Methods, equipment, storage media and devices for calibrating the location of communication resource points

Abstract

This invention relates to the field of communication technology and discloses a method, device, storage medium, and apparatus for calibrating the location of communication resource points. The method includes: acquiring network traffic data of associated users corresponding to the resource point to be calibrated; determining the location information of the associated users based on the network traffic data; calibrating the location of the resource point to be calibrated based on the location information using a preset location calibration model to obtain the calibrated location. Because this invention determines the location information of associated users based on the network traffic data of the associated users corresponding to the resource point to be calibrated and calibrates the location of the resource point to be calibrated using a preset location calibration model, it overcomes the inaccuracy of manually entering resource point locations, thereby ensuring the effective management of resource points.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a method, device, storage medium and apparatus for calibrating the location of communication resource points. Background Technology

[0002] With the development of broadband fiber optic network technology, access networking based on Passive Optical Network (PON) has become the mainstream. Since all devices in PON are passive and thus considered "dumb" resources, they cannot automatically or intelligently record device information. Therefore, data such as the addition, modification, and use of devices can only be recorded manually in the operator's resource management system.

[0003] In practical applications, manual data entry can lead to inaccurate data due to factors such as inadequate training and differences in subjective understanding. In particular, the latitude and longitude of the location of "dumb" resources and their relationship with their respective communities, enterprises, and other units are often inaccurate. As a result, analysis and decision-making are often based on incorrect data, making it difficult for maintenance teams to determine the resources to which they belong. This leads to some resources being left unmanaged, affecting the quality of broadband installation and user satisfaction. Summary of the Invention

[0004] The main objective of this invention is to provide a method, device, storage medium, and apparatus for calibrating the location of communication resource points, aiming to solve the technical problem of inaccurate manual input of the location of passive devices in the prior art.

[0005] To achieve the above objectives, the present invention provides a method for calibrating the location of communication resource points, the method comprising the following steps:

[0006] Obtain network traffic data of the associated users corresponding to the resource point to be calibrated;

[0007] The location information of the associated user is determined based on the network traffic data;

[0008] Based on the location information, the location of the resource point to be calibrated is calibrated using a preset location calibration model to obtain the calibrated location.

[0009] Optionally, before the step of obtaining the network traffic data of the associated user corresponding to the resource point to be calibrated, the method further includes:

[0010] Obtain resource point location samples and associated user location samples corresponding to the resource point location samples;

[0011] The initial location calibration model is trained based on the resource point location samples and the associated user location samples to obtain the preset location calibration model.

[0012] Optionally, the preset position calibration model is a linear regression algorithm model.

[0013] Optionally, the step of determining the location information of the associated user based on the network traffic data includes:

[0014] Extract webpage address data from the network traffic data;

[0015] The location information of the associated user is determined based on the webpage address data.

[0016] Optionally, the step of determining the location information of the associated user based on the webpage address data includes:

[0017] Obtain the data extraction rules corresponding to the network traffic data;

[0018] Based on the data extraction rules, the location information of the associated user is extracted from the webpage address data.

[0019] Optionally, the step of obtaining the data extraction rules corresponding to the network traffic data includes:

[0020] Identify the application corresponding to the network traffic data and obtain the application's program information;

[0021] The data extraction rules corresponding to the network traffic data are determined based on the program information.

[0022] Optionally, before the step of obtaining the network traffic data of the associated user corresponding to the resource point to be calibrated, the method further includes:

[0023] Obtain broadband installation information for the resource points to be calibrated;

[0024] The associated user corresponding to the resource point to be calibrated is determined based on the broadband installation information.

[0025] Furthermore, to achieve the above objectives, the present invention also proposes a communication resource point location calibration device, which includes a memory, a processor, and a communication resource point location calibration program stored in the memory and executable on the processor. The communication resource point location calibration program is configured to implement the communication resource point location calibration method described above.

[0026] In addition, to achieve the above objectives, the present invention also proposes a storage medium storing a communication resource point location calibration program, wherein the communication resource point location calibration program, when executed by a processor, implements the communication resource point location calibration method as described above.

[0027] In addition, to achieve the above objectives, the present invention also proposes a communication resource point location calibration device, which includes: a data acquisition module, a location determination module, and a location calibration module;

[0028] The data acquisition module is used to acquire network traffic data of the associated users corresponding to the resource point to be calibrated;

[0029] The location determination module is used to determine the location information of the associated user based on the network traffic data;

[0030] The location calibration module is used to calibrate the location of the resource point to be calibrated based on the location information using a preset location calibration model, and obtain the calibrated location.

[0031] This invention discloses a method for obtaining network traffic data of associated users corresponding to a resource point to be calibrated, determining the location information of associated users based on the network traffic data, and calibrating the location of the resource point to be calibrated using a preset location calibration model based on the location information to obtain the calibrated location. Because this invention determines the location information of associated users based on the network traffic data of associated users corresponding to the resource point to be calibrated, and calibrates the location of the resource point to be calibrated using a preset location calibration model, it overcomes the shortcomings of inaccurate manual entry of resource point locations, thereby ensuring the effective management of resource points. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the structure of the communication resource point location calibration device in the hardware operating environment involved in the embodiments of the present invention;

[0033] Figure 2 This is a flowchart illustrating the first embodiment of the communication resource point location calibration method of the present invention;

[0034] Figure 3 This is a schematic diagram of communication resource point location calibration according to an embodiment of the communication resource point location calibration method of the present invention;

[0035] Figure 4 This is a flowchart illustrating the second embodiment of the communication resource point location calibration method of the present invention;

[0036] Figure 5 This is a flowchart illustrating the third embodiment of the communication resource point location calibration method of the present invention;

[0037] Figure 6 This is a structural block diagram of the first embodiment of the communication resource point location calibration device of the present invention.

[0038] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0039] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0040] Reference Figure 1 , Figure 1 This is a schematic diagram of the communication resource point location calibration device structure in the hardware operating environment involved in the embodiments of the present invention.

[0041] like Figure 1 As shown, the communication resource point location calibration device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen, and optionally, it may also include a standard wired interface or a wireless interface. In this invention, the wired interface of the user interface 1003 may be a USB interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wireless-Fidelity (Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (RAM) or a non-volatile memory (NVM), such as a disk storage device. The memory 1005 may also optionally be a storage device independent of the aforementioned processor 1001.

[0042] Those skilled in the art will understand that Figure 1 The structure shown does not constitute a limitation on the communication resource point location calibration device, and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0043] like Figure 1 As shown, the memory 1005, which is identified as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a communication resource point location calibration program.

[0044] exist Figure 1 In the communication resource point location calibration device shown, the network interface 1004 is mainly used to connect to the backend server and communicate with the backend server; the user interface 1003 is mainly used to connect to the user equipment; the communication resource point location calibration device calls the communication resource point location calibration program stored in the memory 1005 through the processor 1001 and executes the communication resource point location calibration method provided in the embodiment of the present invention.

[0045] Based on the above hardware structure, an embodiment of the communication resource point location calibration method of the present invention is proposed.

[0046] Reference Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of the communication resource point location calibration method of the present invention, which presents the first embodiment of the communication resource point location calibration method of the present invention.

[0047] Step S10: Obtain network traffic data of the associated user corresponding to the resource point to be calibrated.

[0048] It should be understood that the execution subject of the method in this embodiment may be a communication resource point location calibration device with data processing, network communication and program running functions, such as a server, or other electronic devices that can achieve the same or similar functions. This embodiment does not limit this.

[0049] It should be noted that the resource point to be calibrated can be a passive device in the communication network. A passive device is one that cannot automatically record device information. For example, the resource point to be calibrated can be an optical fiber distribution box in a Passive Optical Network (PON).

[0050] It is understandable that associated users can be users who have network resource associations with a resource point. In practical applications, resource points typically connect multiple user terminals and are used to manage the network resources of these user terminals. For example, an optical fiber distribution box typically connects multiple optical network terminals and is used to manage the optical fiber resources of these terminals.

[0051] It should be noted that network traffic data can be Deep Packet Inspection (DPI) data. In practical applications, DPI data can be fixed-line DPI data in PON.

[0052] Step S20: Determine the location information of the associated user based on the network traffic data.

[0053] It should be noted that the location information of the associated user can be the latitude and longitude of the associated user's location.

[0054] It should be understood that in practical applications, network traffic data may carry user location information. Therefore, determining the location information of associated users based on network traffic data can be achieved by extracting the location information of associated users from the network traffic data based on preset rules. These preset rules can be set in advance.

[0055] Step S30: Based on the location information, calibrate the location of the resource point to be calibrated using a preset location calibration model to obtain the calibrated location.

[0056] It should be noted that the preset location calibration model can be set in advance, and the preset location calibration model can be used to calibrate the location of resource points based on the location information of associated users.

[0057] In practical implementation, the preset position calibration model can be a linear regression algorithm model. For example, the preset position calibration model can be as follows:

[0058] LNG=a1*LNG1+a2*LNG2+……+a n LNG n +b

[0059] LAT=c1*LAT1+c2*LAT2+……+c n *LAT n +d

[0060] In the formula, LNG represents the longitude of the resource point. n LAT represents the longitude of the nth associated user, and LAT represents the latitude of the resource point. n Let a be the dimension of the nth associated user. n b, c n And d is a constant value.

[0061] For ease of understanding, please refer to Figure 3 This will be explained, but not specifically the embodiment described herein. Figure 3 The diagram illustrates the location calibration of communication resource points. In the diagram, the location of associated user 1 is (LNG1, LAT1), the location of associated user 2 is (LNG2, LAT2), and the location of associated user 3 is (LNG3, LAT3). The locations of the associated users are substituted into the preset location calibration model to calibrate the location of the resource point to be calibrated, and the calibrated location (LNG, LAT) is obtained.

[0062] In the first embodiment, the method of obtaining network traffic data of associated users corresponding to the resource point to be calibrated, determining the location information of associated users based on the network traffic data, and calibrating the location of the resource point to be calibrated based on the location information using a preset location calibration model to obtain the calibrated location. Since this embodiment determines the location information of associated users based on the network traffic data of associated users corresponding to the resource point to be calibrated, and calibrates the location of the resource point to be calibrated in combination with the preset location calibration model, it overcomes the defect of inaccurate manual entry of resource point location, thereby ensuring the effective management of resource points.

[0063] Reference Figure 4 , Figure 4 This is a flowchart illustrating the second embodiment of the communication resource point location calibration method of the present invention, based on the above. Figure 2The first embodiment shown presents a second embodiment of the communication resource point location calibration method of the present invention.

[0064] In the second embodiment, before step S10, the method further includes:

[0065] Step S01: Obtain resource point location samples and associated user location samples corresponding to the resource point location samples.

[0066] It should be understood that, in order to ensure the reliability of the preset position calibration model, in this embodiment, the initial position calibration model can be trained in advance to obtain the preset position calibration model.

[0067] It should be noted that the resource point location samples and the corresponding associated user location samples can be pre-entered, and the resource point location samples and associated user location samples can be accurate latitude and longitude.

[0068] Step S02: Train the initial location calibration model based on the resource point location samples and the associated user location samples to obtain the preset location calibration model.

[0069] It should be noted that the initial position calibration model can be a linear regression algorithm model. In a specific implementation, the initial position calibration model can be as follows:

[0070] LNG=A1*LNG1+A2*LNG2+……+A n LNG n +B

[0071] LAT=C1*LAT1+C2*LAT2+……+C n *LAT n +D

[0072] In the formula, LNG represents the longitude of the resource point, and A represents the longitude of the resource point. n For the longitude weight parameter of the nth associated user, LNG n Let LAT be the longitude of the nth associated user, and C be the latitude of the resource point. n LAT is the dimension weight parameter for the nth associated user. n Let B and D be the dimensions of the nth associated user, and let D be the correction values.

[0073] It is understandable that training an initial location calibration model based on resource point location samples and associated user location samples to obtain a preset location calibration model can be achieved by substituting the resource point location samples and associated user location samples into the initial location calibration model for training, thus obtaining A. n B, C n And the parameter value a of D n b, c n And d, and an b, c n The parameter value of d is substituted into the initial position calibration model to obtain the preset position calibration model.

[0074] In a practical implementation, the preset position calibration model can be represented by the following formula:

[0075] LNG=a1*LNG1+a2*LNG2+……+a n LNG n +b

[0076] LAT=c1*LAT1+c2*LAT2+……+c n *LAT n +d

[0077] In the formula, LNG represents the longitude of the resource point. n LAT represents the longitude of the nth associated user, and LAT represents the latitude of the resource point. n Let a be the dimension of the nth associated user. n b, c n And d is a constant value.

[0078] In the second embodiment, it is disclosed that resource point location samples and associated user location samples corresponding to the resource point location samples are obtained, and an initial location calibration model is trained based on the resource point location samples and associated user location samples to obtain a preset location calibration model. Since the initial location calibration model is trained in advance in this embodiment to obtain the preset location calibration model, the reliability of the preset location calibration model can be ensured.

[0079] In the second embodiment, before step S10, the method further includes:

[0080] Step S03: Obtain broadband installation information for the resource point to be calibrated.

[0081] It should be understood that, in order to accurately obtain the associated users corresponding to the resource point to be calibrated, in this embodiment, the broadband installation information of the resource point to be calibrated is first obtained, and then the associated users corresponding to the resource point to be calibrated are determined based on the broadband installation information.

[0082] It should be noted that broadband installation information may include the correspondence between resource points and associated users, and broadband installation information can be entered by the installers when deploying network equipment at the user end.

[0083] It is understandable that obtaining the broadband installation information of the resource point to be calibrated could involve obtaining the name of the resource point to be calibrated and then searching for the broadband installation information corresponding to that name.

[0084] Step S04: Determine the associated user corresponding to the resource point to be calibrated based on the broadband installation information.

[0085] It should be understood that broadband installation information includes the correspondence between resource points and associated users. Therefore, determining the associated users corresponding to the resource point to be calibrated based on the broadband installation information involves searching for the associated users corresponding to the resource point to be calibrated within the broadband installation information.

[0086] In the second embodiment, the method of obtaining broadband installation information of the resource point to be calibrated and determining the associated users corresponding to the resource point to be calibrated based on the broadband installation information is disclosed. Since broadband installation information is additionally introduced in this embodiment to determine the associated users corresponding to the resource point to be calibrated, the accuracy of the associated users is improved.

[0087] Reference Figure 5 , Figure 5 This is a flowchart illustrating the third embodiment of the communication resource point location calibration method of the present invention, based on the above. Figure 4 The first embodiment shown presents a third embodiment of the communication resource point location calibration method of the present invention.

[0088] In the third embodiment, step S20 includes:

[0089] Step S201: Extract webpage address data from the network traffic data.

[0090] It should be understood that in practical applications, users may need to report their location when accessing certain web pages, and the web page address data may carry the user's location information. Therefore, in this embodiment, in order to improve the efficiency of obtaining location information, web page address data can be extracted from network traffic data first, and then the location information of the associated user can be determined based on the web page address data.

[0091] It should be noted that the webpage address data can be Uniform Resource Locator (URL) data.

[0092] Understandably, in practical applications, address data is usually represented in a specific format. Therefore, extracting webpage address data from network traffic data can be done by extracting data in a preset address format from the network traffic data. The preset address format can be pre-defined.

[0093] Step S202: Determine the location information of the associated user based on the webpage address data.

[0094] It is understandable that determining the location information of associated users based on webpage address data can be achieved by extracting the location information of associated users from webpage address data based on preset data extraction rules. These preset data extraction rules can be set in advance.

[0095] In the third embodiment, webpage address data is extracted from network traffic data, and the location information of associated users is determined based on the webpage address data. Since this embodiment first filters the network traffic data to obtain webpage address data, and then extracts the location information of associated users from the webpage address data, the amount of data processing is reduced and the efficiency of obtaining location information is improved.

[0096] Furthermore, considering that fixed data extraction rules may lead to errors in location information extraction, step S202 includes the following steps to overcome these shortcomings:

[0097] Obtain the data extraction rules corresponding to the network traffic data;

[0098] Based on the data extraction rules, the location information of the associated user is extracted from the webpage address data.

[0099] It should be understood that in practical applications, different traffic data correspond to different information carrying methods. Therefore, if the data extraction rules are preset and cannot be adaptively adjusted, it may lead to errors in location information extraction. To overcome the above defects, in this embodiment, the location information of associated users is extracted from web address data based on the data extraction rules corresponding to network traffic data.

[0100] It is understandable that the data extraction rules for obtaining network traffic data can be derived by acquiring the feature information of the network traffic data and searching for the corresponding data extraction rules in a preset rule table. The preset rule table contains the correspondence between feature information and data extraction rules, and this correspondence can be pre-entered.

[0101] Furthermore, in practical applications, users typically access the network through applications, and different applications report user location information in different ways. Therefore, to improve the accuracy of location information, the data extraction rules for obtaining the network traffic data include:

[0102] Identify the application corresponding to the network traffic data and obtain the application's program information;

[0103] The data extraction rules corresponding to the network traffic data are determined based on the program information.

[0104] It should be understood that in practical applications, users typically access the network through applications, and different applications carry location information in different ways when reporting the user's location information. Therefore, in order to improve the accuracy of location information, this embodiment first determines the application corresponding to the network traffic data, and then determines the data extraction rules corresponding to the network traffic data based on the application's program information.

[0105] It should be noted that the application can be an Over-The-Top (OTT) application that provides various application services to users over the network.

[0106] Program information can include program type, program publisher, and program version.

[0107] It is understandable that determining the application corresponding to network traffic data can involve parsing the network traffic information and determining the application corresponding to the network traffic data based on the parsing results.

[0108] In addition, refer to Figure 6 The present invention also proposes a communication resource point location calibration device, which includes: a data acquisition module 10, a location determination module 20 and a location calibration module 30;

[0109] The data acquisition module 10 is used to acquire network traffic data of the associated users corresponding to the resource point to be calibrated.

[0110] It should be noted that the resource point to be calibrated can be a passive device in the communication network. A passive device is one that cannot automatically record device information. For example, the resource point to be calibrated can be an optical fiber distribution box in a Passive Optical Network (PON).

[0111] It is understandable that associated users can be users who have network resource associations with a resource point. In practical applications, resource points typically connect multiple user terminals and are used to manage the network resources of these user terminals. For example, an optical fiber distribution box typically connects multiple optical network terminals and is used to manage the optical fiber resources of these terminals.

[0112] It should be noted that network traffic data can be Deep Packet Inspection (DPI) data. In practical applications, DPI data can be fixed-line DPI data in PON.

[0113] The location determination module 20 is used to determine the location information of the associated user based on the network traffic data.

[0114] It should be noted that the location information of the associated user can be the latitude and longitude of the associated user's location.

[0115] It should be understood that in practical applications, network traffic data may carry user location information. Therefore, determining the location information of associated users based on network traffic data can be achieved by extracting the location information of associated users from the network traffic data based on preset rules. These preset rules can be set in advance.

[0116] The location calibration module 30 is used to calibrate the location of the resource point to be calibrated based on the location information using a preset location calibration model, and obtain the calibrated location.

[0117] It should be noted that the preset location calibration model can be set in advance, and the preset location calibration model can be used to calibrate the location of resource points based on the location information of associated users.

[0118] In practical implementation, the preset position calibration model can be a linear regression algorithm model. For example, the preset position calibration model can be as follows:

[0119] LNG=a1*LNG1+a2*LNG2+……+a n LNG n +b

[0120] LAT=c1*LAT1+c2*LAT2+……+c n *LAT n +d

[0121] In the formula, LNG represents the longitude of the resource point. n LAT represents the longitude of the nth associated user, and LAT represents the latitude of the resource point. n Let a be the dimension of the nth associated user. n b, c n And d is a constant value.

[0122] For ease of understanding, please refer to Figure 3 This will be explained, but not specifically the embodiment described herein. Figure 3 The diagram illustrates the location calibration of communication resource points. In the diagram, the location of associated user 1 is (LNG1, LAT1), the location of associated user 2 is (LNG2, LAT2), and the location of associated user 3 is (LNG3, LAT3). The locations of the associated users are substituted into the preset location calibration model to calibrate the location of the resource point to be calibrated, and the calibrated location (LNG, LAT) is obtained.

[0123] In this embodiment, the method of obtaining network traffic data of associated users corresponding to the resource point to be calibrated, determining the location information of associated users based on the network traffic data, and calibrating the location of the resource point to be calibrated based on the location information using a preset location calibration model to obtain the calibrated location. Since this embodiment determines the location information of associated users based on the network traffic data of associated users corresponding to the resource point to be calibrated, and calibrates the location of the resource point to be calibrated in combination with the preset location calibration model, it overcomes the defects of inaccurate manual entry of resource point locations, thereby ensuring the effective management of resource points.

[0124] In one embodiment, the communication resource point location calibration device further includes: a training module;

[0125] The training module is used to obtain resource point location samples and associated user location samples corresponding to the resource point location samples;

[0126] The training module is also used to train the initial location calibration model based on the resource point location samples and the associated user location samples to obtain a preset location calibration model.

[0127] In one embodiment, the preset position calibration model is a linear regression algorithm model.

[0128] In one embodiment, the location determination module is further configured to extract webpage address data from the network traffic data;

[0129] The location determination module is also used to determine the location information of the associated user based on the webpage address data.

[0130] In one embodiment, the location determination module is further configured to obtain data extraction rules corresponding to the network traffic data;

[0131] The location determination module is also used to extract the location information of the associated user from the webpage address data based on the data extraction rules.

[0132] In one embodiment, the location determination module is further configured to determine the application corresponding to the network traffic data and obtain the application's program information;

[0133] The location determination module is also used to determine the data extraction rules corresponding to the network traffic data based on the program information.

[0134] In one embodiment, the communication resource point location calibration device further includes: a user determination module;

[0135] The user determination module is used to obtain broadband installation information of the resource point to be calibrated;

[0136] The user determination module is also used to determine the associated user corresponding to the resource point to be calibrated based on the broadband installation information.

[0137] Other embodiments or specific implementations of the communication resource point location calibration device of the present invention can be referred to the above-described method embodiments, and will not be repeated here.

[0138] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0139] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0140] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as a read-only memory image (ROM) / random access memory (RAM), magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0141] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A method for calibrating the location of communication resource points, characterized in that, The communication resource point location calibration method includes the following steps: Obtain network traffic data of the associated user corresponding to the resource point to be calibrated, wherein the resource point to be calibrated is a passive device in the communication network, and the network traffic data is fixed network DPI data; The location information of the associated user is determined based on the network traffic data; Based on the location information, the location of the resource point to be calibrated is calibrated using a preset location calibration model to obtain the calibrated location; Prior to the step of obtaining the network traffic data of the associated user corresponding to the resource point to be calibrated, the method further includes: Obtain resource point location samples and associated user location samples corresponding to the resource point location samples; The initial location calibration model is trained based on the resource point location samples and the associated user location samples to obtain the preset location calibration model.

2. The communication resource point location calibration method as described in claim 1, characterized in that, The preset position calibration model is a linear regression algorithm model.

3. The communication resource point location calibration method as described in claim 1, characterized in that, The step of determining the location information of the associated user based on the network traffic data includes: Extract webpage address data from the network traffic data; The location information of the associated user is determined based on the webpage address data.

4. The communication resource point location calibration method as described in claim 3, characterized in that, The step of determining the location information of the associated user based on the webpage address data includes: Obtain the data extraction rules corresponding to the network traffic data; Based on the data extraction rules, the location information of the associated user is extracted from the webpage address data.

5. The communication resource point location calibration method as described in claim 4, characterized in that, The step of obtaining the data extraction rules corresponding to the network traffic data includes: Identify the application corresponding to the network traffic data and obtain the application's program information; The data extraction rules corresponding to the network traffic data are determined based on the program information.

6. The communication resource point location calibration method according to any one of claims 1 to 5, characterized in that, Before the step of obtaining the network traffic data of the associated user corresponding to the resource point to be calibrated, the method further includes: Obtain broadband installation information for the resource points to be calibrated; The associated user corresponding to the resource point to be calibrated is determined based on the broadband installation information.

7. A communication resource point location calibration device, characterized in that, The communication resource point location calibration device includes: a memory, a processor, and a communication resource point location calibration program stored in the memory and executable on the processor. When the communication resource point location calibration program is executed by the processor, it implements the communication resource point location calibration method as described in any one of claims 1 to 6.

8. A storage medium, characterized in that, The storage medium stores a communication resource point location calibration program, which, when executed by a processor, implements the communication resource point location calibration method as described in any one of claims 1 to 6.

9. A communication resource point location calibration device, characterized in that, The communication resource point location calibration device includes: a data acquisition module, a location determination module, and a location calibration module; The data acquisition module is used to acquire network traffic data of the associated user corresponding to the resource point to be calibrated, wherein the resource point to be calibrated is a passive device in the communication network, and the network traffic data is fixed network DPI data. The location determination module is used to determine the location information of the associated user based on the network traffic data; The location calibration module is used to calibrate the location of the resource point to be calibrated based on the location information using a preset location calibration model, and obtain the calibrated location. Before obtaining the network traffic data of the associated user corresponding to the resource point to be calibrated, the method further includes: Obtain resource point location samples and associated user location samples corresponding to the resource point location samples; train the initial location calibration model based on the resource point location samples and the associated user location samples to obtain a preset location calibration model.

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