CN111506643A

CN111506643A - Method, device and system for generating information

Info

Publication number: CN111506643A
Application number: CN201910098635.2A
Authority: CN
Inventors: 李永鹏; 宋曜廷
Original assignee: Beijing Wodong Tianjun Information Technology Co Ltd
Current assignee: Beijing Wodong Tianjun Information Technology Co Ltd
Priority date: 2019-01-31
Filing date: 2019-01-31
Publication date: 2020-08-07
Anticipated expiration: 2039-01-31
Also published as: CN117349546A; CN111506643B

Abstract

The embodiment of the disclosure discloses a method, a device and a system for generating information. One embodiment of the method comprises: acquiring user behavior data generated by a user terminal executing target operation, wherein the target operation is operation aiming at a virtual product, and the virtual product corresponds to a product indicated by a display link; determining user demand information of a user using the user terminal based on the user behavior data, wherein the user demand information represents a degree of demand of the user for a product indicated by a display link; and generating presentation effect information of the user terminal to the display link based on the user demand information. The embodiment enriches the mode of generating the presentation effect information and improves the accuracy of generating the presentation effect information.

Description

Method, device and system for generating information

Technical Field

Embodiments of the present disclosure relate to the field of computer technologies, and in particular, to a method, an apparatus, and a system for generating information.

Background

As computer technology advances, it is desirable to better exploit existing data information for mining. The requirements on the utilization rate of data, the matching degree and other hard indexes are higher and higher.

In the internet industry, many internet companies can use acquired user information to predict placement of a presentation link (e.g., an advertisement) through an own algorithm. Due to the fact that the influence of each operation (such as operations of transferring an object row (for example, purchasing) a product, browsing the product, collecting the product, adding the product into a shopping cart and the like) on the conversion effect (such as the representation of the amount paid by the user and the like) can be measured in the process of the user operation, namely the influence of each display link on the conversion effect can be evaluated after the user views a series of display links and finally makes a setting operation.

Existing attribution schemes mainly include the following two: basic attribution models (generally divided into a first-time interaction model, a U-shaped interaction model, a linear model, a time attenuation model and a final interaction model) and attribution models based on machine learning.

Disclosure of Invention

The embodiment of the disclosure provides a method, a device and a system for generating information.

In a first aspect, an embodiment of the present disclosure provides a method for generating information, the method including: acquiring user behavior data generated by a user terminal executing target operation, wherein the target operation is operation aiming at a virtual product, and the virtual product corresponds to a product indicated by a display link; determining user demand information of a user using the user terminal based on the user behavior data, wherein the user demand information represents a degree of demand of the user for a product indicated by the presentation link; and generating presentation effect information of the user terminal to the display link based on the user demand information.

In a second aspect, embodiments of the present disclosure provide a method for generating a model, the method comprising: acquiring user behavior data generated by executing target operation in a target operation set by a user terminal in a user terminal set, wherein the target operation is operation aiming at a virtual product, and the virtual product corresponds to a product indicated by a display link; and counting the user behavior data to construct a Markov model, wherein the state information of the Markov model is used for representing the user category in the user category set or the target operation in the target operation set, and the user category is the category to which the user using the user terminal in the user terminal set belongs.

In a third aspect, an embodiment of the present disclosure provides a method for generating information, the method including: receiving a display link to be pushed; and generating the demand degree of the user for the product indicated by the to-be-pushed display link based on a pre-generated Markov model, wherein the Markov model is generated according to the method of any one embodiment of the method for generating the model.

In a fourth aspect, an embodiment of the present disclosure provides an apparatus for generating information, the apparatus including: an acquisition unit configured to acquire user behavior data generated by a user terminal performing a target operation, wherein the target operation is an operation for a virtual product corresponding to a product indicated by a presentation link; a first determination unit configured to determine user demand information of a user using the user terminal based on the user behavior data, wherein the user demand information represents a degree of demand of the user for a product indicated by the presentation link; and the first generating unit is configured to generate presentation effect information of the user terminal on the presentation link based on the user requirement information.

In a fifth aspect, an embodiment of the present disclosure provides an apparatus for generating a model, the apparatus including: an acquisition unit configured to acquire user behavior data generated by a user terminal in a set of user terminals executing a target operation in a set of target operations, wherein the target operation is an operation for a virtual product corresponding to a product indicated by a display link; the building unit is configured to count the user behavior data to build a Markov model, wherein state information of the Markov model is used for representing a user category in the user category set or a target operation in the target operation set, and the user category is a category to which a user using a user terminal in the user terminal set belongs.

In a sixth aspect, an embodiment of the present disclosure provides an apparatus for generating information, the apparatus including: the receiving unit is configured to receive the exhibition link to be pushed; the generation unit is configured to generate the demand degree of the user for the product indicated by the to-be-pushed display link based on a pre-generated Markov model, wherein the Markov model is generated according to the method of any embodiment of the method for generating the model.

In a seventh aspect, an embodiment of the present disclosure provides a system for generating information, the system including: the method comprises the following steps that a server and a user terminal are gathered, wherein the user terminal is in communication connection with the server, and the method comprises the following steps: a server configured to: acquiring user behavior data generated by executing target operation in a target operation set by a user terminal in a user terminal set, wherein the target operation is operation aiming at a virtual product, and the virtual product corresponds to a product indicated by a display link; determining user demand information of a user using a user terminal in a user terminal set based on the user behavior data, wherein the user demand information represents a degree of demand of the user for a product indicated by the display link; and generating presentation effect information of the user terminal to the display link based on the user demand information.

In an eighth aspect, an embodiment of the present disclosure provides an electronic device, including: one or more processors; a storage device having one or more programs stored thereon, which when executed by the one or more processors, cause the one or more processors to implement the method for generating information as described above, or the method of any embodiment of the method for generating a model as described above.

In a ninth aspect, embodiments of the present disclosure provide a computer-readable medium, on which a computer program is stored, which when executed by a processor implements the method for generating information as described above, or the method of any of the above methods for generating a model.

The method, the device and the system for generating information provided by the embodiment of the disclosure can acquire user behavior data generated by the user terminal executing the target operation, wherein the target operation is an operation for a virtual product corresponding to a product indicated by a presentation link presented by the user terminal, then, based on the user behavior data, user demand information of the user using the user terminal is determined, wherein the user demand information characterizes a degree of demand of the user for a product indicated by the presentation link in the set of presentation links, and finally, generating presentation effect information of the user terminal to the presentation link based on the user demand information, thereby determining the user demand information based on the user behavior data, and then generating presentation effect information showing the link at the user terminal, thereby enriching the mode of generating the presentation effect information and improving the accuracy of generating the presentation effect information.

Drawings

Other features, objects and advantages of the disclosure will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings in which:

FIG. 1 is an exemplary system architecture diagram in which one embodiment of the present disclosure may be applied;

FIG. 2 is a flow diagram for one embodiment of a method for generating information, according to the present disclosure;

FIG. 3 is a schematic illustration of an image of a user intent function of one embodiment of the present disclosure;

4A-4D are presentation effect information characterized by a skewed distribution function obtained for the user intent function shown in FIG. 3;

FIG. 5 is a schematic diagram of one application scenario of a method for generating information according to the present disclosure;

FIG. 6 is a flow diagram of yet another embodiment of a method for generating information according to the present disclosure;

figure 7 is a schematic diagram of a markov model architecture according to one embodiment of the present disclosure;

FIG. 8 is a flow chart of a third embodiment of a method for generating information according to the present disclosure;

FIG. 9 is a flow chart of a fourth embodiment of a method for generating information according to the present disclosure;

FIG. 10 is a flow chart of a fifth embodiment of a method for generating information according to the present disclosure;

FIG. 11 is a schematic block diagram illustrating one embodiment of an apparatus for generating information according to the present disclosure;

FIG. 12 is a flow diagram for one embodiment of a method for generating a model according to the present disclosure;

FIG. 13 is a schematic diagram of an embodiment of an apparatus for generating models according to the present disclosure;

FIG. 14 is a flow diagram for one embodiment of another method for generating information, according to the present disclosure;

FIG. 15 is a schematic diagram illustrating one embodiment of an apparatus for generating information according to the present disclosure;

FIG. 16 is an interaction process schematic diagram of one embodiment of a system for generating information according to the present disclosure;

FIG. 17 is an interaction process diagram of yet another embodiment of a system for generating information according to the present disclosure;

FIG. 18 is a schematic block diagram of a computer system suitable for use as a server for implementing embodiments of the present disclosure.

Detailed Description

The present disclosure is described in further detail below with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the relevant invention and not restrictive of the invention. It should be noted that, for convenience of description, only the portions related to the related invention are shown in the drawings.

It should be noted that, in the present disclosure, the embodiments and features of the embodiments may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

Fig. 1 illustrates an exemplary system architecture 100 of an embodiment of a method for generating information or an apparatus for generating information to which embodiments of the present disclosure may be applied.

As shown in fig. 1, the system architecture 100 may include

terminal devices

101, 102, 103,

networks

104, 106, and a server 105. The network 104 serves as a medium for providing communication links between the

terminal devices

101, 102 and the server 105. Network 106 is the medium used to provide communication links between terminal devices 103 and server 105. The

networks

104, 106 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

The user may interact with the server 105 via the network 104 using the

terminal devices

101, 102, or with the server 105 via the network 106 using the terminal device 103, to receive or transmit data or the like. The

terminal devices

101, 102, 103 may have installed thereon various communication client applications, such as a web browser application, a shopping-like application, a search-like application, an instant messaging tool, a mailbox client, social platform software, software for providing a presentation link to the server 105, and the like.

When the

terminal devices

101, 102, 103 are hardware, they may be various electronic devices having a display screen and supporting page browsing, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio L layer III, motion Picture Experts compressed standard Audio layer 3), MP4(Moving Picture Experts Group Audio L layer IV, motion Picture Experts compressed standard Audio layer 4) players, laptop portable computers, desktop computers, and the like, when the

terminal devices

101, 102, 103 are software, they may be implemented as a plurality of software or software modules (for example, software or software modules for providing distributed services), or as a single software or software module, but not specifically limited thereto, the

terminal devices

101, 102 may be electronic devices installed with shopping-type applications, the terminal device 103 may be an electronic device installed with a link for providing a link to the terminal device 105, and the terminal device 105 may provide a link to the terminal device 105, and the link may be provided to the terminal device 105 through the link server 105, or the link server 105.

The server 105 may be a server providing various services, such as a background page server providing support for pages displayed on the

terminal devices

101, 102. The background page server may analyze and perform other processing on the received data such as the page request, and feed back a processing result (for example, page data corresponding to the page request) to the

terminal devices

101 and 102. As yet another example, the server 105 may also be a server for receiving a presentation link provided by the terminal device 103 and determining whether to transmit the presentation link to the

terminal devices

101, 102 via the network 104.

It should be noted that the method for generating information provided by the embodiment of the present disclosure is generally performed by the server 105, and accordingly, the apparatus for generating information is generally disposed in the server 105. The method for generating a model provided by the embodiments of the present disclosure is generally performed by the server 105, and accordingly, the apparatus for generating a model is generally disposed in the server 105.

It should be noted that the server may be hardware or software. When the server is hardware, it may be implemented as a distributed server cluster formed by multiple servers, or may be implemented as a single server. When the server is software, it may be implemented as multiple pieces of software or software modules (e.g., software or software modules used to provide distributed services), or as a single piece of software or software module. And is not particularly limited herein.

It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation. For example, the system architecture may include only the electronic device (e.g., server 105) on which the method for generating the information, or the method for generating the model, runs, when the electronic device on which the method for generating the model runs does not require data transfer with other electronic devices.

With continued reference to FIG. 2, a flow 200 of one embodiment of a method for generating information in accordance with the present disclosure is shown. The method for generating information comprises the following steps:

step 201, user behavior data generated by the user terminal executing the target operation is obtained.

In this embodiment, an execution subject (for example, a server shown in fig. 1) of the method for generating information may acquire user behavior data generated by the user terminal executing the target operation by a wired connection manner or a wireless connection manner. Wherein the target operation is an operation for a virtual product corresponding to a product indicated by the presentation link presented by the user terminal.

The user terminal may be a terminal communicatively connected to the execution main body. In practice, the server is usually required to support the application installed in the terminal, so that the corresponding function is realized through the operation of the application. It is to be understood that the user terminal may be a terminal installed with an application supported by the execution main body.

As an example, the user terminal may be installed with shopping software or may open a shopping website through a browser, and the execution body may be a server supporting the shopping software or the shopping website.

The target operation may be an operation for a virtual product corresponding to a product indicated by a presentation link in the presentation link set presented by the user terminal.

The exhibition link may be information for pushing a product. The presentation link may be presented in at least one of the following ways: text, pictures, audio, video, etc. By way of example, when the product is "toothpaste", the display link may be "XX toothpaste, known at all". The user terminal may present all or part of the presentation links in the set of presentation links.

The virtual product may be information representing the product (physical product, such as toothpaste, towel, etc.) corresponding to the product, and presented in software or a website. By way of example, the virtual product described above may be characterized by, but is not limited to, at least one of the following forms: text, pictures, video, etc. As an example, when the product is "toothpaste", the virtual product corresponding to the product may be a picture of toothpaste, a text describing toothpaste, a video of toothpaste.

The target operation may be an operation in which the execution subject responds to the operation of the user on the virtual product after the operation of the user on the virtual product (for example, sharing, clicking, collecting, migrating an object line (for example, purchasing), adding a shopping cart, browsing, agreeing, jumping to a landing page, and the like). For example, when a user wants to migrate a physical product corresponding to a virtual product (e.g., purchase), the user may perform a migration object line operation (e.g., purchase) operation on the virtual product on a page in which the virtual product is presented (e.g., click a migration object line operation (e.g., purchase) button and complete payment), and thereafter, the execution subject may perform the following target operation in response to the migration object line operation (e.g., purchase) operation: jumping to an order page, and adding a migration object row operation (such as purchase) record of the product in the historical migration object row operation (such as purchase) record of the user.

In some usage cases, the user terminal may be a user terminal in a predetermined set of user terminals (e.g., a set of terminals installed with shopping software), and the target operation may be an operation in a predetermined set of operations (e.g., operations that may include sharing, clicking, collecting, migrating an object row (e.g., purchasing), joining a shopping cart, browsing, agreeing, jumping to a landing page, etc.). Therefore, the execution main body can also acquire user behavior data generated by each user terminal in the user terminal set executing the target operation in the target operation set.

Step 202, determining user requirement information of a user using the user terminal based on the user behavior data.

In this embodiment, based on the user behavior data obtained in step 201, the execution subject may determine the user requirement information of the user using the user terminal. The user demand information can represent the demand degree of the user for the products indicated by the display links in the display link set. As an example, the user requirement information may be characterized by words, numerical values, and the like. For example, the user demand information may be "much needed", "generally needed", "hardly needed", and the like. Optionally, the user requirement information may also be "1", "2" or "3". Wherein, 1 can characterize "very desirable", "2" can characterize "general desirable", and "3" can characterize "almost undesirable".

As an example, when the user behavior data is data obtained by the execution main body in response to a migration object row operation (e.g., purchase) operation of the user, the execution main body may determine that the user requirement information of the user using the user terminal is "highly required".

As another example, when the user behavior data is data obtained by the execution main body in response to the sharing operation of the user, the execution main body may determine that the user requirement information of the user using the user terminal is "general requirement".

As still another example, when the user behavior data is data obtained by the execution main body in response to a browsing operation by the user, the execution main body may determine that the user demand information of the user using the user terminal is "almost unnecessary".

It should be noted that, a skilled person may determine the characterization manner and the determination manner of the user requirement information according to the actual requirement, and the above example is merely illustrative and does not constitute a limitation to the embodiment of the present disclosure.

And 203, generating presentation effect information of the user terminal to the display link based on the user requirement information.

In this embodiment, the execution subject may generate presentation effect information of the presentation link in the presentation link set presented by the user terminal based on the user requirement information obtained in step 202. Wherein, the presentation effect information may be information characterizing the presentation effect of the presentation link. The presentation effect information may be represented by words, numbers, or the like. As an example, the presentation effect information may be "good" or "bad", or may be "1" or "2". When the presentation effect information is represented by a numerical value, a technician can specify that the presentation effect information with larger numerical value represents that the presentation effect is better, or that the presentation effect information with smaller numerical value represents that the presentation effect is better.

As an example, when the user demand information is "much need", the execution main body may generate the presentation effect information "1"; when the user requirement information is 'general requirement', the execution main body can generate presentation effect information '2'; when the user demand information is "almost unnecessary", the execution main body may generate the presentation effect information "3". Here, it may be predetermined that the presentation effect information having a larger numerical value represents a better presentation effect.

It should be noted that, a skilled person may determine the representation manner of the presentation effect information and the determination manner according to actual requirements, and the above examples are merely illustrative and do not constitute a limitation to the embodiments of the present disclosure.

It can be understood that the presentation effect information of the presentation link by the user terminal is the presentation effect information of the presentation link in the presentation link set presented to the user terminal.

In some optional implementation manners of this embodiment, the user demand information is represented by a user demand function, and the user demand function represents a correspondence between time and a total demand degree of the user for a product set indicated by the presentation link set. The total degree of demand is characterized by a numerical value.

As an example, please refer to fig. 3. As shown in fig. 3, a diagram illustrating an image of a user's wish function is shown, according to one embodiment of the present disclosure. Wherein the abscissa represents time and the ordinate represents the total demand degree.

It should be noted that the user intention function may represent a trend of the user's demand level for the product indicated by each of the display links in the display link set over a period of time. Here, the image of the user's intention function may be obtained by curve fitting.

It can be understood that through the user intention function, the change trend of the demand degree of the user on the product indicated by each display link in the display link set in the time period can be reflected more intuitively. Therefore, technicians or publishers of the presentation links can be helped to analyze user requirements and the presentation effect of the presentation links.

In some alternative implementations of the present embodiment, the target operation belongs to a predetermined set of target operations. Thus, the executing main body may further execute the step 202 as follows: and determining a user intention function corresponding to the user using the user terminal based on the association probability set.

Wherein the set of association probabilities is determined based on the user behavior data. The association probability is time dependent. The association probability characterizes any one of: the user category in the user category set is converted into the probability of the user category in the user category set, the probability of executing any target operation in the target operation set after executing the target operation in the target operation set, the probability of using the user terminal to execute the target operation in the target operation set by the user belonging to the user category in the user category set, and the probability of using the user belonging to the user category in the user category set by the user terminal to execute the target operation in the target operation set.

It will be appreciated that the association probabilities described above may be derived from statistics of user behaviour data (data derived from a plurality of user terminals). As an example, assuming that the user category of 50 users among 100 users belonging to the class a is converted into the class b, the association probability may be 0.5.

The user categories described above may be used to characterize the categories of users. As an example, the user category in the user category set may be one of: potential users, cognitive users, interested users, migrated object row operations (e.g., purchasing) users, loyalty users. The number of user categories in the user category set may be set by a technician, and the user category set may include 5 user categories, for example.

Here, the execution agent or another electronic device communicatively connected to the execution agent may obtain the user category of each user in a user set (for example, a set of users who have used certain shopping software) by inputting user behavior data of the user into a classification model trained in advance. For example, the classification model may be various existing models for classification, such as a user life cycle model, or other models, and the training method of the above model is a well-known technique widely studied at present and is not described herein again.

The target operation may be an operation such as sharing, clicking, collecting, migrating an object line (e.g., purchasing), joining a shopping cart, browsing, praise, jumping to a landing page, and the like. The number of target operations in the target operation set may be set by a technician, and the target operation set may include 10 target operations, as an example.

Here, taking the user category set including 5 user categories and the target operation set including 10 target operations as an example, the execution subject may determine the total demand degree by the following formula, that is, the following formula may characterize a user intention function corresponding to a user using the user terminal:

wherein Q represents the total demand level. i and j are used to identify the state. Iij characterizes the probability of the j-th state transitioning to the i-th state. Oij characterize the probability of transitioning to the j-th state. Iij and Oij are the associated probabilities, respectively. Since the user category set includes 5 user categories, the target operation set includes 10 target operations. Thus, the associated probability set may characterize the probability of each of the 50 states transitioning to each of the 50 states. Wherein the condition is characterized by any one of: the user category in the user category set is converted into the user category in the user category set, any target operation in the target operation set is executed after the target operation in the target operation set is executed, the user belonging to the user category in the user category set executes the target operation in the target operation set by using the user terminal, and the user of the user terminal executing the target operation in the target operation set belongs to the user category in the user category set. pij is a preset state incoming gain factor (i.e., weight) for Iij, and qij is a preset state outgoing gain factor (i.e., weight) of Oij. mi is a preset weight of the ith state. The pij, qij, mi may be pre-stored parameters, respectively.

Optionally, the result of the weighted sum of the association probability sets may also be determined as the total demand degree, so as to further obtain a user intention function corresponding to the user using the user terminal.

It will be appreciated that since the association probability is time dependent, for example, the association probability may be characterized as a function of time, and thus, the user intent function described above may be a function of time. Therefore, the user intention function corresponding to the user using the user terminal is determined through the pre-obtained association probability set, and the change trend of the demand degree of the user on products indicated by each display link in the display link set within a time period can be reflected more accurately and rapidly. Further assisting a technician or publisher of the presentation link in analyzing the user's needs and the presentation effect of the presentation link.

wherein Q represents the total demand level. i and j are used to identify the state. Iij characterizes the probability of the j-th state transitioning to the i-th state. Oij characterize the probability of transitioning to the j-th state. Iij and Oij are the associated probabilities, respectively. Since the user category set includes 5 user categories, the target operation set includes 10 target operations. Thus, the associated probability set may characterize the probability of each of the 50 states transitioning to each of the 50 states. Wherein the condition is characterized by any one of: the user category in the user category set is converted into the user category in the user category set, any target operation in the target operation set is executed after the target operation in the target operation set is executed, the user belonging to the user category in the user category set executes the target operation in the target operation set by using the user terminal, and the user of the user terminal executing the target operation in the target operation set belongs to the user category in the user category set. p is a radical of_ijIs a state afferent gain factor (i.e., weight), q, preset for Iij_ijIs a preset Oij state outgoing profit-and-loss factor (i.e., weight). mi is preset, the second

The weight of the i state. P is above_ij、q_ijMi may be pre-stored parameters, respectively.

In some optional implementations of this embodiment, the executing main body may further execute the step 203 according to the following steps:

firstly, dividing a user intention function according to the presentation time of the presentation links in the presentation link set presented by the user terminal, and determining the division result as a user product intention function set.

The presentation time of the presentation links in the set of presentation links is predetermined. The user product willingness function represents the corresponding relation between the time and the user demand degree for the product indicated by each display link in the display link set.

As an example, please refer to fig. 4A-4D. Fig. 4A-4D are presentation effect information characterized by a skewed distribution function obtained for the user intent function shown in fig. 3. The execution body may divide the image of the user intention function by the presentation time (time 1, time 2, time 3, and time 4 in the figure, respectively) of the presentation links in the presentation link set (including 4 presentation links).

And then, carrying out Laplace transformation on the user product intention function according to the user product intention function in the user product intention function set to obtain presentation effect information of the user terminal to the display link, wherein the presentation effect information is represented by a skewed distribution function.

Please continue to refer to fig. 4A-4D. The execution body generates presentation effect information which is represented by the skewed distribution function and is used for presenting the presentation links in the presentation link set by the user terminal. Fig. 4A to 4D are respectively presentation effect information of each presentation link in the user terminal presentation link set obtained by dividing the user intention function shown in fig. 3.

Specifically, the execution body may first decompose the willingness characterizing waveform (i.e., the waveform of the user's willingness function) in time based on the laplacian waveform transform. Since the product will of the product indicated by the display link by the user can be characterized as a biased effect curve, the starting points of the curve are divided by the determined push time (for example, T1 and T2 …) of the display link on a time axis, the total will curve of one user is decomposed into a biased curve which represents the actual desired effect of the display link and takes the determined push time of each display link as the starting point through laplace transform, and the deviation coefficient, the expectation E and the variance corresponding to each curve are obtained.

Through the above transformation decomposition, the obtained data is a willingness curve (as shown in fig. 4A-4D) for each of multiple (illustrated as 4) presence links for multiple users.

It can be understood that the presentation effect information of each presentation link in the presentation link set presented by the user terminal can be obtained by dividing the user intention function and performing laplace transform. Therefore, the technical staff or the publisher of the display link can be helped to analyze the degree of the demand of the user on each product indicated by each display link in the display link set and the presentation effect and the pushing effect of each display link, and the technical staff or the publisher of the display link can be helped to better know the demand and the interest of the user.

In some usage cases, the executing body may further use each of a plurality of user terminals as the user terminal according to the method, so as to obtain, from the plurality of user terminals, presentation effect information of each presentation link in the set of presentation links presented by each of the plurality of user terminals. Then, for each user terminal in the plurality of user terminals, determining presentation effect information of each presentation link in the presentation link set presented by the user terminal, which is characterized by a skewed distribution function. And then calculating deviation coefficients, expected values and variance values of the presentation effect information represented by the skewed distribution function of each presentation link presented by the user terminal. Therefore, deviation coefficients, expected values and variance values of the presentation effect information represented by the skewed distribution function of each presentation link presented by each user terminal in the plurality of user terminals are obtained. And taking the obtained average value of the deviation coefficients as the deviation coefficients of the plurality of users to the single display link, taking the obtained average value of the expected values as the expected values of the plurality of users to the single display link, and taking the obtained average value of the variance values as the variance values of the plurality of users to the single display link. Thus, a biased distribution function of multiple users for a single presentation link can be obtained.

It can be understood that by obtaining the biased distribution function of multiple users for a single display link, the demand degree of multiple users for a product indicated by the single display link can be obtained, thereby helping a technician or a publisher of the display link to analyze the pushing effect of the single display link in a user group and present the presentation effect of each display link in multiple user terminals used by the user group.

In some optional implementation manners of this embodiment, the obtaining user behavior data generated by the user terminal executing the target operation includes: acquiring user behavior data generated by the user terminal executing the target operation in the target operation set in the target historical time period, and acquiring the user behavior data generated by the user terminal executing the target operation in the target operation set in the target historical time period. Thus, the execution body may further: and generating an effect value of a presentation link in the presentation link set of the user terminal in a target historical time period and an effect value of a time point in the target historical time period based on the generated presentation effect information represented by the skewed distribution function.

The effect value can be used for representing the presentation effect and/or the push effect of the display links in the display link set. The technical personnel can set that the larger the effect value is, the better the presentation effect and/or the push effect of the representation display link is, or the smaller the effect value is, the better the presentation effect and/or the push effect of the representation display link is.

The target history time period may be any history time period in which the presentation link is presented in the target terminal device.

As an example, the effect value in the above target history period may be obtained by the following formula:

wherein, the i is used for identifying the display links in the display link set, the k is used for identifying the display links in the display link set, the n represents the number of the display links in the display link set, and the P represents the number of the display links in the display link set_iCharacterizing the effect value presented by the presentation link identified as i within the target historical time period. Sigma_i ²And characterizing the variance of the biased distribution function of the plurality of users for the presentation link identified as i (i.e. the mean of the variance values of the presentation effect information characterized by the biased distribution function of each presentation link presented by each user terminal of the plurality of user terminals). Sigma_k ²The variance of the skewed distribution function of the plurality of users for the presented links identified as k is characterized.

It will be appreciated that after obtaining the fitted bias curves of n display links in a long-time sequence, the variance of each curve can be used to characterize the influence on the user's will, so that the ith display link-only long-time contribution distribution parameter P in the time sequence can be characterized by the above formula (i.e. the above formula about P_iExpression (c).

It should be noted that the sum of the effect values of the presentation links in the presentation link set in the target historical time period may be a preset value (e.g., 1).

Optionally, the executing body may further determine a variance of a skewness distribution function of the multiple users for each presentation link in the presentation link set as an effect value of the presentation link within the target historical time period.

Here, the above-mentioned effect value at the time point within the target history period may be obtained by the following formula:

wherein, the i is used for identifying the display link in the display link set, the k is used for identifying the display link in the display link set, and the n represents the display linkFollowing the number of presentation links in the collection, L_iThe presentation link identified as i characterizes the effect value presented at a point in time (i.e., time of day) within the target historical time period. f. of_i(τ) characterizes the degree of demand of the display chain identified as i at time τ. f. of_k(τ) characterizes the degree of demand at time τ for the display chain identified as k. Here, the demand level f at time τ is linked to a show identified as i_i(τ) may be derived from the skewed distribution function shown in FIGS. 4A-4D, i.e., the abscissa of the image of the skewed distribution function shown in FIGS. 4A-4D represents the time τ, and the ordinate represents the degree of demand f_i(τ). Similarly, for

Can be obtained from the image of the user's intention function shown in fig. 3, i.e. the abscissa of the image of the user's intention function shown in fig. 3 represents the time τ and the ordinate represents the time τ

At the same time, if focus is placed on the distribution of the user's impact effects on the presentation links at a particular time, then the time contribution L distribution parameter may be characterized by the above formula (i.e., the above-described formula with respect to L)_iFormula(s) i assign a contribution to n exposed links with a parameter L, completing the characterization of the point-in-time result for the interaction between the exposed links.

It should be noted that, the sum of the effect values of the presentation links in the presentation link set at the time point in the target historical time period may be a preset value (e.g., 1).

It can be understood that by determining the effect value of the display link in the target historical time period and the effect value of the display link at the time point in the target historical time period, the way of measuring the display effect and the push effect of the display link is enriched.

With continued reference to fig. 5, fig. 5 is a schematic diagram of an application scenario of the method for generating information according to the present embodiment. In the application scenario of fig. 5, after browsing the presentation link presented at the user terminal 501, the user wants to pay attention to the price change situation of the first product indicated by the presentation link in the future time period, and thus, the user performs the attention operation using the user terminal 501. Subsequently, the user terminal 501 performs an operation for responding to the operation of attention (i.e., a target operation), and generates user behavior data 5021 "the user pays attention to the first product", after which the server 502 acquires the above-mentioned user behavior data 5021 from the user terminal 501, then, the server 502 determines, based on the user behavior data 5021, user requirement information 5022 of a user using the user terminal (the requirement degree is 80% in the drawing, where the requirement degree can be represented by a numerical value between 0 and 1, and the larger the numerical value, the higher the requirement degree can be represented), and finally, the server 502 generates, based on the user requirement information 5022, presentation effect information 5023 of the user terminal for presenting the link (the presentation effect is 80 points in the drawing, where the requirement degree can be represented by a score between 0 and 100 points, and the larger the numerical value, the better the presentation effect can be represented).

The method provided by the above-mentioned embodiment of the present disclosure includes obtaining user behavior data generated by the user terminal executing the target operation, wherein the target operation is an operation for a virtual product corresponding to a product indicated by a presentation link presented by the user terminal, then, based on the user behavior data, user demand information of the user using the user terminal is determined, wherein the user demand information characterizes a degree of demand of the user for a product indicated by the presentation link in the set of presentation links, and finally, generating presentation effect information of the presentation links in the presentation link set presented by the user terminal based on the user demand information, thereby determining the user demand information based on the user behavior data, and then generating presentation effect information showing the link at the user terminal, thereby enriching the mode of generating the presentation effect information and improving the accuracy of generating the presentation effect information.

With further reference to fig. 6, a flow 600 of yet another embodiment of a method for generating information is shown. The flow 600 of the method for generating information comprises the steps of:

step 601, acquiring user behavior data generated by the user terminal executing the target operation.

In this embodiment, step 601 is substantially the same as step 201 in the corresponding embodiment of fig. 2, and is not described herein again.

Step 602, a Markov model is constructed based on the association probability set, the predetermined user category set and the target operation set.

In this embodiment, an executing agent (e.g., a server shown in fig. 1) of the method for generating information may construct a markov model (MarkovModel) based on the association probability set, the predetermined user category set, and the target operation set. The state information of the Markov model is used for representing the user category in the user category set or the target operation in the target operation set, and the element of the probability matrix is the association probability in the association probability set. The probability matrix is derived based on the association probability set.

As an example, please refer to fig. 7. Figure 7 illustrates a markov model structure diagram according to one embodiment of the present disclosure. As shown, the markov model includes state information of "state information 1, state information 2, … state information n". Where n represents the amount of state information. For example, when the user category set includes 5 user categories and the target operation set includes 10 target operations, the value of n may be 50. The elements in the probability matrix included in the markov model may be associated probabilities in the associated probability set.

Here, a Hidden Markov Model (HMM) is a double stochastic process consisting of a Markov process (i.e., a Markov Model) and a general stochastic process, which can perform the following tasks according to different algorithms:

task one: and (5) solving a historical data sorting problem. The forward and backward algorithm: and solving the probability of the observed sequence under the given model.

And a second task: new data access problems. Viterbi (Viterbi) algorithm: and solving a state sequence corresponding to the observation sequence under the given model.

And a third task: and (5) integral model training. Baum-Welch algorithm: an optimal model of the sequence of states is generated.

It should be noted that the construction method of the markov model is a well-known technology widely studied at present, and is not described herein again.

Turning now to fig. 6.

Step 603, determining a user intention function corresponding to the user using the user terminal based on the Markov model.

In this embodiment, the execution subject may determine a user intention function corresponding to a user using the user terminal based on a probability matrix included in the markov model.

Here, the execution body may determine the total demand degree by the following formula, that is, the following formula may characterize a user intention function corresponding to a user using the user terminal:

wherein Q represents the total demand level. n characterizes the product of the number of user categories in the set of user categories and the number of target operations in the set of target operations, or in other words, n characterizes the total number of elements in the probability matrix comprised by the Markov model (e.g., if the set of user categories comprises 5 user categories and the set of target operations comprises 10 target operations, then the value of n in the formula may be 50) i and j are used to identify the state. Iij characterizes the probability of the j-th state transitioning to the i-th state. Oij characterize the probability of transitioning to the j-th state. Iij and Oij are the elements in the probability matrix, respectively. p is a radical of_ijIs a state afferent gain factor (predetermined weight for Iij), q, preset for Iij_ijIs a preset Oij state outgoing profit-and-loss factor (weight predetermined for Oij). m is_iIs a preset weight of the i-th state. P is above_ij、q_ij、m_iMay be pre-stored parameters, respectively.

Optionally, the result of the weighted summation of the elements in the probability matrix may be determined as a requirement degree, so as to further obtain a user intention function corresponding to the user using the user terminal.

And step 604, generating presentation effect information of the user terminal on the display link based on the user requirement information.

In this embodiment, step 604 is substantially the same as step 203 in the corresponding embodiment of fig. 2, and is not described herein again.

As an example, the data acquired by the execution subject can be user behavior data (including data generated by operations such as browsing, paying attention, buying, and migrating object line operations (e.g. purchasing) on a category or a single product at various times) from a network and behavior data (including data generated by operations such as exposure, clicking on a page, and the like at various times) of a platform for pushing a show link, and a fitting degree of a product will of a user on a product indicated by the show link is obtained through a cross analysis of L TV (life time value) model and the user behavior.

In fig. 7, a structural schematic diagram of the markov model according to an embodiment of the present disclosure is shown, and a state jump stability probability (O0101-O0150, O0201-O0250 …) and a jump stability probability (I0101-I0150, I0201-I0250 …) can be determined by weighting a state space of a user attribute × behavior with respect to a total willingness level Q (i.e., a total demand degree), wherein m is a weight of an I-th state, p is a state gain factor, and Q is a state jump loss factor, which are parameters obtained in a database.

Wherein Q represents the total demand level. n characterizes the product of the number of user categories in the set of user categories and the number of target operations in the set of target operations, or in other words, n characterizes the total number of elements in the probability matrix comprised by the Markov model (e.g., if the set of user categories comprises 5 user categories and the set of target operations comprises 10 target operations, then the value of n in the formula may be 50) i and j are used to identify the state. Iij characterizes the probability of the j-th state transitioning to the i-th state. Oij characterize the probability of transitioning to the j-th state. Iij and Oij are the elements in the probability matrix, respectively. p is a radical of_ijIs preset for IijQ (predetermined weight for Iij), q_ijIs a preset Oij state outgoing profit-and-loss factor (weight predetermined for Oij). m is_iIs a preset weight of the i-th state. P is above_ij、q_ij、m_iMay be pre-stored parameters, respectively.

It can be understood that the representation degree of the total demand degree can be obtained by the above expression, and the total demand degree can be represented as a fluctuating curve through a time axis.

In some use cases, on the basis of the theory, the functional application with rich content and diversified forms can be further realized.

1. And predicting the willingness behaviors of the user.

Different from a violent machine learning algorithm, the technical scheme provided by the disclosure can generate the comprehensive effect (long-term brand effect and real-time effect) prediction of products in real time according to the historical data of users, the expressions of all links can artificially correct parameters according to actual conditions, and the method is beneficial to the user behavior difference between different categories and different brands, for example, the household appliances and snacks have a migration object row operation (for example, purchase) interval with large difference, and the computers and the mothers and babies have audience orientation with large difference. For the dimension intersection among different merchants, different industries and different audience groups, the exhibition link contribution distribution system can meet the following requirements:

(1) future behavior expectations based on historical behavior of the user.

A Hidden Markov Model-HMM (Hidden Markov Model-HMM) is a dual stochastic process consisting of a Markov process and a general stochastic process, which can perform the following tasks according to different algorithms:

historical data collation problem-forward and backward algorithm: solving the probability of an observation sequence under a given model;

new data access problem-Viterbi algorithm: solving a state sequence corresponding to the observation sequence under a given model;

integral model training problem-Baum-Welch algorithm: generating an optimal model of the sequence of states;

the method comprises the steps of firstly, conducting history arrangement on user historical behavior data, fitting the association degree between user attributes and behaviors and the association degree of each attribute and behavior, wherein the association degree comprises the probability of making a certain behavior by an attribute user, the time flow rate of converting the certain behavior into other attributes, the types of the up-and-down associated behaviors of a certain behavior, the change rate of the flow direction of the corresponding attributes and the like.

(2) And displaying link release period expectation based on user intention representation.

The actual effect of the display link at each stage can be fitted to the user through the wish bias curve, the influence of the new display link on the user wish can be estimated after the total statistics of historical display link data, the forecast of the display link release period for maintaining the user brand wish to be higher than the threshold value is completed, and the display link release system can be brought into the full-automatic era.

2. And enhancing the display link scheduling system logic.

Most of the prior display link scheduling systems complete scheduling of display link exposure in a certain time period in the future according to 'crowd pack orientation' + 'traffic estimation', and after the display link contribution distribution based on the display link contribution distribution system, check logic of the display link on a timeline can be strengthened, so that the effectiveness of the display link effect in the display link scheduling logic is obviously improved, and valuable traffic resources of media are saved.

3. And enhancing the logic of the display link creative platform.

At present, the working mode of most display and link creative platforms is a mode of randomly generating pictures and documentations, and more advanced customized platforms can automatically generate documentations by using a more advanced CNN or RNN mode, wherein data sets are derived from existing display and link documentations and pictures existing in the market, are sorted according to click rate and are handed to a system for learning. The reward setting is single, and after the contribution conclusion of the exhibition link contribution distribution system is applied, the exhibition link can be customized according to the conditions in batches and in different time periods instead of using the same reward logic facing different brand periods and different audience groups, so that the driving capability of user behavior data on the exhibition link creative idea is greatly improved, and the exhibition link creative platform has more, more perfect and more comprehensive reference bases.

4. And increasing the display effect of the display link end plan.

All the exhibition link proposal reports on the market only cover the demonstration of the effect of single exhibition link release, and the data comprises exposure times, click rate, operation (e.g. purchase) rate of the migration object row and the like. After the exhibition link contribution analysis platform is added, long-term influence of exhibition links can be given to the exhibition link party on a long-term time sequence, so that the exhibition link effect is more truly and comprehensively presented to the exhibition link party, and an important theoretical basis is provided for subsequent optimization of user experience.

In some optional implementations of this embodiment, the executing body may further execute the following steps (including step one and step two):

step one, responding to the received display link to be pushed, and determining whether the display link to be pushed is displayed at the user terminal or not based on the display effect information.

For example, the executing body may first determine whether the category to which the display link presented by the user terminal belongs is the same as or similar to the category to which the display link to be pushed belongs (for example, when the category to which the display link belongs is "600-" and the category to which the display link to be pushed belongs is "600-" it may be determined that the category to which the display link belongs is similar to the category to which the display link to be pushed belongs), and if the categories are the same as or similar to each other, the executing body may determine that the display link to be pushed is presented at the user terminal; if not, the execution body may determine not to present the to-be-pushed presentation link in the user terminal.

As another example, the executing entity may first determine a similarity between product information of a product indicated by the display link presented by the user terminal and product information of a product indicated by the display link to be pushed, then the executing entity may determine whether the determined similarity is greater than a predetermined similarity threshold, and if so, the executing entity may determine that the display link to be pushed is presented at the user terminal; if the current link is less than or equal to the push link, the execution body may determine not to present the to-be-pushed presentation link in the user terminal.

It should be noted that, a skilled person may determine whether to present the to-be-pushed presentation link in the user terminal according to actual needs, and the above example is merely illustrative and does not constitute a limitation to the embodiments of the present disclosure.

It can be understood that whether the display link to be pushed is presented at the user terminal is determined by presenting the effect information, so that more targeted information pushing can be realized. For example, after the executing agent determines that the to-be-pushed display link is presented at the user terminal, the executing agent may send the to-be-pushed display link to the user terminal, so that the user terminal presents the to-be-pushed display link; and under the condition that the execution main body determines that the display link to be pushed is not presented at the user terminal, the user terminal cannot present the display link to be pushed. Therefore, more targeted information pushing is realized, the information pushing modes are enriched, and the information pushing accuracy is improved.

And step two, responding to the confirmation that the display link to be pushed is presented at the user terminal, and sending the display link to be pushed to the user terminal so that the user terminal presents the display link to be pushed.

In some optional implementations of this embodiment, the execution main body may further adopt the following steps (including sub-step one and sub-step two) instead of the execution of the step two:

and the first substep is to determine the presentation information of the display link to be pushed at the user terminal. Wherein the presence information comprises at least one of: presenting initial time and presenting duration.

For example, the execution subject may determine the presentation information of the to-be-pushed presentation link at the user terminal according to the category (e.g., clothing category, fresh category, etc.) to which the to-be-pushed presentation link belongs. As an example, it is assumed that a technician sets corresponding presentation information for a category to which each to-be-pushed display link belongs in advance (for example, presentation information "18: 00, 3 h" of a clothing category, which indicates that if the category to which the to-be-pushed display link belongs is the clothing category, then 6 pm every day is used as presentation initial time of the to-be-pushed display link, 3 hours is used as presentation duration of the to-be-pushed display link, and presentation information "11: 00, 2 h" of a fresh category indicates that if the category to which the to-be-pushed display link belongs is the fresh category, then 11 am every day is used as presentation initial time of the to-be-pushed display link, and 2 hours is used as presentation duration of the to-be-pushed display link), therefore, the execution main body can use the presentation information corresponding to the category to which the display link to be pushed belongs as the presentation information of the display link to be pushed on the user terminal.

As another example, the executing entity may further determine the presence information of the to-be-pushed presentation link at the user terminal based on the markov model.

Here, the execution body may use at least one to-be-pushed presentation link as an observation sequence, so as to use the markov model to predict the behavior of the user. For example, for each display link to be pushed, the probability of each target operation in the target operation set executed by the user is determined, so as to determine the target operation in the target operation set corresponding to the maximum probability in each probability, and thus determine the presentation information of the display link to be pushed at the user terminal according to the time corresponding to each probability. For example, the target operation set includes a target operation "migration object row operation (e.g., purchase)", and the probability that the user performs the target operation "migration object row operation (e.g., purchase)" from 1 point to 2 points through the user terminal is predicted to be 0.1 according to the markov model; the probability that the user performs the target operation "migration object row operation (e.g., purchase)" from 2 o 'clock to 3 o' clock through the user terminal is 0.8; the probability that the user performs the target operation "migration object line operation (e.g., purchase)" through the user terminal at 3 o 'clock to 4 o' clock is 0.1. Then, the executing entity may use the presentation information (for example, presentation initial time "2 points", presentation duration "1 hour") corresponding to the probability that the probability value is greater than the preset threshold (for example, 0.5) as the presentation information of the to-be-pushed presentation link at the user terminal.

And step two, sending the display link to be pushed and the presentation information to the user terminal so that the user terminal presents the display link to be pushed according to the presentation mode indicated by the presentation information.

It is understood that the executing body may send the to-be-pushed presentation link and the presentation information to the user terminal. After receiving the display link to be pushed and the presentation information, the user terminal may present the display link to be pushed at a presentation initial time indicated by the presentation information, and hide (i.e., not present) the display link to be pushed after a presentation time indicated by the presentation information elapses from the presentation initial time.

In some optional implementation manners of this embodiment, in the case that it is determined that the to-be-pushed presentation link is presented at the user terminal, the execution main body may further determine a presentation time of the to-be-pushed presentation link at the user terminal. The presentation time may be a duration of presenting the to-be-pushed presentation link (for example, continuously presenting for 2 hours), or may be a time point of presenting the to-be-pushed presentation link (for example, presenting from 0 point to 24 points on 14 days of 2 months).

As an example, the execution subject may determine a presentation time of the presentation link presented by the user terminal as a presentation time of the presentation link to be pushed on the user terminal. Optionally, the execution main body may further determine, as the presentation time of the to-be-pushed presentation link in the user terminal, the presentation time of the presentation link presented by the user terminal plus a predetermined time (for example, 3 months).

For example, if the display link presented by the user terminal is an european style lady one-piece dress, the presentation time of the display link is "7 month 1 day to 7 month 31 day", and the display link to be pushed is an european style woolen lady coat, the execution main body may determine the presentation time of the display link presented by the user terminal plus a predetermined time (e.g., 3 months) as the presentation time of the display link to be pushed at the user terminal, and thus, the execution main body may determine that the presentation time of the display link to be pushed at the user terminal is "10 month 1 day to 10 month 31 day".

It can be understood that the information push mode can be further enriched by determining the presentation time of the display link to be pushed at the user terminal. Therefore, the display effect of the display link to be pushed on the user terminal can be ensured, and other display links except the display link to be pushed can be pushed in time.

In some optional implementation manners of this embodiment, the execution main body may further send the presentation effect information to the presentation link providing end, so that the presentation link providing end presents the presentation effect information. The display link provider may be configured to provide a display link (e.g., an advertisement), and the display link provider may be a server or a terminal device.

It can be understood that after the display link providing end presents the presentation effect information, relevant personnel (for example, a worker responsible for pushing the display link) can intuitively determine the presentation effect of the historical display link through the presentation effect information presented by the display link providing end, so that the display link suitable for providing is determined based on the presentation effect information.

As can be seen from fig. 6, compared with the embodiment corresponding to fig. 2, the flow 600 of the method for generating information in the present embodiment highlights the step of determining the user willingness function corresponding to the user using the user terminal by using the constructed markov model. The solution described in this embodiment thus enriches the way of determining the user willingness function corresponding to the user using the user terminal, and, in addition, since the embodiment firstly arranges the user behavior data to obtain the association probability set, and further constructs the Markov model, thus, when new data is accessed (for example, effect prediction needs to be carried out on the link to be pushed and shown), the executive body can carry out prediction on the new data through the Markov model, therefore, the conversion situation (for example, the probability of the user migrating the object row to operate (for example, purchase) the product indicated by the exhibition link to be pushed) between the state information of the new data and the relation between the conversion situation and the time (for example, the time of the user migrating the object row to operate (for example, purchase) the product with knowledge of the exhibition link to be pushed) are obtained, and compared with the prior art, the prediction accuracy can be improved by utilizing the Markov model for prediction. Moreover, the display effect information of the display links to be pushed can be predicted through the Markov model, so that the display links to be pushed with good display effect (for example, the effect value is greater than the preset effect threshold value or the preset number of the display links to be pushed with good display effect information) can be further sent to the terminal equipment through comparing the display effects of the display links to be pushed, and the display links to be pushed can be presented by the terminal equipment.

With further reference to fig. 8, a flow 800 of a third embodiment of a method for generating information is shown. The flow 800 of the method for generating information comprises the steps of:

step 801, user behavior data generated by the user terminal executing the target operation is acquired.

Step 802, determining user demand information of a user using a user terminal based on user behavior data.

And 803, generating presentation effect information of the user terminal on the display link based on the user requirement information.

In this embodiment, steps 801 to 803 are substantially the same as steps 201 to 203 in the corresponding embodiment of fig. 2, and are not described herein again.

Step 804, in response to receiving the display link to be pushed, determining whether to present the display link to be pushed at the user terminal based on the presentation effect information.

In this embodiment, in response to receiving the to-be-pushed presentation link, an execution subject (e.g., the server shown in fig. 1) of the method for generating information may determine whether to present the to-be-pushed presentation link at the user terminal based on the presentation effect information.

Step 805, in response to determining that the to-be-pushed display link is presented at the user terminal, sending the to-be-pushed display link to the user terminal, so that the user terminal presents the to-be-pushed display link.

In this embodiment, in response to determining that the to-be-pushed presentation link is presented at the user terminal, the execution main body may send the to-be-pushed presentation link to the user terminal, so that the user terminal presents the to-be-pushed presentation link.

It should be noted that, besides the features and effects described above with respect to the embodiment corresponding to fig. 8, the embodiment corresponding to fig. 8 may further include the features and effects corresponding to the above-mentioned fig. 2 to fig. 6, and the embodiments of the present disclosure are not described again here.

As can be seen from fig. 8, compared with the embodiment corresponding to fig. 2, the process 800 of the method for generating information in this embodiment determines whether to present the display link to be pushed on the user terminal through the presentation effect information, so that more targeted information pushing can be implemented. For example, after the executing agent determines that the to-be-pushed display link is presented at the user terminal, the executing agent may send the to-be-pushed display link to the user terminal, so that the user terminal presents the to-be-pushed display link; and under the condition that the execution main body determines that the display link to be pushed is not presented at the user terminal, the user terminal cannot present the display link to be pushed. Therefore, more targeted information pushing is realized, the information pushing modes are enriched, and the information pushing accuracy is improved. In addition, after the display link to be pushed is determined to be presented at the user terminal, the display link to be pushed is sent to the user terminal so that the display link to be pushed can be presented at the user terminal, and therefore selective sending of the display link to be pushed to the user terminal can be achieved (selective sending of the display link to be pushed is achieved for a specific user terminal instead of all the display links to be pushed, and selective sending of the display link to the user terminal is achieved for the specific display link instead of all the user terminals) can be achieved, and therefore the scheme provided by the embodiment can be small in occupation of network resources and network traffic can be saved.

With further reference to fig. 9, a flow 900 of a fourth embodiment of a method for generating information is shown. The process 900 of the method for generating information includes the steps of:

step 901, obtaining user behavior data generated by the user terminal executing the target operation.

Step 902, determining user demand information of a user using a user terminal based on user behavior data.

And 903, generating presentation effect information of the user terminal on the display link based on the user requirement information.

In this embodiment, steps 901 to 903 are substantially the same as steps 201 to 203 in the embodiment corresponding to fig. 2, and are not described here again.

Step 904, in response to receiving the display link to be pushed, determining whether to present the display link to be pushed at the user terminal based on the presentation effect information.

Step 905, in response to determining that the to-be-pushed display link is presented at the user terminal, determining presentation information of the to-be-pushed display link at the user terminal.

In this embodiment, in response to determining that the to-be-pushed presentation link is presented at the user terminal, the execution main body may determine presentation information of the to-be-pushed presentation link at the user terminal. Wherein the presence information comprises at least one of: presenting initial time and presenting duration.

Step 906, sending the display link to be pushed and the presentation information to the user terminal, so that the user terminal presents the display link to be pushed according to the presentation mode indicated by the presentation information.

In this embodiment, the execution main body may send the display link to be pushed and the presentation information to the user terminal, so that the user terminal presents the display link to be pushed according to the presentation manner indicated by the presentation information.

It should be noted that, besides the features and effects described above with respect to the embodiment corresponding to fig. 9, the embodiment corresponding to fig. 9 may further include the features and effects corresponding to the above-mentioned fig. 2 to fig. 6, and the embodiments of the disclosure are not described again here.

As can be seen from fig. 9, compared with the embodiment corresponding to fig. 2, in the flow 900 of the method for generating information in this embodiment, the execution main body may send the display link to be pushed and the presentation information to the user terminal. After receiving the display link to be pushed and the presentation information, the user terminal may present the display link to be pushed at a presentation initial time indicated by the presentation information, and hide (i.e., not present) the display link to be pushed after a presentation time indicated by the presentation information elapses from the presentation initial time. After hiding one show link, it may present another show link, so that an initial time and a presentation duration for each show link may be determined.

With further reference to fig. 10, a flow 1000 of a fifth embodiment of a method for generating information is shown. The process 1000 of the method for generating information comprises the following steps:

step 1001, user behavior data generated by the user terminal executing the target operation is acquired.

Step 1002, determining user requirement information of a user using a user terminal based on the user behavior data.

And 1003, generating presentation effect information of the user terminal on the display link based on the user requirement information.

In this embodiment, steps 1001 to 1003 are substantially the same as steps 201 to 203 in the embodiment corresponding to fig. 2, and are not described herein again.

Step 1004, sending the presentation effect information to the presentation link provider for the presentation link provider to present the presentation effect information.

In this embodiment, an execution subject (for example, a server shown in fig. 1) of the method for generating information may send the presentation effect information to the presentation link provider, so that the presentation link provider presents the presentation effect information.

It should be noted that, besides the features and effects described above with respect to the embodiment corresponding to fig. 10, the embodiment corresponding to fig. 10 may further include the features and effects corresponding to the above-mentioned fig. 2 to fig. 6, and the embodiments of the present disclosure are not described again here.

As can be seen from fig. 10, compared with the embodiment corresponding to fig. 2, in the process 1000 of the method for generating information in this embodiment, after the display link providing end presents the presentation effect information, a relevant person (for example, a worker responsible for pushing the display link) can intuitively determine the presentation effect of the historical display link through the presentation effect information presented by the display link providing end, so as to determine the display link suitable for providing based on the presentation effect information.

With further reference to fig. 11, as an implementation of the methods illustrated in the above figures, the present disclosure provides an embodiment of an apparatus for generating information, the apparatus embodiment corresponding to the method embodiment illustrated in fig. 2, and the apparatus embodiment may further include the same or corresponding features as the method embodiment illustrated in fig. 2, in addition to the features described below. The device can be applied to various electronic equipment.

As shown in fig. 11, the apparatus 1100 for generating information of the present embodiment includes: an acquisition unit 1101, a first determination unit 1102, and a first generation unit 1103. The obtaining unit 1101 is configured to obtain user behavior data generated by the user terminal performing a target operation, wherein the target operation is an operation for a virtual product corresponding to a product indicated by a presentation link presented by the user terminal; the first determining unit 1102 is configured to determine user demand information of a user using the user terminal based on the user behavior data, wherein the user demand information characterizes a degree of demand of the user for a product indicated by a presentation link in the presentation link set; the first generating unit 1103 is configured to generate presentation effect information of the user terminal to the presentation link based on the user demand information.

In this embodiment, the acquisition unit 1101 of the apparatus 1100 for generating information may acquire user behavior data generated by the user terminal performing the target operation by a wired connection manner or a wireless connection manner.

The target operation may be an operation for a virtual product corresponding to a product indicated by a display link in the display link set presented by the user terminal.

In this embodiment, based on the user behavior data obtained by the obtaining unit 1101, the first determining unit 1102 may determine the user requirement information of the user using the user terminal. The user demand information can represent the demand degree of the user for the products indicated by the display links in the display link set. As an example, the user requirement information may be characterized by words, numerical values, and the like. For example, the user demand information may be "much needed", "generally needed", "hardly needed", and the like. Optionally, the user requirement information may also be "1", "2" or "3". Wherein, 1 can characterize "very desirable", "2" can characterize "general desirable", and "3" can characterize "almost undesirable".

In this embodiment, based on the user requirement information obtained by the first determining unit 1102, the first generating unit 1103 may generate the presentation effect information of the user terminal on the presentation link. Wherein, the presentation effect information may be information characterizing the presentation effect of the presentation link. The presentation effect information may be represented by words, numbers, or the like. As an example, the presentation effect information may be "good" or "bad", or may be "1" or "2". When the presentation effect information is represented by a numerical value, a technician can specify that the presentation effect information with larger numerical value represents that the presentation effect is better, or that the presentation effect information with smaller numerical value represents that the presentation effect is better.

In some optional implementation manners of this embodiment, the user demand information is represented by a user demand function, and the user demand function represents a corresponding relationship between time and a total demand degree of the user for a product set indicated by the presentation link set.

In some optional implementations of this embodiment, the target operation belongs to a predetermined set of target operations; and the first determination unit 1102 includes: the first determining subunit (not shown in the figures) is configured to determine a user willingness function corresponding to a user using the user terminal based on a set of association probabilities, wherein the set of association probabilities is determined based on the user behavior data, and the association probabilities characterize any one of: the user category in the user category set is converted into the probability of the user category in the user category set, the probability of executing any target operation in the target operation set after executing the target operation in the target operation set, the probability of using the user terminal to execute the target operation in the target operation set by the user belonging to the user category in the user category set, and the probability of using the user belonging to the user category in the user category set by the user terminal to execute the target operation in the target operation set.

In some optional implementation manners of this embodiment, the user demand information is represented by a user demand function, the user demand function represents a corresponding relationship between time and a total demand degree of the user for a product set indicated by the display link set, and the total demand degree is represented by a value.

In some optional implementations of this embodiment, the first determining subunit includes: the dividing module (not shown in the figure) is configured to divide the user intention function according to the presentation time of the display link to obtain a user product intention function set; the transformation module (not shown in the figure) is configured to perform laplace transformation on the user product intention function according to the user product intention function in the user product intention function set to obtain presentation effect information of the user terminal on the presentation link, wherein the presentation effect information is represented by a skewed distribution function.

In some optional implementations of this embodiment, the obtaining unit 1101 includes: an acquisition subunit (not shown in the figure) is configured to acquire user behavior data generated by the user terminal executing a target operation in the target operation set within a target history time period; and the apparatus 1100 further comprises: the second generating unit (not shown in the figure) is configured to generate an effect value of a presentation link in the presentation link set of the user terminal in the target historical time period and an effect value at a time point in the target historical time period based on the generated presentation effect information characterized by the skewed distribution function.

In some optional implementations of this embodiment, the first determining subunit includes: a building module (not shown in the figure) is configured to build a Markov model based on the association probability set, the predetermined user category set and the target operation set, wherein state information of the Markov model is used for characterizing the user category in the user category set or the target operation in the target operation set, and elements of the probability matrix are association probabilities in the association probability set; the determination module (not shown in the figures) is configured to determine, based on the markov model, a corresponding user willingness function for the user using the user terminal.

In some optional implementations of this embodiment, the apparatus 1100 further includes: the second determining unit (not shown in the figure) is configured to respond to the receiving of the exhibition link to be pushed, and determine whether to present the exhibition link to be pushed on the user terminal based on the presentation effect information; the first sending unit (not shown in the figure) is configured to send the to-be-pushed presentation link to the user terminal in response to determining that the to-be-pushed presentation link is presented at the user terminal, so that the user terminal presents the to-be-pushed presentation link.

In some optional implementations of this embodiment, the first sending unit 1103 includes: the second determining subunit (not shown in the figure) is configured to determine presence information linked to the user terminal by the to-be-pushed presentation, wherein the presence information includes at least one of the following: presenting initial time and presenting duration; the sending subunit (not shown in the figure) is configured to send the display link to be pushed and the presentation information to the user terminal, so that the user terminal presents the display link to be pushed according to the presentation manner indicated by the presentation information.

In some optional implementations of this embodiment, the apparatus 1100 further includes: the second sending unit (not shown in the figure) is configured to send the presentation effect information to the presentation link providing terminal, so that the presentation link providing terminal presents the presentation effect information.

The apparatus provided by the above-mentioned embodiment of the present disclosure acquires, by the acquiring unit 1101, user behavior data generated by a user terminal performing a target operation, where the target operation is an operation for a virtual product corresponding to a product indicated by a presentation link presented by the user terminal, then the first determining unit 1102 determines user demand information of a user using the user terminal based on the user behavior data, where the user demand information characterizes a degree of demand of the user for the product indicated by the presentation link in a set of presentation links, and then the first generating unit 1103 generates presentation effect information of the user terminal for the presentation link based on the user demand information, thereby determining the user demand information based on the user behavior data, and further generating presentation effect information of the presentation link at the user terminal, thereby enriching a manner of generating the presentation effect information, the accuracy of generating the presentation effect information is improved.

Referring now to FIG. 12, a flow 1200 of one embodiment of a method for generating a model in accordance with the present disclosure is shown. The method for generating the model comprises the following steps:

step 1201, acquiring user behavior data generated by the user terminal in the user terminal set executing the target operation in the target operation set.

In this embodiment, an execution subject (for example, a server shown in fig. 1) of the method for generating information may acquire, in a wired manner or a wireless manner, user behavior data generated by a user terminal in a user terminal set executing a target operation in a target operation set from a local or other electronic device. Wherein the target operation is an operation for a virtual product corresponding to the product indicated by the presentation link.

And 1202, counting the user behavior data to construct a Markov model.

In this embodiment, the execution subject may perform statistics on the user behavior data to construct a Markov Model (Markov Model). The state information of the Markov model is used for representing the user category in the user category set or the target operation in the target operation set, and the user category is the category to which the user using the user terminal in the user terminal set belongs.

The method provided by the above embodiment of the present disclosure includes acquiring user behavior data generated by a user terminal in a user terminal set executing a target operation in a target operation set, where the target operation is an operation for a virtual product, the virtual product corresponds to a product indicated by a display link, and then performing statistics on the user behavior data to construct a markov model, where state information of the markov model is used to characterize a user category in a user category set or the target operation in the target operation set, and the user category is a category to which a user using the user terminal in the user terminal set belongs, so that training modes of the model are enriched, and it is helpful for predicting a behavior of the user based on the obtained model, thereby reducing network resource occupation and reducing network traffic.

With continuing reference to fig. 13, as an implementation of the method shown in fig. 12 described above, the present disclosure provides an embodiment of an apparatus for generating a model, the embodiment of the apparatus corresponding to the embodiment of the method shown in fig. 12, and the embodiment of the apparatus may further include the same or corresponding features as the embodiment of the method shown in fig. 12, except for the features described below. The device can be applied to various electronic equipment.

As shown in fig. 13, the apparatus 1300 for generating information of the present embodiment includes: an obtaining unit 1301 and a constructing unit 1302. The obtaining unit 1301 is configured to obtain user behavior data generated by a user terminal in the user terminal set executing a target operation in the target operation set, where the target operation is an operation for a virtual product, and the virtual product corresponds to a product indicated by the display link; the constructing unit 1302 is configured to count the user behavior data to construct a markov model, where state information of the markov model is used to characterize a user category in the set of user categories or a target operation in the set of target operations, and the user category is a category to which a user using a user terminal in the set of user terminals belongs.

In this embodiment, the obtaining unit 1301 of the apparatus 1300 for generating a model may obtain, by a wired manner or a wireless manner, user behavior data generated by a user terminal in the set of user terminals executing a target operation in the set of target operations from a local or other electronic device. Wherein the target operation is an operation for a virtual product corresponding to the product indicated by the presentation link.

In this embodiment, the constructing unit 1302 may perform statistics on the user behavior data to construct a Markov Model (Markov Model). The state information of the Markov model is used for representing the user category in the user category set or the target operation in the target operation set, and the user category is the category to which the user using the user terminal in the user terminal set belongs.

The apparatus provided by the foregoing embodiment of the present disclosure obtains, by the obtaining unit 1301, user behavior data generated by a user terminal in a user terminal set executing a target operation in a target operation set, where the target operation is an operation for a virtual product, and the virtual product corresponds to a product indicated by a display link, and then, the building unit 1302 counts the user behavior data to build a markov model, where state information of the markov model is used to characterize a user category in a user category set or the target operation in the target operation set, and the user category is a category to which a user using the user terminal in the user terminal set belongs, so that training modes of the model are enriched, and it is helpful to predict behaviors of the user based on the obtained model, thereby reducing network resource occupation and reducing network traffic.

Turning next to fig. 14, a flow 1400 of one embodiment of another method for generating information in accordance with the present disclosure is illustrated. The method for generating information comprises the following steps:

step 1401, receiving a display link to be pushed.

In this embodiment, an execution subject (for example, a server shown in fig. 1) of the method for generating information may receive the exhibition link to be pushed in a wired connection manner or a wireless connection manner.

Here, the to-be-pushed exhibition link may be information (e.g., advertisement) to be pushed for pushing a product. The presentation link may be presented in at least one of the following ways: text, pictures, audio, video, etc. By way of example, when the product is "toothpaste", the display link may be "XX toothpaste, known at all". The user terminal may present all or part of the presentation links in the set of presentation links.

Step 1402, generating a demand degree of the user for the product indicated by the to-be-pushed display link based on the pre-generated Markov model.

In this embodiment, the executing entity may generate a demand level of the user for the product indicated by the to-be-pushed display link based on a pre-generated markov model. Wherein the Markov model is generated according to the method of any one of the embodiments of the method for generating a model as described above.

Here, the execution body may use at least one display link to be pushed as an observation sequence, so as to predict the behavior of the user by using the markov model, thereby generating the demand level of the user for the product indicated by the display link to be pushed. For example, for the display link to be pushed, the probability of each target operation in the target operation set executed by the user is determined, so as to determine the target operation in the target operation set corresponding to the maximum probability in each probability, and thus determine the presentation information of the display link to be pushed at the user terminal according to the time corresponding to each probability. For example, the target operation set includes a target operation "migration object row operation (e.g., purchase)", and the probability that the user performs the target operation "migration object row operation (e.g., purchase)" from 1 point to 2 points through the user terminal is predicted to be 0.1 according to the markov model; the probability that the user performs the target operation "migration object row operation (e.g., purchase)" from 2 o 'clock to 3 o' clock through the user terminal is 0.8; the probability that the user performs the target operation "migration object line operation (e.g., purchase)" through the user terminal at 3 o 'clock to 4 o' clock is 0.1. Then, the executing entity may use the presentation information (for example, presentation initial time "2 points", presentation duration "1 hour") corresponding to the probability that the probability value is greater than the preset threshold (for example, 0.5) as the presentation information of the to-be-pushed presentation link at the user terminal.

Next, the execution subject may generate the demand degree of the user for the product indicated by the to-be-pushed display link based on the probability value of each time and a numerical value representing the demand degree of the product, which is set in advance for the target operation. For example, the probability value of each time and a value which is set for the target operation in advance and represents the demand degree of the product, the result of weighted summation of the two certificates, or the product of the result of weighted summation and a preset value (for example, 100) are determined as the demand degree of the user for the product indicated by the display link to be pushed.

In some optional implementation manners of this embodiment, the execution main body may further determine whether to push the to-be-pushed presentation link to the target user terminal based on the degree of demand. The target user terminal may be any user terminal in the user terminal set, or may be any user terminal that can accept the presentation link.

For example, the executing entity may first determine whether the category to which the display link presented by the target user terminal belongs is the same as or similar to the category to which the display link to be pushed belongs (for example, when the category to which the display link belongs is "500-" 600- "and the category to which the display link to be pushed belongs is" 600- "it may be determined that the category to which the display link belongs is similar to the category to which the display link to be pushed belongs), and if the same as or similar to the category to which the display link to be pushed belongs, the executing entity may determine that the display link to be pushed is presented at the user terminal; if not, the execution body may determine not to present the to-be-pushed presentation link in the user terminal.

In some optional implementation manners of this embodiment, in response to determining that the to-be-pushed display link is pushed to the target user terminal, the execution main body may further send the to-be-pushed display link to the target user terminal, so that the target user terminal presents the to-be-pushed display link.

In some optional implementation manners of this embodiment, sending the display link to be pushed to the target user terminal, so that the target user terminal presents the display link to be pushed, includes the following steps:

step one, determining the presentation information of the display link to be pushed at the target user terminal. Wherein the presence information comprises at least one of: presenting initial time and presenting duration.

Here, the execution body may use at least one to-be-pushed presentation link as an observation sequence, so as to use the markov model to predict the behavior of the user. For example, for each display link to be pushed, the probability of each target operation in the target operation set executed by the user is determined, so as to determine the target operation in the target operation set corresponding to the maximum probability in each probability, and thus determine the presentation information of the display link to be pushed at the user terminal according to the time corresponding to each probability. For example, the target operation set includes a target operation "purchase", and the predicted probability that the user performs the target operation "purchase" through the user terminal at 1 point to 2 points is 0.1 according to the markov model; the probability that the user performs the target operation 'purchase' through the user terminal from 2 o 'clock to 3 o' clock is 0.8; the probability that the user performs the target operation "purchase" through the user terminal at 3 o 'clock to 4 o' clock is 0.1. Then, the executing entity may use the presentation information (for example, presentation initial time "2 points", presentation duration "1 hour") corresponding to the probability that the probability value is greater than the preset threshold (for example, 0.5) as the presentation information of the to-be-pushed presentation link at the user terminal.

And step two, sending the display link to be pushed and the presentation information to the target user terminal so that the target user terminal presents the display link to be pushed according to the presentation mode indicated by the presentation information.

In some optional implementation manners of this embodiment, the execution main body may further send the presentation effect information to the presentation link providing end, so that the presentation link providing end presents the presentation effect information.

The display link provider may be configured to provide a display link (e.g., an advertisement), and the display link provider may be a server or a terminal device.

The method provided by the above embodiment of the present disclosure generates the degree of demand of the user for the product indicated by the exhibition link to be pushed by receiving the exhibition link to be pushed, based on the markov model generated by the method of any one of the above methods for generating a model, and thereby predicts the behavior of the user based on the obtained model, which is helpful for reducing network resource occupation and reducing network traffic.

With continuing reference to fig. 15, as an implementation of the method shown in fig. 14 described above, the present disclosure provides an embodiment of an apparatus for generating information, where the embodiment of the apparatus corresponds to the embodiment of the method shown in fig. 14, and the embodiment of the apparatus may include the same or corresponding features as the embodiment of the method shown in fig. 14, except for the features described below. The device can be applied to various electronic equipment.

As shown in fig. 15, the apparatus 1500 for generating information of the present embodiment includes: a receiving unit 1501 and a generating unit 1502. Wherein, the receiving unit 1501 is configured to receive a to-be-pushed presentation link; the generating unit 1502 is configured to generate the demand degree of the user for the product indicated by the to-be-pushed presentation link based on a pre-generated markov model, wherein the markov model is generated according to the method of any one of the embodiments of the method for generating a model as described above.

In this embodiment, the receiving unit 1501 of the apparatus 1500 for generating a model may receive the exhibition link to be pushed in a wired connection manner or a wireless connection manner.

In this embodiment, the generating unit 1502 may generate the degree of demand of the user for the product indicated by the to-be-pushed display link based on a pre-generated markov model. Wherein the Markov model is generated according to the method of any one of the embodiments of the method for generating a model as described above.

In some optional implementations of this embodiment, the apparatus 1500 further includes: the determining unit (not shown in the figure) is configured to determine whether to push the to-be-pushed presentation link to the target user terminal based on the demand degree.

In some optional implementations of this embodiment, the apparatus 1500 further includes: the first sending unit (not shown in the figure) is configured to send the to-be-pushed display link to the target user terminal in response to determining that the to-be-pushed display link is pushed to the target user terminal, so that the target user terminal can present the to-be-pushed display link.

In some optional implementations of this embodiment, the first sending unit includes: the determining subunit (not shown in the figure) is configured to determine the presence information of the to-be-pushed presentation link at the target user terminal, wherein the presence information includes at least one of the following: presenting initial time and presenting duration; the sending subunit (not shown in the figure) is configured to send the display link to be pushed and the presentation information to the target user terminal, so that the target user terminal presents the display link to be pushed according to the presentation manner indicated by the presentation information.

In some optional implementations of this embodiment, the apparatus 1500 further includes: the second sending unit (not shown in the figure) is configured to send the presentation effect information to the presentation link providing terminal, so that the presentation link providing terminal presents the presentation effect information.

The apparatus provided by the foregoing embodiment of the present disclosure receives the display link to be pushed through the obtaining unit 1501, and then the generating unit 1502 generates the demand level of the user for the product indicated by the display link to be pushed based on the markov model generated by the method according to any one of the foregoing embodiments of the method for generating a model, thereby predicting the behavior of the user based on the obtained model, which is helpful for reducing network resource occupation and reducing network traffic.

Continuing to refer to FIG. 16, a schematic diagram of an interaction process is shown for one embodiment of a system for generating information in accordance with the present disclosure.

In this embodiment, the system for generating information includes: the system comprises a server and a user terminal set, wherein the user terminal is in communication connection with the server. Wherein: a server configured to: acquiring user behavior data generated by executing target operation in a target operation set by a user terminal in a user terminal set, wherein the target operation is operation aiming at a virtual product, and the virtual product corresponds to a product indicated by a display link; determining user demand information of a user using a user terminal in a user terminal set based on the user behavior data, wherein the user demand information represents a degree of demand of the user for a product indicated by the display link; and generating presentation effect information of the user terminal to the display link based on the user demand information.

As shown in fig. 16, in step 1601, the set of user terminals executes a target operation in the set of target operations, and generates user behavior data.

In this embodiment, the user terminals in the set of user terminals may execute the target operations in the set of target operations, thereby generating the user behavior data. Wherein the target operation is an operation for a virtual product corresponding to the product indicated by the presentation link.

The user terminal may be a terminal in communication connection with the server. In practice, the service end is usually required to support the application installed in the user terminal, so as to implement the corresponding function through the operation of the application. It is to be understood that the user terminal may be a terminal installed with an application supported by the server.

As an example, the user terminal may be installed with shopping software, or may open a shopping website through a browser, and the server may be a server supporting the shopping software or the shopping website.

The presentation link may be information (e.g., an advertisement) for pushing the product. The presentation link may be presented in at least one of the following ways: text, pictures, audio, video, etc. By way of example, when the product is "toothpaste", the display link may be "XX toothpaste, known at all". The user terminal may present all or part of the presentation links in the set of presentation links.

The target operation may be an operation that the user terminal or the server responds to the operation of the user on the virtual product after the operation of the user on the virtual product (for example, sharing, clicking, collecting, purchasing, adding to a shopping cart, browsing, agreeing, jumping to a landing page, and the like). For example, when a user wants to purchase a physical product corresponding to a virtual product, the user may perform a purchase operation on the virtual product on a page in which the virtual product is presented (e.g., click a purchase button and complete payment), and thereafter, the server may perform the following target operations in response to the purchase operation: and jumping to an order page, and adding a purchase record of the product in the historical purchase record of the user.

In some usage cases, the user terminal may be a user terminal in a predetermined set of user terminals (e.g., a set of terminals installed with shopping software), and the target operation may be an operation in a predetermined set of operations (e.g., may include sharing, clicking, collecting, purchasing, joining a shopping cart, browsing, agreeing, jumping to a landing page, etc.). Therefore, the server can also acquire user behavior data generated by each user terminal in the user terminal set executing the target operation in the target operation set.

In step 1602, the ue set sends user behavior data to the server.

In this embodiment, the user terminals in the user terminal set may send the user behavior data acquired in step 1601 to the server.

Here, the step 1602 may be executed in a manner that the user terminal actively transmits the user behavior data acquired in the step 1601 to the server, or the server actively acquires the user behavior data from the user terminals in the user terminal set.

Step 1603, the server determines user demand information for users using user terminals in the set of user terminals based on the user behavior data.

In this embodiment, the server may determine, based on the user behavior data, user requirement information of a user using a user terminal in the user terminal set. As an example, the user requirement information may be characterized by words, numerical values, and the like. For example, the user demand information may be "much needed", "generally needed", "hardly needed", and the like. Optionally, the user requirement information may also be "1", "2" or "3". Wherein, 1 can characterize "very desirable", "2" can characterize "general desirable", and "3" can characterize "almost undesirable".

As an example, when the user behavior data is data obtained by the server in response to a purchase operation of the user, the server may determine that the user requirement information of the user using the user terminal is "highly required".

As another example, when the user behavior data is data obtained by the server in response to the sharing operation of the user, the server may determine that the user requirement information of the user using the user terminal is "general requirement".

As still another example, when the user behavior data is data obtained by the server in response to a browsing operation of the user, the server may determine that the user requirement information of the user using the user terminal is "almost unnecessary".

And 1604, the server generates the presentation effect information of the user terminal to the display link based on the user requirement information.

In this embodiment, the server may generate presentation effect information of the user terminal on the presentation link based on the user demand information.

Wherein, the presentation effect information may be information characterizing the presentation effect of the presentation link. The presentation effect information may be represented by words, numbers, or the like. As an example, the presentation effect information may be "good" or "bad", or may be "1" or "2". When the presentation effect information is represented by a numerical value, a technician can specify that the presentation effect information with larger numerical value represents that the presentation effect is better, or that the presentation effect information with smaller numerical value represents that the presentation effect is better.

As an example, when the user requirement information is "very required", the server may generate the presentation effect information "1"; when the user requirement information is 'general requirement', the server can generate presentation effect information '2'; when the user demand information is "almost unnecessary", the server may generate the presentation effect information "3". Here, it may be predetermined that the presentation effect information having a larger numerical value represents a better presentation effect.

It should be noted that, besides the features and effects described above with respect to the embodiment corresponding to fig. 16, the embodiment corresponding to fig. 16 may further include the features and effects corresponding to the above-mentioned fig. 2 to fig. 6, and the embodiments of the present disclosure are not described again here.

The system for generating information provided by the embodiment of the disclosure includes that, first, a server obtains user behavior data generated by a user terminal in a user terminal set executing a target operation in a target operation set, wherein the target operation is an operation for a virtual product, the virtual product corresponds to a product indicated by a display link, then, based on the user behavior data, determines user demand information of a user using the user terminal in the user terminal set, wherein the user demand information represents a degree of demand of the user for the product indicated by the display link, and finally, based on the user demand information, generates presentation effect information of the user terminal for the display link, thereby determining the user demand information based on the user behavior data, and further generating presentation effect information of the display link at the user terminal, thereby enriching a manner of generating the presentation effect information, the accuracy of generating the presentation effect information is improved.

Continuing to refer to FIG. 17, a schematic diagram of an interaction process for yet another embodiment of a system for generating information in accordance with the present disclosure is shown.

In this embodiment, the system for generating information includes: the system comprises a server, a user terminal set and a display link providing terminal, wherein the user terminal is in communication connection with the server, and the display link providing terminal is in communication connection with the server. Wherein: a server configured to: acquiring user behavior data generated by executing target operation in a target operation set by a user terminal in a user terminal set, wherein the target operation is operation aiming at a virtual product, and the virtual product corresponds to a product indicated by a display link; determining user demand information of a user using a user terminal in a user terminal set based on the user behavior data, wherein the user demand information represents a degree of demand of the user for a product indicated by the display link; generating presentation effect information of the user terminal to the display link based on the user demand information; sending the presentation effect information to a presentation link providing end; the exhibition link provider is configured to: and presenting the presentation effect information.

As shown in fig. 17, in step 1701, the set of user terminals executes a target operation in the set of target operations to generate user behavior data.

In this embodiment, the user terminals in the set of user terminals may execute the target operations in the set of target operations, thereby generating the user behavior data.

Step 1702, the set of user terminals sends user behavior data to the server.

In this embodiment, the user terminals in the user terminal set may send the user behavior data to the server.

Step 1703, the server determines user requirement information of a user using the user terminal in the user terminal set based on the user behavior data.

In this embodiment, the server may determine, based on the user behavior data, user requirement information of a user using a user terminal in the user terminal set.

And step 1704, the server generates presentation effect information of the user terminal on the display link based on the user requirement information.

In this embodiment, steps 1701-1704 are substantially the same as steps 1701-1704 in the embodiment corresponding to fig. 16, and are not described herein again.

Step 1705, the server sends the presentation effect information to the display link provider.

In this embodiment, the server may send the presentation effect information generated in step 1704 to the presentation link provider.

Step 1706, displaying the presentation effect information presented by the link providing end.

In this embodiment, the presentation link provider may present the presentation effect information received in step 1705.

In some optional implementation manners of this embodiment, the display link providing end may further select, based on the presentation effect information, a to-be-pushed display link that meets a preset selection condition from a predetermined to-be-pushed display link set.

The preset selection condition may be various preset conditions for selecting one or more to-be-pushed display links from a predetermined to-be-pushed display link set.

For example, the preset selection condition may be one or more to-be-pushed display links in the predetermined to-be-pushed display link set, which are close to the category of the display link that the user browses last time through the user terminal (for example, when the category to which the display link belongs is "500-" 600- "and the category to which the to-be-pushed display link belongs is" 700- "), the category to which the display link belongs may be determined to be close to the category to which the to-be-pushed display link belongs. Thus, this alternative implementation may be performed as follows:

the display link providing end may first determine whether the category to which the display link presented by the user terminal belongs is the same as or similar to the category to which the display link to be pushed belongs (for example, when the category to which the display link belongs is "500-" 600- "and the category to which the display link to be pushed belongs is" 600- "then it may be determined that the category to which the display link belongs is similar to the category to which the display link to be pushed belongs), and if the categories are the same as or similar to each other, the service end may determine that the display link to be pushed is presented at the user terminal; if not, the server side can determine not to present the display link to be pushed on the user terminal.

As another example, the preset selection condition may also be one or more to-be-pushed display links in a predetermined to-be-pushed display link set, where a similarity between the to-be-pushed display links and a display link that a user has browsed through the user terminal last time is greater than a preset similarity threshold. Thus, this alternative implementation may be performed as follows:

the display link providing end may further determine, first, a similarity between product information of a product indicated by the display link presented by the user terminal and product information of a product indicated by the display link to be pushed, and then, the display link providing end may determine whether the determined similarity is greater than a predetermined similarity threshold, and if so, the display link providing end may determine that the display link to be pushed is presented at the user terminal; if the number of the display links is less than or equal to the number of the display links to be pushed, the display link providing end can determine that the display links to be pushed are not presented at the user terminal.

In some optional implementation manners of this embodiment, the display link providing end may further send the selected display link to be pushed to the server. The server side can also determine whether the selected display link to be pushed is displayed on the target user terminal or not based on the display effect information; and in response to the fact that the selected display link to be pushed is displayed on the target user terminal, sending the selected display link to be pushed to the target user terminal so that the target user terminal can display the display link to be pushed.

In some optional implementation manners of this embodiment, the display link providing end may further send the selected display link to be pushed to the server. And the server side can also determine the presentation information of the to-be-pushed presentation link at the target user terminal based on the presentation effect information. Wherein the presence information comprises at least one of: presenting initial time and presenting duration. And sending the display link to be pushed and the presentation information to the target user terminal so that the target user terminal presents the display link to be pushed according to the presentation mode indicated by the presentation information.

For example, the server may determine the presentation information of the to-be-pushed presentation link at the user terminal according to the category (e.g., clothing category, fresh category, etc.) to which the to-be-pushed presentation link belongs. As an example, it is assumed that a technician sets corresponding presentation information for a category to which each to-be-pushed display link belongs in advance (for example, presentation information "18: 00, 3 h" of a clothing category, which indicates that if the category to which the to-be-pushed display link belongs is the clothing category, then 6 pm every day is used as presentation initial time of the to-be-pushed display link, 3 hours is used as presentation duration of the to-be-pushed display link, and presentation information "11: 00, 2 h" of a fresh category indicates that if the category to which the to-be-pushed display link belongs is the fresh category, then 11 am every day is used as presentation initial time of the to-be-pushed display link, and 2 hours is used as presentation duration of the to-be-pushed display link), therefore, the server can use the presentation information corresponding to the category to which the presentation link to be pushed belongs as the presentation information of the presentation link to be pushed at the user terminal.

As another example, the server may further determine, based on the markov model, presence information of the to-be-pushed presentation link at the user terminal.

Here, the server may use at least one to-be-pushed presentation link as an observation sequence, so as to use the markov model to predict the behavior of the user. For example, for each display link to be pushed, the probability of each target operation in the target operation set executed by the user is determined, so as to determine the target operation in the target operation set corresponding to the maximum probability in each probability, and thus determine the presentation information of the display link to be pushed at the user terminal according to the time corresponding to each probability. For example, the target operation set includes a target operation "purchase", and the predicted probability that the user performs the target operation "purchase" through the user terminal at 1 point to 2 points is 0.1 according to the markov model; the probability that the user performs the target operation 'purchase' through the user terminal from 2 o 'clock to 3 o' clock is 0.8; the probability that the user performs the target operation "purchase" through the user terminal at 3 o 'clock to 4 o' clock is 0.1. Then, the server may use the presentation information (for example, presentation initial time "2 points", presentation duration "1 hour") corresponding to the probability that the probability value is greater than the preset threshold (for example, 0.5) as the presentation information of the to-be-pushed presentation link at the user terminal.

It should be noted that, besides the features and effects described above with respect to the embodiment corresponding to fig. 17, the embodiment corresponding to fig. 17 may further include the features and effects corresponding to the above-mentioned fig. 2 to fig. 6, and the embodiments of the present disclosure are not described again here.

The system for generating information provided by the embodiment of the disclosure includes that, firstly, a server obtains user behavior data generated by a user terminal in a user terminal set executing a target operation in a target operation set, wherein the target operation is an operation for a virtual product, the virtual product corresponds to a product indicated by a display link, then, based on the user behavior data, user demand information of a user using the user terminal in the user terminal set is determined, wherein the user demand information represents a degree of demand of the user for the product indicated by the display link, then, based on the user demand information, presentation effect information of the user terminal to the display link is generated, then, the presentation effect information is sent to the display link providing terminal, so that the display link providing terminal presents the presentation effect information, after the display link providing terminal presents the presentation effect information, relevant personnel (for example, workers in charge of pushing the display links) can visually determine the presentation effect of the historical display links through the presentation effect information presented by the display link providing end, so that the display links suitable for providing are determined based on the presentation effect information.

Referring now to FIG. 18, shown is a block diagram of a computer system 1800 suitable for use as a server in implementing embodiments of the present disclosure. The server shown in fig. 18 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.

As shown in fig. 18, the computer system 1800 includes a Central Processing Unit (CPU)1801, which can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)1802 or a program loaded from a storage portion 1808 into a Random Access Memory (RAM) 1803. In the RAM 1803, various programs and data necessary for the operation of the system 1800 are also stored. The CPU1801, ROM 1802, and RAM 1803 are connected to each other via a bus 1804. An input/output (I/O) interface 1805 is also connected to bus 1804.

To the I/O interface 1805, AN input portion 1806 including a keyboard, a mouse, and the like, AN output portion 1807 including a device such as a Cathode Ray Tube (CRT), a liquid crystal display (L CD), and the like, a speaker, and the like, a storage portion 1808 including a hard disk, and the like, and a communication portion 1809 including a network interface card such as a L AN card, a modem, and the like, the communication portion 1809 performs communication processing via a network such as the internet, a drive 1810 is also connected to the I/O interface 1805 as necessary, a removable medium 1811 such as a magnetic disk, AN optical disk, a magneto-optical disk, a semiconductor memory, and the like is mounted on the drive 1810 as necessary so that a computer program read out therefrom is mounted into the storage portion 1808 as necessary.

In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via the communication portion 1809, and/or installed from the removable media 1811. The computer program, when executed by the Central Processing Unit (CPU)1801, performs the above-described functions defined in the methods of the present disclosure.

It should be noted that the computer readable medium of the present disclosure may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer-readable signal medium may include a propagated data signal with computer-readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.

Computer program code for carrying out operations of the present disclosure may be written in any combination of one or more programming languages, including AN object oriented programming language such as Python, Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The units described in the embodiments of the present disclosure may be implemented by software or hardware. The described units may also be provided in a processor, and may be described as: a processor includes an acquisition unit, a first determination unit, and a first generation unit. The names of these units do not in some cases constitute a limitation on the units themselves, and for example, the acquiring unit may also be described as a "unit that acquires user behavior data generated by the user terminal performing a target operation".

As another aspect, the present disclosure also provides a computer-readable medium, which may be contained in the server described in the above embodiments; or may exist separately and not be assembled into the server. The computer readable medium carries one or more programs which, when executed by the server, cause the server to: acquiring user behavior data generated by a user terminal executing target operation, wherein the target operation is operation aiming at a virtual product, and the virtual product corresponds to a product indicated by a display link presented by the user terminal; determining user demand information of a user using the user terminal based on the user behavior data, wherein the user demand information represents the degree of demand of the user on a product indicated by a display link in the display link set; and generating presentation effect information of the user terminal to the display link based on the user demand information. Or, causing the server to: acquiring user behavior data generated by executing target operation in a target operation set by a user terminal in a user terminal set, wherein the target operation is operation aiming at a virtual product, and the virtual product corresponds to a product indicated by a display link; and counting the user behavior data to construct a Markov model, wherein the state information of the Markov model is used for representing the user category in the user category set or the target operation in the target operation set, and the user category is the category to which the user using the user terminal in the user terminal set belongs.

The foregoing description is only exemplary of the preferred embodiments of the disclosure and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention in the present disclosure is not limited to the specific combination of the above-mentioned features, but also encompasses other embodiments in which any combination of the above-mentioned features or their equivalents is possible without departing from the inventive concept as defined above. For example, the above features and (but not limited to) technical features disclosed in the present disclosure having similar functions are mutually replaced to form the technical solution.

Claims

1. A method for generating information, comprising:

acquiring user behavior data generated by a user terminal executing target operation, wherein the target operation is operation aiming at a virtual product, and the virtual product corresponds to a product indicated by a display link;

determining user demand information of a user using the user terminal based on the user behavior data, wherein the user demand information represents a degree of demand of the user for a product indicated by a display link;

and generating presentation effect information of the user terminal to the display link based on the user demand information.

2. The method of claim 1, wherein the user demand information is characterized by a user intention function, and the user intention function represents a correspondence between time and a total demand degree of the user for the product set indicated by the presentation link set.

3. The method of claim 2, wherein the target operation belongs to a predetermined set of target operations; and

the determining user demand information of the user using the user terminal based on the user behavior data includes:

determining a user willingness function corresponding to a user using the user terminal based on an association probability set, wherein the association probability set is determined based on the user behavior data, and the association probability represents any one of the following items: the method comprises the steps of converting a user category in a predetermined user category set into a probability of the user category in the user category set, executing any target operation in the target operation set after executing the target operation in the target operation set, executing the target operation in the target operation set by a user belonging to the user category in the user category set, and executing the probability of the user belonging to the user category in the user category set by a user terminal of the target operation in the user category set.

4. The method of claim 3, wherein the generating of the presentation effect information of the user terminal on the presentation link based on the user requirement information comprises:

dividing the user intention function according to the presentation time of the display link to obtain a user product intention function set;

and carrying out Laplace transformation on the user product intention function according to the user product intention function in the user product intention function set to obtain presentation effect information of the user terminal on the display link, wherein the presentation effect information is represented by a skewed distribution function.

5. The method of claim 4, wherein the obtaining of the user behavior data generated by the user terminal executing the target operation comprises:

acquiring user behavior data generated by the user terminal executing the target operation in the target operation set within a target historical time period; and

the method further comprises the following steps:

and generating an effect value of a display link in the display link set in the target historical time period and an effect value at a time point in the target historical time period by the user terminal based on the generated presentation effect information represented by the skewed distribution function.

6. The method of claim 5, wherein the determining a user willingness function corresponding to a user using the user terminal based on a set of association probabilities comprises:

constructing a Markov model based on an association probability set, a predetermined user category set and the target operation set, wherein state information of the Markov model is used for representing user categories in the user category set or target operations in the target operation set, and elements of a probability matrix are association probabilities in the association probability set;

and determining a user willingness function corresponding to the user using the user terminal based on the Markov model.

7. The method according to one of claims 1-6, wherein the method further comprises:

in response to receiving the display link to be pushed, determining whether to present the display link to be pushed on the user terminal based on the presentation effect information;

and responding to the confirmation that the display link to be pushed is presented at the user terminal, and sending the display link to be pushed to the user terminal so that the user terminal presents the display link to be pushed.

8. The method of claim 7, wherein the sending the link to be pushed to the user terminal for the user terminal to present the link to be pushed comprises:

determining the presentation information of the to-be-pushed presentation link at the user terminal, wherein the presentation information comprises at least one of the following items: presenting initial time and presenting duration;

and sending the display link to be pushed and the presentation information to a user terminal so that the user terminal presents the display link to be pushed according to the presentation mode indicated by the presentation information.

9. The method of claim 7 or 8, wherein the method further comprises:

and sending the presentation effect information to a presentation link providing end so that the presentation link providing end presents the presentation effect information.

10. A method for generating a model, comprising:

acquiring user behavior data generated by executing target operation in a target operation set by a user terminal in a user terminal set, wherein the target operation is operation aiming at a virtual product, and the virtual product corresponds to a product indicated by a display link;

and counting the user behavior data to construct a Markov model, wherein the state information of the Markov model is used for representing the user category in a user category set or the target operation in the target operation set, and the user category is the category to which the user using the user terminal in the user terminal set belongs.

11. A method for generating information, comprising:

receiving a display link to be pushed;

generating a demand degree of a user for a product indicated by the to-be-pushed exhibition link based on a pre-generated Markov model, wherein the Markov model is generated according to the method of claim 10.

12. The method of claim 11, wherein the method further comprises:

and determining whether to push the display link to be pushed to a target user terminal or not based on the demand degree.

13. The method of claim 12, wherein the method further comprises:

and in response to the fact that the display link to be pushed is pushed to the target user terminal, sending the display link to be pushed to the target user terminal so that the target user terminal can present the display link to be pushed.

14. The method of claim 13, wherein the sending the to-be-pushed presentation link to the target user terminal for the target user terminal to present the to-be-pushed presentation link comprises:

determining the presentation information of the to-be-pushed presentation link at the target user terminal, wherein the presentation information comprises at least one of the following items: presenting initial time and presenting duration;

and sending the display link to be pushed and the presentation information to the target user terminal so that the target user terminal presents the display link to be pushed according to the presentation mode indicated by the presentation information.

15. The method of claim 13 or 14, wherein the method further comprises: and sending the presentation effect information to a presentation link providing end so that the presentation link providing end presents the presentation effect information.

16. An apparatus for generating information, comprising:

an acquisition unit configured to acquire user behavior data generated by a user terminal performing a target operation, wherein the target operation is an operation for a virtual product corresponding to a product indicated by a presentation link;

a first determining unit configured to determine user demand information of a user using the user terminal based on the user behavior data, wherein the user demand information represents a degree of demand of the user for a product indicated by a presentation link;

and the first generating unit is configured to generate presentation effect information of the user terminal on the presentation link based on the user requirement information.

17. The apparatus of claim 16, wherein the user demand information is characterized by a user demand function, and the user demand function characterizes a correspondence between time and a total demand level of the user for the product set indicated by the presentation link set.

18. The apparatus of claim 17, wherein the target operation belongs to a predetermined set of target operations; and

the first determination unit includes:

a first determining subunit configured to determine a user willingness function corresponding to a user using the user terminal based on a set of association probabilities, wherein the set of association probabilities is determined based on the user behavior data, and an association probability characterizes any one of: the method comprises the steps of converting a user category in a predetermined user category set into a probability of the user category in the user category set, executing any target operation in the target operation set after executing the target operation in the target operation set, executing the target operation in the target operation set by a user belonging to the user category in the user category set, and executing the probability of the user belonging to the user category in the user category set by a user terminal of the target operation in the user category set.

19. The apparatus of claim 18, wherein the determining subunit comprises:

the dividing module is configured to divide the user intention function according to the presentation time of the display link to obtain a user product intention function set;

and the transformation module is configured to perform Laplace transformation on the user product intention function according to the user product intention function in the user product intention function set to obtain presentation effect information of the user terminal on the display link, wherein the presentation effect information is represented by a skewed distribution function.

20. The apparatus of claim 19, wherein the obtaining unit comprises:

an obtaining subunit, configured to obtain user behavior data generated by the user terminal executing a target operation in the target operation set within a target history time period; and

the device further comprises:

a second generating unit configured to generate, based on the generated presentation effect information characterized by the skewed distribution function, an effect value of the user terminal presenting the presentation link in the presentation link set within the target historical time period and an effect value at a time point within the target historical time period.

21. The apparatus of claim 20, wherein the determining subunit comprises:

a building module configured to build a Markov model based on an association probability set, a predetermined user category set and the target operation set, wherein state information of the Markov model is used for characterizing a user category in the user category set or a target operation in the target operation set, and an element of a probability matrix is an association probability in the association probability set;

a determination module configured to determine a user willingness function corresponding to a user using the user terminal based on the Markov model.

22. The apparatus according to one of claims 16-21, wherein the apparatus further comprises:

a second determining unit, configured to determine, in response to receiving a to-be-pushed presentation link, whether to present the to-be-pushed presentation link at the user terminal based on the presentation effect information;

the first sending unit is configured to respond to the fact that the display link to be pushed is determined to be presented on the user terminal, and send the display link to be pushed to the user terminal so that the user terminal can present the display link to be pushed.

23. The apparatus of claim 22, wherein the first transmitting unit comprises:

a second determining subunit, configured to determine presentation information of the to-be-pushed presentation link at the user terminal, where the presentation information includes at least one of: presenting initial time and presenting duration;

and the sending subunit is configured to send the display link to be pushed and the presentation information to the user terminal, so that the user terminal presents the display link to be pushed according to the presentation mode indicated by the presentation information.

24. The apparatus of claim 22 or 23, wherein the apparatus further comprises:

the second sending unit is configured to send the presentation effect information to a presentation link providing end so that the presentation link providing end presents the presentation effect information.

25. An apparatus for generating a model, comprising:

an acquisition unit configured to acquire user behavior data generated by a user terminal in a set of user terminals executing a target operation in a set of target operations, wherein the target operation is an operation for a virtual product corresponding to a product indicated by a display link;

a constructing unit configured to count the user behavior data to construct a markov model, where state information of the markov model is used to characterize a user category in a user category set or a target operation in the target operation set, and the user category is a category to which a user using a user terminal in the user terminal set belongs.

26. An apparatus for generating information, comprising:

the receiving unit is configured to receive the exhibition link to be pushed;

a generating unit configured to generate a demand level of a user for a product indicated by the to-be-pushed exhibition link based on a pre-generated markov model, wherein the markov model is generated according to the method of claim 10.

27. The apparatus of claim 26, wherein the apparatus further comprises:

the determining unit is configured to determine whether to push the display link to be pushed to a target user terminal based on the demand degree.

28. The apparatus of claim 27, wherein the apparatus further comprises:

a first sending unit configured to send the to-be-pushed display link to the target user terminal in response to determining that the to-be-pushed display link is pushed to the target user terminal, so that the target user terminal presents the to-be-pushed display link.

29. The apparatus of claim 28, wherein the first transmitting unit comprises:

a determining subunit configured to determine presence information of the to-be-pushed presentation link at the target user terminal, wherein the presence information includes at least one of: presenting initial time and presenting duration;

and the sending subunit is configured to send the display link to be pushed and the presentation information to the target user terminal, so that the target user terminal presents the display link to be pushed according to the presentation mode indicated by the presentation information.

30. The apparatus of claim 28 or 29, wherein the apparatus further comprises: the second sending unit is configured to send the presentation effect information to a presentation link providing end so that the presentation link providing end presents the presentation effect information.

31. A system for generating information, the system comprising: the method comprises a server and a user terminal set, wherein the user terminal is in communication connection with the server, and the method comprises the following steps:

the server is configured to: acquiring user behavior data generated by executing target operation in a target operation set by a user terminal in the user terminal set, wherein the target operation is operation aiming at a virtual product, and the virtual product corresponds to a product indicated by a display link; determining user demand information of a user using a user terminal in the user terminal set based on the user behavior data, wherein the user demand information represents a degree of demand of the user for a product indicated by a display link; and generating presentation effect information of the user terminal to the display link based on the user demand information.

32. The system of claim 31, wherein the system further comprises a show link provider communicatively coupled to the server, and;

the server is further configured to: sending the presentation effect information to the display link providing end;

the exhibition link provider is further configured to: and presenting the presentation effect information.

33. The system of claim 32, wherein,

the exhibition link provider is further configured to: and selecting the display link to be pushed meeting the preset selection condition from a predetermined display link set to be pushed based on the presentation effect information.

34. The system of claim 33, wherein,

the exhibition link provider is further configured to: sending the selected display link to be pushed to the server;

the server is further configured to: determining whether the selected display link to be pushed is presented at the target user terminal or not based on the presentation effect information; and in response to the fact that the selected display link to be pushed is displayed on the target user terminal, sending the selected display link to be pushed to the target user terminal so that the target user terminal can display the display link to be pushed.

35. The system of claim 33, wherein,

the server is further configured to: determining presentation information of the to-be-pushed presentation link at a target user terminal based on the presentation effect information, wherein the presentation information comprises at least one of the following items: presenting initial time and presenting duration; and sending the display link to be pushed and the presentation information to the target user terminal so that the target user terminal presents the display link to be pushed according to the presentation mode indicated by the presentation information.

36. A server, comprising:

one or more processors;

a storage device having one or more programs stored thereon,

when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-15.

37. A computer-readable medium, on which a computer program is stored, wherein the program, when executed by a processor, implements the method of any one of claims 1-15.