CN109271587B - Page generation method and device - Google Patents
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- CN109271587B CN109271587B CN201811035995.XA CN201811035995A CN109271587B CN 109271587 B CN109271587 B CN 109271587B CN 201811035995 A CN201811035995 A CN 201811035995A CN 109271587 B CN109271587 B CN 109271587B
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Abstract
The application discloses a page generation method and a device, wherein the method comprises the following steps: creating a page generation model corresponding to a general scene, wherein the general scene is suitable for at least two different business projects; performing model training on the page generation model according to a general page element material to obtain a trained page generation model, wherein the general page element material is suitable for the general scene; aiming at any one of the at least two different business projects, generating a personalized page corresponding to the business project according to the trained page generation model, thereby effectively improving the universality of the trained page generation model and further improving the page generation efficiency.
Description
Technical Field
The present application relates to the field of internet technologies, and in particular, to a page generation method and apparatus.
Background
With the rapid development of internet technology, the page design of internet products such as application programs and websites generally directly affects the acceptance of users on the internet products. Therefore, it is important for internet products to provide a user with pages that meet the user's preferences.
At present, user preferences are generally memorized by training a page generation model, and then a page according with the user preferences is provided for a user by the trained page generation model.
However, the page generation model trained in the prior art is only suitable for a single business project, and the universality is poor, so that the page generation efficiency is poor.
Disclosure of Invention
The embodiment of the application provides a page generation method and device, and aims to solve the problem that in the prior art, the page generation efficiency is low due to the fact that the universality of a trained page generation model is poor.
The embodiment of the application provides a page generation method, which comprises the following steps:
creating a page generation model corresponding to a general scene, wherein the general scene is suitable for at least two different business projects;
performing model training on the page generation model according to a general page element material to obtain a trained page generation model, wherein the general page element material is suitable for the general scene;
and aiming at any one of the at least two different business projects, generating a personalized page corresponding to the business project according to the trained page generation model.
An embodiment of the present application further provides a page generating apparatus, including:
the system comprises a creating module, a generating module and a processing module, wherein the creating module is used for creating a page generating model corresponding to a general scene, and the general scene is suitable for at least two different business projects;
the training module is used for carrying out model training on the page generation model according to a general page element material to obtain a trained page generation model, wherein the general page element material is suitable for the general scene;
and the page generation module is used for generating a personalized page corresponding to the business project according to the trained page generation model aiming at any one of the at least two different business projects.
An embodiment of the present application further provides an electronic device, including:
a memory for storing a program;
a processor for executing the program stored in the memory, and specifically executing:
creating a page generation model corresponding to a general scene, wherein the general scene is suitable for at least two different business projects;
performing model training on the page generation model according to a general page element material to obtain a trained page generation model, wherein the general page element material is suitable for the general scene;
and aiming at any one of the at least two different business projects, generating a personalized page corresponding to the business project according to the trained page generation model.
Embodiments of the present application also provide a computer-readable storage medium storing one or more programs that, when executed by an electronic device including a plurality of application programs, cause the electronic device to perform the following method:
creating a page generation model corresponding to a general scene, wherein the general scene is suitable for at least two different business projects;
performing model training on the page generation model according to a general page element material to obtain a trained page generation model, wherein the general page element material is suitable for the general scene;
and aiming at any one of the at least two different business projects, generating a personalized page corresponding to the business project according to the trained page generation model.
The embodiment of the application adopts at least one technical scheme which can achieve the following beneficial effects:
the method comprises the steps of creating a page generation model corresponding to a general scene suitable for at least two different business projects, and then performing model training on the page generation model according to general page element materials suitable for the general scene to obtain a trained page generation model, so that a personalized page corresponding to the business project is generated for any one of the at least two different business projects according to the trained page generation model, the universality of the trained page generation model is effectively improved, and the page generation efficiency is further improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flowchart of a page generation method according to an embodiment of the present application;
fig. 2 is a schematic diagram of a page generation method provided in an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of a page generation apparatus according to an embodiment of the present application.
Detailed Description
The technical solutions of the present application will be described clearly and completely below with reference to the specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
Fig. 1 is a schematic flowchart of a page generation method according to an embodiment of the present application. The method may be as follows.
102, creating a page generation model corresponding to a general scene, wherein the general scene is suitable for at least two different service projects.
Aiming at least two different service projects, and under the condition that the at least two different service projects are similar service projects, corresponding page generation models are created for the common scenes suitable for the at least two different service projects.
For example, the first business item is the credit card promotion activity of bank A, and the second business item is the credit card promotion activity of bank B. And if the first service project and the second service project are different but similar service projects and the common scene suitable for the first service project and the second service project is credit card promotion activity, establishing a page generation model corresponding to the common scene (credit card promotion activity).
It should be noted that, a many-to-many relationship exists between the service item and the general scenario, that is, one service item may use a plurality of general scenarios, and one general scenario may be applicable to a plurality of service items.
When there are a plurality of general scenes applicable to at least two different business projects, a page generation model is created for each general scene.
And 104, performing model training on the page generation model according to the general page element material to obtain a trained page generation model, wherein the general page element material is suitable for a general scene.
And aiming at any general scene, determining general page element materials suitable for the general scene.
In an embodiment of the present application, the general page element material includes at least one of the following:
the system comprises a plurality of page frames, a plurality of background pictures, a plurality of control shapes, a plurality of control colors, a plurality of styles of page containers and a plurality of styles of popularization words.
It should be noted that, the general page element material may include other page element materials besides the above description, and is not limited specifically here.
In the embodiment of the application, according to general page element materials, model training is performed on the page generation model to obtain a trained page generation model, which includes:
determining different page templates according to the general page element materials;
and training a page generation model by using a preset algorithm according to different page templates and taking the page conversion rate maximization as a training target to obtain the trained page generation model, wherein the trained page generation model comprises the display probabilities corresponding to the different page templates.
Wherein the preset algorithm is a Bandit algorithm.
And aiming at a page generation model corresponding to a certain general scene, determining different page templates according to general page element materials suitable for the general scene, wherein the different page templates can be composed of different general page element materials.
And distributing the display probability and the display times of different page templates by using a Bandit algorithm, and determining the page conversion rates corresponding to the different page templates in different page access states by taking the maximum page conversion rate as a training target. For a page template with a higher page conversion rate in a certain page access state, the trained page generation template can improve the display probability of the page template when the same page access state is faced next time.
Wherein, different page access states include: different time information (season, time, weather, holidays, etc.) and/or different user information (age, gender, device model, etc.).
It should be noted that, in addition to the above description, the access states of different pages may also include other state information, which is not specifically limited herein;
the preset algorithm may be a Bandit algorithm, and may also be other algorithms, which is not specifically limited herein.
Still taking the above-mentioned page generation model created for the general scenario (credit card promotion activity) applicable to the first business project and the second business project as an example, it is found in the model training process that when the page access state includes: in summer and under the condition of men, the page conversion rate corresponding to the page template A (the page template taking Bihai blue sky and surfing as main background key) is higher; when the page access state includes summer and lady, the page conversion rate corresponding to the page template B (the page template which takes agreeable shopping in cool markets as the background basic tone) is higher.
Then the access states for other pages also include: in summer and under the condition of men, the trained page generation template can show the personalized page generated according to the page template A (the page template with the blue sky and surfing as main backgrounds); the access states for other pages also include: in summer and in lady, the trained page generation template can show a personalized page generated according to a page template B (a page template which is basically adjusted with agreeable shopping in cool markets as a main background).
And 106, aiming at any one of at least two different business projects, generating a personalized page corresponding to the business project according to the trained page generation model.
Specifically, for any one of at least two different business items, generating a personalized page corresponding to the business item according to the trained page generation model includes:
receiving a page access request sent by a user, wherein the page access request comprises: identification information and user information corresponding to the service item;
determining a special page element material corresponding to the business project according to the identification information corresponding to the business project;
and displaying the personalized page corresponding to the business project to the user according to the special page element material corresponding to the business project, the user information and the trained page generation model.
The special page element material corresponding to the business project comprises at least one of the following materials: icon information corresponding to the service item, content information corresponding to the service item, and link information corresponding to the service item;
the user information includes at least one of: the time information corresponding to the user sending the page access request, the sex of the user, the age of the user, and the model of the mobile terminal used by the user sending the page access request.
And aiming at different business projects, determining the special page element material corresponding to each business project.
Still, the first business item is the credit card promotion activity of bank a, and the second business item is the credit card promotion activity of bank B.
For a first business project, determining a special page element material corresponding to the first business project: the method comprises the following steps that (1) the LOGO information of a bank A is a proprietary icon, the detail introduction characters of the credit card promotion activities of the bank A, the registration links of the credit card promotion activities of the bank A and the like;
and for the second service project, determining a special page element material corresponding to the second service project: the LOGO information LOGO specific to bank B, the detail introduction text of the credit card promotion activity of bank B, the registration link of the credit card promotion activity of bank B, etc.
After a page access request sent by a user is received, determining a special page element material corresponding to a service project according to identification information corresponding to the service project included in the page access request.
And determining the page access state according to the user information included in the page access request. And determining a page template corresponding to the page access state according to the page access state and the trained page generation model. And then generating and displaying the personalized page corresponding to the business project to the user according to the determined page template and the special page element material corresponding to the business project.
Still take the above-mentioned page generation model created for the general scenario (credit card promotion activity) applicable to the first business project and the second business project, and take the trained page generation model obtained after model training of the page generation model as an example.
Receiving a page access request sent by a user, wherein the page access request comprises: the identification information of the first service project and the corresponding time information when the user sends the page access request are summer, and the gender of the user is lady.
Then, according to the identification information of the first service item, the special page element material corresponding to the first item can be determined: the method comprises the following steps that (1) the LOGO information of a bank A is a proprietary icon, the detail introduction characters of the credit card promotion activities of the bank A, the registration links of the credit card promotion activities of the bank A and the like;
determining a page template B (a page template with the cool and agreeable shopping in a mall as the background basic tone) according to the fact that the corresponding time information when a user sends a page access request is summer and the gender of the user is female;
and then according to the special page element material corresponding to the first project and the page template B, generating a personalized page corresponding to the first business project for the user: the personalized page is based on background and background of satisfied shopping in cool markets.
In the embodiment of the present application, the method further includes:
acquiring feedback information of a user on a personalized page corresponding to a service project;
and updating the trained page generation model according to the feedback information.
After a personalized page corresponding to a certain service item is displayed to a user, feedback information (for example, stay time, participation in an activity, clicking a certain control, and the like) of the user for the personalized page is acquired, and then the trained page generation model is updated according to the feedback information, that is, the display probability corresponding to different page templates included in the trained page generation model is adjusted.
For example, for an individualized page generated by using a page template with a red control color of the control a, if it is found according to feedback information of a user on the individualized page that the click rate of the control a is low, the trained page generation model is updated, that is, in the updated trained page generation model, the display probability corresponding to the page template with the red control color of the control a is reduced, and the display probability corresponding to the page templates with the other control colors of the control a is improved.
The trained page generation model is continuously adjusted according to the feedback information of the user on the personalized page, so that the capability of generating the personalized page according with the user preference by the trained page generation model can be improved.
The trained page generation model is obtained by training the page generation model created by the general scene suitable for at least two different business projects, so that the trained page generation model can be directly used for generating the personalized page corresponding to the business project for other business projects similar to the at least two different business projects, namely for other business projects which can also use the general scene, and the universality of the trained page generation model is effectively improved.
According to the technical scheme, the page generation model corresponding to the general scene suitable for the at least two different business projects is created, model training is conducted on the page generation model according to the general page element materials suitable for the general scene, and the trained page generation model is obtained, so that the personalized page corresponding to the business project is generated according to the trained page generation model for any business project of the at least two different business projects, the universality of the trained page generation model is effectively improved, and the page generation efficiency is improved.
Fig. 2 is a schematic diagram of a page generation method according to an embodiment of the present application. The method may be as follows.
According to the technical scheme, the page generation model corresponding to the general scene suitable for the at least two different business projects is created, model training is conducted on the page generation model according to the general page element materials suitable for the general scene, and the trained page generation model is obtained, so that the personalized page corresponding to the business project is generated according to the trained page generation model for any business project of the at least two different business projects, the universality of the trained page generation model is effectively improved, and the page generation efficiency is improved.
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 3, at the hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory, such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, the network interface, and the memory may be connected to each other via an internal bus, which may be an ISA (Industry Standard Architecture) bus, a PCI (peripheral component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 3, but this does not indicate only one bus or one type of bus.
And a memory for storing the program. In particular, the program may include program code comprising computer operating instructions. The memory may include both memory and non-volatile storage and provides instructions and data to the processor.
The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to form the page generating device on the logic level. The processor executes the program stored in the memory and specifically executes the following operations:
creating a page generation model corresponding to a general scene, wherein the general scene is suitable for at least two different business projects;
performing model training on the page generation model according to the general page element material to obtain a trained page generation model, wherein the general page element material is suitable for a general scene;
and aiming at any one of at least two different business projects, generating a personalized page corresponding to the business project according to the trained page generation model.
The method described above with reference to fig. 1 may be applied in or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present specification may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the embodiments of the present specification may be embodied directly in a hardware decoding processor, or in a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
The electronic device may further execute the method executed in the embodiment shown in fig. 1, and implement the functions of the embodiment shown in fig. 1, which are not described herein again in this specification.
An embodiment of the present application further provides a computer-readable storage medium, where the computer-readable storage medium stores one or more programs, where the one or more programs include instructions, which, when executed by an electronic device including multiple application programs, enable the electronic device to perform the page generation method in the embodiment shown in fig. 1, and specifically perform the following operations:
creating a page generation model corresponding to a general scene, wherein the general scene is suitable for at least two different business projects;
performing model training on the page generation model according to the general page element material to obtain a trained page generation model, wherein the general page element material is suitable for a general scene;
and aiming at any one of at least two different business projects, generating a personalized page corresponding to the business project according to the trained page generation model.
Fig. 4 is a schematic structural diagram of a page generation apparatus according to an embodiment of the present application. The apparatus 400 shown in fig. 4 comprises:
a creating module 401, configured to create a page generation model corresponding to a general scene, where the general scene is applicable to at least two different service projects;
a training module 402, configured to perform model training on a page generation model according to a general page element material to obtain a trained page generation model, where the general page element material is suitable for a general scene;
the page generating module 403 is configured to generate, for any one of at least two different business items, a personalized page corresponding to the business item according to the trained page generating model.
Optionally, the generic page element material comprises at least one of:
the system comprises a plurality of page frames, a plurality of background pictures, a plurality of control shapes, a plurality of control colors, a plurality of styles of page containers and a plurality of styles of popularization words.
Optionally, the training module 402 is specifically configured to:
determining different page templates according to the general page element materials;
and training a page generation model by using a preset algorithm according to different page templates and taking the page conversion rate maximization as a training target to obtain the trained page generation model, wherein the trained page generation model comprises the display probabilities corresponding to the different page templates.
Optionally, the page generating module 403 is specifically configured to:
receiving a page access request sent by a user, wherein the page access request comprises: identification information and user information corresponding to the service item;
determining a special page element material corresponding to the business project according to the identification information corresponding to the business project;
and displaying the personalized page corresponding to the business project to the user according to the special page element material corresponding to the business project, the user information and the trained page generation model.
Optionally, the dedicated page element material corresponding to the business project includes at least one of the following:
icon information corresponding to the service item, content information corresponding to the service item, and link information corresponding to the service item.
Optionally, the user information includes at least one of:
the time information corresponding to the user sending the page access request, the sex of the user, the age of the user, and the model of the mobile terminal used by the user sending the page access request.
Optionally, the apparatus 400 further comprises:
the acquisition module is used for acquiring feedback information of the user to the personalized page corresponding to the service project;
and the updating module is used for updating the trained page generation model according to the feedback information.
Optionally, the preset algorithm is a Bandit algorithm.
According to the page generation device, a creation module creates a page generation model corresponding to a general scene, wherein the general scene is suitable for at least two different business projects; the training module performs model training on the page generation model according to the general page element material to obtain a trained page generation model, wherein the general page element material is suitable for a general scene; the page generation module generates a personalized page corresponding to the business project according to the trained page generation model aiming at any business project of at least two different business projects, so that the universality of the trained page generation model is effectively improved, and the page generation efficiency is further improved.
In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Language Description Language), traffic, pl (core unified Programming Language), HDCal, JHDL (Java Hardware Description Language), langue, Lola, HDL, laspam, hardsradware (Hardware Description Language), vhjhd (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the units may be implemented in one or more software and/or hardware when implementing the present application.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.
Claims (8)
1. A page generation method is characterized by comprising the following steps:
creating a page generation model corresponding to a general scene, wherein the general scene is suitable for at least two different business projects; aiming at least two different service projects, and under the condition that the at least two different service projects are similar service projects, creating corresponding page generation models for general scenes suitable for the at least two different service projects; when a plurality of general scenes suitable for at least two different service projects exist, creating a page generation model for each general scene;
performing model training on the page generation model according to a general page element material to obtain a trained page generation model, wherein the general page element material is suitable for the general scene;
aiming at any one of the at least two different business projects, generating a personalized page corresponding to the business project according to the trained page generation model;
according to the general page element materials, performing model training on the page generation model to obtain a trained page generation model, and the method comprises the following steps:
generating a model aiming at a page corresponding to a certain general scene, and determining different page templates according to general page element materials suitable for the general scene, wherein the different page templates are composed of different general page element materials;
according to the different page templates, taking the page conversion rate maximization as a training target, and training the page generation model by using a preset algorithm to obtain the trained page generation model, wherein the trained page generation model comprises display probabilities corresponding to the different page templates; the method comprises the steps that a Bandit algorithm is used for distributing display probabilities and display times of different page templates, the page conversion rates corresponding to the different page templates in different page access states are determined by taking the page conversion rate maximization as a training target, and the display probability of the page template can be improved by a trained page generation model aiming at the page template with higher page conversion rate in a certain page access state when the same page access state is faced next time;
aiming at any one of the at least two different business projects, generating a personalized page corresponding to the business project according to the trained page generation model, wherein the personalized page comprises:
receiving a page access request sent by a user, wherein the page access request comprises: identification information and user information corresponding to the service item;
determining a special page element material corresponding to the service project according to the identification information corresponding to the service project;
and generating a model according to the special page element material corresponding to the business project, the user information and the trained page, and displaying the personalized page corresponding to the business project to the user.
2. The method of claim 1, wherein the generic page element material comprises at least one of:
the system comprises a plurality of page frames, a plurality of background pictures, a plurality of control shapes, a plurality of control colors, a plurality of styles of page containers and a plurality of styles of popularization words.
3. The method of claim 1, wherein the dedicated page element material corresponding to the business item comprises at least one of:
icon information corresponding to the service item, content information corresponding to the service item, and link information corresponding to the service item.
4. The method of claim 1, wherein the user information comprises at least one of:
the time information corresponding to the time when the user sends the page access request, the gender of the user, the age of the user, and the model of the mobile terminal used when the user sends the page access request.
5. The method of claim 1, wherein the method further comprises:
acquiring feedback information of the user to the personalized page corresponding to the service project;
and updating the trained page generation model according to the feedback information.
6. A page generating apparatus, comprising:
the system comprises a creating module, a generating module and a processing module, wherein the creating module is used for creating a page generating model corresponding to a general scene, and the general scene is suitable for at least two different business projects; aiming at least two different service projects, and under the condition that the at least two different service projects are similar service projects, creating corresponding page generation models for general scenes suitable for the at least two different service projects; when a plurality of general scenes suitable for at least two different service projects exist, creating a page generation model for each general scene;
the training module is used for carrying out model training on the page generation model according to a general page element material to obtain a trained page generation model, wherein the general page element material is suitable for the general scene;
the page generation module is used for generating a personalized page corresponding to the business project according to the trained page generation model aiming at any one of the at least two different business projects;
wherein the training module is specifically configured to:
generating a model aiming at a page corresponding to a certain general scene, and determining different page templates according to general page element materials suitable for the general scene, wherein the different page templates are composed of different general page element materials;
according to the different page templates, taking the page conversion rate maximization as a training target, and training the page generation model by using a preset algorithm to obtain the trained page generation model, wherein the trained page generation model comprises display probabilities corresponding to the different page templates; the method comprises the steps that a Bandit algorithm is used for distributing display probabilities and display times of different page templates, the page conversion rates corresponding to the different page templates in different page access states are determined by taking the page conversion rate maximization as a training target, and the display probability of the page template can be improved by a trained page generation model aiming at the page template with higher page conversion rate in a certain page access state when the same page access state is faced next time;
the page generation module is specifically configured to:
receiving a page access request sent by a user, wherein the page access request comprises: identification information and user information corresponding to the service item;
determining a special page element material corresponding to the service project according to the identification information corresponding to the service project;
and generating a model according to the special page element material corresponding to the business project, the user information and the trained page, and displaying the personalized page corresponding to the business project to the user.
7. An electronic device, comprising:
a memory for storing a program;
a processor for executing the program stored in the memory, and specifically executing:
creating a page generation model corresponding to a general scene, wherein the general scene is suitable for at least two different business projects; aiming at least two different service projects, and under the condition that the at least two different service projects are similar service projects, creating corresponding page generation models for general scenes suitable for the at least two different service projects; when a plurality of general scenes suitable for at least two different service projects exist, creating a page generation model for each general scene;
performing model training on the page generation model according to a general page element material to obtain a trained page generation model, wherein the general page element material is suitable for the general scene;
aiming at any one of the at least two different business projects, generating a personalized page corresponding to the business project according to the trained page generation model;
according to the general page element materials, performing model training on the page generation model to obtain a trained page generation model, and the method comprises the following steps:
generating a model aiming at a page corresponding to a certain general scene, and determining different page templates according to general page element materials suitable for the general scene, wherein the different page templates are composed of different general page element materials;
according to the different page templates, taking the page conversion rate maximization as a training target, and training the page generation model by using a preset algorithm to obtain the trained page generation model, wherein the trained page generation model comprises display probabilities corresponding to the different page templates; the method comprises the steps that a Bandit algorithm is used for distributing display probabilities and display times of different page templates, the page conversion rates corresponding to the different page templates in different page access states are determined by taking the page conversion rate maximization as a training target, and the display probability of the page template can be improved by a trained page generation model aiming at the page template with higher page conversion rate in a certain page access state when the same page access state is faced next time;
aiming at any one of the at least two different business projects, generating a personalized page corresponding to the business project according to the trained page generation model, wherein the personalized page comprises:
receiving a page access request sent by a user, wherein the page access request comprises: identification information and user information corresponding to the service item;
determining a special page element material corresponding to the service project according to the identification information corresponding to the service project;
and generating a model according to the special page element material corresponding to the business project, the user information and the trained page, and displaying the personalized page corresponding to the business project to the user.
8. A computer-readable storage medium storing one or more programs which, when executed by an electronic device including a plurality of application programs, cause the electronic device to perform a method of:
creating a page generation model corresponding to a general scene, wherein the general scene is suitable for at least two different business projects; aiming at least two different service projects, and under the condition that the at least two different service projects are similar service projects, creating corresponding page generation models for general scenes suitable for the at least two different service projects; when a plurality of general scenes suitable for at least two different service projects exist, creating a page generation model for each general scene;
performing model training on the page generation model according to a general page element material to obtain a trained page generation model, wherein the general page element material is suitable for the general scene;
aiming at any one of the at least two different business projects, generating a personalized page corresponding to the business project according to the trained page generation model;
according to the general page element materials, performing model training on the page generation model to obtain a trained page generation model, and the method comprises the following steps:
generating a model aiming at a page corresponding to a certain general scene, and determining different page templates according to general page element materials suitable for the general scene, wherein the different page templates are composed of different general page element materials;
according to the different page templates, taking the page conversion rate maximization as a training target, and training the page generation model by using a preset algorithm to obtain the trained page generation model, wherein the trained page generation model comprises display probabilities corresponding to the different page templates; the method comprises the steps that a Bandit algorithm is used for distributing display probabilities and display times of different page templates, the page conversion rates corresponding to the different page templates in different page access states are determined by taking the page conversion rate maximization as a training target, and the display probability of the page template can be improved by a trained page generation model aiming at the page template with higher page conversion rate in a certain page access state when the same page access state is faced next time;
aiming at any one of the at least two different business projects, generating a personalized page corresponding to the business project according to the trained page generation model, wherein the personalized page comprises:
receiving a page access request sent by a user, wherein the page access request comprises: identification information and user information corresponding to the service item;
determining a special page element material corresponding to the service project according to the identification information corresponding to the service project;
and generating a model according to the special page element material corresponding to the business project, the user information and the trained page, and displaying the personalized page corresponding to the business project to the user.
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| CN110136252B (en) * | 2019-05-21 | 2022-12-13 | 腾讯云计算（北京）有限责任公司 | Multi-scene data visualization system |
| CN110148214B (en) * | 2019-05-21 | 2022-12-13 | 腾讯云计算（北京）有限责任公司 | Multi-scene data visualization method and device |
| CN112068914B (en) * | 2020-08-26 | 2024-03-05 | 北京百度网讯科技有限公司 | Material content processing method and device, electronic equipment and storage medium |
| CN114024851A (en) * | 2021-12-01 | 2022-02-08 | 深圳绿米联创科技有限公司 | Network access configuration information generation method, network access configuration method and device and electronic equipment |
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