example the user for investment-orientation is characterized in, there is investment record or factoring purchaser record, have
Certain ability to pay.For investment-orientation classification, feature tag is investment, then settable label: interest, consumption, investment, guarantor
Reason.It is when carrying out Products Show, can is user's recommended products from interest, consumption, investment and factoring four dimensions.
S404 is ranked up each label of classification according to preset rules, obtains label sequence of all categories.
Specifically, label sequence by being ranked up to obtain to label, wherein the rule that label is ranked up can by manually into
Row setting.In one embodiment, default label is ranked up according to user's acceptable degree.Interest tags can be first set, then
Setting consumption label, factoring label and credit label.Since the sequence of recommended products is identical as label sequence, it is thus possible to first to
User recommend with the matched product of interest, then recommend and consume matched product, then recommend the product to match with factoring and
The product to match with credit, to improve the acceptable degree of the recommended products of high consumption.Wherein, user's acceptable degree can
User obtains the feedback of the corresponding Products Show of respective labels in big data.
S406 establishes the corresponding relationship of classification Yu label sequence.
The step of above-mentioned determination corresponding label sequence of all categories, be the preprocessing process of Products Show, in advance to building
Of all categories and label sequence corresponding relationship is found, when needing to determine recommended products for user, according to this corresponding relationship
Determine the corresponding label sequence of the category.
In another embodiment, the step of determining the corresponding relationship of user identifier and classification, as shown in figure 5, include with
Lower step:
S502 is obtained preset of all categories.
In the present embodiment, the setting of classification can be by being manually configured according to the type of product to be recommended.Such as, according to production
The scope of business of product party in request, pre-setting classification includes: consumption-orientation, investment-orientation and credit type.
S504 classifies to user according to user information, obtains classification belonging to each user information.
Specifically, carrying out classification according to user's information can rule-based classifier or artificial neural network
Classify, obtains classification belonging to each user information.According to user information, user is assigned under this pre-set classification.
For example, the user has loan documentation by user information, then the user is divided into credit type.
S506 establishes the corresponding relationship of user identifier and classification.
According to classification results, classification belonging to user identifier is determined, establish the corresponding relationship of user identifier and classification.
The step of corresponding relationship of above-mentioned determination user identifier and classification, be the preprocessing process of Products Show, in advance
Classification is set, classifies to the user information of whole users, establishes the corresponding relationship of user identifier and classification, when needs are use
When family determines recommended products, according to this corresponding relationship, that is, classification belonging to user identifier can determine.
In another embodiment, the corresponding user information of user identifier is obtained, and affiliated class is obtained according to user information
The corresponding user of other each label draw a portrait label the step of, comprising: obtain the corresponding user information of user identifier, obtain user institute
Each label of the classification of category extracts user property of each user under each label according to user information, according to user property and
Corresponding label obtains user's portrait label.
Specifically, according to user information, user property of each user under corresponding label is extracted.Specifically, it sets in advance
The corresponding keyword of each label is set, according to keyword from the user property under corresponding label in user data.For example, name
For the label of consumption, settable next stage label spending amount consumes address, consumes classification.In another example being named as credit
The label of situation, settable junior label, practical refund and is refunded the time at the time at the latest, according to the two times calculating user
Whether refund on time, obtains the credit situation of user.Wherein, the setting of next stage label should table related to user property
Field name it is consistent, so as to accurately extract related data from associated traffic data table or daily record data, marked
The user property signed.
To the user property under each label, probability statistics, for the user property under same label, each row can be carried out
For the probability of generation, it sets the behavior of maximum probability on user's portrait label of label.For example, for consumption label,
Consumption classification may include the classifications such as cuisines, clothing, life payment, if maximum classification is cuisines, settable label is consumption
User draw a portrait label be cuisines.
For another example according to the consumption of user and positioning scenarios, discovery user interest is cuisines, then interest tags are corresponding
User's portrait be cuisines, in another example, according to the Assets of user, it is found that user has more assets, and have loan, then invest
Investment user portrait in label is strong etc. for credit wish.
According to label and user data in the present embodiment, draws a portrait for user and determine user's portrait label.
In another embodiment, label includes interest tags, according to user property and corresponding label, obtains user
The step of portrait label, comprising: when user property includes the interest attribute of user, interest is obtained according to the interest attribute of user
The corresponding user's portrait label of label obtains classification belonging to user, obtains when user property does not include the interest attribute of user
The user interest information for taking classification obtains the corresponding user's portrait label of interest tags according to the user interest information of classification.
In the present embodiment, when user interest attribute can be extracted according to user property, determined according to user interest attribute
The user of interest tags draws a portrait.When user interest attribute can not be extracted according to user property, according to same cluster classification
The user interest information of user determines user's portrait of the interest tags of the user.
It should be understood that although each step in the flow chart of Fig. 2-5 is successively shown according to the instruction of arrow,
These steps are not that the inevitable sequence according to arrow instruction successively executes.Unless expressly stating otherwise herein, these steps
Execution there is no stringent sequences to limit, these steps can execute in other order.Moreover, at least one in Fig. 2-5
Part steps may include that perhaps these sub-steps of multiple stages or stage are not necessarily in synchronization to multiple sub-steps
Completion is executed, but can be executed at different times, the execution sequence in these sub-steps or stage is also not necessarily successively
It carries out, but can be at least part of the sub-step or stage of other steps or other steps in turn or alternately
It executes.
In one embodiment, as shown in fig. 6, providing a kind of Products Show device, comprising: user obtains module, class
It Huo Qu module, label acquisition module, portrait label acquisition module, recommended products determining module and sequence determining module, in which:
User obtains module 602, for obtaining the user identifier of user to be recommended.
Classification obtains module 604, for determining classification belonging to user identifier.
Label acquisition module 606, for obtaining the corresponding label sequence of classification.
Portrait label acquisition module 608, for obtaining the corresponding user information of user identifier, and obtains according to user information
The corresponding user's portrait label of each label of generic.
Recommended products determining module 610, for being the determining recommended products corresponding with each user portrait label of user.
Sequence determining module 612, for obtaining the recommendation order of the recommended products of user according to label sequence；
Recommending module 614, for successively recommending corresponding product to user according to the recommendation order.
The said goods recommendation apparatus determines classification belonging to user, obtains the corresponding label sequence of classification, is believed according to user
Breath obtains the corresponding user tag portrait of each label of generic, determines that recommendation corresponding with each portrait label produces for user
Product obtain the sequence of the recommended products of user according to label sequence, according to recommendation order, successively recommend corresponding production to user
Product.Using this method, the recommended products determined for user is no longer single, but is determined according to different user's portrait labels
Different recommended products, then be based on label sequence, it is determined that the recommendation order of recommended products, can sequentially recommend from multiple dimensions according to
It is secondary to user's recommended products so that the contents diversification of recommended products.
In another embodiment, Products Show device further include:
Data obtaining module, for obtaining the user information of each user identifier.
Cluster module obtains multiple cluster classifications and each user information institute for carrying out clustering to user information
The cluster classification of category；
Class relations establish module, for establishing the corresponding relationship of user identifier and classification.
In another embodiment, Products Show device further include:
Label acquisition module, for obtaining feature tag of all categories；
Presetting module obtains module, for obtaining default label of all categories according to feature tag；
Label sequence obtains module, is ranked up, is obtained of all categories according to preset rules for the default label to classification
Label sequence；
Label ordinal relation establishes module, for establishing the corresponding relationship of classification Yu label sequence.
In another embodiment, Products Show device further include:
Classification obtains module, preset of all categories for obtaining；
Categorization module, for classifying to user, obtaining classification belonging to each user information according to user information；
Class relations establish module, for establishing the corresponding relationship of user identifier and classification.
In another embodiment, portrait label acquisition module, comprising:
Attribute obtains module, for obtaining the corresponding user information of user identifier, obtains each mark of classification belonging to user
Label, according to user information, extract user property of each user under each label；
Portrait module, for obtaining user's portrait label according to user property and corresponding label.
In another embodiment, label includes interest tags, module of drawing a portrait, for including the emerging of user when user property
When interesting attribute, the corresponding user's portrait label of interest tags is obtained according to the interest attribute of user；
When user property does not include the interest attribute of user, classification belonging to user is obtained, the user for obtaining classification is emerging
Interesting information obtains the corresponding user's portrait label of interest tags according to the user interest information of classification.
Specific about Products Show device limits the restriction that may refer to above for Products Show method, herein not
It repeats again.Modules in the said goods recommendation apparatus can be realized fully or partially through software, hardware and combinations thereof.On
Stating each module can be embedded in the form of hardware or independently of in the processor in computer equipment, can also store in a software form
In memory in computer equipment, the corresponding operation of the above modules is executed in order to which processor calls.
In one embodiment, a kind of computer equipment is provided, which can be terminal, internal structure
Figure can be as shown in Figure 7.The computer equipment includes processor, the memory, network interface, display connected by system bus
Screen and input unit.Wherein, the processor of the computer equipment is for providing calculating and control ability.The computer equipment is deposited
Reservoir includes non-volatile memory medium, built-in storage.The non-volatile memory medium is stored with operating system and computer journey
Sequence.The built-in storage provides environment for the operation of operating system and computer program in non-volatile memory medium.The calculating
The network interface of machine equipment is used to communicate with external terminal by network connection.When the computer program is executed by processor with
Realize a kind of Products Show method.The display screen of the computer equipment can be liquid crystal display or electric ink display screen,
The input unit of the computer equipment can be the touch layer covered on display screen, be also possible to be arranged on computer equipment shell
Key, trace ball or Trackpad, can also be external keyboard, Trackpad or mouse etc..
It will be understood by those skilled in the art that structure shown in Fig. 7, only part relevant to application scheme is tied
The block diagram of structure does not constitute the restriction for the computer equipment being applied thereon to application scheme, specific computer equipment
It may include perhaps combining certain components or with different component layouts than more or fewer components as shown in the figure.
In one embodiment, a kind of computer equipment, including memory and processor are provided, which is stored with
Computer program, the processor perform the steps of when executing computer program
Obtain the user identifier of user to be recommended；
Determine classification belonging to user identifier；
Obtain the corresponding label sequence of classification；
The corresponding user information of user identifier is obtained, and obtains the corresponding use of each label of generic according to user information
Family portrait label；
For the determining recommended products corresponding with each user portrait label of user；
According to label sequence, the recommendation order of the recommended products of user is obtained；
According to recommendation order, successively recommend corresponding product to user.
In one embodiment, it is also performed the steps of when processor executes computer program
Obtain the user information of each user identifier；
Clustering is carried out to user information, obtains cluster classification belonging to multiple cluster classifications and each user information；
Establish the corresponding relationship of user identifier and classification.
In one embodiment, it is also performed the steps of when processor executes computer program
Obtain feature tag of all categories；
Default label of all categories is obtained according to feature tag；
The default label of classification is ranked up according to preset rules, obtains label sequence of all categories；
Establish the corresponding relationship of classification Yu label sequence.
In one embodiment, it is also performed the steps of when processor executes computer program
It obtains preset of all categories；
According to user information, classify to user, obtains classification belonging to each user information；
Establish the corresponding relationship of user identifier and classification.
In one embodiment, the corresponding user information of user identifier is obtained, and generic is obtained according to user information
The corresponding user of each label draw a portrait label the step of, comprising:
Obtain the corresponding user information of user identifier；
Obtain each label of classification belonging to user；
According to user information, user property of each user under each label is extracted；
According to user property and corresponding label, user's portrait label is obtained.
In one embodiment, label includes interest tags, according to user property and corresponding label, obtains user's picture
As the step of label, comprising:
When user property includes the interest attribute of user, the corresponding use of interest tags is obtained according to the interest attribute of user
Family portrait label；
When user property does not include the interest attribute of user, classification belonging to user is obtained；
Obtain the user interest information of classification；
The corresponding user's portrait label of interest tags is obtained according to the user interest information of classification.
In one embodiment, a kind of computer readable storage medium is provided, computer program is stored thereon with, is calculated
Machine program performs the steps of when being executed by processor
Obtain the user identifier of user to be recommended；
Determine classification belonging to user identifier；
Obtain the corresponding label sequence of classification；
The corresponding user information of user identifier is obtained, and obtains the corresponding use of each label of generic according to user information
Family portrait label；
For the determining recommended products corresponding with each user portrait label of user；
According to label sequence, the recommendation order of the recommended products of user is obtained；
According to recommendation order, successively recommend corresponding product to user.
In one embodiment, it is also performed the steps of when processor executes computer program
Obtain the user information of each user identifier；
Clustering is carried out to user information, obtains cluster classification belonging to multiple cluster classifications and each user information；
Establish the corresponding relationship of user identifier and classification.
In one embodiment, it is also performed the steps of when processor executes computer program
Obtain feature tag of all categories；
Default label of all categories is obtained according to feature tag；
The default label of classification is ranked up according to preset rules, obtains label sequence of all categories；
Establish the corresponding relationship of classification Yu label sequence.
In one embodiment, it is also performed the steps of when processor executes computer program
It obtains preset of all categories；
According to user information, classify to user, obtains classification belonging to each user information；
Establish the corresponding relationship of user identifier and classification.
In one embodiment, the corresponding user information of user identifier is obtained, and generic is obtained according to user information
The corresponding user of each label draw a portrait label the step of, comprising:
Obtain the corresponding user information of user identifier；
Obtain each label of classification belonging to user；
According to user information, user property of each user under each label is extracted；
According to user property and corresponding label, user's portrait label is obtained.
In one embodiment, label includes interest tags, according to user property and corresponding label, obtains user's picture
As the step of label, comprising:
When user property includes the interest attribute of user, the corresponding use of interest tags is obtained according to the interest attribute of user
Family portrait label；
When user property does not include the interest attribute of user, classification belonging to user is obtained；
Obtain the user interest information of classification；
The corresponding user's portrait label of interest tags is obtained according to the user interest information of classification.
Those of ordinary skill in the art will appreciate that realizing all or part of the process in above-described embodiment method, being can be with
Relevant hardware is instructed to complete by computer program, the computer program can be stored in a non-volatile computer
In read/write memory medium, the computer program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein,
To any reference of memory, storage, database or other media used in each embodiment provided herein,
Including non-volatile and/or volatile memory.Nonvolatile memory may include read-only memory (ROM), programming ROM
(PROM), electrically programmable ROM (EPROM), electrically erasable ROM (EEPROM) or flash memory.Volatile memory may include
Random access memory (RAM) or external cache.By way of illustration and not limitation, RAM is available in many forms,
Such as static state RAM (SRAM), dynamic ram (DRAM), synchronous dram (SDRAM), double data rate sdram (DDRSDRAM), enhancing
Type SDRAM (ESDRAM), synchronization link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM
(RDRAM), direct memory bus dynamic ram (DRDRAM) and memory bus dynamic ram (RDRAM) etc..
Each technical characteristic of above embodiments can be combined arbitrarily, for simplicity of description, not to above-described embodiment
In each technical characteristic it is all possible combination be all described, as long as however, the combination of these technical characteristics be not present lance
Shield all should be considered as described in this specification.
The several embodiments of the application above described embodiment only expresses, the description thereof is more specific and detailed, but simultaneously
It cannot therefore be construed as limiting the scope of the patent.It should be pointed out that coming for those of ordinary skill in the art
It says, without departing from the concept of this application, various modifications and improvements can be made, these belong to the protection of the application
Range.Therefore, the scope of protection shall be subject to the appended claims for the application patent.
Claims (10)
1. a kind of Products Show method, which comprises
Obtain the user identifier of user to be recommended；
Determine classification belonging to the user identifier；
Obtain the corresponding label sequence of the classification；
The corresponding user information of the user identifier is obtained, and obtains the corresponding use of each label of generic according to user information
Family portrait label；
For the determining recommended products corresponding with each user's portrait label of user；
According to the label sequence, the recommendation order of the recommended products of user is obtained；
According to the recommendation order, successively recommend corresponding product to user.
2. the method according to claim 1, wherein the method also includes:
Obtain the user information of each user identifier；
Clustering is carried out to the user information, obtains cluster classification belonging to multiple cluster classifications and each user information；
Establish the corresponding relationship of the user identifier and classification.
3. according to the method described in claim 2, it is characterized in that, the method also includes:
Obtain feature tag of all categories；
Default label of all categories is obtained according to the feature tag；
The default label of the classification is ranked up according to preset rules, obtains label sequence of all categories；
Establish the corresponding relationship of the classification Yu the label sequence.
4. the method according to claim 1, wherein the method also includes:
It obtains preset of all categories；
According to user information, classify to user, obtains classification belonging to each user information；
Establish the corresponding relationship of the user identifier and classification.
5. the method according to claim 1, wherein described obtain the corresponding user information of the user identifier,
And according to the corresponding user of each label that user information obtains generic draw a portrait label the step of, comprising:
Obtain the corresponding user information of the user identifier；
Obtain each label of classification belonging to user；
According to user information, user property of each user under each label is extracted；
According to the user property and corresponding label, user's portrait label is obtained.
6. according to method described in right 5, which is characterized in that the label includes interest tags, according to the user property with
And corresponding label, obtain user draw a portrait label the step of, comprising:
When user property includes the interest attribute of user, the corresponding user of interest tags is obtained according to the interest attribute of user and is drawn
As label；
When user property does not include the interest attribute of user, classification belonging to user is obtained；
Obtain the user interest information of the classification；
The corresponding user's portrait label of interest tags is obtained according to the user interest information of the classification.
7. a kind of Products Show device, which is characterized in that described device includes:
User obtains module, for obtaining the user identifier of user to be recommended；
Classification obtains module, for determining classification belonging to the user identifier；
Label acquisition module, for obtaining the corresponding label sequence of the classification；
Portrait label acquisition module obtains institute for obtaining the corresponding user information of the user identifier, and according to user information
Belong to the corresponding user's portrait label of each label of classification；
Recommended products determining module, for for the determining recommended products corresponding with each user's portrait label of user；
Sequence determining module, for obtaining the recommendation order of the recommended products of user according to the label sequence；
Recommending module, for successively recommending corresponding product to user according to the recommendation order.
8. device according to claim 7, which is characterized in that described device further include:
Data obtaining module, for obtaining the user information of each user identifier；
Cluster module obtains multiple cluster classifications and each user information institute for carrying out clustering to the user information
The cluster classification of category；
Class relations establish module, for establishing the corresponding relationship of the user identifier and classification.
9. a kind of computer equipment, including memory and processor, the memory are stored with computer program, feature exists
In the step of processor realizes any one of claims 1 to 6 the method when executing the computer program.
10. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the computer program
The step of method described in any one of claims 1 to 6 is realized when being executed by processor.
Priority Applications (1)
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| CN201910007061.3A CN109493199A (en) | 2019-01-04 | 2019-01-04 | Products Show method, apparatus, computer equipment and storage medium |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910007061.3A CN109493199A (en) | 2019-01-04 | 2019-01-04 | Products Show method, apparatus, computer equipment and storage medium |
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| CN109493199A true CN109493199A (en) | 2019-03-19 |
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| CN201910007061.3A Pending CN109493199A (en) | 2019-01-04 | 2019-01-04 | Products Show method, apparatus, computer equipment and storage medium |
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