CN113282847A - Website ranking optimization method and device and storage medium - Google Patents
Website ranking optimization method and device and storage medium Download PDFInfo
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- CN113282847A CN113282847A CN202110827965.8A CN202110827965A CN113282847A CN 113282847 A CN113282847 A CN 113282847A CN 202110827965 A CN202110827965 A CN 202110827965A CN 113282847 A CN113282847 A CN 113282847A
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- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
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Abstract
The application relates to the technical field of internet, and the embodiment of the application discloses a website ranking optimization method, a device and a storage medium, which are used for receiving a target request which is triggered by a user and used for improving the website ranking, wherein the target request carries a target website identification and a target expense package identification of a target website; acquiring first attribute information of the target website according to the target website identification; optimizing the first attribute information according to the target expense package identification pair to obtain second attribute information; optimizing the target website according to the second attribute information; monitoring the website ranking of the target website within a preset time period; and when the website ranking of the target website is in a preset range, pushing the ranking data of the target website to the user. By adopting the method and the device, the ranking of the website can be improved.
Description
Technical Field
The application relates to the technical field of internet, in particular to a website ranking optimization method, a website ranking optimization device and a storage medium.
Background
With the development of information technology, electronic devices (such as smart phones) have become a part of people's lives. People can acquire information needed to be known from the network, and further, the information can be searched through a search engine, and the information from different websites is integrated and displayed to users through the search engine for the users to browse.
In life, a search engine often displays search results in a sorted manner when displaying the search results to a user, and often, a website in front of the search engine also plays a good propaganda role, and the user often only browses a part of the search results in front of the search engine when browsing the search results, so that the problem of how to promote the website ranking needs to be solved urgently.
Disclosure of Invention
The embodiment of the application provides a website ranking optimization method, a website ranking optimization device and a storage medium, which can improve website ranking.
In a first aspect, an embodiment of the present application provides a website ranking optimization method, where the method includes:
receiving a target request for improving website ranking triggered by a user, wherein the target request carries a target website identifier and a target expense package identifier of a target website;
acquiring first attribute information of the target website according to the target website identification;
optimizing the first attribute information according to the target expense package identification to obtain second attribute information;
optimizing the target website according to the second attribute information;
monitoring the website ranking of the target website within a preset time period;
and when the website ranking of the target website is in a preset range, pushing the ranking data of the target website to the user.
In a second aspect, an embodiment of the present application provides a website ranking optimization apparatus, where the apparatus includes: a receiving unit, an obtaining unit, a first optimizing unit, a second optimizing unit, a monitoring unit and a pushing unit, wherein,
the receiving unit is used for receiving a target request which is triggered by a user and used for improving website ranking, wherein the target request carries a target website identifier of a target website and a target expense package identifier;
the acquisition unit is used for acquiring first attribute information of the target website according to the target website identification;
the first optimization unit is used for optimizing the first attribute information according to the target expense package identification to obtain second attribute information;
the second optimization unit is used for optimizing the target website according to the second attribute information;
the monitoring unit is used for monitoring the website ranking of the target website within a preset time period;
the pushing unit is used for pushing the ranking data of the target website to the user when the website ranking of the target website is within a preset range.
In a third aspect, an embodiment of the present application provides a server, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program enables a computer to perform some or all of the steps described in the first aspect of the embodiment of the present application.
In a fifth aspect, embodiments of the present application provide a computer program product, where the computer program product includes a non-transitory computer-readable storage medium storing a computer program, where the computer program is operable to cause a computer to perform some or all of the steps as described in the first aspect of the embodiments of the present application. The computer program product may be a software installation package.
The embodiment of the application has the following beneficial effects:
it can be seen that, in the website ranking optimization method, apparatus, and storage medium described in the embodiments of the present application, a target request triggered by a user for raising a website ranking is received, where the target request carries a target website identifier of a target website and a target fee package identifier, a first attribute information of the target website is obtained according to the target website identifier, the first attribute information is optimized according to the target fee package identifier to obtain a second attribute information, the target website is optimized according to the second attribute information, the website ranking of the target website is monitored within a preset time period, when the website ranking of the target website is within a preset range, ranking data of the target website is pushed to the user, on one hand, a website that the user needs to optimize can be optimized according to the fee package identifier selected by the user, on the other hand, an optimization effect can be monitored in real time, when the optimization effect meets expectations, the method and the device can be pushed to the user, so that the website optimization can be realized, and the user experience can be improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flowchart of a website ranking optimization method provided in an embodiment of the present application;
FIG. 2 is a schematic flow chart of another website ranking optimization method provided in the embodiments of the present application;
fig. 3 is a schematic structural diagram of another server provided in the embodiment of the present application;
fig. 4 is a block diagram illustrating functional units of a website ranking optimization apparatus according to an embodiment of the present disclosure.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The following describes embodiments of the present application in detail;
referring to fig. 1, fig. 1 is a schematic flowchart of a website ranking optimization method according to an embodiment of the present disclosure, and as shown in the figure, the website ranking optimization method includes:
101. receiving a target request for improving website ranking triggered by a user, wherein the target request carries a target website identifier and a target expense package identifier of a target website.
In the specific implementation, different fee package identifications correspond to different package contents, the speed and the degree of optimizing the website ranking of different package contents are different, and certainly, the higher the package fee is, the higher the speed and the degree of optimizing the website ranking are. The package content corresponding to the target expense identification can comprise at least one of the following contents: the search engine scope, the optimization degree scope, the optimization speed scope, the optimization website specific content scope, etc., which are not limited herein. The target website identification may include at least one of: website name, website link, IP address, etc., without limitation. Taking the scope of the search engine as an example, different search engines have different search algorithms and different heat ranks of the keywords, and in the embodiment of the application, different search engines can be optimized, so that the optimized website is more suitable for the search engine specified by the user. The target website may be composed of one or more web pages, for example, the target website may be a web portal, and for example, the target website may be a microblog, or the like.
Specifically, when a user browses a service platform, a plurality of fee packages can be displayed on the service platform, a fee package selected by the user is subjected to target fee package identification, the user can input a target website identification of a target website needing to promote website ranking, and then sends a target request, and a server can receive a target request triggered by the user and used for promoting website ranking, wherein the target request carries the target website identification of the target website and the target fee package identification.
102. And acquiring first attribute information of the target website according to the target website identification.
The attribute information corresponding to different attribute information is different, and the first attribute information may include at least one of the following: website weight, keywords, keyword density, keyword popularity, keyword location, internal and external links, etc., which are not limited herein. In specific implementation, a user may allow some rights of the server, and the server may obtain the first attribute information of the target website according to the target website identifier, when the user allows the rights of the server. In the concrete implementation, the website weight influences the website optimization progress to a certain extent, and the website weight means that a search engine gives a certain authority value to a website (including a webpage) and evaluates the authority of the website (including the webpage). The higher the weight of a website, the larger the share of the website in a search engine, and the better the ranking in the search engine.
103. And optimizing the first attribute information according to the target expense package identification to obtain second attribute information.
In the specific implementation, the optimized contents and the optimized degrees of different expense package identifiers are different, so that the first attribute information can be optimized according to the target expense package identifier, and the first attribute information can be specifically optimized based on the package contents corresponding to the target expense package identifier to obtain the second attribute information.
Optionally, in step 102, optimizing the first attribute information according to the target expense package identifier to obtain second attribute information, may include the following steps:
21. determining target attribute identification information corresponding to the target user package according to a mapping relation between a preset expense package identification and attribute identification information;
22. screening the first attribute information according to the target attribute identification information to obtain third attribute information;
23. determining a target optimization factor corresponding to the target expense package identification;
24. and optimizing the third attribute information according to the target optimization factor to obtain the second attribute information.
In a specific implementation, the server may pre-store a mapping relationship between a preset expense package identifier and attribute identifier information, where the attribute identifier information may include at least one of the following: website weight, keywords, web page layout, internal and external links, etc., without limitation.
Specifically, the server may determine target attribute identification information corresponding to a target user package according to a mapping relationship between preset cost package identifications and attribute identification information, and then screen the first attribute information according to the target attribute identification information to obtain third attribute information, that is, only optimization content covered in a package is optimized, and then determine a target optimization factor corresponding to the target cost package identifications, where the target optimization factor may be preset or may be determined by website weights of a target website, that is, a preset optimization factor is adjusted by the website weights to obtain the target optimization factor, specifically, the larger the website weight is, the larger the optimized optimization factor is, the smaller the website weight is, and the smaller the optimized optimization factor is. The objective optimization factor is used for expressing the optimization degree or the optimization speed of the expense package identifier, and the third attribute information may be optimized according to the objective optimization factor to obtain the second attribute information, in a specific implementation, the optimization factor may be related to the optimization degree of the third attribute information, and the optimization content is increased or the optimization degree is increased as the optimization factor is larger, for example, the optimization keyword may be increased, the keyword may be decreased, the keyword may be replaced, the keyword density may be increased, the keyword density may be decreased, and the like, which is not limited herein, and for example, the optimization of the inner and outer chains may be increased or decreased, and the length of the inner and outer chains may be decreased or increased, and the like, which is not limited herein.
Further, optionally, when the third attribute information includes a first keyword and a first keyword density corresponding to the first keyword, the step 24 of optimizing the third attribute information according to the target optimization factor to obtain the second attribute information may include the following steps:
241. determining a reference heat value for the first keyword;
242. the reference heat value is improved according to the target optimization factor to obtain a target heat value;
243. optimizing the first keyword according to the target heat value to obtain a second keyword, wherein the keyword density of the second keyword is equal to the density of the first keyword;
244. predicting the contribution strength of the second keyword to obtain reference contribution strength;
245. determining an adjustment factor of the density of the first keyword according to the reference contribution degree to obtain a target adjustment factor;
246. adjusting the keyword density of the second keyword according to the target adjustment factor to obtain a keyword density adjustment parameter;
247. and taking the second keyword and the keyword density adjusting parameter as the second attribute information.
In a specific implementation, the third attribute information may include the first keyword and a density of the first keyword corresponding to the first keyword. Because the corresponding heat (or flow) of different keywords is different, the server can determine the reference heat value of the first keyword, in specific implementation, the optimization factor can be a specific value, and then the reference heat value is increased according to the target optimization factor to obtain the target heat value, wherein a specific calculation formula is as follows:
target heat value = reference heat value (1 + target optimization factor)
Furthermore, the server may optimize the first keyword according to the target popularity value to obtain the second keyword, for example, the second keyword may be replaced with a synonym or a synonym having a popularity value greater than the current popularity value, and the keyword density of the second keyword is equal to the keyword density of the first keyword when the second keyword is completely replaced with the first keyword.
In a specific implementation, the server may further predict the contribution of the second keyword through a prediction model to obtain a reference contribution, where the prediction model may include at least one of the following: convolutional neural network models, fully-connected neural network models, recurrent neural network models, and so forth, without limitation, the predictive model may be, for example, a click-through rate (CTR) predictive model. In the concrete implementation, the target websites of the first keywords and the target websites of the second keywords can be respectively subjected to ranking prediction through a prediction model, the ranking difference between the two is determined, the contribution degree is determined according to the difference between the two, of course, the higher the ranking is, the greater the contribution degree is, or the target websites of the first keywords and the target websites of the second keywords can be respectively subjected to ranking prediction through the prediction model, the difference of the quantity of search results between the two is determined, and the contribution degree is determined according to the difference between the two. If the contribution is too large, the ranking of the target website may exceed the upper limit value of the preset range, and if the contribution is too small, the ranking of the target website may be lower than the lower limit value of the preset range.
Therefore, the server may determine an adjustment factor of the first keyword density according to the reference contribution strength to obtain a target adjustment factor, where the adjustment factors corresponding to different reference contribution strengths are different, specifically, the server may obtain a reference keyword density adjustment range of the first keyword density, where the reference keyword density adjustment range includes a lower limit adjustment value and an upper limit adjustment value, determine a mean value of the lower limit adjustment value and the upper limit adjustment value, determine a reference adjustment coefficient corresponding to the reference contribution strength according to a preset mapping relationship between the contribution strength and the adjustment coefficient, where the reference adjustment coefficient may be-0.5 to 0.5, and determine the target adjustment factor according to the reference adjustment coefficient and the mean value, where:
target adjustment factor = (1 + reference adjustment coefficient) × mean value
Further, the target adjustment factor may be dynamically changed, the server may adjust the keyword density of the second keyword according to the target adjustment factor to obtain a keyword density adjustment parameter, the keyword density adjustment parameter may be a dynamic adjustment parameter, for example, the first keyword may be partially or completely replaced by the dynamic adjustment parameter, for example, the position of the first keyword or the second keyword may be dynamically changed by the dynamic adjustment parameter, and then the second keyword and the keyword density adjustment parameter are used as the second attribute information.
Of course, the optimization of the internal and external links and the web page layout may also refer to the above manner, or the number or length of the internal and external links may be changed, or the web page layout may be modified, so as to achieve the goal of optimizing the website.
104. And optimizing the target website according to the second attribute information.
Specifically, the second attribute information may be used to replace corresponding information in the target website, so as to achieve the purpose of optimizing the target website.
105. And monitoring the website ranking of the target website in a preset time period.
Wherein, the preset time period can be set by the user or the default of the system. Of course, the fee package may also include a preset time period, for example, the preset time period may be 24 hours. In a specific implementation, the website ranking of the target website may be monitored through a prediction model or special monitoring software.
106. And when the website ranking of the target website is in a preset range, pushing the ranking data of the target website to the user.
Wherein, the preset range can be set by the user or the default of the system. The server may push ranking data of the target website to the user when the website ranking of the target website is within a preset range, where the change data may include the ranking of the target website or a ranking change curve of the target website. The present application is equivalent to Search Engine Optimization (SEO), and to a certain extent, the SEO optimization function is realized.
Optionally, the first attribute information includes a website weight of the target website, and in step 102, after the first attribute information of the target website is obtained according to the target website identifier; and 103, before optimizing the first attribute information according to the target expense package identifier and obtaining second attribute information, the method further comprises the following steps:
a1, when the website weight is in a preset weight range, executing the step of optimizing the first attribute information according to the target expense package identification to obtain second attribute information;
a2, when the weight of the website is lower than the lower limit value of a preset weight range, acquiring a reference time limit corresponding to the target expense package identification;
a3, determining a target difference value between the lower limit value and the website weight;
a4, determining the expected delay time consumption corresponding to the target difference value;
a5, determining a prediction reference time limit according to the reference time limit and the predicted delay time consumption;
a6, pushing the prediction reference time limit to the user;
a7, when receiving the confirmation message confirmed by the user, executing the step of optimizing the first attribute information according to the target expense package identification to obtain second attribute information.
Wherein, the preset weight range can be preset or default by the system. In a specific implementation, when the website weight is within the preset weight range, step 103 may be executed. Certainly, when the website weight is lower than the lower limit value of the preset weight range, the server may obtain a reference time limit corresponding to the target expense package identifier, and may further determine a target difference value between the lower limit value and the website weight, a mapping relationship between the difference value and the delay time consumption may be stored in the server in advance, and further, a predicted delay time consumption corresponding to the target difference value may be determined according to the mapping relationship, and then, a predicted reference time limit may be determined according to the reference time limit and the predicted delay time consumption, that is, the predicted reference time limit = the reference time limit + the predicted delay time consumption, and the predicted reference time limit may be pushed to the user, when a confirmation message confirmed by the user is received, step 103 is executed, that is, when different website weights are received, the difficulty in optimizing the ranking is different, and when the website weight is lower, the user may be reminded to optimize the time consumption possibly required for the ranking to a certain extent, the user experience can be improved.
Optionally, the method may further include the following steps:
b1, acquiring a target ranking change curve of the website ranking of the target website, wherein the horizontal axis of the target ranking change curve is time, and the vertical axis of the target ranking change curve is a ranking sequence number;
b2, sampling the target ranking change curve to obtain a plurality of sampling points;
b3, fitting the plurality of sampling points to obtain a first fitted straight line;
b4, acquiring a reference fitting straight line of the target expense package mark;
b5, determining the variation difference situation between the first fitted straight line and the reference fitted straight line;
and B6, adjusting the target optimization factor according to the change difference condition to obtain a first optimization factor.
In a specific implementation, the server may obtain a target ranking change curve of the website ranking of the target website, where a horizontal axis of the target ranking change curve is time and a vertical axis of the target ranking change curve is ranking number, and may sample the target ranking change curve to obtain a plurality of sampling points, for example, the target ranking change curve of any time period within the time period of optimization of the target website may be sampled, and the sampling mode may be random sampling or uniform sampling.
Further, the server can fit a plurality of sampling points to obtain a first fitting straight line, different expense package identifications and a reference curve for optimizing the ranking, can further obtain a reference fitting straight line of the target expense package identification, can also determine the change difference condition between the first fitting straight line and the reference fitting straight line, the change difference condition can be reflected by the slope difference between the first fitting straight line and the reference fitting straight line, then the target optimization factor is adjusted according to the change difference condition to obtain a first optimization factor, specifically, the target optimization factor corresponding to the target slope difference between the first fitting straight line and the reference fitting straight line is determined according to the mapping relation between the preset slope difference and the optimization factor, the target optimization factor is optimized according to the optimization factor to obtain the first optimization factor, which is equivalent to optimizing the attribute information of the target website based on the change condition of the ranking, making its ranking change as expected. And then, optimizing the second attribute information by the first optimization factor, optimizing the target website by the optimized attribute information, and further monitoring the target website on the basis. Therefore, the ranking optimization depth can meet the expectation, the optimization effect depth can meet the cost package, and the service quality can be guaranteed.
It can be seen that, the website ranking optimization method described in the embodiments of the present application receives a target request triggered by a user for promoting website ranking, where the target request carries a target website identifier of a target website and a target fee package identifier, obtains first attribute information of the target website according to the target website identifier, optimizes the first attribute information according to the target fee package identifier to obtain second attribute information, optimizes the target website according to the second attribute information, monitors the website ranking of the target website within a preset time period, and pushes ranking data of the target website to the user when the website ranking of the target website is within a preset range, on one hand, the website which the user needs to optimize can be optimized according to the fee package identifier selected by the user, on the other hand, the optimization effect can be monitored in real time, and when the optimization effect meets expectations, the method and the device can be pushed to the user, so that the website optimization can be realized, and the user experience can be improved.
Referring to fig. 2, fig. 2 is a schematic flowchart of a website ranking optimization method according to an embodiment of the present application, where as shown in the figure, the website ranking optimization method includes:
201. receiving a target request for improving website ranking triggered by a user, wherein the target request carries a target website identifier and a target expense package identifier of a target website.
202. And acquiring first attribute information of the target website according to the target website identification.
203. And when the website weight is in a preset weight range, optimizing the first attribute information according to the target expense package identification to obtain second attribute information.
204. And optimizing the target website according to the second attribute information.
205. And monitoring the website ranking of the target website in a preset time period.
206. And when the website ranking of the target website is in a preset range, pushing the ranking data of the target website to the user.
207. And when the weight of the website is lower than the lower limit value of a preset weight range, acquiring a reference time limit corresponding to the target expense package identification.
208. Determining a target difference between the lower limit value and the website weight.
209. Determining an expected delay time corresponding to the target difference.
210. And determining a predicted reference time limit according to the reference time limit and the predicted time consumption of the time delay.
211. And pushing the predicted reference time limit to the user.
212. And when receiving a confirmation message confirmed by the user, executing the step of optimizing the first attribute information according to the target expense package identification to obtain second attribute information.
The detailed description of the steps 201 to 212 may refer to the corresponding steps of the website ranking optimization method described in fig. 1, and will not be repeated herein.
The website ranking optimization method described in the embodiment of the application can optimize websites, which need to be optimized, of a user according to a cost package identifier selected by the user, can monitor an optimization effect in real time, and when the optimization effect is expected, the optimization effect is pushed to the user, and different website weights are considered, so that the difficulty or time consumption for optimizing the ranking is different, when the website weight is lower, the user can be reminded of the time consumption possibly needed for optimizing the ranking, and the website optimization is realized and the user experience is deeply improved to a certain extent.
Referring to fig. 3, in accordance with the above-mentioned embodiment, fig. 3 is a schematic structural diagram of a server according to an embodiment of the present application, and as shown in the drawing, the server includes a processor, a memory, a communication interface, and one or more programs, the one or more programs are stored in the memory and configured to be executed by the processor, and in an embodiment of the present application, the programs include instructions for performing the following steps:
receiving a target request for improving website ranking triggered by a user, wherein the target request carries a target website identifier and a target expense package identifier of a target website;
acquiring first attribute information of the target website according to the target website identification;
optimizing the first attribute information according to the target expense package identification to obtain second attribute information;
optimizing the target website according to the second attribute information;
monitoring the website ranking of the target website within a preset time period;
and when the website ranking of the target website is in a preset range, pushing the ranking data of the target website to the user.
Optionally, in the aspect that the first attribute information is optimized according to the target expense package identifier to obtain the second attribute information, the program includes instructions for executing the following steps:
determining target attribute identification information corresponding to the target user package according to a mapping relation between a preset expense package identification and attribute identification information;
screening the first attribute information according to the target attribute identification information to obtain third attribute information;
determining a target optimization factor corresponding to the target expense package identification;
and optimizing the third attribute information according to the target optimization factor to obtain the second attribute information.
Further, optionally, when the third attribute information includes a first keyword and a first keyword density corresponding to the first keyword, in the aspect of optimizing the third attribute information according to the target optimization factor to obtain the second attribute information, the program includes instructions for executing the following steps:
determining a reference heat value for the first keyword;
the reference heat value is improved according to the target optimization factor to obtain a target heat value;
optimizing the first keyword according to the target heat value to obtain a second keyword, wherein the keyword density of the second keyword is equal to the density of the first keyword;
predicting the contribution strength of the second keyword to obtain reference contribution strength;
determining an adjustment factor of the density of the first keyword according to the reference contribution degree to obtain a target adjustment factor;
adjusting the keyword density of the second keyword according to the target adjustment factor to obtain a keyword density adjustment parameter;
and taking the second keyword and the keyword density adjusting parameter as the second attribute information.
Optionally, the program further includes instructions for performing the following steps:
acquiring a target ranking change curve of the website ranking of the target website, wherein the horizontal axis of the target ranking change curve is time, and the vertical axis of the target ranking change curve is a ranking sequence number;
sampling the target ranking change curve to obtain a plurality of sampling points;
fitting the plurality of sampling points to obtain a first fitted straight line;
acquiring a reference fitting straight line of the target expense package mark;
determining a variation difference condition between the first fitted straight line and the reference fitted straight line;
and adjusting the target optimization factor according to the change difference condition to obtain a first optimization factor.
Optionally, the first attribute information includes a website weight of the target website, and after the first attribute information of the target website is obtained according to the target website identifier; before optimizing the first attribute information according to the target expense package identifier and obtaining second attribute information, the program further includes instructions for executing the following steps:
when the website weight is in a preset weight range, executing the step of optimizing the first attribute information according to the target expense package identification to obtain second attribute information;
when the website weight is lower than the lower limit value of a preset weight range, acquiring a reference time limit corresponding to the target expense package identification;
determining a target difference between the lower limit value and the website weight;
determining an expected delay time consumption corresponding to the target difference value;
determining a predicted reference time limit according to the reference time limit and the predicted time consumption of the time delay;
pushing the predicted reference time limit to the user;
and when receiving a confirmation message confirmed by the user, executing the step of optimizing the first attribute information according to the target expense package identification to obtain second attribute information.
It can be seen that, the server described in the embodiment of the present application receives a target request triggered by a user for raising a website ranking, where the target request carries a target website identifier of a target website and a target fee package identifier, obtains first attribute information of the target website according to the target website identifier, optimizes the first attribute information according to the target fee package identifier to obtain second attribute information, optimizes the target website according to the second attribute information, monitors the website ranking of the target website within a preset time period, and pushes ranking data of the target website to the user when the website ranking of the target website is within a preset range, on one hand, a website which the user needs to optimize can be optimized according to the fee package identifier selected by the user, on the other hand, the optimization effect can be monitored in real time, and when the optimization effect meets expectations, the optimization effect is pushed to the user, therefore, the website optimization can be realized, and the user experience can be improved.
Fig. 4 is a block diagram of functional units of the website ranking optimization apparatus 400 according to the embodiment of the present application. The website ranking optimizing device 400, the device 400 comprises: a receiving unit 401, an obtaining unit 402, a first optimizing unit 403, a second optimizing unit 404, a monitoring unit 405 and a pushing unit 406, wherein,
the receiving unit 401 is configured to receive a target request triggered by a user and used for promoting a website ranking, where the target request carries a target website identifier of a target website and a target fee package identifier;
the obtaining unit 402 is configured to obtain first attribute information of the target website according to the target website identifier;
the first optimizing unit 403 is configured to optimize the first attribute information according to the target expense package identifier to obtain second attribute information;
the second optimizing unit 404 is configured to optimize the target website according to the second attribute information;
the monitoring unit 405 is configured to monitor the website ranking of the target website within a preset time period;
the pushing unit 406 is configured to push the ranking data of the target website to the user when the website ranking of the target website is within a preset range.
Optionally, in the aspect that the first attribute information is optimized according to the target expense package identifier to obtain second attribute information, the first optimizing unit 403 is specifically configured to:
determining target attribute identification information corresponding to the target user package according to a mapping relation between a preset expense package identification and attribute identification information;
screening the first attribute information according to the target attribute identification information to obtain third attribute information;
determining a target optimization factor corresponding to the target expense package identification;
and optimizing the third attribute information according to the target optimization factor to obtain the second attribute information.
Further, optionally, when the third attribute information includes a first keyword and a first keyword density corresponding to the first keyword, in terms of optimizing the third attribute information according to the target optimization factor to obtain the second attribute information, the first optimizing unit 403 is specifically configured to:
determining a reference heat value for the first keyword;
the reference heat value is improved according to the target optimization factor to obtain a target heat value;
optimizing the first keyword according to the target heat value to obtain a second keyword, wherein the keyword density of the second keyword is equal to the density of the first keyword;
predicting the contribution strength of the second keyword to obtain reference contribution strength;
determining an adjustment factor of the density of the first keyword according to the reference contribution degree to obtain a target adjustment factor;
adjusting the keyword density of the second keyword according to the target adjustment factor to obtain a keyword density adjustment parameter;
and taking the second keyword and the keyword density adjusting parameter as the second attribute information.
Optionally, the apparatus 400 is further specifically configured to:
acquiring a target ranking change curve of the website ranking of the target website, wherein the horizontal axis of the target ranking change curve is time, and the vertical axis of the target ranking change curve is a ranking sequence number;
sampling the target ranking change curve to obtain a plurality of sampling points;
fitting the plurality of sampling points to obtain a first fitted straight line;
acquiring a reference fitting straight line of the target expense package mark;
determining a variation difference condition between the first fitted straight line and the reference fitted straight line;
and adjusting the target optimization factor according to the change difference condition to obtain a first optimization factor.
Optionally, the first attribute information includes a website weight of the target website, and after the first attribute information of the target website is obtained according to the target website identifier; before optimizing the first attribute information according to the target expense package identifier to obtain second attribute information, the apparatus 400 is further specifically configured to:
when the website weight is in a preset weight range, executing the step of optimizing the first attribute information according to the target expense package identification to obtain second attribute information;
when the website weight is lower than the lower limit value of a preset weight range, acquiring a reference time limit corresponding to the target expense package identification;
determining a target difference between the lower limit value and the website weight;
determining an expected delay time consumption corresponding to the target difference value;
determining a predicted reference time limit according to the reference time limit and the predicted time consumption of the time delay;
pushing the predicted reference time limit to the user;
and when receiving a confirmation message confirmed by the user, executing the step of optimizing the first attribute information according to the target expense package identification to obtain second attribute information.
It can be seen that, the website ranking optimization device described in the embodiment of the present application receives a target request triggered by a user for promoting a website ranking, where the target request carries a target website identifier of a target website and a target fee package identifier, obtains first attribute information of the target website according to the target website identifier, optimizes the first attribute information according to the target fee package identifier to obtain second attribute information, optimizes the target website according to the second attribute information, monitors the website ranking of the target website within a preset time period, and pushes ranking data of the target website to the user when the website ranking of the target website is within a preset range, on one hand, a website which the user needs to optimize can be optimized according to the fee package identifier selected by the user, on the other hand, the optimization effect can be monitored in real time, and when the optimization effect meets expectations, the method and the device can be pushed to the user, so that the website optimization can be realized, and the user experience can be improved.
It can be understood that the functions of each program module of the website ranking optimization apparatus in this embodiment may be specifically implemented according to the method in the foregoing method embodiment, and the specific implementation process may refer to the related description of the foregoing method embodiment, which is not described herein again.
Embodiments of the present application also provide a computer storage medium, wherein the computer storage medium stores a computer program for electronic data exchange, and the computer program enables a computer to execute part or all of the steps of any one of the methods as described in the above method embodiments.
Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as described in the above method embodiments. The computer program product may be a software installation package.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of some interfaces, devices or units, and may be an electric or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (10)
1. A website ranking optimization method is characterized by comprising the following steps:
receiving a target request for improving website ranking triggered by a user, wherein the target request carries a target website identifier and a target expense package identifier of a target website;
acquiring first attribute information of the target website according to the target website identification;
optimizing the first attribute information according to the target expense package identification to obtain second attribute information;
optimizing the target website according to the second attribute information;
monitoring the website ranking of the target website within a preset time period;
and when the website ranking of the target website is in a preset range, pushing the ranking data of the target website to the user.
2. The method of claim 1, wherein optimizing the first attribute information based on the target cost package identification to obtain second attribute information comprises:
determining target attribute identification information corresponding to the target user package according to a mapping relation between a preset expense package identification and attribute identification information;
screening the first attribute information according to the target attribute identification information to obtain third attribute information;
determining a target optimization factor corresponding to the target expense package identification;
and optimizing the third attribute information according to the target optimization factor to obtain the second attribute information.
3. The method according to claim 2, wherein when the third attribute information includes a first keyword and a first keyword density corresponding to the first keyword, the optimizing the third attribute information according to the target optimization factor to obtain the second attribute information includes:
determining a reference heat value for the first keyword;
the reference heat value is improved according to the target optimization factor to obtain a target heat value;
optimizing the first keyword according to the target heat value to obtain a second keyword, wherein the keyword density of the second keyword is equal to the density of the first keyword;
predicting the contribution strength of the second keyword to obtain reference contribution strength;
determining an adjustment factor of the density of the first keyword according to the reference contribution degree to obtain a target adjustment factor;
adjusting the keyword density of the second keyword according to the target adjustment factor to obtain a keyword density adjustment parameter;
and taking the second keyword and the keyword density adjusting parameter as the second attribute information.
4. The method of claim 2, further comprising:
acquiring a target ranking change curve of the website ranking of the target website, wherein the horizontal axis of the target ranking change curve is time, and the vertical axis of the target ranking change curve is a ranking sequence number;
sampling the target ranking change curve to obtain a plurality of sampling points;
fitting the plurality of sampling points to obtain a first fitted straight line;
acquiring a reference fitting straight line of the target expense package mark;
determining a variation difference condition between the first fitted straight line and the reference fitted straight line;
and adjusting the target optimization factor according to the change difference condition to obtain a first optimization factor.
5. The method according to any one of claims 1-4, wherein the first attribute information comprises a website weight of the target website, after the first attribute information of the target website is obtained according to the target website identification; before optimizing the first attribute information according to the target expense package identifier and obtaining second attribute information, the method further comprises:
when the website weight is in a preset weight range, executing the step of optimizing the first attribute information according to the target expense package identification to obtain second attribute information;
when the website weight is lower than the lower limit value of a preset weight range, acquiring a reference time limit corresponding to the target expense package identification;
determining a target difference between the lower limit value and the website weight;
determining an expected delay time consumption corresponding to the target difference value;
determining a predicted reference time limit according to the reference time limit and the predicted time consumption of the time delay;
pushing the predicted reference time limit to the user;
and when receiving a confirmation message confirmed by the user, executing the step of optimizing the first attribute information according to the target expense package identification to obtain second attribute information.
6. An apparatus for optimizing website ranking, the apparatus comprising: a receiving unit, an obtaining unit, a first optimizing unit, a second optimizing unit, a monitoring unit and a pushing unit, wherein,
the receiving unit is used for receiving a target request which is triggered by a user and used for improving website ranking, wherein the target request carries a target website identifier of a target website and a target expense package identifier;
the acquisition unit is used for acquiring first attribute information of the target website according to the target website identification;
the first optimization unit is used for optimizing the first attribute information according to the target expense package identification to obtain second attribute information;
the second optimization unit is used for optimizing the target website according to the second attribute information;
the monitoring unit is used for monitoring the website ranking of the target website within a preset time period;
the pushing unit is used for pushing the ranking data of the target website to the user when the website ranking of the target website is within a preset range.
7. The apparatus according to claim 6, wherein, in the aspect that the first attribute information is optimized according to the target expense package identifier to obtain second attribute information, the first optimizing unit is specifically configured to:
determining target attribute identification information corresponding to the target user package according to a mapping relation between a preset expense package identification and attribute identification information;
screening the first attribute information according to the target attribute identification information to obtain third attribute information;
determining a target optimization factor corresponding to the target expense package identification;
and optimizing the third attribute information according to the target optimization factor to obtain the second attribute information.
8. The apparatus according to claim 7, wherein when the third attribute information includes a first keyword and a first keyword density corresponding to the first keyword, in terms of optimizing the third attribute information according to the target optimization factor to obtain the second attribute information, the first optimizing unit is specifically configured to:
determining a reference heat value for the first keyword;
the reference heat value is improved according to the target optimization factor to obtain a target heat value;
optimizing the first keyword according to the target heat value to obtain a second keyword, wherein the keyword density of the second keyword is equal to the density of the first keyword;
predicting the contribution strength of the second keyword to obtain reference contribution strength;
determining an adjustment factor of the density of the first keyword according to the reference contribution degree to obtain a target adjustment factor;
adjusting the keyword density of the second keyword according to the target adjustment factor to obtain a keyword density adjustment parameter;
and taking the second keyword and the keyword density adjusting parameter as the second attribute information.
9. A server, comprising a processor, a memory for storing one or more programs and configured to be executed by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-5.
10. A computer-readable storage medium, characterized in that a computer program for electronic data exchange is stored, wherein the computer program causes a computer to perform the method according to any one of claims 1-5.
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