CN112149024A - Self-adaptive configuration method, device, equipment and storage medium for homepage - Google Patents
Self-adaptive configuration method, device, equipment and storage medium for homepage Download PDFInfo
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Abstract
The invention discloses a homepage self-adaptive configuration method, a homepage self-adaptive configuration device, equipment and a storage medium, wherein the homepage self-adaptive configuration method comprises the steps of obtaining memory information, chip information, use time, a scoring table and a weight information table of an intelligent terminal; determining the target model grade of the intelligent terminal according to the memory information, the chip information, the service time, the rating table and the weight information table; and carrying out homepage configuration of the intelligent terminal according to the target model grade to form a target homepage. According to the invention, the target model grade of the intelligent terminal is determined by various parameters such as the memory information, the chip information, the service time, the rating table and the weight information table, so that the accuracy of the determined target model grade is higher, and the target homepage is configured according to the target model grade with high accuracy, so that the target homepage is adapted to the intelligent terminal, the situations of jamming and the like are avoided, and the usability of the homepage of the intelligent terminal is improved.
Description
Technical Field
The invention relates to the technical field of televisions, in particular to a homepage self-adaptive configuration method, a homepage self-adaptive configuration device, homepage self-adaptive configuration equipment and a storage medium.
Background
The homepage is used as a main entrance for the smart television user to acquire content and applications, and the main entrance determines that the smart television user needs to display more content and a dazzling interface. On the other hand, it is also required to smoothly present and interact with the contents of the interface. The method for starting, demonstrating and interacting the homepage smoothly while dazzling the homepage as far as possible has great significance in the development of the intelligent television operating system.
At present, the smart television is divided into a high-end version, a medium-end version and a low-end version, a high-end version is adapted to a homepage of a high-end version, a medium-end version and a low-end version, the high-end version is adapted to the homepage of the high-end version, the medium-end version is adapted to the homepage of a common version, and the low-end version is adapted to the homepage of a simple version.
Disclosure of Invention
The invention mainly aims to provide a homepage self-adaptive configuration method, a homepage self-adaptive configuration device, equipment and a storage medium, and aims to solve the technical problem that the usability of the homepage of the current intelligent terminal is low.
In order to achieve the above object, an embodiment of the present invention provides a homepage adaptive configuration method, where the homepage adaptive configuration method includes:
acquiring memory information, chip information, use time, a rating table and a weight information table of the intelligent terminal;
determining the target model grade of the intelligent terminal according to the memory information, the chip information, the service time, the rating table and the weight information table;
and carrying out homepage configuration of the intelligent terminal according to the target model grade to form a target homepage.
Preferably, the configuring the homepage of the intelligent terminal according to the target model class, and the step of forming the target homepage includes:
and acquiring parameter information of each homepage module when the target homepage runs, and adjusting the target homepage according to the parameter information to form an updated homepage.
Preferably, the step of adjusting the target homepage according to the parameter information to form an updated homepage includes:
determining a target homepage module needing to be adjusted in the target homepage according to the parameter information;
carrying out forward feedback on the target homepage module to generate a feedback result;
and optimizing and adjusting the target homepage according to the feedback result to form an updated homepage.
Preferably, the step of determining the target model grade of the intelligent terminal according to the memory information, the chip information, the service time, the score table and the weight information table includes:
extracting memory weight information, chip weight information and time weight information which respectively correspond to the memory information, the chip information and the service time in the weight information table;
extracting memory scoring information, chip scoring information and time scoring information which respectively correspond to the memory information, the chip information and the service time in the scoring table;
and determining the target model grade of the intelligent terminal according to the memory weight information, the chip weight information, the time weight information, the memory grading information, the chip grading information and the time grading information.
Preferably, the step of determining the target model grade of the intelligent terminal according to the memory weight information, the chip weight information, the time weight information, the memory rating information, the chip rating information, and the time rating information includes:
calculating the memory weight information and the memory scoring information to obtain first scoring information;
calculating the chip weight information and the chip grading information to obtain second grading information;
calculating the time weight information and the time scoring information to obtain third scoring information;
calculating the first scoring information, the second scoring information and the third scoring information to obtain a target scoring value;
and determining the target model grade of the intelligent terminal according to the target score value.
Preferably, the step of determining the target model grade of the intelligent terminal according to the target score value comprises the following steps;
and acquiring a preset standard scoring range group for judging the model grade of the intelligent terminal, matching the target scoring value with the preset standard scoring range group, and determining the model grade corresponding to the preset standard scoring range matched with the target scoring value in the preset standard scoring range group as the target model grade.
Preferably, the step of configuring the homepage of the intelligent terminal according to the target model class to form a target homepage includes:
acquiring a homepage configuration standard of the intelligent terminal, and determining a homepage module group according to the homepage configuration standard and the target machine type grade;
and carrying out homepage configuration on the intelligent terminal based on the homepage module group to form a target homepage.
In order to achieve the above object, the present invention further provides a homepage adaptive configuration device, including:
the acquisition module is used for acquiring the memory information, the chip information, the service time, the scoring table and the weight information table of the intelligent terminal;
the determining module is used for determining the target model grade of the intelligent terminal according to the memory information, the chip information, the service time, the scoring table and the weight information table;
and the configuration module is used for configuring the homepage of the intelligent terminal according to the target model grade to form a target homepage.
Further, to achieve the above object, the present invention also provides a homepage adaptive configuration device, which includes a memory, a processor, and a homepage adaptive configuration program stored in the memory and executable on the processor, wherein the homepage adaptive configuration program implements the steps of the homepage adaptive configuration method when executed by the processor.
Further, to achieve the above object, the present invention also provides a storage medium having a homepage adaptive configuration program stored thereon, wherein the homepage adaptive configuration program implements the steps of the homepage adaptive configuration method when executed by a processor.
The embodiment of the invention provides a homepage self-adaptive configuration method, a homepage self-adaptive configuration device, equipment and a storage medium, wherein the homepage self-adaptive configuration method, the homepage self-adaptive configuration device, the equipment and the storage medium are used for acquiring the memory information, the chip information, the service time, a scoring table and a weight information table of an intelligent terminal; determining the target model grade of the intelligent terminal according to the memory information, the chip information, the service time, the rating table and the weight information table; and carrying out homepage configuration of the intelligent terminal according to the target model grade to form a target homepage. According to the invention, the target model grade of the intelligent terminal is determined by various parameters such as the memory information, the chip information, the service time, the rating table and the weight information table, so that the accuracy of the determined target model grade is higher, and the target homepage is configured according to the target model grade with high accuracy, so that the target homepage is adapted to the intelligent terminal, the situations of jamming and the like are avoided, and the usability of the homepage of the intelligent terminal is improved.
Drawings
FIG. 1 is a schematic structural diagram of a hardware operating environment according to an embodiment of a home page adaptive configuration method of the present invention;
FIG. 2 is a flowchart illustrating a homepage adaptive configuration method according to a first embodiment of the present invention;
FIG. 3 is a flowchart illustrating a homepage adaptive configuration method according to a second embodiment of the present invention;
FIG. 4 is a flowchart illustrating a homepage adaptive configuration method according to a third embodiment of the present invention;
FIG. 5 is a flowchart illustrating a homepage adaptive configuration method according to a fourth embodiment of the present invention;
FIG. 6 is a functional block diagram of a homepage adaptive configuration device according to a preferred embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The embodiment of the invention provides a homepage self-adaptive configuration method, a homepage self-adaptive configuration device, equipment and a storage medium, wherein the homepage self-adaptive configuration method, the homepage self-adaptive configuration device, the equipment and the storage medium are used for acquiring the memory information, the chip information, the service time, a scoring table and a weight information table of an intelligent terminal; determining the target model grade of the intelligent terminal according to the memory information, the chip information, the service time, the rating table and the weight information table; and carrying out homepage configuration of the intelligent terminal according to the target model grade to form a target homepage. According to the invention, the target model grade of the intelligent terminal is determined by various parameters such as the memory information, the chip information, the service time, the rating table and the weight information table, so that the accuracy of the determined target model grade is higher, and the target homepage is configured according to the target model grade with high accuracy, so that the target homepage is adapted to the intelligent terminal, the situations of jamming and the like are avoided, and the usability of the homepage of the intelligent terminal is improved.
As shown in fig. 1, fig. 1 is a schematic structural diagram of a homepage adaptive configuration device of a hardware operating environment according to an embodiment of the present invention.
In the following description, suffixes such as "module", "component", or "unit" used to denote elements are used only for facilitating the explanation of the present invention, and have no specific meaning in itself. Thus, "module", "component" or "unit" may be used mixedly.
The homepage self-adaptive configuration equipment of the embodiment of the invention can be a PC, and can also be mobile terminal equipment such as a tablet computer, a portable computer and the like.
As shown in fig. 1, the homepage adaptive configuration device may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a storage device separate from the processor 1001.
It will be understood by those skilled in the art that the structure of the home page adaptive configuration device shown in FIG. 1 does not constitute a limitation of the home page adaptive configuration device, and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a storage medium, may include therein an operating system, a network communication module, a user interface module, and a homepage adaptive configuration program.
In the device shown in fig. 1, the network interface 1004 is mainly used for connecting to a backend server and performing data communication with the backend server; the user interface 1003 is mainly used for connecting a client (user side) and performing data communication with the client; and the processor 1001 may be configured to invoke the homepage adaptive configuration program stored in the memory 1005 and perform the following operations:
acquiring memory information, chip information, use time, a rating table and a weight information table of the intelligent terminal;
determining the target model grade of the intelligent terminal according to the memory information, the chip information, the service time, the rating table and the weight information table;
and carrying out homepage configuration of the intelligent terminal according to the target model grade to form a target homepage.
Further, after the step of configuring the home page of the intelligent terminal according to the target model class to form a target home page, the processor 1001 may be configured to call a home page adaptive configuration program stored in the memory 1005, and perform the following operations:
and acquiring parameter information of each homepage module when the target homepage runs, and adjusting the target homepage according to the parameter information to form an updated homepage.
Further, the step of adjusting the target homepage according to the parameter information to form an updated homepage includes:
determining a target homepage module needing to be adjusted in the target homepage according to the parameter information;
carrying out forward feedback on the target homepage module to generate a feedback result;
and optimizing and adjusting the target homepage according to the feedback result to form an updated homepage.
Further, the step of determining the target model grade of the intelligent terminal according to the memory information, the chip information, the service time, the rating table and the weight information table includes:
extracting memory weight information, chip weight information and time weight information which respectively correspond to the memory information, the chip information and the service time in the weight information table;
extracting memory scoring information, chip scoring information and time scoring information which respectively correspond to the memory information, the chip information and the service time in the scoring table;
and determining the target model grade of the intelligent terminal according to the memory weight information, the chip weight information, the time weight information, the memory grading information, the chip grading information and the time grading information.
Further, the step of determining the target model grade of the intelligent terminal according to the memory weight information, the chip weight information, the time weight information, the memory grading information, the chip grading information, and the time grading information includes:
calculating the memory weight information and the memory scoring information to obtain first scoring information;
calculating the chip weight information and the chip grading information to obtain second grading information;
calculating the time weight information and the time scoring information to obtain third scoring information;
calculating the first scoring information, the second scoring information and the third scoring information to obtain a target scoring value;
and determining the target model grade of the intelligent terminal according to the target score value.
Further, the step of determining the target model grade of the intelligent terminal according to the target score value comprises the following steps;
and acquiring a preset standard scoring range group for judging the model grade of the intelligent terminal, matching the target scoring value with the preset standard scoring range group, and determining the model grade corresponding to the preset standard scoring range matched with the target scoring value in the preset standard scoring range group as the target model grade.
Further, the step of configuring the homepage of the intelligent terminal according to the target model class to form a target homepage includes:
acquiring a homepage configuration standard of the intelligent terminal, and determining a homepage module group according to the homepage configuration standard and the target machine type grade;
and carrying out homepage configuration on the intelligent terminal based on the homepage module group to form a target homepage.
For a better understanding of the above technical solutions, exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
In order to better understand the technical solution, the technical solution will be described in detail with reference to the drawings and the specific embodiments.
Referring to fig. 2, a first embodiment of the invention provides a flowchart illustrating a homepage adaptive configuration method. In this embodiment, the homepage adaptive configuration method includes the following steps:
step S10, acquiring the memory information, chip information, service time, a scoring table and a weight information table of the intelligent terminal;
the homepage self-adaptive configuration method in this embodiment is applied to a control system of an intelligent terminal, the control system in this embodiment can at least control the intelligent terminal to generate and display a homepage, so that a user can interact with the homepage displayed, the intelligent terminal can be a smart phone, a tablet computer, a smart television, and the like, and in this embodiment, the smart phone is mainly taken as an example. As can be appreciated, the main portal for the smart tv user to access content and applications determines that the smart tv user must display more content and a more dazzling interface. On the other hand, it is also required to smoothly present and interact with the contents of the interface. The method for starting, demonstrating and interacting the homepage smoothly while dazzling the homepage as far as possible has great significance in the development of the intelligent television operating system. The home page concept of the smart television is consistent with that of the smart phone, and is a main interactive entrance of the terminal and the user, and the basic expression form is to display and arrange a plurality of function icons and compile the function icons into an independent app (Application program), so that the home page is an independent Application program and is also a part of an operating system. From the user's perspective, it is common to forgo using an application with a poor operating experience, and if the operating experience of the homepage is poor, the user may consider the operating system to be poor, and may forgo purchasing the product. A good homepage must guarantee a good operating experience.
However, in the current practice, the intelligent terminal is classified into a plurality of different model classes according to the size of the internal memory of the intelligent terminal, and generally classified into high, medium and low end models, and the high, medium and low end models are respectively integrated with homepage apps of high, medium and low end versions. The method is characterized in that a high-end machine is matched with a high-edition homepage, a medium-end machine is matched with a common-edition homepage, and a low-end machine is matched with a simple-edition homepage. In order to solve the problems, the invention provides a homepage self-adaptive configuration method, which determines the target machine type grade of an intelligent terminal through various parameters such as memory information, chip information, using time, a scoring table, a weight information table and the like, so that the accuracy of the determined target machine type grade is higher, and the target homepage is matched with the intelligent terminal according to the target machine type grade with high accuracy, so that the situations of jamming and the like are avoided, and the usability of the homepage of the intelligent terminal is improved.
Further, when the user opens the intelligent terminal, in order to generate and display an optimal home page of the intelligent terminal, the control system obtains internal storage information and chip information of the intelligent terminal, specifically, since the intelligent terminal generates local memory information, such as a total memory and an available memory, according to a storage condition of the intelligent terminal during production, and generates chip information according to an adopted processor chip, the chip information may include a core number of a CPU (central Processing Unit) and a GPU (Graphics Processing Unit), a chip platform, and the like, and stores the generated memory information and chip information into the internal storage, the control system may search and extract the internal memory information and chip information of the intelligent terminal from the internal storage through a control relationship to the internal storage. It can be understood that the model grade of the intelligent terminal can be preliminarily determined through the memory information and the chip information, but the accuracy is still not high enough, so that the control system also needs to acquire the background activation time and the current time of the intelligent terminal under the networking condition, calculate the time difference between the activation time and the current time, and use the calculated time difference as the service time of the intelligent terminal. In addition, in order to more accurately determine the model grade of the intelligent terminal, the control system further needs to obtain a score table and a weight information table preset in the intelligent terminal, wherein the score table includes scores of each memory or memory range when the model grade is determined, scores of different chips when the model grade is determined, and scores of the intelligent terminal when different use times are determined, and the weight information table includes memory information, chip information and weight information of the use times when the model grade is determined. The evaluation table and the weight information table are combined with the memory information, the chip information and the service time, so that whether the target model grade of the intelligent terminal is a high-end model, a middle-end model or a low-end model is accurately determined.
Step S20, determining the target model grade of the intelligent terminal according to the memory information, the chip information, the service time, the scoring table and the weight information table;
further, the control system firstly finds out the memory weight information corresponding to the memory information from the weight information table, finds out the chip weight information corresponding to the chip information from the weight information table, and finds out the time weight information corresponding to the use time from the weight information table; and searching memory scoring information corresponding to the memory information from the scoring table, searching chip scoring information corresponding to the chip information from the scoring table, and searching time scoring information corresponding to the use time from the scoring table. It can be understood that the control system can determine the target model grade of the intelligent terminal by calculating the memory weight information, the chip weight information, the memory scoring information and the chip scoring information, but since the determined model grade is determined only by integrating the memory information and the chip information, it is known that the difference of the use time of the intelligent terminal can cause the performance of hardware and/or software in the intelligent terminal to be reduced and can also cause the model grade of the intelligent terminal to be changed, if the model grade determined according to the memory information and the chip information is taken as the final model grade of the intelligent terminal, the accuracy of the model grade is low, therefore, in order to make the determined model grade have higher accuracy, the control system needs to determine the target model grade according to the memory weight information, the memory scoring information, the chip weight information, the chip scoring information, the time weighting information, the time scoring information and the like, and determining the target model grade of the intelligent terminal by combining a weighting algorithm.
And step S30, configuring the homepage of the intelligent terminal according to the target model grade to form a target homepage.
Further, after the target model grade of the intelligent terminal is determined, understandably, the control system adopts the same homepage app to configure the target homepage, specifically, the control system searches a corresponding homepage module group according to the target model grade, adaptively configures the homepage module group in the homepage app, and generates the target homepage after completing the configuration of all homepage modules in the homepage module group, so that a user can interact with the intelligent terminal according to the target homepage.
The embodiment provides a homepage self-adaptive configuration method, a homepage self-adaptive configuration device, equipment and a storage medium, and the homepage self-adaptive configuration method, the homepage self-adaptive configuration device, the equipment and the storage medium are used for acquiring the memory information, the chip information, the service time, a scoring table and a weight information table of an intelligent terminal; determining the target model grade of the intelligent terminal according to the memory information, the chip information, the service time, the rating table and the weight information table; and carrying out homepage configuration of the intelligent terminal according to the target model grade to form a target homepage. According to the invention, the target model grade of the intelligent terminal is determined by various parameters such as the memory information, the chip information, the service time, the rating table and the weight information table, so that the accuracy of the determined target model grade is higher, and the target homepage is configured according to the target model grade with high accuracy, so that the target homepage is adapted to the intelligent terminal, the situations of jamming and the like are avoided, and the usability of the homepage of the intelligent terminal is improved.
Further, referring to fig. 3, a second embodiment of the home page adaptive configuration method of the present invention is proposed based on the first embodiment of the home page adaptive configuration method of the present invention, in the second embodiment, the step of configuring the home page of the intelligent terminal according to the target model class, and forming the target home page includes:
and step S40, acquiring parameter information of each homepage module when the target homepage runs, and adjusting the target homepage according to the parameter information to form an updated homepage.
It can be understood that, in addition to determining the model grades of the high, medium and low ends of the intelligent terminal according to the above memory information, chip information and service time, and adaptively configuring each module of the homepage to form the target homepage with different display effects, the control system should properly adjust the running condition of each homepage module in the target homepage, specifically, the control system monitors the running of the target homepage in real time, and obtains the parameter information of each homepage module in the running of the target homepage, then determines the target homepage module to be adjusted according to the obtained parameter information, and performs forward feedback on the target homepage module, and performs optimization adjustment on the target homepage according to the feedback result of the forward feedback to form a homepage update, so that the homepage module in the target homepage is more suitable for the current user to use, and improves the user experience.
Further, the step of adjusting the target homepage according to the parameter information to form an updated homepage includes:
step S41, determining a target homepage module needing to be adjusted in the target homepage according to the parameter information;
step S42, carrying out forward feedback on the target homepage module to generate a feedback result;
and step S43, optimizing and adjusting the target homepage according to the feedback result to form an updated homepage.
Further, the control system firstly analyzes whether a homepage module with abnormal parameters exists in the homepage module group of the target homepage according to the acquired parameter information, and if so, the homepage module is determined as the target homepage module needing to be adjusted. After the target homepage module is determined, the control system carries out forward feedback on the target homepage module, carries out forward feedback on real parameters of the homepage module during operation, and generates a feedback result according to the real parameters of the forward feedback. Further, the control system adjusts the target homepage module by taking the feedback result as an adjustment basis, specifically, software or hardware repair can be performed on the target homepage module, or the target machine type grade of the intelligent terminal is adjusted, and the target homepage is configured again in a self-adaptive manner according to the adjusted target machine type grade, so that the target homepage is optimized and adjusted, and the situation of parameter abnormity cannot occur when the optimized updated homepage runs. For example, in the running process of the target homepage, the memory situation occupied by the process of the target homepage, the total memory/residual memory of the current system, the CPU resource and GPU resource and other parameters occupied by each module of the homepage in the running process are analyzed in real time. And distinguishing high, middle and low-end models according to the judgment standard, determining a target homepage module with abnormal parameters, performing forward feedback on the target homepage module which is actually operated by the currently and dynamically loaded target homepage, and further adjusting the target homepage according to a feedback result. For example: the method comprises the steps that a television of a certain machine type is judged to be a high-end machine, each homepage module of a target homepage occupies less CPU and GPU resources in the running process, the problems of blocking and the like basically do not occur in the homepage operation process, the performance indexes of each homepage module of the target homepage are fed back to homepage apps, and the judgment and control system is reasonable in distinguishing and positioning of the target machine type grade of the intelligent terminal; if the homepage module in the target homepage occupies more CPU and GPU resources, the homepage module in the target homepage is easy to have the problems of unsmooth operation, unsmooth blocking and the like in the use process, the performance index of the target homepage module is fed back to the target homepage, namely, the distinguishing and positioning of the control system are judged to be unreasonable, the control system degrades the target homepage module configuration judged to be a high-end machine type into the homepage module configuration of a middle-end machine type or performs dynamic loading optimization on the target homepage module which is blocked according to the obtained machine core-machine type data, and the homepage module which is suitable for the machine type is updated and loaded. By carrying out forward feedback on the machine core-machine type in the actual operation process, the loaded homepage is more suitable for the machine type used by the current user, and the user experience is further improved. For example, the model Q80L is used, the Android version is 8.0, the memory is 4GB, the haisi platform Hi3751V811, the quad-core CPU, the Cortex a 73X 2+ a 53X 2, and the five-core GPU chip are used. According to the established standard, the high-end machine is considered, but in an AI (Artificial intelligence) entertainment page of a target homepage, a large cool dynamic picture needs to be loaded on the first screen, although the memory of the Q80L is enough, the performances of a chip CPU (Central processing Unit) and a GPU (graphics processing Unit) are poor, and the large dynamic picture playing on the page is blocked, so that the parameters are abnormal. Therefore, the control system obtains the performance index of the main page module corresponding to the AI entertainment page when the target main page runs by the model: for example, when other homepage modules run, the CPU resource occupied by the target homepage process is about 15-20%, but when the homepage module corresponding to the AI entertainment page runs, the CPU resource occupied by the target homepage process is about 50%, at this time, the CPU idle resource of the whole system is about 15%, and the total memory/remaining memory of the system is: 3751M/2415M, wherein the homepage process occupies a memory 350M; although the memory of the high-end computer Q80L is completely enough through analysis, the performance of a chip CPU and a GPU is poor, and excessive CPU resources are occupied during loading of the cool dynamic pictures, so that animation playing is not smooth and unsmooth, and the influence on user experience is avoided. The performance indexes of all modules of the target homepage need to be fed back to the target homepage in a forward direction, the target homepage module with abnormal parameters is determined, the unreasonable distinguishing and positioning of the intelligent terminal machine type grades is judged, the control system degrades the target homepage-AI entertainment page configuration which is judged to be a Q80L high-end machine into a middle-end machine type according to the obtained 9H85-Q80L data, and static pictures are loaded to complete the optimization of the target homepage module, so that an updated homepage is formed.
According to the embodiment, the homepage module in the target homepage is properly adjusted according to the parameter information of each homepage module during the operation of the target homepage, so that the homepage module is more suitable for the current user to use, and the user experience is further improved.
Further, referring to fig. 4, a third embodiment of the home page adaptive configuration method of the present invention is proposed based on the first embodiment of the home page adaptive configuration method of the present invention, and in the third embodiment, the step of determining the target model class of the intelligent terminal according to the memory information, the chip information, the usage time, the rating table, and the weight information table includes:
step S21, extracting memory weight information, chip weight information, and time weight information respectively corresponding to the memory information, the chip information, and the usage time in the weight information table;
step S22, extracting memory scoring information, chip scoring information and time scoring information respectively corresponding to the memory information, the chip information and the service time in the scoring table;
step S23, determining a target model grade of the intelligent terminal according to the memory weight information, the chip weight information, the time weight information, and the memory score information, the chip score information, and the time score information.
Further, the control system searches the memory weight information corresponding to the memory information from the weight information table by using the memory information as a search key, extracts the searched memory weight information, uses the chip information as the search key, searches the chip weight information corresponding to the chip information from the weight information table, extracts the searched chip weight information, uses the use time as the search key, searches the time weight information corresponding to the use time from the weight information table, and extracts the searched time weight information. Further, the control system searches memory scoring information corresponding to the memory information from the scoring table by using the memory information as a search key word, extracts the searched memory scoring information, searches chip scoring information corresponding to the chip information from the scoring table by using the chip information as the search key word, extracts the searched chip scoring information, searches time scoring information corresponding to the use time from the scoring table by using the use time as the search key word, and extracts the searched time scoring information. After the memory weight information, the chip weight information and the time weight information, and the memory scoring information, the chip scoring information and the time scoring information are extracted, the control system respectively determines first scoring information of the memory weight information and the memory scoring information, second scoring information of the chip weight information and the chip scoring information, and third scoring information of the time weight information and the time scoring information, then calculates a target scoring value according to the first scoring information, the second scoring information and the third scoring information, and finally determines a target model grade of the intelligent terminal according to the target scoring value.
Further, the step of determining the target model grade of the intelligent terminal according to the memory weight information, the chip weight information, the time weight information, the memory grading information, the chip grading information, and the time grading information includes:
step S231, calculating the memory weight information and the memory rating information to obtain first rating information;
step S232, calculating the chip weight information and the chip grading information to obtain second grading information;
step S233, calculating the time weight information and the time scoring information to obtain third scoring information;
step S234, calculating the first grading information, the second grading information and the third grading information to obtain a target grading value;
and S235, determining the target model grade of the intelligent terminal according to the target score value.
Further, the control system calculates the extracted memory weight information, chip weight information, time weight information, and memory scoring information, chip scoring information, time scoring information according to a weighting algorithm, and first performs product operation on the memory weight information and the memory scoring information, specifically, multiplies the memory weight information and the memory scoring information, and calculates to obtain first scoring information for scoring the memory information; performing product operation on the chip weight information and the chip scoring information, specifically, multiplying the chip weight information and the chip scoring information, and calculating to obtain second scoring information for scoring the chip information; and performing product operation on the time weight information and the time scoring information, specifically, multiplying the time weight information and the time scoring information, and calculating to obtain third scoring information for scoring the use time. Further, after the first scoring information, the second scoring information and the third scoring information are calculated, the control system performs summation operation on the first scoring information, the second scoring information and the third scoring information, and calculates a target scoring value for performing comprehensive scoring on the memory information, the chip information and the service time. After the target score value is calculated, the control system determines the target model grade of the intelligent terminal through a preset standard score range group according to the target score value, wherein the preset standard score range group is composed of a plurality of score ranges, each score range corresponds to one model grade, for example, 0-59 scores correspond to low-end models, 60-79 scores correspond to medium-end models, and 80-100 scores correspond to high-end models.
Further, the step of determining the target model grade of the intelligent terminal according to the target score value comprises the following steps;
step S2351, acquiring a preset standard scoring range group for judging the model grade of the intelligent terminal, matching the target scoring value with the preset standard scoring range group, and determining the model grade corresponding to the preset standard scoring range matched with the target scoring value in the preset standard scoring range group as the target model grade.
Further, the control system acquires a preset standard scoring range group for judging the model grade of the intelligent terminal from the internal memory, and matches the calculated target scoring value with a plurality of weight ranges in the preset standard scoring range group, for example: in the preset standard scoring range group, 0-59 points correspond to low-end machine models, 60-79 points correspond to medium-end machine models, 80-100 points correspond to high-end machine models, if the calculated target scoring value is 45 points, the target scoring value corresponds to the scoring range of 0-59 points in the preset standard scoring range group, and the scoring range of 0-59 points corresponds to the low-end machine models, so that the control system determines the low-end machine models as the target machine model grade of the optimal machine model grade of the intelligent terminal; if the calculated target score value is 75 scores, the target score value corresponds to a score range of 60-79 scores in the preset standard score range group, and the score range of 60-79 scores corresponds to the middle-end model, so that the control system determines the middle-end model as the target model grade of the optimal model grade of the intelligent terminal; if the calculated target score value is 88 scores, the target score value corresponds to a score range of 80-100 scores in the preset standard score range group, and the score range of 80-100 scores corresponds to a high-end model, so that the control system determines the high-end model as the target model grade of the optimal model grade of the intelligent terminal.
In this embodiment, the target model grade of the intelligent terminal is determined according to the memory information, the chip information, the service time, the rating table and the weight information table, and the target model grade is determined through various parameters, so that the accuracy of the determined target model grade is high, and homepage configuration is facilitated according to the target model grade.
Further, referring to fig. 5, a fourth embodiment of the home page adaptive configuration method according to the present invention is proposed based on the first embodiment of the home page adaptive configuration method according to the present invention, and in the fourth embodiment, the step of performing home page configuration of the intelligent terminal according to the target model class, and forming a target home page includes:
step S31, acquiring a homepage configuration standard of the intelligent terminal, and determining a homepage module group according to the homepage configuration standard and the target machine type grade;
and step S32, performing homepage configuration on the intelligent terminal based on the homepage module group to form a target homepage.
Further, after the target machine type grade of the intelligent terminal is determined, the control system acquires a homepage configuration standard of the intelligent terminal from the internal memory, wherein the homepage configuration standard comprises homepage modules corresponding to different machine type grades, the control system searches a plurality of homepage modules corresponding to the target machine type grade from a module library of the internal memory according to the acquired homepage configuration standard, and combines the homepage modules into a homepage module group to be extracted. Furthermore, the control system adaptively configures the homepage module group into the homepage app of the intelligent terminal according to a preset arrangement format, and after the configuration of all homepage modules in the homepage module group is completed, a target homepage with corresponding display effect is formed, so that understandably, target homepages with different target machine type grade adaptive configurations have different display effects, such as high-end machine type adaptation high-configuration homepage (the modules are numerous, the content is full and rich, the picture gives visual impact to people, dazzling, the homepage configures small-window video playing, no advertisement module, the homepage does not push advertisements), middle-end machine type adaptation common-version homepage (the modules are not much as high-configuration page, but the visual sensation of the picture gives people is general, the advertisement module and the homepage push advertisements), low-end machine type adaptation simple-version homepage (part of the modules with high requirement on the system memory are removed, for example, a game module, an AI entertainment module, a small window video playing module, an advertisement module and a homepage push advertisement are removed), the user can interact with the intelligent terminal through the target homepage, the use requirement of the user is met, and the use experience of the user is improved.
The home page configuration of the intelligent terminal is rapidly and adaptively carried out according to the target model grade to form the target home page, the home page configuration is carried out according to different model grades to form the target home page with different display effects, and the target home page is configured according to the target model grade with high accuracy to adapt to the intelligent terminal, so that the situations of jamming and the like are avoided, and the usability of the home page of the intelligent terminal is improved.
Furthermore, the invention also provides a homepage self-adaptive configuration device.
Referring to fig. 6, fig. 6 is a functional block diagram of a homepage adaptive configuration device according to a first embodiment of the present invention.
The homepage self-adaptive configuration device comprises:
the acquisition module 10 is used for acquiring the memory information, the chip information, the service time, the scoring table and the weight information table of the intelligent terminal;
the determining module 20 is configured to determine a target model grade of the intelligent terminal according to the memory information, the chip information, the service time, the rating table and the weight information table;
and the configuration module 30 is configured to configure the homepage of the intelligent terminal according to the target model class to form a target homepage.
Further, the determining module 20 includes:
a first extracting unit, configured to extract memory weight information, chip weight information, and time weight information that respectively correspond to the memory information, the chip information, and the usage time in the weight information table;
the second extraction unit is used for extracting memory scoring information, chip scoring information and time scoring information which respectively correspond to the memory information, the chip information and the service time in the scoring table;
and the first determining unit is used for determining the target model grade of the intelligent terminal according to the memory weight information, the chip weight information, the time weight information, the memory grading information, the chip grading information and the time grading information.
Further, the determining module 20 further includes:
the first operation unit is used for operating the memory weight information and the memory scoring information to obtain first scoring information;
the second operation unit is used for operating the chip weight information and the chip grading information to obtain second grading information;
the third operation unit is used for operating the time weight information and the time scoring information to obtain third scoring information;
the fourth operation unit is used for operating the first scoring information, the second scoring information and the third scoring information to obtain a target scoring value;
and the second determining unit is used for determining the target model grade of the intelligent terminal according to the target score value.
Further, the determining module 20 further includes:
and the matching unit is used for acquiring a preset standard scoring range group for judging the model grade of the intelligent terminal, matching the target scoring value with the preset standard scoring range group, and determining the model grade corresponding to the preset standard scoring range matched with the target scoring value in the preset standard scoring range group as the target model grade.
Further, the configuration module 30 includes:
the acquisition unit is used for acquiring a homepage configuration standard of the intelligent terminal and determining a homepage module group according to the homepage configuration standard and the target machine type grade;
and the configuration unit is used for carrying out homepage configuration on the intelligent terminal based on the homepage module group to form a target homepage.
Further, the homepage adaptive configuration device further comprises:
and the adjusting module 40 is used for acquiring the parameter information of each homepage module when the target homepage runs, and adjusting the target homepage according to the parameter information to form an updated homepage.
Further, the adjusting module 40 includes:
the third determining unit is used for determining a target homepage module needing to be adjusted in the target homepage according to the parameter information;
the feedback unit is used for carrying out forward feedback on the target homepage module and generating a feedback result;
and the optimization unit is used for optimizing and adjusting the target homepage according to the feedback result to form an updated homepage.
Furthermore, the present invention also provides a storage medium, preferably a computer readable storage medium, having stored thereon a homepage adaptive configuration program, which when executed by a processor implements the steps of the embodiments of the homepage adaptive configuration method described above.
In the embodiments of the home page adaptive configuration device and the computer readable medium of the present invention, all technical features of the embodiments of the home page adaptive configuration method are included, and the explanation and explanation contents are basically the same as those of the embodiments of the home page adaptive configuration method, and are not described herein again.
It should be noted that, in this document, 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 above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solution of the present invention or a part contributing to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk), and includes a plurality of instructions for enabling a terminal device (which may be a fixed terminal, such as an internet of things smart device including smart homes, such as a smart air conditioner, a smart lamp, a smart power supply, a smart router, etc., or a mobile terminal, including a smart phone, a wearable networked AR/VR device, a smart sound box, an autonomous driving automobile, etc.) to execute the method according to each embodiment of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A homepage adaptive configuration method, characterized in that, the homepage adaptive configuration method comprises:
acquiring memory information, chip information, use time, a rating table and a weight information table of the intelligent terminal;
determining the target model grade of the intelligent terminal according to the memory information, the chip information, the service time, the rating table and the weight information table;
and carrying out homepage configuration of the intelligent terminal according to the target model grade to form a target homepage.
2. The homepage adaptive configuration method of claim 1, wherein the homepage configuration of the intelligent terminal according to the target model class, and the step of forming a target homepage comprises:
and acquiring parameter information of each homepage module when the target homepage runs, and adjusting the target homepage according to the parameter information to form an updated homepage.
3. The homepage adaptive configuration method of claim 2, wherein the step of forming an updated homepage by adjusting the target homepage according to the parameter information comprises:
determining a target homepage module needing to be adjusted in the target homepage according to the parameter information;
carrying out forward feedback on the target homepage module to generate a feedback result;
and optimizing and adjusting the target homepage according to the feedback result to form an updated homepage.
4. The homepage adaptive configuration method of claim 1, wherein the step of determining the target model class of the intelligent terminal according to the memory information, the chip information, the usage time, the rating table, and the weight information table comprises:
extracting memory weight information, chip weight information and time weight information which respectively correspond to the memory information, the chip information and the service time in the weight information table;
extracting memory scoring information, chip scoring information and time scoring information which respectively correspond to the memory information, the chip information and the service time in the scoring table;
and determining the target model grade of the intelligent terminal according to the memory weight information, the chip weight information, the time weight information, the memory grading information, the chip grading information and the time grading information.
5. The home page adaptive configuration method according to claim 4, wherein the step of determining the target model class of the intelligent terminal according to the memory weight information, the chip weight information, the time weight information, and the memory score information, the chip score information, the time score information comprises:
calculating the memory weight information and the memory scoring information to obtain first scoring information;
calculating the chip weight information and the chip grading information to obtain second grading information;
calculating the time weight information and the time scoring information to obtain third scoring information;
calculating the first scoring information, the second scoring information and the third scoring information to obtain a target scoring value;
and determining the target model grade of the intelligent terminal according to the target score value.
6. The home page adaptive configuration method according to claim 5, wherein the step of determining the target model class of the intelligent terminal according to the target score value comprises;
and acquiring a preset standard scoring range group for judging the model grade of the intelligent terminal, matching the target scoring value with the preset standard scoring range group, and determining the model grade corresponding to the preset standard scoring range matched with the target scoring value in the preset standard scoring range group as the target model grade.
7. The homepage adaptive configuration method of claim 1, wherein the homepage configuration of the intelligent terminal according to the target model class, and the step of forming a target homepage comprises:
acquiring a homepage configuration standard of the intelligent terminal, and determining a homepage module group according to the homepage configuration standard and the target machine type grade;
and carrying out homepage configuration on the intelligent terminal based on the homepage module group to form a target homepage.
8. A homepage adaptive configuration device, comprising:
the acquisition module is used for acquiring the memory information, the chip information, the service time, the scoring table and the weight information table of the intelligent terminal;
the determining module is used for determining the target model grade of the intelligent terminal according to the memory information, the chip information, the service time, the scoring table and the weight information table;
and the configuration module is used for configuring the homepage of the intelligent terminal according to the target model grade to form a target homepage.
9. Homepage adaptive configuration device, characterized in that, the homepage adaptive configuration device comprises a memory, a processor and a homepage adaptive configuration program stored on the memory and executable on the processor, the homepage adaptive configuration program, when executed by the processor, implementing the steps of the homepage adaptive configuration method according to any one of claims 1 to 7.
10. A storage medium, characterized in that the storage medium has stored thereon a homepage adaptive configuration program, which when executed by a processor implements the steps of the homepage adaptive configuration method according to any one of claims 1 to 7.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112632432A (en) * | 2020-12-30 | 2021-04-09 | 平安证券股份有限公司 | Page refreshing method and device based on terminal, computer equipment and storage medium |
| CN113485132A (en) * | 2021-06-21 | 2021-10-08 | 青岛海尔科技有限公司 | Management method and device for smart home system and smart home system |
| CN113553134A (en) * | 2021-07-28 | 2021-10-26 | 支付宝(杭州)信息技术有限公司 | Page generation method, device, equipment and medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060080404A1 (en) * | 2002-06-19 | 2006-04-13 | Knut Haber-Land-Schlosser | Method and device for generating a mobile homepage in accordance with context related information |
| CN104503877A (en) * | 2014-12-30 | 2015-04-08 | 北京奇虎科技有限公司 | Method and device for evaluating intelligent terminal |
| CN104679852A (en) * | 2015-02-12 | 2015-06-03 | 广东欧珀移动通信有限公司 | Method and device for recommending application software |
| CN106055586A (en) * | 2016-05-21 | 2016-10-26 | 乐视控股（北京）有限公司 | Application recommendation system and method, terminal, and server |
-
2020
- 2020-10-16 CN CN202011114689.2A patent/CN112149024A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060080404A1 (en) * | 2002-06-19 | 2006-04-13 | Knut Haber-Land-Schlosser | Method and device for generating a mobile homepage in accordance with context related information |
| CN104503877A (en) * | 2014-12-30 | 2015-04-08 | 北京奇虎科技有限公司 | Method and device for evaluating intelligent terminal |
| CN104679852A (en) * | 2015-02-12 | 2015-06-03 | 广东欧珀移动通信有限公司 | Method and device for recommending application software |
| CN106055586A (en) * | 2016-05-21 | 2016-10-26 | 乐视控股（北京）有限公司 | Application recommendation system and method, terminal, and server |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112632432A (en) * | 2020-12-30 | 2021-04-09 | 平安证券股份有限公司 | Page refreshing method and device based on terminal, computer equipment and storage medium |
| CN112632432B (en) * | 2020-12-30 | 2023-07-18 | 平安证券股份有限公司 | Terminal-based page refreshing method and device, computer equipment and storage medium |
| CN113485132A (en) * | 2021-06-21 | 2021-10-08 | 青岛海尔科技有限公司 | Management method and device for smart home system and smart home system |
| CN113485132B (en) * | 2021-06-21 | 2024-03-22 | 青岛海尔科技有限公司 | Management method and device for intelligent home system and intelligent home system |
| CN113553134A (en) * | 2021-07-28 | 2021-10-26 | 支付宝(杭州)信息技术有限公司 | Page generation method, device, equipment and medium |
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