CN108566615A - Information-pushing method, device and client - Google Patents
Information-pushing method, device and client Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0255—Targeted advertisements based on user history
- G06Q30/0256—User search
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0261—Targeted advertisements based on user location
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/52—Network services specially adapted for the location of the user terminal
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/55—Push-based network services
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Abstract
A kind of information-pushing method of this specification embodiment offer, device and client.This method includes：Obtain the location information of target user；The hobby degree of association based on the pushed information within the scope of the push corresponding to the location information and between target user chooses target push information from the pushed information, and the hobby degree of association can characterize fancy grade of the user to pushed information；The target push information is pushed to the target user.
Description
Technical field
This specification embodiment is related to field of location service technology, more particularly to a kind of information-pushing method, device and visitor
Family end.
Background technology
With the development of mobile communication technology and universal, location based service (LBS, the Location- of computer technology
Based Service) technology coming into people’s lives.In the application of LBS technologies, radio communication network can be passed through
(such as GSM nets, CDMA nets) or external positioning method (such as GPS) obtain the location information (geographical coordinate, or big of mobile terminal user
Ground coordinate), and then the related service information near its present position information is provided for the mobile terminal user, for example search institute
The preferential action message of hotel, movie theatre, shopping plaza of the geographic vicinity residing for mobile terminal etc. is stated, and the information is pushed away
It send to mobile terminal for selection by the user.
In the prior art after by being positioned the location information to obtain mobile terminal user to mobile terminal, generally
The pushed information of a certain range of businessman near user current location information can be obtained, then, directly by the pushed information
It is pushed to user, the information of push is often stereotyped, not targetedly, user is caused to need from a large amount of invalid information
The brush choosing for carrying out effective information, not only causes to harass, user experience is deteriorated to user；User is low to shop rate simultaneously, substantially reduces
The validity of information push.Accordingly, it is desirable to provide more effective scheme.
Invention content
The purpose of this specification embodiment is to provide a kind of information-pushing method, device and client, ensure that push letter
The validity of breath improves user to shop rate, improves user experience.
This specification embodiment is realized in：
A kind of information-pushing method, including：
The location information for obtaining target user, determines the pushed information within the scope of the push corresponding to the location information；
Based on the hobby degree of association between the pushed information and the target user mesh is chosen from the pushed information
Mark pushed information, fancy grade of the hobby association table requisition family to pushed information；
The target push information is pushed to the target user.
A kind of information push-delivery apparatus, including：
Position information acquisition module, the location information for obtaining target user；
First pushed information determining module, for determining that the push within the scope of the push corresponding to the location information is believed
Breath；
Second pushed information determining module, for being associated with based on the hobby between the pushed information and the target user
Degree chooses target push information, hobby journey of the hobby association table requisition family to pushed information from the pushed information
Degree；
Info push module, for the target push information to be pushed to the target user.
A kind of information push client, including processor and memory, the memory storage are executed by the processor
Computer program instructions, the computer program instructions include：
The location information for obtaining target user, determines the pushed information within the scope of the push corresponding to the location information；
Based on the hobby degree of association between the pushed information and the target user mesh is chosen from the pushed information
Mark pushed information, fancy grade of the hobby association table requisition family to pushed information；
The target push information is pushed to the target user.
As seen from the above, this specification one or more embodiment is by combining the location information of user and characterizing user couple
The hobby degree of association of the fancy grade of pushed information can be determined to meet what customer consumption was liked near user position
The pushed information of businessman ensure that the validity of pushed information, so can greatly improve user to shop rate；Meanwhile recommending
User can be saved and select the time to the brush of effective information by meeting the pushed information of the businessman of customer consumption hobby, improve user's body
It tests.
Description of the drawings
In order to illustrate more clearly of this specification one or more embodiment or technical solution in the prior art, below will
A brief introduction will be made to the drawings that need to be used in the embodiment or the description of the prior art, it should be apparent that, in being described below
Attached drawing is only some embodiments described in this specification, for those of ordinary skill in the art, is not paying creation
Property labour under the premise of, other drawings may also be obtained based on these drawings.
Fig. 1 is a kind of flow diagram of the embodiment for the information-pushing method that this specification provides；
Fig. 2 be this specification provide based on the hobby degree of association between the pushed information and the target user from institute
State a kind of flow diagram for embodiment that target push information is chosen in pushed information；
Fig. 3 be this specification provide based on the hobby degree of association between the pushed information and the target user from institute
State the flow diagram for another embodiment that target push information is chosen in pushed information；
Fig. 4 be this specification provide based on the hobby degree of association between the pushed information and the target user from institute
State the flow diagram for another embodiment that target push information is chosen in pushed information；
Fig. 5 be this specification provide based on the hobby degree of association between the pushed information and the target user from institute
State the flow diagram for another embodiment that target push information is chosen in pushed information；
Fig. 6 is a kind of schematic diagram for embodiment using the training of probability identification model and application that this specification provides；
Fig. 7 is a kind of schematic diagram of embodiment of the target push information for the push that this specification provides；
Fig. 8 is the schematic diagram of another embodiment of the target push information for the push that this specification embodiment provides；
Fig. 9 is a kind of structural schematic diagram of the embodiment for the information push-delivery apparatus that this specification provides；
Figure 10 is the schematic configuration diagram that client is pushed according to the information of an exemplary embodiment of this specification.
Specific implementation mode
A kind of information-pushing method of this specification embodiment offer, device and client.
In order to make those skilled in the art more fully understand the technical solution in this specification, below in conjunction with this explanation
Attached drawing in book embodiment is clearly and completely described the technical solution in this specification embodiment, it is clear that described
Embodiment be only this specification a part of the embodiment, instead of all the embodiments.The embodiment of base in this manual,
Every other embodiment obtained by those of ordinary skill in the art without making creative efforts, should all belong to
The range of this specification protection.
A kind of a kind of specific embodiment of information-pushing method of this specification introduced below.Fig. 1 is that this specification provides
A kind of flow diagram of embodiment of information-pushing method, present description provides the methods as described in embodiment or flow chart
Operating procedure, but may include either more or less operating procedure without performing creative labour based on routine.In embodiment
The step of enumerating sequence is only a kind of mode in numerous step execution sequences, does not represent and unique executes sequence.In reality
In system or client production when executing, can either method shown in the drawings sequence be executed or is held parallel according to embodiment
Row (such as environment of parallel processor or multiple threads).It is specific as shown in Figure 1, the method may include：
S102：The location information for obtaining target user, determines the push within the scope of the push corresponding to the location information
Information.
In practical applications, on line or offline businesses can by Internet service platform (hereinafter referred to as service platform) into
The push of action message is sold to improve user to shop rate in field headquarters.It, can be based on the location information of user in this specification embodiment
By the information recommendation of the relevant user preferences in user position to user, to ensure that the information pushed to user preferably meets
User demand, improve information push validity and user to shop rate.
Specifically, target user described in this specification embodiment may include any user on service platform.Specifically
, the location information can include but is not limited to the scene locations such as longitude and latitude location information, position the country one belongs to, city, commercial circle
Information etc., the location information can pass through radio communication network (such as GSM nets, CDMA nets) or external positioning (such as GPS)
Mode obtains.
In practical applications, when the information for carrying out user's permanent residence pushes processing, it is contemplated that user can more like selection
It is consumed in the closer place of distance.User's permanent residence can be chosen in this specification embodiment nearby as push range.Phase
It answers, the push range corresponding to the location information may include the range apart from the location information pre-determined distance, or away from
Commercial circle from the location information pre-determined distance.In other scenes, the scene that user occurs once in a while, such as user are arrived
The scene that certain city or some country travel, go on business.Corresponding city or country can be chosen as push range.Correspondingly,
Push range corresponding to the location information includes the location information location.Specifically, location here can wrap
Include city or country.
Specifically, the pushed information corresponding to the push range may include that the push range region corresponds to quotient
The default activity service information at family etc., such as information on services, favor information etc..
S104：It is selected from the pushed information based on the hobby degree of association between the pushed information and the target user
Take target push information, fancy grade of the hobby association table requisition family to pushed information.
In this specification embodiment, the hobby degree of association can characterize fancy grade of the user to pushed information.Hobby
The degree of association is higher, and characterization user is higher to the fancy grade of corresponding pushed information.
Specifically, the hobby degree of association at least may include one of the following：
The social degree of association between consumption user corresponding to the target user and the pushed information；
Similarity between the history consumption information and the pushed information of the target user；
Like the consumption of group in consumption user corresponding to the pushed information for same consumption with the target user
Cluster similarity between user and the target user；
User's portrait information and consumption preference information based on the target user carry out the institute trained using probability
It states target user and probability is used to the pushed information.
In some embodiments, between the preferable user of social networks, often there is same or analogous consumption hobby.
Therefore, can using the social degree of association between user as characterization user to the hobby degree of association of the fancy grade of pushed information,
In specific embodiment, as shown in Fig. 2, when the hobby degree of association is corresponding to the target user and the pushed information
When the social degree of association between consumption user, the hobby degree of association based between the pushed information and the target user
Target push information is chosen from the pushed information may include：
S202：It is determined based on the social networks between the consumption user corresponding to the target user and the pushed information
The social degree of association between consumption user corresponding to the target user and the pushed information；
S204：The social degree of association between the target user is more than or equal to the pushed information of first threshold as institute
State target push information.
Specifically, the consumption user corresponding to the pushed information may include the retail shop corresponding to the pushed information
Carry out the user of post-consumer.
Specifically, the social degree of association in this specification embodiment between user may include social association journey between user
The characterization of degree characterizes.Specifically, social correlation degree between user can be lived by good friend each other, the same area,
Same school such as goes to school at the social networks reflection, and when the social networks between user are more, the corresponding social activity degree of association is higher.Accordingly
, in practical applications, the characterization corresponding to the social correlation degree between user can be characterized and pass through default rule
It is quantified as a particular value.In turn, the value of the quantization can be subsequently utilized to characterize the corresponding social degree of association.In a common example
In son, the value of some possible dimension be " in ", then can quantify the binary value or hexadecimal that the character is its ASCII character
Value.
In further embodiments, user's history consumption information can often reflect the consumption hobby of the user.Correspondingly,
It can be using the similarity between the history consumption information of target user and the pushed information as table in this specification embodiment
Take over the hobby degree of association of the family to the fancy grade of pushed information for use.In specific embodiment, as shown in figure 3, when the hobby is closed
It is described to be based on the push when connection degree is the similarity between the history consumption information and the pushed information of the target user
The hobby degree of association between information and the target user chooses target push information from the pushed information：
S302：Determine the similarity between the history consumption information of the target user and the pushed information；
S304：The similarity of history consumption information with the target user is more than or equal to the pushed information of second threshold
As the target push information.
Specifically, history consumption information described in this specification embodiment may include the Business Information of customer consumption state,
The favor information that user got, the merchandise news etc. bought.It is similar between the history consumption information and pushed information
Degree can reflect the similarity degree between user's history consumption hobby and pushed information.Specifically, the history consumption information with
Similarity between pushed information may include being determined by the collaborative filtering in machine learning.In a specific implementation
In example, similarity between history consumption information and pushed information can be two information feature vector between cosine it is similar
Degree, when the numerical value for the cosine similarity that the feature vector based on two information is calculated is bigger, can indicate two information it
Between similarity it is better, can conversely, the numerical value for the cosine similarity being calculated when the feature vector based on two information is smaller
To indicate that the similarity between two information is poorer.
Certainly, the similarity in this specification embodiment between two information is not limited only to above-mentioned cosine similarity,
Can also in addition, in some cases, the similarity may not be numerical value, but be including Pearson correlation coefficient etc.
The characterization of similarity degree or trend between user's history consumption hobby and pushed information characterizes, in this case, can be with
By default rule so that the content of characterization characterization is quantified as a particular value.In turn, the quantization can subsequently be utilized
Similarity degree between value two information of characterization.In a common example, the value of some possible dimension be " in ", then may be used
With quantify the character be its ASCII character binary value or hexadecimal value, the described two information of this specification embodiment it
Between similarity be not limited with above-mentioned.
In further embodiments, can by the consumption user corresponding to pushed information with the target user be it is same
Cluster similarity between the consumption user and the target user of consumption hobby group is as characterization user to pushed information
The hobby degree of association of fancy grade, in specific embodiment, as shown in figure 4, when the hobby degree of association is the pushed information
With the target user be in corresponding consumption user same consumption like group consumption user and the target user it
Between cluster similarity when, the hobby degree of association based between the pushed information and the target user is from the push
Target push information is chosen in information may include：
S402：It determines in the consumption user corresponding to the pushed information and likes group in same consumption with the target user
The user of group, wherein consumption hobby group is that the feature vector of the consumption preference information based on characterization user clusters
Analysis determination；
S404：Calculate the user in the same consumption hobby group and the cluster similarity between the target user；
S406：Cluster similarity between the target user is more than or equal to the pushed information of third threshold value as institute
State target push information.
Specifically, in this specification embodiment, the consumption preference information of the user may include the history consumption of user
Information and the preferential click information of historical search information, history etc. can reflect the information of customer consumption hobby.The consumption hobby
The consumption preference information of user can be quantified as particular value by the feature vector of information based on default quantizing rule；Then, it is based on
The feature vector of the consumption preference information of particular value structure characterization user after quantization；
Specifically, in view of that can reflect that the consumption preference information of customer consumption hobby may include a variety of different types of
The module of information, the particular value after different types of consumption preference information quantization is different, can be in this specification embodiment
Particular value after quantization is standardized, and based on the consumption happiness of the particular value structure characterization user after standardization
The feature vector of good information.
Further, determine characterization user consumption preference information feature vector after, can based on obtain feature to
Amount carries out clustering processing.Specifically, the processing of clustering described in this specification embodiment can include but is not limited to adopt
With：DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clusters are calculated
Method or k-means clustering algorithms carry out clustering processing.
In addition, the cluster similarity between user can reflect between user the similarity degree for consuming hobby here.One
In a specific embodiment, cluster similarity between user can be the consumption preference information of characterization user feature vector it
Between cosine similarity can indicate corresponding when the numerical value for the cosine similarity being calculated based on two feature vectors is bigger
Cluster similarity between two users is better；Conversely, when the number for the cosine similarity being calculated based on two feature vectors
It is worth smaller, can indicates that the cluster similarity between corresponding two users is poorer.
Certainly, it is similar to be not limited only to above-mentioned cosine for the cluster similarity in this specification embodiment between two users
Degree, can also including Pearson correlation coefficient etc., in addition, in some cases, the cluster similarity may not be numerical value, and
It is that the characterization characterization for the similarity degree or trend that hobby is only consumed between user in this case can be by default
Rule make the characterization characterize content be quantified as a particular value.In turn, the value characterization two of the quantization can subsequently be utilized
The similarity degree of consumption hobby between a user.In a common example, the value of some possible dimension be " in ", then
It can quantify the binary value or hexadecimal value that the character is its ASCII character, the described two users' of this specification embodiment
Between cluster similarity be not limited with above-mentioned.
In further embodiments, by the portrait information of the user based on target user and preference information can be consumed into enforcement
Use hobby using probability as characterization user to pushed information of the target user that probability is trained to the pushed information
The hobby degree of association of degree, in specific embodiment, as shown in figure 5, when the hobby degree of association is described based on target user
User draw a portrait information and consumption preference information is carried out the target user trained using probability and makes to the pushed information
When with probability, the hobby degree of association based between the pushed information and the target user is selected from the pushed information
The target push information is taken to may include：
S502：User's portrait information, consumption preference information and the pushed information input of the target user are used
Probability identification model is trained, and is obtained the target user and is used probability to the pushed information；Wherein, described using general
Rate identification model is to draw a portrait information, consumption preference information and sample of users to pushing away to the user of sample of users based on machine learning
Deliver letters breath feedback information be trained it is determining.
S504：Probability will be used to be more than or equal to the pushed information of the 4th threshold value as the target push information.
Specifically, the user draws a portrait, information may include the basic personal information of user, such as gender, occupational information, religion
Educate information etc..The consumption preference information of the user may include the history consumption information and historical search information, history of user
Preferential click information etc. can reflect the information of customer consumption hobby.
Specifically, machine learning here can include but is not limited to convolutional neural networks, logistic regression algorithm etc..One
In a specific embodiment, with using convolutional neural networks to the user of sample of users draw a portrait information, consumption preference information and
Sample of users to the feedback information of pushed information be trained using for probability identification model, specifically can be with
Include the following steps：
User's portrait information, consumption preference information and the pushed information for mixing the sample with family input pre-set convolutional Neural
Network is trained；
Adjust the use that currently exports of the parameter up to the convolutional neural networks of each layer in the convolutional neural networks
Probability is matched with default using probability, using current convolutional neural networks as using probability identification model.
Specifically, sample of users may include searching for the history push user of pushed information.In addition, described default using general
Rate can be configured the feedback information to pushed information according to sample of users, such as user (pushes away a certain discount coupon
Deliver letters breath) it clicks and uses, the use of probability can be 1 correspondingly, default；For another example user is to a certain discount coupon, (push is believed
Breath) it clicks but is not used, correspondingly, it can be 0.5 to preset using probability；For another example user is to a certain discount coupon, (push is believed
Breath) it does not click on and uses, correspondingly, it can be 0 to preset using probability.
As shown in fig. 6, a kind of embodiment using the training of probability identification model and application that Fig. 6, which is this specification, to be provided
Schematic diagram.6 as it can be seen that obtaining user's portrait information, consumption preference information and the sample of users based on sample of users from figure
After the use probability identification model being trained to the feedback information of pushed information, subsequently, by a new user
User draw a portrait information, consumption preference information input this use probability identification model, this can be exported using probability identification model
The new user uses probability to corresponding recommendation information.
Further, in this specification embodiment, it is described when the hobby degree of association include at least it is above-mentioned social activity the degree of association,
Similarity, cluster similarity and when using two kinds in probability, due to the social degree of association, similarity, cluster similarity and use
Probability metrics standard is not necessarily identical.It therefore, can be similar to the social degree of association, similarity, cluster in this specification embodiment
Degree is standardized using probability, and in the laggard weighted sum processing of standardization, by the result after weighted sum
As the hobby degree of association between the target user and pushed information.
Correspondingly, the method can also include：
When characterize user to the hobby degree of association of the fancy grade of pushed information is multiple when, determine the multiple happiness respectively
The weight coefficient of the good degree of association is weighted read group total to the multiple hobby degree of association, using the result being calculated as
The hobby degree of association between the pushed information and the target user；
Specifically, the social degree of association, similarity, cluster similarity and the weight system using probability in this specification embodiment
Number can be configured the influence degree of customer consumption hobby in conjunction in practical application, and the social degree of association, similarity, cluster
The weight coefficient of similarity and use probability is directly proportional to the influence degree liked customer consumption.
In addition, it is necessary to illustrate, in this specification embodiment, first threshold, second threshold, third threshold value and the 4th threshold
Value can be configured in conjunction with practical situations.
S106：The target push information is pushed to the target user.
In this specification embodiment, after determining target push information, target push information can be pushed to described
Target user.In the particular embodiment, as shown in fig. 7, Fig. 7 is the one of the target push information for the push that this specification provides
The schematic diagram of kind embodiment.From figure 7, it is seen that when pushing target push information, can be shown in conjunction with the location information of user
Push official documents and correspondence information including target push information, to reach better user experience.Subsequently, user is by clicking official documents and correspondence letter
Breath can obtain corresponding target push information (Suzhou gardens admission ticket discount coupon).
It the target push information be pushed to the target user may include correspondingly, described：It will include the mesh
The push official documents and correspondence information of mark pushed information is pushed to the target user.
Specifically, can also include the interactions such as presetting interactive information etc., for example registering, chat in the push official documents and correspondence information
Information.
In further embodiments, when the target push information is multiple, the method can also include：
Based on the hobby degree of association between the target push information and the target user to the target push information
It is ranked up；
Correspondingly, described, the target push information is pushed to the target user includes by the target push information
The target user is pushed to after sequence.
Specifically, as shown in figure 8, Fig. 8 is the another kind of the target push information for the push that this specification embodiment provides
The schematic diagram of embodiment.Specifically, in Fig. 8 as it can be seen that when the target push information be 5 when, can be by 5 target push informations
According to being pushed to the target user after the hobby relational degree taxis between the target user.Subsequently, user can basis
The demand of oneself clicks corresponding target push information, to obtain corresponding preferential or information on services.
It can be seen that passing through the position of combination user in a kind of one or more embodiments of information-pushing method of this specification
Confidence ceases and characterization user can determine near user position the hobby degree of association of the fancy grade of pushed information
The pushed information for meeting the businessman of customer consumption hobby, ensure that the validity of pushed information, and then can greatly improve user
Arrive shop rate；Meanwhile the brush for recommending the pushed information for meeting the businessman of customer consumption hobby that can save user to effective information
The time is selected, user experience is improved.
On the other hand this specification also provides a kind of information push-delivery apparatus, Fig. 9 is the information push dress that this specification provides
The structural schematic diagram for a kind of embodiment set, as shown in figure 9, described device 900 may include：
Position information acquisition module 910 can be used for obtaining the location information of target user；
First pushed information determining module 920 is determined within the scope of the push corresponding to the location information
Pushed information；
Second pushed information determining module 930, can be used for based between the pushed information and the target user
The hobby degree of association chooses target push information from the pushed information, and the hobby association table takes over family for use to pushed information
Fancy grade；
Info push module 940 can be used for the target push information being pushed to the target user.
In another embodiment, the hobby degree of association at least may include one of the following：
The social degree of association between consumption user corresponding to the target user and the pushed information；
Similarity between the history consumption information and the pushed information of the target user；
Like the consumption of group in consumption user corresponding to the pushed information for same consumption with the target user
Cluster similarity between user and the target user；
User's portrait information and consumption preference information based on the target user carry out the institute trained using probability
It states target user and probability is used to the pushed information.
In another embodiment, when the hobby degree of association is the target user and the consumption corresponding to the pushed information
When the social degree of association between user, the second pushed information determining module 930 may include：
Social degree of association determination unit can be used for based on the consumption corresponding to the target user and the pushed information
Social networks between user determine the social pass between the consumption user corresponding to the target user and the pushed information
Connection degree；
First object pushed information determination unit can be used for the social degree of association between the target user being more than
Equal to the pushed information of first threshold as the target push information.
In another embodiment, when the hobby degree of association is that the history consumption information of the target user and the push are believed
When similarity between breath, the second pushed information determining module 930 may include：
Similarity determining unit, be determined for the history consumption information of the target user and the pushed information it
Between similarity；
Second target push information determination unit, can be used for will be similar to the history consumption information of the target user
Degree is more than or equal to the pushed information of second threshold as the target push information.
In another embodiment, when it is described hobby the degree of association be the pushed information corresponding to consumption user in the mesh
When marking the cluster similarity between the consumption user and the target user that user is same consumption hobby group, described second pushes away
The information determination module 930 is sent to may include：
User's determination unit is determined in the consumption user corresponding to the pushed information and the target user
In the user of same consumption hobby group, wherein consumption hobby group is the consumption preference information based on characterization user
Feature vector carries out clustering determination；
Similarity calculated is clustered, can be used for calculating the user in the same consumption hobby group and the target
Cluster similarity between user；
Third target push information determination unit can be used for the cluster similarity between the target user being more than
Equal to third threshold value pushed information as the target push information.
In another embodiment, when the hobby degree of association is that user's portrait information based on the target user is liked with consumption
Good information carries out the target user trained using probability to the pushed information when using probability, and described second pushes away
The information determination module 930 is sent to may include：
Using probability determining unit, can be used for by the user of the target user draw a portrait information, consumption preference information and
The pushed information input is trained using probability identification model, obtains use of the target user to the pushed information
Probability；
4th target push information determination unit, the pushed information that can be used for that probability will be used to be more than or equal to the 4th threshold value
As the target push information；
Wherein, described using probability identification model is drawn a portrait information, consumption to the user of sample of users based on machine learning
Preference information and sample of users are trained the feedback information of pushed information determining.
In another embodiment, described device 900 can also include：
Weighted calculation module can be used for as characterization user being multiple to the hobby degree of association of the fancy grade of pushed information
When, the weight coefficient of the multiple hobby degree of association is determined respectively, and read group total is weighted to the multiple hobby degree of association,
Using the result being calculated as the hobby degree of association between the pushed information and the target user；
Wherein, the weight coefficient for liking the degree of association is directly proportional to the influence degree liked customer consumption.
In another embodiment, described information pushing module 940 specifically can be used for：
Push official documents and correspondence information including the target push information is pushed to the target user.
In another embodiment, described device 900 can also include：
Sorting module can be used for, when the target push information is multiple, being based on the target push information and institute
The hobby degree of association stated between target user is ranked up the target push information；
Correspondingly, described information pushing module is specifically used for being pushed to the target after the target push information sorts
User.
The above- mentioned information method for pushing or device that this specification embodiment provides can be executed by processor in a computer
Corresponding program instruction realizes, such as using the c++ language of windows operating systems the ends PC realize or other for example using
Android, iOS system programming language are realized in intelligent terminal, and realization of the processing logic based on quantum computer etc..
As shown in Figure 10, Figure 10 is the schematic configuration diagram that client is pushed according to the information of an exemplary embodiment of this specification.
Hardware view, the client may include processor, internal bus, network interface, memory and nonvolatile memory, certainly
It is also possible that the required hardware of other business.Processor read from nonvolatile memory corresponding computer program to
It is then run in memory, forms information push-delivery apparatus on logic level.Certainly, other than software realization mode, this explanation
Other realization methods, such as the mode etc. of logical device or software and hardware combining is not precluded in book, that is to say, that following processing
The executive agent of flow is not limited to each logic unit, can also be hardware or logical device.
Specifically, on the other hand this specification also provides a kind of information push client, including processor and memory, institute
It states memory and stores the computer program instructions executed by the processor, the computer program instructions may include：
The location information for obtaining target user, determines the pushed information within the scope of the push corresponding to the location information；
Based on the hobby degree of association between the pushed information and the target user mesh is chosen from the pushed information
Mark pushed information, fancy grade of the hobby association table requisition family to pushed information；
The target push information is pushed to the target user.
In this specification embodiment, the processor may include central processing unit (CPU) or graphics processor
(GPU), naturally it is also possible to including other microcontroller, logic gates, integrated circuits with logic processing capability etc. or its
It is appropriately combined.Memory described in this specification embodiment can be for protecting stored memory device.In digital display circuit,
The equipment that binary data can be preserved can be memory；In integrated circuits, one not physical form have storage work(
The circuit of energy may be memory, such as RAM, FIFO；In systems, the storage device with physical form, which can also be named, deposits
Reservoir etc..When realization, which can also be realized by the way of cloud storage, specific implementation, this specification
It is good to limit.
It can be seen that the embodiment of a kind of information-pushing method of this specification, device or client is by combining user's
Location information and characterization user can determine near user position the hobby degree of association of the fancy grade of pushed information
Meet customer consumption hobby businessman pushed information, ensure that the validity of pushed information, and then use can be greatly improved
Shop rate is arrived at family；Meanwhile recommending the pushed information for meeting the businessman of customer consumption hobby that can save user to effective information
Brush selects the time, improves user experience.
It is above-mentioned that this specification specific embodiment is described.Other embodiments are in the scope of the appended claims
It is interior.In some cases, the action recorded in detail in the claims or step can be come according to different from the sequence in embodiment
It executes and desired result still may be implemented.In addition, the process described in the accompanying drawings not necessarily require show it is specific suitable
Sequence or consecutive order could realize desired result.In some embodiments, multitasking and parallel processing be also can
With or it may be advantageous.
In the 1990s, the improvement of a technology can be distinguished clearly be on hardware improvement (for example,
Improvement to circuit structures such as diode, transistor, switches) or software on improvement (improvement for method flow).So
And with the development of technology, the improvement of current many method flows can be considered as directly improving for hardware circuit.
Designer nearly all obtains corresponding hardware circuit by the way that improved method flow to be programmed into hardware circuit.Cause
This, it cannot be said that the improvement of a method flow cannot be realized with hardware entities module.For example, programmable logic device
(Programmable Logic Device, PLD) (such as field programmable gate array (Field Programmable Gate
Array, FPGA)) it is exactly such a integrated circuit, logic function determines device programming by user.By designer
Voluntarily programming comes a digital display circuit " integrated " on a piece of PLD, designs and makes without asking chip maker
Dedicated IC chip.Moreover, nowadays, substitution manually makes IC chip, this programming is also used instead mostly " patrols
Volume compiler (logic compiler) " software realizes that software compiler used is similar when it writes with program development,
And the source code before compiling also write by handy specific programming language, this is referred to as hardware description language
(Hardware Description Language, HDL), and HDL is also not only a kind of, but there are many kind, such as ABEL
(Advanced Boolean Expression Language)、AHDL(Altera Hardware Description
Language)、Confluence、CUPL(Cornell University Programming Language)、HDCal、JHDL
(Java Hardware Description Language)、Lava、Lola、MyHDL、PALASM、RHDL(Ruby
Hardware Description Language) etc., VHDL (Very-High-Speed are most generally used at present
Integrated Circuit Hardware Description Language) and Verilog.Those skilled in the art also answer
This understands, it is only necessary to method flow slightly programming in logic and is programmed into integrated circuit with above-mentioned several hardware description languages,
The hardware circuit for realizing the logical method flow can be readily available.
Controller can be implemented in any suitable manner, for example, controller can take such as microprocessor or processing
The computer for the computer readable program code (such as software or firmware) that device and storage can be executed by (micro-) processor can
Read medium, logic gate, switch, application-specific integrated circuit (Application Specific Integrated Circuit,
ASIC), the form of programmable logic controller (PLC) and embedded microcontroller, the example of controller includes but not limited to following microcontroller
Device：ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20 and Silicone Labs C8051F320, are deposited
Memory controller is also implemented as a part for the control logic of memory.It is also known in the art that in addition to
Pure computer readable program code mode is realized other than controller, can be made completely by the way that method and step is carried out programming in logic
Controller is obtained in the form of logic gate, switch, application-specific integrated circuit, programmable logic controller (PLC) and embedded microcontroller etc. to come in fact
Existing identical function.Therefore this controller is considered a kind of hardware component, and to including for realizing various in it
The device of function can also be considered as the structure in hardware component.Or even, it can will be regarded for realizing the device of various functions
For either the software module of implementation method can be the structure in hardware component again.
Device, module or the unit that above-described embodiment illustrates can specifically be realized, Huo Zheyou by computer chip or entity
Product with certain function is realized.It is a kind of typically to realize that equipment is computer.Specifically, computer for example can be a
People's computer, laptop computer, cellular phone, camera phone, smart phone, personal digital assistant, media player, navigation
Any equipment in equipment, electronic mail equipment, game console, tablet computer, wearable device or these equipment
Combination.
For convenience of description, it is divided into various units when description apparatus above with function to describe respectively.Certainly, implementing this
The function of each unit is realized can in the same or multiple software and or hardware when specification.
It should be understood by those skilled in the art that, the embodiment of the present invention can be provided as method, apparatus or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the present invention
Apply the form of example.Moreover, the present invention can be used in one or more wherein include computer usable program code computer
The computer program production implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.
The present invention be with reference to according to the method for the embodiment of the present invention, the flow of equipment (device) and computer program product
Figure and/or block diagram describe.It should be understood that can be realized by computer program instructions every first-class in flowchart and/or the block diagram
The combination of flow and/or box in journey and/or box and flowchart and/or the block diagram.These computer programs can be provided
Instruct the processor of all-purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine so that the instruction executed by computer or the processor of other programmable data processing devices is generated for real
The device for the function of being specified in present one flow of flow chart or one box of multiple flows and/or block diagram or multiple boxes.
These computer program instructions, which may also be stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that instruction generation stored in the computer readable memory includes referring to
Enable the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one box of block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device so that count
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, in computer or
The instruction executed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in a box or multiple boxes.
In a typical configuration, computing device includes one or more processors (CPU), input/output interface, net
Network interface and memory.
Memory may include computer-readable medium in volatile memory, random access memory (RAM) and/or
The forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM).Memory is computer-readable medium
Example.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology realizes information storage.Information can be computer-readable instruction, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase transition internal memory (PRAM), static RAM (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), fast flash memory bank or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storages, magnetic tape cassette, tape magnetic disk storage, graphene stores or other
Magnetic storage apparatus or any other non-transmission medium can be used for storage and can be accessed by a computing device information.According to herein
In define, computer-readable medium does not include temporary computer readable media (transitory media), such as data of modulation
Signal and carrier wave.
It should also be noted that, the terms "include", "comprise" or its any other variant are intended to nonexcludability
Including so that process, method, commodity or equipment including a series of elements include not only those elements, but also wrap
Include other elements that are not explicitly listed, or further include for this process, method, commodity or equipment intrinsic want
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that wanted including described
There is also other identical elements in the process of element, method, commodity or equipment.
It will be understood by those skilled in the art that the embodiment of this specification can be provided as method, apparatus or computer program production
Product.Therefore, complete hardware embodiment, complete software embodiment or implementation combining software and hardware aspects can be used in this specification
The form of example.Moreover, this specification can be used in one or more wherein include computer usable program code computer
The computer program production implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.
This specification can describe in the general context of computer-executable instructions executed by a computer, such as journey
Sequence module.Usually, program module include routines performing specific tasks or implementing specific abstract data types, program, object,
Component, data structure etc..This specification can also be put into practice in a distributed computing environment, in these distributed computing environment
In, by executing task by the connected remote processing devices of communication network.In a distributed computing environment, program module
It can be located in the local and remote computer storage media including storage device.
Each embodiment in this specification is described in a progressive manner, identical similar portion between each embodiment
Point just to refer each other, and each embodiment focuses on the differences from other embodiments.Especially for device and
For client embodiment, since it is substantially similar to the method embodiment, so description is fairly simple, related place is referring to side
The part of method embodiment illustrates.
The foregoing is merely the embodiments of this specification, are not limited to this specification.For art technology
For personnel, this specification can have various modifications and variations.It is all this specification spirit and principle within made by it is any
Modification, equivalent replacement, improvement etc., should be included within right.
Claims (19)
1. a kind of information-pushing method, including：
The location information for obtaining target user, determines the pushed information within the scope of the push corresponding to the location information；
Target is chosen based on the hobby degree of association between the pushed information and the target user from the pushed information to push away
It delivers letters breath, fancy grade of the hobby association table requisition family to pushed information；
The target push information is pushed to the target user.
2. according to the method described in claim 1, wherein, the hobby degree of association includes at least one of the following：
The social degree of association between consumption user corresponding to the target user and the pushed information；
Similarity between the history consumption information and the pushed information of the target user；
Like the consumption user of group in consumption user corresponding to the pushed information for same consumption with the target user
Cluster similarity between the target user；
User's portrait information and consumption preference information based on the target user carry out the mesh trained using probability
It marks user and probability is used to the pushed information.
3. method according to claim 1 or 2, wherein when the hobby degree of association is that the target user pushes away with described
When the social degree of association between the consumption user delivered letters corresponding to breath, it is described based on the pushed information and the target user it
Between the hobby degree of association choose target push information from the pushed information and include：
The target is determined based on the social networks between the consumption user corresponding to the target user and the pushed information
The social degree of association between consumption user corresponding to user and the pushed information；
The pushed information that the social degree of association between the target user is more than or equal to first threshold is pushed away as the target
It delivers letters breath.
4. method according to claim 1 or 2, wherein when the history that the hobby degree of association is the target user disappears
When similarity between charge information and the pushed information, the happiness based between the pushed information and the target user
The good degree of association chooses target push information from the pushed information：
Determine the similarity between the history consumption information of the target user and the pushed information；
The similarity of history consumption information with the target user is more than or equal to the pushed information of second threshold as described in
Target push information.
5. method according to claim 1 or 2, wherein when the hobby degree of association is corresponding to the pushed information
Like the cluster between the consumption user and the target user of group in consumption user for same consumption with the target user
When similarity, the hobby degree of association based between the pushed information and the target user is selected from the pushed information
The target push information is taken to include：
Determine the user for liking group in the consumption user corresponding to the pushed information in same consumption with the target user,
Wherein, consumption hobby group is the feature vector progress clustering determination based on the consumption preference information of characterization user
's；
Calculate the user in the same consumption hobby group and the cluster similarity between the target user；
The pushed information that cluster similarity between the target user is more than or equal to third threshold value is pushed away as the target
It delivers letters breath.
6. method according to claim 1 or 2, wherein when the hobby degree of association is the use based on the target user
Family portrait information and consumption preference information made to the pushed information using the target user that probability is trained
When with probability, the hobby degree of association based between the pushed information and the target user is selected from the pushed information
The target push information is taken to include：
User's portrait information, consumption preference information and the pushed information input of the target user are identified into mould using probability
Type is trained, and is obtained the target user and is used probability to the pushed information；
Probability will be used to be more than or equal to the pushed information of the 4th threshold value as the target push information；
Wherein, described using probability identification model is liked draw a portrait information, consumption of the user of sample of users based on machine learning
Information and sample of users are trained the feedback information of pushed information determining.
7. method according to claim 1 or 2, wherein the method further includes：
When characterize user to the hobby degree of association of the fancy grade of pushed information is multiple when, determine the multiple hobby pass respectively
The weight coefficient of connection degree is weighted read group total, using the result being calculated as described in the multiple hobby degree of association
The hobby degree of association between pushed information and the target user；
Wherein, the weight coefficient for liking the degree of association is directly proportional to the influence degree liked customer consumption.
8. method according to claim 1 or 2, wherein described that the target push information is pushed to the target use
Family includes：
Push official documents and correspondence information including the target push information is pushed to the target user.
9. method according to claim 1 or 2, wherein the method further includes：
When the target push information is multiple, closed based on the hobby between the target push information and the target user
Connection degree is ranked up the target push information；
Correspondingly, described, the target push information is pushed to the target user includes that the target push information sorts
After be pushed to the target user.
10. a kind of information push-delivery apparatus, including：
Position information acquisition module, the location information for obtaining target user；
First pushed information determining module, for determining the pushed information within the scope of the push corresponding to the location information；
Second pushed information determining module, for based on the hobby degree of association between the pushed information and the target user from
Target push information, fancy grade of the hobby association table requisition family to pushed information are chosen in the pushed information；
Info push module, for the target push information to be pushed to the target user.
11. device according to claim 10, wherein the hobby degree of association includes at least one of the following：
The social degree of association between consumption user corresponding to the target user and the pushed information；
Similarity between the history consumption information and the pushed information of the target user；
Like the consumption user of group in consumption user corresponding to the pushed information for same consumption with the target user
Cluster similarity between the target user；
User's portrait information and consumption preference information based on the target user carry out the mesh trained using probability
It marks user and probability is used to the pushed information.
12. the device according to claim 10 or 11, wherein when the hobby degree of association be the target user with it is described
When the social degree of association between the consumption user corresponding to pushed information, the second pushed information determining module includes：
Social degree of association determination unit, for based between the consumption user corresponding to the target user and the pushed information
Social networks determine the social degree of association between the consumption user corresponding to the target user and the pushed information；
First object pushed information determination unit, for the social degree of association between the target user to be more than or equal to first
The pushed information of threshold value is as the target push information.
13. the device according to claim 10 or 11, wherein when the history that the hobby degree of association is the target user
When similarity between consumption information and the pushed information, the second pushed information determining module includes：
Similarity determining unit, it is similar between the history consumption information of the target user and the pushed information for determining
Degree；
Second target push information determination unit, be used to the similarity of the history consumption information with the target user being more than etc.
In second threshold pushed information as the target push information.
14. the device according to claim 10 or 11, wherein when the hobby degree of association is corresponding to the pushed information
Consumption user in the target user to be that same consumption is liked poly- between the consumption user and the target user of group
When class similarity, the second pushed information determining module includes：
User's determination unit disappears with the target user same for determining in the consumption user corresponding to the pushed information
Take the user of hobby group, wherein consumption hobby group is the feature vector of the consumption preference information based on characterization user
Carry out clustering determination；
Similarity calculated is clustered, for calculating the user in the same consumption hobby group and between the target user
Cluster similarity；
Third target push information determination unit, for the cluster similarity between the target user to be more than or equal to third
The pushed information of threshold value is as the target push information.
15. the device according to claim 10 or 11, wherein when the hobby degree of association is based on the target user's
The target user that user's portrait information and consumption preference information trained using probability is to the pushed information
When using probability, the second pushed information determining module includes：
Using probability determining unit, it is used for user's portrait information, consumption preference information and the push of the target user
Information input is trained using probability identification model, is obtained the target user and is used probability to the pushed information；
4th target push information determination unit, for probability will to be used to be more than or equal to described in the pushed information conduct of the 4th threshold value
Target push information；
Wherein, described using probability identification model is liked draw a portrait information, consumption of the user of sample of users based on machine learning
Information and sample of users are trained the feedback information of pushed information determining.
16. the device according to claim 10 or 11, wherein described device further includes：
Weighted calculation module, for when characterize user to the hobby degree of association of the fancy grade of pushed information is multiple when, respectively
The weight coefficient for determining the multiple hobby degree of association, is weighted read group total to the multiple hobby degree of association, will calculate
Obtained result is as the hobby degree of association between the pushed information and the target user；
Wherein, the weight coefficient for liking the degree of association is directly proportional to the influence degree liked customer consumption.
17. the device according to claim 10 or 11, wherein described information pushing module is specifically used for：
Push official documents and correspondence information including the target push information is pushed to the target user.
18. the device according to claim 10 or 11, wherein described device further includes：
Sorting module, for when the target push information is multiple, being used based on the target push information and the target
The hobby degree of association between family is ranked up the target push information；
Correspondingly, described information pushing module is specifically used for being pushed to the target use after the target push information sorts
Family.
19. a kind of information pushes client, including processor and memory, what the memory storage was executed by the processor
Computer program instructions, the computer program instructions include：
The location information for obtaining target user, determines the pushed information within the scope of the push corresponding to the location information；
Target is chosen based on the hobby degree of association between the pushed information and the target user from the pushed information to push away
It delivers letters breath, fancy grade of the hobby association table requisition family to pushed information；
The target push information is pushed to the target user.
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| CN201810146000.0A CN108566615A (en) | 2018-02-12 | 2018-02-12 | Information-pushing method, device and client |
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| CN201810146000.0A CN108566615A (en) | 2018-02-12 | 2018-02-12 | Information-pushing method, device and client |
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| CN114398560A (en) * | 2022-03-24 | 2022-04-26 | 深圳市秦丝科技有限公司 | Marketing interface setting method, device, equipment and medium based on WEB platform |
| CN114398560B (en) * | 2022-03-24 | 2022-05-27 | 深圳市秦丝科技有限公司 | Marketing interface setting method, device, equipment and medium based on WEB platform |
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