Target region determination method, device and readable storage medium

Abstract

The application discloses a target area determination method and device and a readable storage medium, relates to the technical field of communication, and aims at improving the accuracy of determining a target area. The method comprises the following steps: acquiring a plurality of to-be-analyzed addresses, the to-be-analyzed addresses being addresses of terminal devices sending complaint information, and the complaint information being used for indicating abnormal communication signals of the terminal devices; determining a plurality of keywords from the plurality of to-be-analyzed addresses; the area corresponding to the keywords is smaller than an area threshold; determining a target area, the target area being an area corresponding to a target keyword, and the target keyword being a keyword whose ranking of occurrence times in the plurality of keywords is greater than a ranking threshold.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method, apparatus and readable storage medium for determining a target area. Background Technology

[0002] User complaints are a crucial reference in the planning and maintenance of wireless communication networks. By analyzing the address information in user complaints, it is possible to quickly pinpoint areas with poor signal quality, further optimize site construction plans, and improve network coverage and service effectiveness.

[0003] However, the address information in user complaints is vast, some detailed and specific, others incomplete, requiring further statistical analysis. Furthermore, traditional manual statistical methods are inefficient and inaccurate. Summary of the Invention

[0004] This application provides a target area determination method, apparatus, and readable storage medium to improve the accuracy of determining base station locations.

[0005] To achieve the above objectives, this application adopts the following technical solution:

[0006] Firstly, a method for determining a target region is provided. The method includes: acquiring multiple addresses to be analyzed, where the addresses to be analyzed are the addresses of the terminal devices that send complaint information, and the complaint information is used to indicate abnormal communication signals of the terminal devices; determining multiple keywords from the multiple addresses to be analyzed; the area of ​​the region corresponding to the keyword is less than an area threshold; and determining a target region, where the target region is the region corresponding to the target keyword, and the target keyword is the keyword whose frequency of occurrence among the multiple keywords is greater than a ranking threshold.

[0007] Optionally, multiple keywords can be determined from multiple addresses to be analyzed, including: performing word segmentation on each address to be analyzed to obtain multiple word information; the number of bytes in the word information is greater than or equal to a byte number threshold; filtering out preset stop words from the multiple word information to obtain keywords for multiple addresses to be analyzed.

[0008] Optionally, the method further includes: determining the focus of the target area, where the focus is the ratio of complaining users in the target area to the number of users in the target area; and optimizing the network in the target area based on the focus.

[0009] Optionally, optimizing the network in the target area based on the focus degree includes: increasing the number of network devices in the target area when the focus degree is in the first focus interval; and increasing the coverage of network devices in the target area when the focus degree is in the second focus interval, wherein any focus degree in the second focus interval is less than any focus degree in the first focus interval.

[0010] Based on the technical solution provided in this application, after obtaining multiple addresses to be analyzed, multiple keywords can be identified from these addresses, thereby determining the target region. Since the target region is the area corresponding to the target keyword, and the target keyword is the keyword whose frequency of occurrence among multiple keywords is greater than a ranking threshold, that is, the high frequency of the target keyword's occurrence reflects a large number of complaining users in the area corresponding to the target keyword. Thus, the probability of network anomalies in the area corresponding to the target keyword is higher, improving the accuracy of target region identification. Furthermore, the area corresponding to the keyword is smaller than the area threshold, which filters out words with larger corresponding areas, reducing data processing volume and improving the efficiency of target region identification.

[0011] Secondly, a target area determination device is provided, comprising: an acquisition unit and a determination unit; the acquisition unit is used to acquire multiple addresses to be analyzed, the addresses to be analyzed being the addresses of the terminal devices that send complaint information, and the complaint information being used to indicate abnormal communication signals of the terminal devices; the determination unit is used to determine multiple keywords from the multiple addresses to be analyzed, wherein the area of ​​the region corresponding to the keyword is less than an area threshold; the determination unit is further used to determine a target region, the target region being the region corresponding to the target keyword, and the target keyword being the keyword whose frequency of occurrence among the multiple keywords ranks greater than a ranking threshold.

[0012] Optionally, the device further includes an acquisition unit and a determination unit, specifically used for: performing word segmentation on each address to be analyzed to obtain multiple word information; the number of bytes in the word information is greater than or equal to a byte number threshold; filtering preset stop words in the multiple word information to obtain keywords for multiple addresses to be analyzed.

[0013] Optionally, the device further includes a processing unit; a determining unit, further configured to: determine the focus of the target area, the focus being the ratio of complaining users in the target area to the number of users in the target area; and a processing unit, configured to: optimize the network of the target area based on the focus.

[0014] Optionally, the processing unit is specifically used to: increase the number of network devices in the target area when the focus is in the first focus interval; and increase the coverage of the network devices in the target area when the focus is in the second focus interval, wherein any focus in the second focus interval is less than any focus in the first focus interval.

[0015] Thirdly, a target region determination device is provided, which can realize the functions performed by the target region determination device in the above aspects or possible designs. The functions can be implemented by hardware. For example, in one possible design, the target region determination device may include a processor and a communication interface. The processor can be used to support the target region determination device in realizing the functions involved in the first aspect or any possible design of the first aspect.

[0016] In another possible design, the target region determination apparatus may further include a memory for storing necessary computer execution instructions and data. When the target region determination apparatus is in operation, the processor executes the computer execution instructions stored in the memory to cause the target region determination apparatus to perform the first aspect or any of the possible target region determination methods described above.

[0017] Fourthly, a computer-readable storage medium is provided, which may be a readable non-volatile storage medium storing computer instructions or programs that, when executed on a computer, enable the computer to perform the first aspect or any of the possible target area determination methods described above.

[0018] Fifthly, a computer program product containing instructions is provided, which, when run on a computer, enables the computer to execute the target region determination method of the first aspect or any possible design of the above aspects.

[0019] A sixth aspect provides an electronic device comprising one or more processors and one or more memories. The one or more memories are coupled to the one or more processors, and the one or more memories are used to store computer program code, including computer instructions, which, when executed by the one or more processors, cause the electronic device to perform the target region determination method as described in the first aspect or any possible design of the first aspect.

[0020] In a seventh aspect, a chip system is provided, including a processor and a communication interface, which can be used to implement the functions performed by the target region determination device in the first aspect or any possible design of the first aspect. In one possible design, the chip system further includes a memory for storing program instructions and / or data. The chip system may be composed of chips or may include chips and other discrete devices, without limitation. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of the structure of a target area determination system provided in an embodiment of this application;

[0022] Figure 2 This is a schematic diagram of the structure of a target area determination device provided in an embodiment of this application;

[0023] Figure 3 A flowchart illustrating a target region determination method provided in an embodiment of this application;

[0024] Figure 4 A flowchart illustrating another target region determination method provided in this application embodiment;

[0025] Figure 5 A flowchart illustrating another target region determination method provided in this application embodiment;

[0026] Figure 6 This is a functional diagram of a data preprocessing module provided in an embodiment of this application;

[0027] Figure 7 This is a functional diagram of a word frequency calculation module provided in an embodiment of this application;

[0028] Figure 8 A functional diagram of a strategy module provided in an embodiment of this application;

[0029] Figure 9 This is a schematic diagram of another target area determination device provided in an embodiment of this application. Detailed Implementation

[0030] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings.

[0031] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0032] It should also be understood that the term "comprising" indicates the presence of the described feature, whole, step, operation, element and / or component, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements and / or components.

[0033] User complaints are a crucial reference in the planning and maintenance of wireless communication networks. By analyzing the address information in user complaints, it is possible to quickly pinpoint areas with poor signal quality, further optimize site construction plans, and improve network coverage and service effectiveness.

[0034] In related technologies, all addresses to be matched can be determined based on the address string to be segmented; each address to be matched is traversed to obtain a result array; and a segmentation array is constructed based on the obtained result array to achieve address segmentation.

[0035] For example, an OCR recognition algorithm can be used to convert a business card image into text information. Then, using regular expression matching methods and a preset deep learning text classification model, sub-text information can be extracted from the text information according to preset categories and categorized sequentially.

[0036] For example, in response to a received message, information sent by the server in the message can be retrieved; the sensitive information database can be traversed using the information sent by the server, wherein the sensitive information database includes a tree structure for sensitive information; and if it is determined that the information sent by the server contains sensitive information, the detection result association information can be output according to a preset strategy.

[0037] However, the address information in user complaints is vast, some detailed and specific, others incomplete, requiring further statistical analysis. Furthermore, traditional manual statistical methods are inefficient and inaccurate.

[0038] In view of this, embodiments of this application provide a method for determining a target region, including:

[0039] Obtain multiple addresses to be analyzed, which are the addresses of the terminal devices that send complaint information. The complaint information is used to indicate abnormal communication signals of the terminal devices. Identify multiple keywords from the multiple addresses to be analyzed. The area of ​​the region corresponding to the keyword is less than the area threshold. Determine the target region, which is the region corresponding to the target keyword. The target keyword is the keyword whose frequency of occurrence is greater than the ranking threshold among the multiple keywords.

[0040] The methods provided in the embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0041] It should be noted that the network system described in the embodiments of this application is for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and does not constitute a limitation on the technical solutions provided in the embodiments of this application. As those skilled in the art will know, with the evolution of network systems and the emergence of other network systems, the technical solutions provided in the embodiments of this application are also applicable to similar technical problems.

[0042] Figure 1 The diagram shown is a schematic representation of a target area determination system 10 provided in an embodiment of this application. Figure 1 As shown, the target area determination system 10 may include a terminal device 11 and a server 12. For example, the terminal device 11 and the server 12 can be connected wirelessly.

[0043] In this application, the terminal device 11 involved in the embodiments can be used to report complaint information, including the address information of the terminal device. The terminal device 11 involved in this application can also be called a terminal, mobile station (MS), mobile terminal (MT), etc., and is a device that provides voice and / or data connectivity to a user. For example, the terminal device 11 can be a handheld device with wireless connectivity, an in-vehicle device, etc. Specifically, it can be a smartphone, pocket personal computer (PPC), handheld computer, personal digital assistant (PDA), laptop computer, tablet computer, wearable device, or in-vehicle device, etc. The embodiments of this application do not limit the specific technology, quantity, or form of the terminal device 11.

[0044] Server 12 can be used to determine a target area based on address information in complaint information. Server 12 can be a single server or a server cluster consisting of multiple servers. In some embodiments, the server cluster can also be a distributed cluster. This application does not limit the specific technology, quantity, or form of server 12.

[0045] It should be noted that, Figure 1 This is just an example framework diagram. Figure 1 The names of the various devices included are unrestricted, and except for Figure 1 In addition to the functional nodes shown, other nodes may also be included, but this application embodiment does not limit this.

[0046] In practical implementation, Figure 1 Each device in the process can be adopted Figure 2 The shown composition structure, or including Figure 2 The components shown. Figure 2This is a schematic diagram illustrating the composition of a target region determination device 200 provided in an embodiment of this application. The target region determination device 200 can be a server, or it can be a chip or system-on-a-chip within the server. Figure 2 As shown, the target area determination device 200 includes a processor 201, a communication interface 202, and a communication line 203.

[0047] Furthermore, the target area determination device 200 may also include a memory 204. The processor 201, memory 204, and communication interface 202 can be connected via a communication line 203.

[0048] The processor 201 can be a CPU, a general-purpose processor, a network processor (NP), a digital signal processor (DSP), a microprocessor, a microcontroller, a programmable logic device (PLD), or any combination thereof. The processor 201 can also be other devices with processing capabilities, such as circuits, devices, or software modules, without limitation.

[0049] Communication interface 202 is used to communicate with other devices or other communication networks. Communication interface 202 can be a module, circuit, communication interface, or any device capable of enabling communication.

[0050] Communication line 203 is used to transmit information between the components included in the target area determination device 200.

[0051] Memory 204 is used to store instructions. These instructions can be computer programs.

[0052] The memory 204 can be a read-only memory (ROM) or other type of static storage device that can store static information and / or instructions; it can also be a random access memory (RAM) or other type of dynamic storage device that can store information and / or instructions; it can also be an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, etc., without limitation.

[0053] It should be noted that the memory 204 can exist independently of the processor 201 or can be integrated with the processor 201. The memory 204 can be used to store instructions, program code, or some data, etc. The memory 204 can be located inside or outside the target region determining device 200, without limitation. The processor 201 is used to execute the instructions stored in the memory 204 to implement the target region determining method provided in the following embodiments of this application.

[0054] In one example, processor 201 may include one or more CPUs, for example, Figure 2 CPU0 and CPU1 in the CPU.

[0055] As an optional implementation, the target area determination device 200 includes multiple processors, for example, besides Figure 2 In addition to processor 201, it may also include processor 205.

[0056] It should be pointed out that, Figure 2 The composition shown does not constitute a basis for the interpretation of this invention. Figure 1 The limitations of each device in the process, except Figure 2 In addition to the components shown, Figure 1 The various devices in the can include ratio Figure 2 More or fewer components, or combinations of certain components, or different arrangements of components.

[0057] In this embodiment of the application, the chip system may be composed of chips or may include chips and other discrete devices.

[0058] Furthermore, the actions, terms, etc., involved in the various embodiments of this application can be referenced interchangeably without limitation. The message names or parameter names in the messages exchanged between the various devices in the embodiments of this application are merely examples, and other names may be used in specific implementations without limitation.

[0059] To facilitate a clear description of the technical solutions in the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish identical or similar items with essentially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, and the terms "first" and "second" are not necessarily different.

[0060] It should be noted that, in this application, the terms "exemplary" or "for example" are used to indicate that something is being described as an example, illustration, or illustration. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design solutions. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner.

[0061] In this application, "at least one" means one or more, and "more than one" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A alone, A and B simultaneously, or B alone, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0062] The following is combined with Figure 1 The target region determination system shown herein describes the target region determination method provided in the embodiments of this application.

[0063] Figure 3 This application provides a method for determining a target region, applicable to a server, but also applicable to devices within the server, such as chips. For example, the server can be... Figure 1 Server 12 in the example. This application uses a server as an example for illustration, such as... Figure 3 As shown, the method includes the following steps S301-S303:

[0064] S301. Obtain multiple addresses to be analyzed.

[0065] The multiple addresses to be analyzed are the addresses of the terminal devices sending the complaint information, which indicate abnormal communication signals of the terminal devices. For example, the multiple addresses to be analyzed could be "xx province xx city xx district xx," etc. Abnormal communication signals can include: no signal, signal strength less than the signal strength threshold, etc.

[0066] As one possible implementation, the terminal device can respond to control commands by sending complaint information to the server. The server then receives the complaint information and parses multiple addresses from it for analysis.

[0067] It should be noted that control commands can refer to instructions generated in response to control operations performed by an operator. For example, control commands can be instructions input by an end user through the input device of a terminal device (such as a touch screen).

[0068] In some embodiments, the addresses to be analyzed can be stored in a table (such as an Excel spreadsheet) on a storage device. The server can use the pandas library to read the Excel spreadsheet and obtain multiple addresses to be analyzed.

[0069] In practical applications, the server can read multiple addresses to be analyzed into Python.

[0070] S302. Identify multiple keywords from multiple addresses to be analyzed.

[0071] Among these, the area corresponding to the keyword is less than the area threshold. The area threshold can be set as needed, for example, it can be 3000 square meters.

[0072] As one possible implementation, the server can split each address to be analyzed into multiple word information and filter from the multiple word information to obtain multiple keywords.

[0073] Each word corresponds to a geographical region. For example, it could be: province, city, district, street, neighborhood, etc.

[0074] It should be noted that the specific steps for splitting each address to be analyzed into multiple word information and filtering from multiple word information to obtain multiple keywords can be referred to the following section, and will not be repeated here.

[0075] S303. Determine the target area.

[0076] The target region is the region corresponding to the target keyword, and the target keyword is the keyword whose frequency of occurrence among multiple keywords exceeds a ranking threshold. The ranking threshold can be set as needed. For example, it can be set to the top 50% of the rankings.

[0077] As one possible implementation, the server can determine the frequency of each keyword among multiple keywords, sort each keyword according to the frequency of occurrence, and if the ranking of a keyword is greater than the ranking threshold, then the keyword is taken as the target keyword, and the region corresponding to the target keyword is taken as the target region.

[0078] In one example, the server can use a pre-defined statistics library to determine the frequency of each keyword among multiple keywords. For example, the pre-defined statistics library could be a Python library such as os, glob, pandas, or nltk.

[0079] With the default statistics library being the nltk library, the server can use the FreqDist class in the nltk library to calculate the frequency of each word and find the top N words with the highest frequency.

[0080] In practical applications, FreqDist can perform word frequency statistics on text data such as lists and strings, and after completing the word frequency statistics, it returns a dictionary type containing the number of times each word appears.

[0081] Understandably, by using high-frequency words, we can identify which addresses are in areas with poor signal, which in turn helps network operators to more quickly identify network bottlenecks, reduce user churn, and improve user satisfaction.

[0082] Based on the technical solution provided in this application, after obtaining multiple addresses to be analyzed, multiple keywords can be identified from these addresses, thereby determining the target region. Since the target region is the area corresponding to the target keyword, and the target keyword is the keyword whose frequency of occurrence among multiple keywords is greater than a ranking threshold, that is, the high frequency of the target keyword's occurrence reflects a large number of complaining users in the area corresponding to the target keyword. Thus, the probability of network anomalies in the area corresponding to the target keyword is higher, improving the accuracy of target region identification. Furthermore, the area corresponding to the keyword is smaller than the area threshold, which filters out words with larger corresponding areas, reducing data processing volume and improving the efficiency of target region identification.

[0083] One possible implementation, such as Figure 4 As shown, the method for determining the target area in this application may further include the following steps S401-S402.

[0084] S401. Determine the focus of the target area.

[0085] The focus is the ratio of the number of complaining users in the target area to the number of users in the target area.

[0086] As one possible implementation, the server can determine the focus of the target area using the following formula.

[0087] For example, Formula 1 can be:

[0088]

[0089] Where p represents the focus of the target area, A represents the number of addresses to be analyzed within the target area, and N represents the total number of terminal devices within the target area.

[0090] S402. Optimize the network in the target area based on the focus.

[0091] As one possible implementation, the server can optimize the network of the target area based on the optimization strategy corresponding to the focus range where the focus is located.

[0092] The focus interval includes a first focus interval and a second focus interval. The optimization strategy for the first focus interval is to increase the number of network devices within the target area; the optimization strategy for the second focus interval is to increase the coverage area of ​​the network devices within the target area. Any focus level in the second focus interval is less than any focus level in the first focus interval.

[0093] If the server determines that the focus of the target area is within the first focus range, it can increase the number of network devices within the target area; if it determines that the focus of the target area is within the second focus range, it can increase the coverage of the network devices within the target area.

[0094] The first and second focusing intervals can be set as needed. For example, the first focusing interval can be 30%-100%, and the second focusing interval can be 0%-30%.

[0095] In some embodiments, adding a network device at a target location within a target area may include: determining the target location and setting the added network device at the target location.

[0096] The target location can be the coverage edge of network devices within the target area.

[0097] In some embodiments, increasing the coverage of network devices within the target area when the focus is in the second focus range may include adjusting the antenna downtilt angle of the target network device.

[0098] The adjusted antenna downtilt angle is smaller than the original antenna downtilt angle.

[0099] Understandably, optimizing the network in a target area based on different focuses can improve the efficiency and accuracy of network planning and maintenance, help network operators identify network bottlenecks more quickly, reduce user churn, and improve user satisfaction.

[0100] One possible implementation, such as Figure 5 As shown, in order to determine keywords for multiple addresses to be analyzed, the target area determination method of this application may further include the following steps S501-S502.

[0101] S501. Perform word segmentation on each address to be analyzed to obtain multiple word information.

[0102] The number of bytes for vocabulary information must be greater than or equal to a byte count threshold. This threshold can be set as needed; for example, it can be 4 bytes.

[0103] As one possible implementation, the server can use a pre-defined word segmentation tool to segment each address and obtain multiple word information.

[0104] For example, the default tokenization tool can be a regular expression tokenizer, the RegexpTokenizer class from the nltk library, etc.

[0105] S502. Filter the preset stop words in multiple word information to obtain the keywords of multiple addresses to be analyzed.

[0106] The preset stop words can be set as needed. For example, they can include provinces, cities, etc.

[0107] As one possible implementation, the server can obtain preset stop words from a preset stop word library, and delete word information that is the same as the preset stop words from multiple word information to filter the preset stop words in multiple word information and obtain keywords for multiple addresses to be analyzed.

[0108] It should be noted that the server can predetermine multiple preset stop words and input these preset stop words into the target database to form a preset stop word library.

[0109] For example, the server can iterate through each word and determine the area corresponding to each word, and identify words whose area is greater than or equal to the area threshold as preset stopped words.

[0110] In practical applications, the stop word list can be stored in a file named "stopwords.txt".

[0111] Understandably, by filtering preset stop words from multiple word information, the influence of some useless words can be reduced, and the efficiency of identifying target areas can be improved.

[0112] In one possible embodiment, the target region determination device in this application may include a data preprocessing module, a word frequency calculation module, and a processing module.

[0113] Figure 6 A functional diagram of a data preprocessing module is shown, such as... Figure 6 As shown, the data preprocessing module can be used to obtain multiple addresses to be analyzed, perform word segmentation on each address to be analyzed to obtain multiple vocabulary information, and set a deactivated vocabulary library.

[0114] Figure 7A functional diagram of a word frequency calculation module is shown, such as... Figure 7 As shown, the word frequency calculation module can be used to determine the number of times each word appears, and to identify keywords whose frequency of occurrence is greater than a ranking threshold among multiple keywords.

[0115] Figure 8 A functional diagram of a strategy module is shown, such as... Figure 8 As shown, the strategy module is used to set multiple focus intervals and the corresponding solution strategies for each focus interval, as well as to optimize the network of the target area based on the focus interval.

[0116] The various solutions in the above embodiments of this application can be combined without contradiction.

[0117] This application embodiment can divide the target area determination device into functional modules or functional units according to the above method example. For example, each function can be divided into a separate functional module or functional unit, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or in software functional modules or functional units. The module or unit division in this application embodiment is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0118] When dividing each function into modules according to its corresponding function. Figure 9 A schematic diagram of a target region determination device 900 is shown. The target region determination device can be a server or a chip applied in a server. The target region determination device 900 can be used to perform the functions of the server involved in the above embodiments. Figure 9 The target area determination device 900 shown may include: an acquisition unit 901 and a determination unit 902; the acquisition unit 901 is used to acquire multiple addresses to be analyzed, the addresses to be analyzed are the addresses of the terminal devices that send complaint information, and the complaint information is used to indicate that the communication signal of the terminal devices is abnormal; the determination unit 902 is used to determine multiple keywords from the multiple addresses to be analyzed; the area of ​​the region corresponding to the keyword is less than the area threshold; the determination unit 902 is also used to determine the target region, the target region is the region corresponding to the target keyword, and the target keyword is the keyword whose ranking of the number of occurrences is greater than the ranking threshold among the multiple keywords.

[0119] Optionally, the device further includes an acquisition unit 901; and a determination unit 902, specifically used for: performing word segmentation on each address to be analyzed to obtain multiple word information; the number of bytes in the word information is greater than or equal to a byte number threshold; filtering preset stop words in the multiple word information to obtain keywords for multiple addresses to be analyzed.

[0120] Optionally, the device further includes a processing unit 903; the determining unit 902 is further configured to: determine the focus of the target area, the focus being the ratio of the number of complaining users in the target area to the number of users in the target area; the processing unit 903 is configured to: optimize the network of the target area based on the focus.

[0121] Optionally, the processing unit 903 is specifically used to: increase the number of network devices in the target area when the focus is in the first focus interval; and increase the coverage of the network devices in the target area when the focus is in the second focus interval, wherein any focus in the second focus interval is less than any focus in the first focus interval.

[0122] This application also provides a computer-readable storage medium. All or part of the processes in the above method embodiments can be implemented by a computer program instructing related hardware. This program can be stored in the computer-readable storage medium, and when executed, it can include the processes of the above method embodiments. The computer-readable storage medium can be an internal storage unit of the target region determination device (including a data sending end and / or a data receiving end) in any of the foregoing embodiments, such as the hard disk or memory of the target region determination device. The computer-readable storage medium can also be an external storage device of the terminal device, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device. Further, the computer-readable storage medium can include both the internal storage unit of the target region determination device and an external storage device. The computer-readable storage medium is used to store the computer program and other programs and data required by the target region determination device. The computer-readable storage medium can also be used to temporarily store data that has been output or will be output.

[0123] It should be noted that the terms "first" and "second," etc., in the specification, claims, and drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0124] It should be understood that in this application, "at least one (item)" means one or more, "more than one" means two or more, "at least two (items)" means two or three or more, and "and / or" is used to describe the relationship between related objects, indicating that there can be three relationships. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the related objects before and after are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0125] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0126] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another apparatus, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0127] The units described as separate components may or may not be physically separate. A component shown as a unit can be one or more physical units; that is, it can be located in one place or distributed in multiple different locations. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0128] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0129] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, essentially or in other words, the parts that contribute to the prior art, or all or part of the technical solutions, can be embodied in the form of a software product. This software product is stored in a storage medium and includes several instructions to cause a device (which may be a microcontroller, chip, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0130] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for determining a target region, characterized in that, The method includes: Multiple addresses to be analyzed are obtained. The addresses to be analyzed are the addresses of the terminal devices that send complaint information. The complaint information is used to indicate that the communication signals of the terminal devices are abnormal. Each of the multiple addresses to be analyzed is segmented into words to obtain multiple word information; the number of bytes in the word information is greater than or equal to a byte number threshold. Determine the area of ​​the region corresponding to each word, and use words whose area is greater than or equal to the area threshold as preset stop words. Filter the preset stop words from the multiple word information to obtain the keywords of the multiple addresses to be analyzed; the area of ​​the region corresponding to the keyword is less than the area threshold; Determine the target region, which is the region corresponding to the target keyword, and the target keyword is the keyword whose frequency of occurrence among the multiple keywords is greater than a ranking threshold; Determine the focus of the target area, where the focus is the ratio of the number of complaining users in the target area to the number of users in the target area; Optimize the network in the target region based on the focus level.

2. The method according to claim 1, characterized in that, The process of optimizing the network for the target region based on the focus includes: When the focus is within the first focus range, increase the number of network devices within the target area; When the focus is within the second focus range, the coverage of network devices within the target area is increased, wherein any focus in the second focus range is less than any focus in the first focus range.

3. A target area determination device, characterized in that, The device includes: an acquisition unit, a determination unit, and a processing unit; The acquisition unit is used to acquire multiple addresses to be analyzed, the addresses to be analyzed are the addresses of the terminal devices that send complaint information, and the complaint information is used to indicate that the communication signals of the terminal devices are abnormal. The determining unit is used to perform word segmentation on each of the plurality of addresses to be analyzed to obtain a plurality of word information; the number of bytes in the word information is greater than or equal to a byte number threshold. The determining unit is also used to determine the area of ​​the region corresponding to each word information, and to use words whose area is greater than or equal to the area threshold as preset stop words. The determining unit is further configured to filter preset stop words from the plurality of word information to obtain keywords of the plurality of addresses to be analyzed; the area of ​​the region corresponding to the keyword is less than the area threshold. The determining unit is further configured to determine a target region, wherein the target region is the region corresponding to the target keyword, and the target keyword is the keyword whose frequency of occurrence among the plurality of keywords is greater than a ranking threshold; The determining unit is further configured to determine the focus of the target area, wherein the focus is the ratio of the number of complaining users in the target area to the number of users in the target area; The processing unit is used to optimize the network of the target region based on the focus.

4. The apparatus according to claim 3, characterized in that, The processing unit is specifically used for: When the focus is within the first focus range, increase the number of network devices within the target area; When the focus is within the second focus range, the coverage of network devices within the target area is increased, wherein any focus in the second focus range is less than any focus in the first focus range.

5. A computer-readable storage medium, characterized in that, The readable storage medium stores instructions that, when executed, implement the method as described in any one of claims 1-2.

6. A target area determination device, characterized in that, include: The processor, memory, and communication interface; wherein the communication interface is used for communication between the target area determining device and other devices or networks; The memory is used to store one or more programs, the one or more programs including computer-executable instructions, which, when the target region determining device is running, are executed by the processor to execute the computer-executable instructions stored in the memory to cause the target region determining device to perform the method of any one of claims 1-2.

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