CN109753615B - Method and device for preloading webpage, storage medium and electronic equipment - Google Patents
Method and device for preloading webpage, storage medium and electronic equipment Download PDFInfo
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- CN109753615B CN109753615B CN201811584281.4A CN201811584281A CN109753615B CN 109753615 B CN109753615 B CN 109753615B CN 201811584281 A CN201811584281 A CN 201811584281A CN 109753615 B CN109753615 B CN 109753615B
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Abstract
The present disclosure is directed to a method and an apparatus for preloading a web page, a storage medium, and an electronic device, so as to solve the problem in the related art that predicting a preloaded web page is not accurate enough. The method comprises the following steps: determining a target page which can be skipped to from a current page, wherein the target page comprises a page which can be skipped to indirectly from the current page; acquiring browsing behavior information of a user; determining an access weight value of each target page at least according to the browsing behavior information; and preloading the target page with the access weight value meeting the preset condition.
Description
Technical Field
The present disclosure relates to the field of network technologies, and in particular, to a method and an apparatus for preloading a web page, a storage medium, and an electronic device.
Background
When a user browses a webpage, the browser preloads webpage data by using a preloading technology so as to shorten the waiting time of the user for opening the webpage. Preloading refers to loading some main contents before all the web pages are loaded so as to provide better experience for users and reduce waiting time. On the contrary, if the content of one page is too large, the page without the preloading technology will appear as a blank for a long time until all the content is loaded.
In the related art, after the current webpage is loaded, the browser estimates a target webpage which is likely to be accessed by the user in the next step by using the time of browsing the current webpage by the user, downloads the target webpage data and stores the target webpage data in a local cache. Once the user opens the link of the target webpage, the browser directly extracts the target webpage data from the cache and quickly presents the target webpage data to the user.
Disclosure of Invention
The present disclosure is directed to a method and an apparatus for preloading a web page, a storage medium, and an electronic device, so as to solve the problem in the related art that predicting a preloaded web page is not accurate enough.
To achieve the above object, in a first aspect, the present disclosure provides a method of preloading a web page, the method including:
determining a target page which can be skipped to from a current page, wherein the target page comprises a page which can be skipped to indirectly from the current page;
acquiring browsing behavior information of a user;
determining an access weight value of each target page at least according to the browsing behavior information;
and preloading the target page with the access weight value meeting the preset condition.
Optionally, the determining a target page that can be skipped to from the current page includes:
acquiring a skip operation element of the current page;
determining a next-level target page of the current page according to the jump operation element;
if each acquired first-level target page is finished, repeatedly executing the steps of acquiring the jump operation element of the target page and determining the next-level target page of the target page according to the jump operation element until the acquired target page does not have the page jump element;
the target pages which can jump to from the current page comprise the acquired target pages at each level.
Optionally, the determining a target page that can be skipped to from the current page includes:
acquiring skip path information generated according to an actual access path of a user;
and determining a target page which can be jumped to from the current page according to the jump path information.
Optionally, the method further includes:
obtaining a hit rate in a history preloading target page, wherein the hit rate is used for representing the actual access probability of the target page by a user after the target page is subjected to preloading operation;
and adjusting the access weight value of the target page according to the hit rate.
Optionally, the method further includes:
acquiring environment information of equipment loading the current page, wherein the environment information comprises equipment environment information and network environment information;
the determining the access weight value of each target page at least according to the browsing behavior information of the user comprises:
and determining an access weight value of each target page according to the browsing behavior information, the environment information and a weight value calculation model.
Optionally, the independent variable of the weight value calculation model is data of each dimension in the browsing behavior information and the environment information, and the dependent variable of the weight value calculation model is the access weight value;
the method further comprises the following steps:
and adjusting the coefficient of an independent variable in the weight value calculation model according to the acquired browsing behavior information and the acquired environment information.
Optionally, the browsing behavior information includes a data dimension of the number of times of access of the user to the target page;
determining an access weight value of each target page according to the browsing behavior information, the environment information and a weight value calculation model, wherein the determining comprises:
determining the page value of each target page according to the access times of each target page and the corresponding relation between the access times and the page value;
calculating to obtain an initial access weight value of the target page according to the page value of the target page, the page values of other target pages which are at the same level as the target page and the access weight value of a superior page of the target page;
and correcting the initial access weight value according to the browsing behavior information and data of other dimensions in the environment information and a weight correction model to obtain the access weight value.
Optionally, the calculating, according to the page value of the target page, the page values of other target pages at the same level as the target page, and the access weight value of a higher-level page of the target page, to obtain an initial access weight value includes:
calculating an initial access weight value W of the target page according to the following formulan：
Wherein PV is the page value of the target page, Wn-1∑ PV is the sum of the page values of the target pages at the same level as the target page.
Optionally, the preloading a target page whose access weight value meets a preset condition includes:
sequencing the target pages in the sequence of the access weight values from high to low to obtain a target page list;
and preloading the target pages with the preset number in the target page list.
In a second aspect, the present disclosure provides an apparatus for preloading a web page, the apparatus comprising:
the target page determining module is used for determining a target page which can be skipped to from a current page, wherein the target page comprises a page which can be skipped to from the current page indirectly;
the first acquisition module is used for acquiring browsing behavior information of a user;
the weight value determining module is used for determining an access weight value of each target page at least according to the browsing behavior information;
and the preloading module is used for preloading the target page with the access weight value meeting the preset condition.
Optionally, the target page determining module is configured to:
acquiring a skip operation element of the current page;
determining a next-level target page of the current page according to the jump operation element;
if each acquired first-level target page is finished, repeatedly executing the steps of acquiring the jump operation element of the target page and determining the next-level target page of the target page according to the jump operation element until the acquired target page does not have the page jump element;
the target pages which can jump to from the current page comprise the acquired target pages at each level.
Optionally, the target page determining module is configured to:
acquiring skip path information generated according to an actual access path of a user;
and determining a target page which can be jumped to from the current page according to the jump path information.
Optionally, the apparatus further comprises:
the second obtaining module is used for obtaining a hit rate in the target page preloaded in history, wherein the hit rate is used for representing the probability that the target page is actually visited by a user after the target page is preloaded;
and the weight value determining module is used for adjusting the access weight value of the target page according to the hit rate.
Optionally, the apparatus further comprises:
a third obtaining module, configured to obtain environment information of a device that loads the current page, where the environment information includes device environment information and network environment information;
and the weight value determining module is used for determining the access weight value of each target page according to the browsing behavior information, the environment information and a weight value calculating model.
Optionally, the independent variable of the weight value calculation model is data of each dimension in the browsing behavior information and the environment information, and the dependent variable of the weight value calculation model is the access weight value;
and the weight value determining module is used for adjusting the coefficient of an independent variable in the weight value calculation model according to the acquired browsing behavior information and the acquired environment information.
Optionally, the browsing behavior information includes a data dimension of the number of times of access of the user to the target page;
the weight value determining module is configured to:
determining the page value of each target page according to the access times of each target page and the corresponding relation between the access times and the page value;
calculating to obtain an initial access weight value of the target page according to the page value of the target page, the page values of other target pages which are at the same level as the target page and the access weight value of a superior page of the target page;
and correcting the initial access weight value according to the browsing behavior information and data of other dimensions in the environment information and a weight correction model to obtain the access weight value.
Optionally, the weight value determining module is configured to calculate an initial access weight value W of the target page according to the following formulan：
Wherein PV is the page value of the target page, Wn-1∑ PV is the sum of the page values of the target pages at the same level as the target page.
Optionally, the preloading a target page whose access weight value meets a preset condition includes:
sequencing the target pages in the sequence of the access weight values from high to low to obtain a target page list;
and preloading the target pages with the preset number in the target page list.
In a third aspect, the present disclosure provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of any of the methods for preloading web pages.
In a fourth aspect, the present disclosure provides an electronic device comprising:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to implement any of the steps of the method of preloading web pages.
The technical scheme can at least achieve the following technical effects:
and determining target pages which can jump from the current page, determining an access weight value of each target page at least according to the browsing behavior information, and preloading the target pages with the access weight values meeting preset conditions. Therefore, the page accessed by the user can be predicted more accurately, the webpage preloading efficiency is improved, and the time for the user to wait for page loading when browsing the webpage is reduced.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows.
Drawings
The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure without limiting the disclosure. In the drawings:
FIG. 1 is a flow diagram illustrating a method for preloading web pages, according to an exemplary embodiment.
FIG. 2.1 is a flow diagram illustrating another method of preloading web pages, according to an example embodiment.
Fig. 2.2 is a schematic diagram of a page path tree according to the method shown in fig. 2.1.
Fig. 2.3 is a schematic diagram of another page path tree shown according to the method of fig. 2.1.
FIG. 3 is a block diagram illustrating an apparatus for preloading web pages, according to an example embodiment.
FIG. 4 is a block diagram of an electronic device shown in accordance with an example embodiment.
FIG. 5 is a block diagram of another electronic device shown in accordance with an example embodiment.
Detailed Description
The following detailed description of specific embodiments of the present disclosure is provided in connection with the accompanying drawings. It should be understood that the detailed description and specific examples, while indicating the present disclosure, are given by way of illustration and explanation only, not limitation.
FIG. 1 is a flow diagram illustrating a method for preloading web pages, according to an exemplary embodiment. The method can be applied to a user terminal, such as a personal computer, a smart phone and the like, and can also be applied to a network server.
The method comprises the following steps:
and S21, determining a target page which can be skipped to from the current page, wherein the target page comprises pages which can be skipped to indirectly from the current page.
It is worth to be noted that, starting from the current page, the jump can be directly made to the first-level target page, and from the first-level target page, the jump can be directly made to the second-level target page, and so on.
According to actual use requirements, if a certain level of target page can be further jumped to a next level of target page, the next level of target page can be sequentially acquired until all target pages which can be jumped to are acquired. Or setting the jump stage number of the target page, and acquiring the target page corresponding to the jump stage number. For example, the skip level is set to be three levels, and then the fourth-level target page is not obtained any more after the third-level target page is obtained.
And S12, acquiring the browsing behavior information of the user.
The browsing behavior information of the user may include data of multiple dimensions, for example, a length of time that the user stays on the current page, operation behavior information (e.g., sliding up and down) of the user on the current page, a number of times that the user accesses the target page, user portrait information, and the like. In addition, browsing behavior information of a user during historical browsing of the webpage can be acquired.
It is to be noted that the steps S11 and S12 are expressed as a series of combinations of actions for the sake of simple description. In the specific implementation, the execution sequence can be exchanged. For example, the browsing behavior information of the user is collected in real time in the process that the user uses the browser; when the current page is opened, the step of determining the target page which can be skipped to from the current page is executed.
S13, determining the access weight value of each target page at least according to the browsing behavior information.
Specifically, a calculation function of the access weight value obtained by training browsing behavior data as history may be set. The calculation function takes each dimension data in the user browsing behavior information as an independent variable and takes an access weight value as a dependent variable. Specifically, the corresponding coefficient of each independent variable can be obtained by a linear regression algorithm.
In addition, after new user browsing behavior information is obtained each time, adaptive correction can be performed on each coefficient in the calculation function of the access weight value. For example, when the image factor of the operation behavior information in the browsing behavior information of the user becomes large, the coefficient corresponding to the dimension data may be correspondingly improved. In this way, the prediction accuracy of the preloaded pages can be improved.
And S14, preloading the target page with the access weight value meeting the preset condition.
In an optional embodiment, the preloading a target page with the access weight value satisfying a preset condition includes: sequencing the target pages in the sequence of the access weight values from high to low to obtain a target page list; and preloading the target pages with the previous preset number in the target page list.
For example, a total of 20 target pages are acquired. The 20 target pages are sorted from high to low according to the weight value, and the top 5 target pages are preloaded.
The technical scheme can at least achieve the following technical effects:
and determining target pages which can jump from the current page, determining an access weight value of each target page at least according to the browsing behavior information, and preloading the target pages with the access weight values meeting preset conditions. Therefore, the page accessed by the user can be predicted more accurately, the webpage preloading efficiency is improved, and the time for the user to wait for page loading when browsing the webpage is reduced.
FIG. 2.1 is a flow diagram illustrating a method of preloading web pages, according to an exemplary embodiment. The method can be applied to a user terminal, such as a personal computer, a smart phone and the like, and can also be applied to a network server.
The method comprises the following steps:
s21, acquiring the jump operation element of the page.
The jump operation element may be a hyperlink, an option button, or the like.
And S22, acquiring the jump path information generated according to the actual access path of the user.
The jump path information may be reported after other users browse the web pages.
And S23, determining a target page which can be jumped to from the current page according to the jump operation element of the page and the jump path information.
In specific implementation, the determining a target page that can be skipped to from a current page includes: acquiring a skip operation element of the current page; determining a next-level target page of the current page according to the jump operation element; if each acquired first-level target page is finished, repeatedly executing the steps of acquiring the jump operation element of the target page and determining the next-level target page of the target page according to the jump operation element until the acquired target page does not have the page jump element; the target pages which can jump to from the current page comprise the acquired target pages at each level.
That is to say, the next-level page of the current page corresponding to the skip operation element of the current page is taken as the first-level target page; when each level of target page is obtained, the following operations are executed for each target page of the current level: judging whether a target page has a jump operation element or not; if the target page has the jump operation element, taking a next-level page of the target page corresponding to the jump operation element as a next-level target page; and the target pages to which the current page can jump from the beginning comprise the target pages of each level.
In specific implementation, the page structure can be analyzed according to the entry page to obtain the elements of the jump operation, and then the path of the next-level page is obtained, all page paths in the whole business process are obtained through recursive analysis, and then the target page which is possible to jump to is searched according to the jump relation between the pages.
In order to visually represent the jump relationship, a page path tree diagram shown in fig. 2.2 may be referred to. Wherein Page1 represents the current Page; page2 and Page3 represent first-level target pages obtained from the jump operation elements of the current Page; page4, Page5, Page6 and Page7 represent that a second-level target Page is obtained according to the jump operation elements of the first-level Page; page8 represents the tertiary target Page derived from the jump operation elements of the secondary Page.
It should be noted that the jump operation element according to the page may not necessarily obtain all the possible jump target pages, and actually still include some paths that cannot be obtained through the page analysis.
In order to perfect the acquisition of the target path, a user reporting mechanism can be provided, and the page path tree can be continuously supplemented and perfected along with the reporting of the path accessed by the user. With the increase of the user access amount, the jump path of the whole webpage can be covered, and the acquisition of the target page is perfected.
For example, as shown in fig. 2.3, according to the access path reported by the user, a next-level target Page9 of the second-level target Page5 is newly added.
And S24, acquiring the browsing behavior information of the user.
The browsing behavior information of the user may include data of multiple dimensions, for example, a length of time that the user stays on the current page, operation behavior information (e.g., sliding up and down) of the user on the current page, a number of times that the user accesses the target page, user portrait information, and the like.
And S25, acquiring the environment information of the equipment loading the current page.
Wherein the environment information includes device environment information and network environment information. The device environment information may be information such as the size of the memory of the device and the occupation ratio of the memory. The network environment information may be bandwidth, network signal strength, etc. In addition, the network environment information may further include hierarchy information of the target page.
S26, determining the access weight value of each target page according to the browsing behavior information, the environment information and a weight value calculation model.
In an alternative embodiment of step S26, the weight value calculation model may be a weight value calculation function.
The calculation function of the access weight value is obtained by training browsing behavior information as history and the environment information. The calculation function of the weight value takes each dimension data in the user browsing behavior information and the environment information as independent variables and takes the access weight value as a dependent variable. Specifically, the corresponding coefficient of each independent variable can be obtained by a linear regression algorithm.
In addition, a weight value calculation model may be trained according to the browsing behavior information and the environment information. After new user browsing behavior information and environment information are obtained each time, adaptive correction can be performed on each coefficient in the calculation function of the access weight value. For example, when the image factor of the operation behavior information in the browsing behavior information of the user becomes large, the coefficient corresponding to the dimension data may be correspondingly improved. In this way, the prediction accuracy of the preloaded pages can be improved.
In another alternative implementation manner of step S26, an access weight value of the target page may be calculated according to the browsing behavior information, the environment information, and a trained weight value calculation model after training.
For example, the browsing behavior information includes a data dimension of the number of times that the user accesses the target page. Determining an access weight value of each target page according to the browsing behavior information, the environment information and a weight value calculation model, wherein the determining comprises:
determining the Page Value (PV) of each target Page according to the access times of the target pages and the corresponding relation between the access times and the Page value; calculating to obtain an initial access weight value of the target page according to the page value of the target page, the page values of other target pages which are at the same level as the target page and the access weight value of a superior page of the target page; and correcting the initial access weight value according to the browsing behavior information and data of other dimensions in the environment information and a weight correction model to obtain the access weight value.
Specifically, the calculating according to the page value of the target page, the page values of other target pages at the same level as the target page, and the access weight value of a higher-level page of the target page to obtain an initial access weight value includes calculating an initial access weight value W of the target page according to the following formulan：
Wherein PV is the page value of the target page, Wn-1∑ PV is the sum of the page values of the target pages at the same level as the target page.
It should be noted that the specific form of the weight value calculation model may be set according to actual use requirements. In practice, the steps of the two alternative embodiments described above are also combined. For example, an initial access weight value is obtained according to the number of times of page clicking, a coefficient of an independent variable of a correction function is corrected according to data of other dimensions, a corrected access weight value is obtained according to the corrected function, and an access weight value of a target page is further determined according to the initial weight value and the corrected access weight value.
S27, obtaining the history and preloading the hit rate in the target page.
The hit rate is used for representing the probability that the target page is actually accessed by a user after the preloading operation is performed on the target page.
The hit rate may be defined as a ratio of the number of actual accesses of the user to the number of times the target page is preloaded in a preset time period.
And S28, adjusting the access weight value of the target page according to the hit rate.
For example, in the first week, the target page is preloaded 10 times, the actual access times of the user is 5 times, and the hit rate is 0.5. In the second week, the target page is preloaded 10 times, the actual access times of the user are 2 times, and the hit rate is reduced to 0.2. It can be seen that the hit rate tends to decrease. In specific implementation, when it is determined that the hit rate is in a descending trend according to the hit rate of the history of the target page, the access weight value of the target page may be reduced. On the contrary, when the hit rate is determined to have an ascending trend according to the hit rate of the history of the target page, the access weight value of the target page can be increased.
And S29, preloading the target page with the adjusted access weight value meeting the preset condition.
In an optional implementation manner of step S29, the preloading the target page with the access weight value satisfying the preset condition includes: sequencing the target pages in the sequence of the access weight values from high to low to obtain a target page list; and preloading target pages with preset number in front of the target page list. For example, a total of 20 target pages are acquired. The 20 target pages are sorted from high to low according to the weight value, and the top 5 target pages are preloaded.
In another alternative embodiment of step S29, the target page with the access weight value exceeding the preset weight threshold may be preloaded.
The technical scheme can at least achieve the following technical effects:
the access weight value is obtained through the browsing behavior information and the environment information, and is adjusted through the historical hit rate, so that the accuracy of predicting the user access page in the subsequent steps can be further improved, the webpage preloading efficiency is improved, and the preloading pressure of the server is reduced.
FIG. 3 is a block diagram illustrating an apparatus for preloading web pages, according to an example embodiment. The device comprises:
a target page determining module 310, configured to determine a target page that can be skipped to from a current page, where the target page includes a page that can be skipped to indirectly from the current page;
a first obtaining module 320, configured to obtain browsing behavior information of a user;
a weight value determining module 330, configured to determine, according to at least the browsing behavior information, an access weight value of each target page;
the preloading module 340 is configured to preload a target page with the access weight value meeting a preset condition.
The technical scheme can at least achieve the following technical effects:
and determining target pages which can jump from the current page, determining an access weight value of each target page at least according to the browsing behavior information, and preloading the target pages with the access weight values meeting preset conditions. Therefore, the page accessed by the user can be predicted more accurately, the webpage preloading efficiency is improved, and the time for the user to wait for page loading when browsing the webpage is reduced.
Optionally, the target page determining module is configured to:
acquiring a skip operation element of the current page;
determining a next-level target page of the current page according to the jump operation element;
if each acquired first-level target page is finished, repeatedly executing the steps of acquiring the jump operation element of the target page and determining the next-level target page of the target page according to the jump operation element until the acquired target page does not have the page jump element;
the target pages which can jump to from the current page comprise the acquired target pages at each level.
Optionally, the target page determining module is configured to:
acquiring skip path information generated according to an actual access path of a user;
and determining a target page which can be jumped to from the current page according to the jump path information.
Optionally, the apparatus further comprises:
the second obtaining module is used for obtaining a hit rate in the target page preloaded in history, wherein the hit rate is used for representing the probability that the target page is actually visited by a user after the target page is preloaded;
and the weight value determining module is used for adjusting the access weight value of the target page according to the hit rate.
Optionally, the apparatus further comprises:
a third obtaining module, configured to obtain environment information of a device that loads the current page, where the environment information includes device environment information and network environment information;
and the weight value determining module is used for determining the access weight value of each target page according to the browsing behavior information, the environment information and a weight value calculating model.
Optionally, the independent variable of the weight value calculation model is data of each dimension in the browsing behavior information and the environment information, and the dependent variable of the weight value calculation model is the access weight value;
and the weight value determining module is used for adjusting the coefficient of an independent variable in the weight value calculation model according to the acquired browsing behavior information and the acquired environment information.
Optionally, the browsing behavior information includes a data dimension of the number of times of access of the user to the target page;
the weight value determining module is configured to:
determining the page value of each target page according to the access times of each target page and the corresponding relation between the access times and the page value;
calculating to obtain an initial access weight value of the target page according to the page value of the target page, the page values of other target pages which are at the same level as the target page and the access weight value of a superior page of the target page;
and correcting the initial access weight value according to the browsing behavior information and data of other dimensions in the environment information and a weight correction model to obtain the access weight value.
Optionally, the weight value determining module is configured to calculate an initial access weight value W of the target page according to the following formulan：
Wherein PV is the page value of the target page, Wn-1∑ PV is the sum of the page values of the target pages at the same level as the target page.
Optionally, the preloading a target page whose access weight value meets a preset condition includes:
sequencing the target pages in the sequence of the access weight values from high to low to obtain a target page list;
and preloading the target pages with the preset number in the target page list.
With regard to the apparatus in the above-described embodiment, the specific manner in which each module performs the operation has been described in detail in the embodiment related to the method, and will not be elaborated here.
The disclosed embodiments provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of any of the methods of preloading web pages.
An embodiment of the present disclosure provides an electronic device, including:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to implement any of the steps of the method of preloading web pages.
Fig. 4 is a block diagram illustrating an electronic device 400 according to an example embodiment. The electronic device may be provided as a terminal device, e.g. a personal computer, a smart phone, etc. As shown in fig. 4, the electronic device 400 may include: a processor 401 and a memory 402. The electronic device 400 may also include one or more of a multimedia component 403, an input/output (I/O) interface 404, and a communications component 405.
The processor 401 is configured to control the overall operation of the electronic device 400, so as to complete all or part of the steps in the method for preloading a webpage. The memory 402 is used to store various types of data to support operations at the electronic device 400, such as instructions for any application or method operating on the electronic device 400, as well as application-related data, such as access weight value determination model data, hit rates for historical target pages, jump operation element category information for web pages, and so forth. The Memory 402 may be implemented by any type of volatile or non-volatile Memory device or combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Read-Only Memory (PROM), Read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk or optical disk. The multimedia components 403 may include a screen and an audio component. Wherein the screen may be, for example, a touch screen and the audio component is used for outputting and/or inputting audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may further be stored in the memory 402 or transmitted through the communication component 405. The audio assembly also includes at least one speaker for outputting audio signals. The I/O interface 404 provides an interface between the processor 401 and other interface modules, such as a keyboard, mouse, buttons, etc. These buttons may be virtual buttons or physical buttons. The communication component 405 is used for wired or wireless communication between the electronic device 400 and other devices. Wireless Communication, such as Wi-Fi, bluetooth, Near Field Communication (NFC), 2G, 3G, or 4G, or a combination of one or more of them, so that the corresponding Communication component 405 may include: Wi-Fi module, bluetooth module, NFC module.
In an exemplary embodiment, the electronic Device 400 may be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components for performing the above-mentioned method of preloading web pages.
In another exemplary embodiment, a computer readable storage medium comprising program instructions which, when executed by a processor, implement the steps of the method of preloading web pages described above is also provided. For example, the computer readable storage medium may be the memory 402 comprising program instructions executable by the processor 401 of the electronic device 400 to perform the method of preloading web pages as described above.
Fig. 5 is a block diagram illustrating an electronic device 500 in accordance with an example embodiment. For example, the electronic device 500 may be provided as a server, e.g., a web server. Referring to fig. 5, the electronic device 500 comprises a processor 522, which may be one or more in number, and a memory 532 for storing computer programs executable by the processor 522. The computer programs stored in memory 532 may include one or more modules that each correspond to a set of instructions. Further, the processor 522 may be configured to execute the computer program to perform the method of preloading a web page described above.
Additionally, the electronic device 500 may also include a power component 526 and a communication component 550, the power component 526 may be configured to perform power management of the electronic device 500, and the communication component 550 may be configured to enable communication, e.g., wired or wireless communication, of the electronic device 500. In addition, the electronic device 500 may also include input/output (I/O) interfaces 558. The electronic device 500 may operate based on an operating system stored in the memory 532, such as Windows Server, Mac OSXTM, UnixTM, LinuxTM, and the like.
In another exemplary embodiment, a computer readable storage medium comprising program instructions which, when executed by a processor, implement the steps of the method of preloading web pages described above is also provided. For example, the computer readable storage medium may be the memory 532 described above including program instructions that are executable by the processor 522 of the electronic device 500 to perform the method for preloading web pages described above.
The preferred embodiments of the present disclosure are described in detail with reference to the accompanying drawings, however, the present disclosure is not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solution of the present disclosure within the technical idea of the present disclosure, and these simple modifications all belong to the protection scope of the present disclosure.
It should be noted that, in the foregoing embodiments, various features described in the above embodiments may be combined in any suitable manner, and in order to avoid unnecessary repetition, various combinations that are possible in the present disclosure are not described again.
In addition, any combination of various embodiments of the present disclosure may be made, and the same should be considered as the disclosure of the present disclosure, as long as it does not depart from the spirit of the present disclosure.
Claims (10)
1. A method of preloading a web page, the method comprising:
determining a target page which can be skipped to from a current page, wherein the target page comprises a page which can be skipped to indirectly from the current page;
acquiring browsing behavior information of a user, wherein the browsing behavior information comprises user portrait information or comprises the user portrait information and any one of the following three: dwell time, operation behavior, access times;
determining an access weight value of each target page at least according to the browsing behavior information;
preloading a target page with the access weight value meeting a preset condition;
the method further comprises the following steps:
acquiring environment information of equipment loading the current page, wherein the environment information comprises equipment environment information and network environment information;
the determining the access weight value of each target page at least according to the browsing behavior information of the user comprises:
determining an access weight value of each target page according to the browsing behavior information, the environment information and a weight value calculation model;
the weight value calculation model is obtained through training of historical browsing behavior information and the environment information.
2. The method of claim 1, wherein determining a target page that can be skipped from a current page comprises:
acquiring a skip operation element of the current page;
determining a next-level target page of the current page according to the jump operation element;
if each acquired first-level target page is finished, repeatedly executing the steps of acquiring the jump operation element of the target page and determining the next-level target page of the target page according to the jump operation element until the acquired target page does not have the page jump element;
the target pages which can jump to from the current page comprise the acquired target pages at each level.
3. The method of claim 2, wherein determining a target page that can be skipped from a current page comprises:
acquiring skip path information generated according to an actual access path of a user;
and determining a target page which can be jumped to from the current page according to the jump path information.
4. The method of claim 1, further comprising:
obtaining a hit rate of the target page which is preloaded historically, wherein the hit rate is used for representing the actual access probability of the target page by a user after the target page is preloaded;
and adjusting the access weight value of the target page according to the hit rate.
5. The method according to claim 1, wherein the independent variable of the weight value calculation model is data of each dimension in the browsing behavior information and the environment information, and the dependent variable of the weight value calculation model is the access weight value;
the method further comprises the following steps:
and adjusting the coefficient of an independent variable in the weight value calculation model according to the acquired browsing behavior information and the acquired environment information.
6. The method of claim 1, wherein the browsing behavior information comprises a data dimension of a number of accesses by a user to the target page;
determining an access weight value of each target page according to the browsing behavior information, the environment information and a weight value calculation model, wherein the determining comprises:
determining the page value of each target page according to the access times of each target page and the corresponding relation between the access times and the page value;
calculating to obtain an initial access weight value of the target page according to the page value of the target page, the page values of other target pages which are at the same level as the target page and the access weight value of a superior page of the target page;
and correcting the initial access weight value according to the browsing behavior information and data of other dimensions in the environment information and a weight correction model to obtain the access weight value.
7. The method according to any one of claims 1 to 4, wherein the preloading the target page with the access weight value satisfying a preset condition comprises:
sequencing the target pages in the sequence of the access weight values from high to low to obtain a target page list;
and preloading the target pages with the preset number in the target page list.
8. An apparatus for preloading a web page, the apparatus comprising:
the target page determining module is used for determining a target page which can be skipped to from a current page, wherein the target page comprises a page which can be skipped to from the current page indirectly;
the first acquisition module is used for acquiring browsing behavior information of a user, wherein the browsing behavior information comprises user portrait information or user portrait information and any one of the following three: dwell time, operation behavior, access times;
the weight value determining module is used for determining an access weight value of each target page at least according to the browsing behavior information;
the preloading module is used for preloading a target page with the access weight value meeting a preset condition;
the device further comprises:
a third obtaining module, configured to obtain environment information of a device that loads the current page, where the environment information includes device environment information and network environment information;
the weight value determining module is used for determining an access weight value of each target page according to the browsing behavior information, the environment information and a weight value calculating model;
the weight value calculation model is obtained through training of historical browsing behavior information and the environment information.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.
10. An electronic device, comprising:
a memory having a computer program stored thereon;
a processor for executing the computer program in the memory to carry out the steps of the method of any one of claims 1 to 7.
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| CN110134485B (en) * | 2019-05-22 | 2023-05-23 | 维沃移动通信有限公司 | Application content viewing method and mobile terminal |
| CN110262788B (en) * | 2019-06-24 | 2020-08-28 | 北京三快在线科技有限公司 | Page configuration information determination method and device, computer equipment and storage medium |
| CN112732434A (en) * | 2019-10-28 | 2021-04-30 | 华为终端有限公司 | Application management method and device |
| CN110891199B (en) * | 2019-11-14 | 2022-01-21 | 聚好看科技股份有限公司 | Page display method and display equipment |
| CN112861051A (en) * | 2019-11-28 | 2021-05-28 | 北京沃东天骏信息技术有限公司 | Page operation control method and device, electronic equipment and storage medium |
| CN114816557A (en) * | 2021-01-29 | 2022-07-29 | 北京字跳网络技术有限公司 | Data preloading method and device, electronic equipment and computer readable storage medium |
| CN113010831A (en) * | 2021-04-06 | 2021-06-22 | 金宝贝网络科技(苏州)有限公司 | Thermodynamic diagram optimization method, thermodynamic diagram optimization system and storage medium |
| CN113791837B (en) * | 2021-08-12 | 2023-08-11 | 百度在线网络技术（北京）有限公司 | Page processing method, device, equipment and storage medium |
| CN113806653B (en) * | 2021-09-22 | 2024-04-05 | 北京快阅读科技有限公司 | Page preloading method, device, computer equipment and storage medium |
| CN114339364A (en) * | 2021-12-21 | 2022-04-12 | 北京达佳互联信息技术有限公司 | Multimedia data processing method and device, electronic equipment and storage medium |
| CN114461897A (en) * | 2021-12-21 | 2022-05-10 | 北京达佳互联信息技术有限公司 | Information processing method, device, electronic equipment and storage medium |
| CN114518912B (en) * | 2022-02-21 | 2023-04-25 | 度小满科技(北京)有限公司 | Page loading method, device, equipment and readable storage medium |
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