Network optimization method and system based on SiteMap analysis

Abstract

The present invention discloses a network optimization method and system based on SiteMap map analysis, which relates to the technical field of network optimization, including collecting the SiteMap file and user behavior data of a website, constructing the topological structure of the website according to the SiteMap file and calculating the initial index of page importance based on the topological structure of the website; constructing a user access path model according to the user behavior data and calculating the user importance index; comprehensively evaluating the importance of the website based on the initial index of page importance and the user importance index to obtain the page importance index; identifying the website according to the page importance index, obtaining the website classification result and formulating a network optimization strategy; continuously monitoring the SiteMap file and user behavior data of the website and establishing a feedback mechanism to optimize the topological structure and user access path model of the website. The present invention improves the efficiency of page optimization, website quality and user experience by linking the topological structure of the website and the user behavior data.

Description

Technical Field

[0001] The present invention relates to the technical field of network optimization, and in particular to a network optimization method and system based on SiteMap map analysis. Background Art

[0002] In today's Internet era, websites have become an important window for enterprises and individuals to display information, disseminate content and provide services. With the continuous increase in the scale and complexity of websites, effective website architecture optimization and search engine optimization (SEO) have become key requirements for improving website accessibility and user experience. Traditional website optimization methods mainly rely on manual analysis and empirical judgment. Experts browse the website structure and content and give optimization suggestions based on the principles of search engine algorithms. On the other hand, some optimization methods based on website data analysis have also emerged. Among them, the more common ones are based on the website topology and page link relationship. This type of method parses the website's SiteMap XML file to construct the website's hierarchical structure and link model, and then uses the PageRank algorithm to evaluate the importance of the page and optimize the link situation of important pages. However, this optimization method that only considers the static link structure also has certain defects, and it is difficult to reflect the real user behavior pattern and the impact of content quality.

[0003] The common solutions currently available have many shortcomings, including: Search engine optimization (SEO) techniques mainly improve website rankings in search engines by optimizing website content and link structure factors, thereby attracting more traffic, but SEO techniques often ignore user experience, making it difficult to fully evaluate the optimization effect of a website; website analysis tools can collect and analyze user behavior data, such as page views and dwell time, to provide data support for website optimization, but these tools only provide data and cannot directly optimize website structure; some research institutions have proposed website evaluation methods based on user experience, but these methods have relatively subjective evaluation indicators and lack objective data support. Summary of the invention

[0004] In view of the fact that the existing technology mainly relies on manual analysis and experience judgment when optimizing website content, and that the optimization method of static link structure is difficult to reflect the impact of real user behavior patterns and content quality, and it is difficult to comprehensively evaluate the optimization effect of the website, the present invention is proposed.

[0005] Therefore, the problem to be solved by the present invention is how to provide a network optimization method based on SiteMap map analysis, a method for more comprehensively and accurately evaluating the actual importance of web pages based on website link topology and real user behavior data, and improving the automation and intelligence level of the optimization process.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0007] In the first aspect, an embodiment of the present invention provides a network optimization method based on SiteMap map analysis, which includes collecting the SiteMap file and user behavior data of the website, constructing the topology structure of the website according to the SiteMap file and calculating the initial page importance index based on the topology structure of the website; constructing a user access path model according to the user behavior data and calculating the user importance index; comprehensively evaluating the importance of the website based on the initial page importance index and the user importance index to obtain the page importance index; identifying the website according to the page importance index, obtaining the website classification result and formulating the network optimization strategy; continuously monitoring the SiteMap file and user behavior data of the website and establishing a feedback mechanism to optimize the topology structure and user access path model of the website.

[0008] As a preferred solution of the network optimization method based on SiteMap map analysis described in the present invention, wherein: the user behavior data includes user access logs and session data; the calculation of the initial index of page importance includes the following steps: parsing the SiteMap file and extracting all uniform resource locators URLs; constructing the link relationship between the uniform resource locators URLs according to the link element in the SiteMap file; constructing the topological structure of the website, in which the nodes are uniform resource locators URLs and the edges are link relationships; and calculating the initial index of page importance based on the link based on the topological structure of the website.

[0009] As a preferred solution of the network optimization method based on SiteMap map analysis described in the present invention, the calculation formula of the initial index of page importance is as follows:

[0010]

[0011] Among them, P init is the initial index of page importance of the i-th page; I i is the number of inbound links of the ith page; O i is the number of outbound links of the ith page; N is the number of pages on the website; θ is the weight coefficient of outbound links; γ is the weight coefficient of inbound links.

[0012] As a preferred solution of the network optimization method based on SiteMap map analysis described in the present invention, wherein: the user importance index includes user residence time and bounce rate; the calculation of the user importance index includes the following steps: parsing the user access log and extracting the URL access sequence of each session; using the deep learning model to mine the transfer rules of the user access path; counting the number of page views, the number of visiting users and the average residence time of the URL access sequence of each session, and calculating the page residence time index; counting the page bounce situations in the session, and calculating the bounce rate index; calculating based on the page residence time index and the bounce rate index to obtain the user importance index.

[0013] As a preferred solution of the network optimization method based on SiteMap map analysis described in the present invention, the calculation formula of the user importance index is as follows:

[0014]

[0015] Among them, U i is the user importance index, which indicates the user's evaluation of the importance of the i-th page; st i is the user's stay time on the i-th page; μ is the expected value of the page stay time; α is the parameter for adjusting the slope weight of the function; β is the parameter for adjusting the bounce rate weight; BR i The bounce rate of the page.

[0016] As a preferred solution of the network optimization method based on SiteMap map analysis described in the present invention, the calculation formula of the page importance index is as follows:

[0017]

[0018] Among them, P i is the page importance index of the ith page, representing the comprehensive importance of the website page; m is the parameter for adjusting the initial index of page importance; n is the parameter for adjusting the user importance index.

[0019] As a preferred solution of the network optimization method based on SiteMap map analysis described in the present invention, wherein: the website classification results include pages that do not need to be optimized and pages that need to be optimized; the specific situation of formulating the network optimization strategy is as follows: if the page importance index P i is greater than the first threshold, the page is determined to be a page that does not need to be optimized; if the page importance index P i is less than or equal to the first threshold, the page is determined to be a page that needs to be optimized; when the page is a page that needs to be optimized, if the initial index of page importance P init Less than or equal to the second threshold and the user importance index U iIf the value is greater than the third threshold, the page is judged to have insufficient internal links, and a corresponding network optimization strategy is formulated to increase reasonable navigation links and content-related links. When the page is a page that needs to be optimized, if the initial index of page importance P init Greater than the second threshold and the user importance index U i If the page is less than or equal to the third threshold, the page is judged to have poor user experience, and a corresponding network optimization strategy is formulated to optimize the web page content and design; when the page is a page that needs to be optimized, if the initial index of page importance P init Less than or equal to the second threshold and the user importance index U i If the page is less than or equal to the third threshold, it is judged that the page has insufficient internal links and poor user experience, and a corresponding network optimization strategy is formulated to enrich the content and links of the web page; when the page is a page that needs to be optimized, if the initial index of page importance P init Greater than the second threshold and the user importance index U i If it is greater than the third threshold, a corresponding network optimization strategy is formulated to check web page links and eliminate meaningless link loops, repair broken links, and improve internal link integrity.

[0020] On the second aspect, in order to further solve the security problems existing in network optimization, the present invention provides a network optimization system based on SiteMap map analysis in an embodiment, which includes: a network evaluation module, which is used to collect the SiteMap file and user behavior data of the website and calculate the initial page importance index and the user importance index; an optimization strategy module, which is used to calculate the page importance index according to the initial page importance index and the user importance index, identify the type of website and formulate a network optimization strategy; a feedback update module, which is used to continuously monitor the SiteMap file and user behavior data of the website, update the constructed website topology structure and user access path model in real time, adjust the model parameters, and adjust the website.

[0021] In a third aspect, an embodiment of the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the network optimization method based on SiteMap map analysis as described in the first aspect of the present invention is implemented.

[0022] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the network optimization method based on SiteMap map analysis as described in the first aspect of the present invention is implemented.

[0023] The beneficial effects of the present invention are as follows: the present invention obtains a comprehensive page importance index by calculating the initial page importance index based on the website link topology structure and the user importance index based on real user behavior data, which can more comprehensively and accurately evaluate the actual importance of web pages, improve page optimization efficiency, and enhance website quality and user experience; it can automatically identify web pages that need to be optimized and diagnose the optimization type, and then formulate corresponding optimization strategies, thereby improving the automation and intelligence level of the optimization process. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0025] Figure 1 This is a flow chart of formulating a network optimization strategy of the present invention in Example 1. DETAILED DESCRIPTION

[0026] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0027] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0028] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0029] Example 1

[0030] Reference Figure 1 , which is the first embodiment of the present invention, and provides a network optimization method based on SiteMap analysis, comprising the following steps:

[0031] S1: Collect the website's SiteMap file and user behavior data, build the website's topology according to the SiteMap file, and calculate the initial page importance index based on the website's topology.

[0032] Preferably, Figure 1 The figure shows the process of formulating network optimization strategies. By collecting the SiteMap file and user behavior data of the website, the initial page importance index, user importance index and page importance index are calculated, and then the website is identified and judged using the page importance index. If the page importance index is greater than the first threshold, the corresponding page is a page that does not need to be optimized. If the page importance index is less than or equal to the first threshold, the corresponding page is a page that needs to be optimized and is judged based on the initial page importance index. If the initial page importance index is greater than the second threshold, it is directly judged based on the user importance index. If the initial page importance index is less than or equal to the second threshold, the page has insufficient internal links and is judged based on the user importance index. If the user importance index is less than or equal to the third threshold, the user experience of the page is poor. If the user importance index is greater than the third threshold, the web page link is checked and repaired. Finally, the corresponding network optimization strategy is formulated based on the judgment result.

[0033] Preferably, the user behavior data includes user access logs and session data.

[0034] Specifically, calculating the initial index of page importance includes the following steps: parsing the SiteMap file and extracting all uniform resource locators URLs.

[0035] Build the link relationship between the uniform resource locators URL according to the link element in the SiteMap file.

[0036] Construct the topological structure of the website, where nodes are uniform resource locators (URLs) and edges are link relationships.

[0037] Calculate an initial link-based index of page importance based on the topology of the website.

[0038] Specifically, the calculation formula for the initial index of page importance is as follows:

[0039]

[0040] Among them, P init is the initial index of page importance of the i-th page; I i is the number of inbound links of the ith page; O i is the number of outbound links of the ith page; N is the number of pages on the website; θ is the weight coefficient of outbound links; γ is the weight coefficient of inbound links.

[0041] S2: Build a user access path model based on user behavior data and calculate user importance indicators.

[0042] Preferably, the user importance indicators include user residence time and bounce rate.

[0043] Specifically, calculating the user importance index includes the following steps: parsing the user access log and extracting the URL access sequence of each session.

[0044] Use deep learning models to mine the transfer patterns of user access paths.

[0045] Count the number of page views, number of visiting users and average dwell time of the URL access sequence of each session, and calculate the page dwell time index.

[0046] Count page bounces in a session and calculate the bounce rate metric.

[0047] The user importance index is calculated based on the page dwell time index and the bounce rate index.

[0048] Specifically, the calculation formula of the user importance index is as follows:

[0049]

[0050] Among them, U i is the user importance index, which indicates the user's evaluation of the importance of the i-th page; st i is the user's stay time on the i-th page; μ is the expected value of the page stay time; α is the parameter for adjusting the slope weight of the function; β is the parameter for adjusting the bounce rate weight; BR i The bounce rate of the page.

[0051] Specifically, by utilizing user behavior data to construct a user access path model and calculating user importance indicators, including page dwell time indicators and bounce rate indicators, a new user importance evaluation indicator is proposed by combining website analysis and user behavior analysis technology. It can more accurately evaluate users' evaluation of pages and improve user experience.

[0052] S3: Based on the initial page importance index and the user importance index, the importance of the website is comprehensively evaluated to obtain the page importance index.

[0053] Preferably, the calculation formula of the page importance index is as follows:

[0054]

[0055] Among them, P i is the page importance index of the ith page, representing the comprehensive importance of the website page; m is the parameter for adjusting the initial index of page importance; n is the parameter for adjusting the user importance index.

[0056] Specifically, by combining the initial page importance index with the user importance index, we get the page importance index, which reflects the dual consideration of website content quality and user experience, and can more comprehensively and accurately evaluate the actual importance of web pages, thereby improving page optimization efficiency.

[0057] S4: Identify websites based on page importance indicators, obtain website classification results and formulate network optimization strategies.

[0058] Preferably, the website classification results include pages that do not need to be optimized and pages that need to be optimized.

[0059] Specifically, the specific situation of formulating network optimization strategy is as follows: If the page importance index P i If the value is greater than the first threshold, the page is determined to be a page that does not need to be optimized.

[0060] If the page importance index P i If the value is less than or equal to the first threshold, the page is determined to be a page that needs to be optimized.

[0061] When a page is to be optimized, if the initial index of page importance P init Less than or equal to the second threshold and the user importance index U i If it is greater than the third threshold, it is determined that the page has insufficient internal links, and a corresponding network optimization strategy is formulated to add reasonable navigation links and content-related links.

[0062] When a page is to be optimized, if the initial index of page importance P init Greater than the second threshold and the user importance index U i If it is less than or equal to the third threshold, the page is judged to have a poor user experience, and a corresponding network optimization strategy is formulated to optimize the web page content and design.

[0063] When a page is to be optimized, if the initial index of page importance P init Less than or equal to the second threshold and the user importance index U i If it is less than or equal to the third threshold, the page is judged to have insufficient internal links and poor user experience, and a corresponding network optimization strategy is formulated to enrich the content and links of the web page.

[0064] When a page is to be optimized, if the initial index of page importance P init Greater than the second threshold and the user importance index U i If it is greater than the third threshold, a corresponding network optimization strategy is formulated to check web page links and eliminate meaningless link loops, repair broken links, and improve internal link integrity.

[0065] Specifically, different network optimization strategies are formulated according to the different page importance status, covering multiple dimensions of internal link optimization, content optimization and link optimization, which effectively improves the website quality and user experience and improves the optimization efficiency.

[0066] S5: Continuously monitor the website's SiteMap files and user behavior data and establish a feedback mechanism to optimize the website's topology and user access path model.

[0067] Specifically, a feedback mechanism is established to continuously collect the website's SiteMap files and user behavior data, monitor changes in page rankings, traffic, and user behavior, analyze changes in page dwell time indicators and bounce rate indicators based on new data, determine the network optimization effect, and then update the constructed website's topology and user access path model in real time, adjust model parameters, and adjust the website's structure, navigation, content, and operation based on the obtained page importance indicators.

[0068] This embodiment also provides a network optimization system based on SiteMap map analysis, including: a network evaluation module, which is used to collect the SiteMap file and user behavior data of the website and calculate the initial page importance index and the user importance index; an optimization strategy module, which is used to calculate the page importance index based on the initial page importance index and the user importance index, identify the type of website and formulate a network optimization strategy; a feedback update module, which is used to continuously monitor the SiteMap file and user behavior data of the website, update the constructed website topology structure and user access path model in real time, adjust the model parameters, and adjust the website.

[0069] This embodiment also provides a computer device, which is suitable for the network optimization method based on SiteMap map analysis, including: a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute computer executable instructions to implement the network optimization method based on SiteMap map analysis proposed in the above embodiment.

[0070] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0071] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the network optimization method based on SiteMap map analysis proposed in the above embodiment is implemented; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Red-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0072] In summary, the present invention obtains a comprehensive page importance index by calculating the initial page importance index based on the website link topology structure and the user importance index based on real user behavior data. It can more comprehensively and accurately evaluate the actual importance of web pages, improve page optimization efficiency, and enhance website quality and user experience. It can automatically identify web pages that need to be optimized and diagnose the optimization type, and then formulate corresponding optimization strategies, thereby improving the automation and intelligence level of the optimization process.

[0073] Example 2

[0074] Referring to Tables 1 to 3, the second embodiment of the present invention is shown. This embodiment is different from the first embodiment in that, in order to verify its beneficial effects, operating data and related instructions of the present invention in an actual environment are provided.

[0075] This example collects the SiteMap file and user behavior data of a website, calculates the corresponding initial page importance index and user importance index, and then evaluates the actual situation of the website page, determines the type of page and formulates the corresponding network optimization strategy.

[0076] As shown in Tables 1 and 2, the parsing results of the website's SiteMap file and the user behavior data, the topological link structure of the website can be constructed by parsing the SiteMap file, providing a data basis for the subsequent calculation of the link importance index of the page, and by displaying the URL access sequence in the session and the dwell time of each URL, the user behavior path and dwell time are analyzed, thereby better evaluating the importance of the page to the user.

[0077] Table 1 Parsing results of SiteMap file

[0078] URL Number of incoming URLs Number of outbound URLs 1 0 6 2 2 0 3 2 3 ... ... ... n 3 0

[0079] Table 2 User behavior data table

[0080] Session ID URL Access Sequence Dwell time(s) 1 5 30，120，45，180，300 2 6 45，240，105，60，90，180 3 4 90，30，420，105 ... ... ... n 3 120，45，30

[0081] Table 3 shows the importance evaluation indicators for website pages.

[0082] Table 3 Page importance evaluation index table

[0083] URL Initial indicators of page importance User importance index Page importance index 1 0.88 0.91 0.90 2 0.35 0.49 0.44 3 0.61 0.73 0.69 ... ... ... ... n 0.24 0.12 0.16

[0084] As can be seen from the above table, by combining the website's link structure and user experience to evaluate the website pages, using the initial page importance index, user importance index and page importance index to identify the specific type of page, and then formulate a corresponding network optimization strategy, it shows that compared with the prior art, the present invention is more objective and comprehensive in evaluation, and can adjust the priority in a targeted manner according to the page importance index, thereby improving page optimization efficiency, website quality and user experience.

[0085] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A network optimization method based on SiteMap analysis, characterized in that: include: Collecting the SiteMap file and user behavior data of the website, constructing the topology structure of the website according to the SiteMap file and calculating the initial index of page importance based on the topology structure of the website; Build a user access path model based on user behavior data and calculate user importance indicators; Comprehensively evaluating the importance of the website based on the initial page importance index and the user importance index to obtain a page importance index; Identify websites based on the page importance index, obtain website classification results and formulate network optimization strategies; Continuously monitor the website's SiteMap files and user behavior data and establish a feedback mechanism to optimize the website's topology and user access path model; The calculation formula of the initial index of page importance is as follows: Among them, P init is the initial index of page importance of the i-th page; I i is the number of inbound links of the ith page; O i is the number of outbound links of the i-th page; N is the number of pages on the website; θ is the weight coefficient of outbound links; γ is the weight coefficient of inbound links; The user importance indicators include user residence time and bounce rate; The calculation of the user importance index comprises the following steps: Parse user access logs and extract URL access sequences for each session; Use deep learning models to explore the transfer patterns of user access paths; Count the page views, number of visiting users and average dwell time of the URL access sequence of each session, and calculate the page dwell time index; Count page bounces in a session and calculate the bounce rate indicator; Calculating based on the page dwell time index and the bounce rate index to obtain a user importance index; The calculation formula of the user importance index is as follows: Among them, U i is the user importance index, which indicates the user's evaluation of the importance of the i-th page; st i is the user's stay time on the i-th page; μ is the expected value of the page stay time; α is the parameter for adjusting the slope weight of the function; β is the parameter for adjusting the bounce rate weight; BR i is the bounce rate of the page; The calculation formula of the page importance index is as follows: Among them, P i is the page importance index of the ith page, representing the comprehensive importance of the website page; m is the parameter for adjusting the initial index of page importance; n is the parameter for adjusting the user importance index; The website classification results include pages that do not need to be optimized and pages that need to be optimized; The specific situation of formulating the network optimization strategy is as follows: If the page importance index P i If it is greater than the first threshold, the page is determined to be a page that does not need to be optimized; If the page importance index P i If the value is less than or equal to the first threshold, the page is determined to be a page that needs to be optimized; When a page is to be optimized, if the initial index of page importance P init Less than or equal to the second threshold and the user importance index U i If it is greater than the third threshold, the page is judged to have insufficient internal links, and reasonable navigation links and content-related links are added; When a page is to be optimized, if the initial index of page importance P init Greater than the second threshold and the user importance index U i If it is less than or equal to the third threshold, the page is judged to have a poor user experience and the webpage content and design are optimized; When a page is to be optimized, if the initial index of page importance P init Less than or equal to the second threshold and the user importance index U i If it is less than or equal to the third threshold, the page is judged to have insufficient internal links and poor user experience, and the content and links of the webpage are enriched; When a page is to be optimized, if the initial index of page importance P init Greater than the second threshold and the user importance index U i If it is greater than the third threshold, the web page links are checked and meaningless link loops are eliminated to repair the broken link problem.

2. The network optimization method based on SiteMap analysis according to claim 1, characterized in that: The user behavior data includes user access logs and session data; The calculation of the initial index of page importance comprises the following steps: Parse the SiteMap file and extract all Uniform Resource Locator URLs; Construct the link relationship between the uniform resource locators URL according to the link element in the SiteMap file; Construct the topological structure of the website, where nodes are uniform resource locators (URLs) and edges are link relationships; Calculate an initial link-based index of page importance based on the topology of the website.

3. A network optimization system based on SiteMap analysis, based on the network optimization method based on SiteMap analysis according to any one of claims 1 and 2, characterized in that: it includes: The network evaluation module is used to collect the website's SiteMap file and user behavior data and calculate the initial index of page importance and the user importance index; The optimization strategy module is used to calculate the page importance index based on the initial page importance index and the user importance index, identify the type of website and formulate a network optimization strategy; The feedback update module is used to continuously monitor the SiteMap file and user behavior data of the website, update the constructed website topology structure and user access path model in real time, adjust the model parameters, and adjust the website.

4. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the network optimization method based on SiteMap map analysis described in any one of claims 1 and 2 are implemented.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the network optimization method based on SiteMap map analysis described in any one of claims 1 and 2 are implemented.

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