WO2021139430A1 - 车辆召回提示信息的发送方法、装置、计算机设备 - Google Patents

车辆召回提示信息的发送方法、装置、计算机设备 Download PDF

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Publication number
WO2021139430A1
WO2021139430A1 PCT/CN2020/131769 CN2020131769W WO2021139430A1 WO 2021139430 A1 WO2021139430 A1 WO 2021139430A1 CN 2020131769 W CN2020131769 W CN 2020131769W WO 2021139430 A1 WO2021139430 A1 WO 2021139430A1
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information
recall
vehicle
identity information
vehicle identity
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PCT/CN2020/131769
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English (en)
French (fr)
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范骏超
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平安科技（深圳）有限公司
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/30—Administration of product recycling or disposal
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02W—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO WASTEWATER TREATMENT OR WASTE MANAGEMENT
    • Y02W90/00—Enabling technologies or technologies with a potential or indirect contribution to greenhouse gas [GHG] emissions mitigation

Definitions

  • This application relates to the field of artificial intelligence technology, and in particular to a method, device, and computer equipment for sending vehicle recall prompt information.
  • the embodiments of the application provide a method, device, computer equipment, and storage medium for sending vehicle recall reminder information, which are intended to solve the problem that the vehicle owner cannot be timely and accurate in the way of issuing recall notices in the existing prior art methods. Learn about the issue of recall information.
  • an embodiment of the present application provides a method for sending vehicle recall prompt information, which includes:
  • the vehicle recall prompt information corresponding to the recall analysis information is sent to the client corresponding to the information receiving address.
  • an embodiment of the present application provides a device for sending vehicle recall prompt information, which includes:
  • a newly-added recall notification acquisition unit is used to periodically monitor the recall notifications issued in the webpage to be monitored corresponding to the webpage information according to the preset monitoring cycle if the webpage information input by the user is received to obtain the newly added webpage information.
  • a recall notice analysis unit configured to analyze the newly added recall notice according to preset analysis rules to obtain corresponding recall analysis information
  • the matching unit is configured to match the vehicle identity information in the pre-stored database according to the recall analysis information, and use the vehicle identity information matching the recall analysis information as the target vehicle identity information;
  • the prompt information sending unit is configured to send the vehicle recall prompt information corresponding to the recall analysis information to the client corresponding to the information receiving address according to the information receiving address in the target vehicle identity information.
  • an embodiment of the present application provides a computer device, which includes a memory, a processor, and a computer program stored on the memory and running on the processor, and the processor executes the computer
  • the program implements the method for sending the vehicle recall prompt information described in the first aspect above.
  • the embodiments of the present application also provide a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the processor executes the above-mentioned first On the one hand, the method for sending reminder information of vehicle recall.
  • the embodiments of the present application provide a method, device, computer equipment, and storage medium for sending vehicle recall prompt information, which involve artificial intelligence technology.
  • the recall analysis information includes the recall scope information and the defect level
  • the target vehicle identity information that matches the recall analysis information is obtained from the database
  • the vehicle recall prompt information is sent To the client corresponding to the information receiving address in the target vehicle's identity information.
  • the above technical methods also involve big data processing.
  • the new recall notice is obtained through the monitoring webpage and automatically analyzed to obtain the recall analysis information.
  • the vehicle recall reminder information can be sent to the corresponding client in a targeted manner, which can ensure that the vehicle owner can obtain timely and accurate information. Recall information has greatly improved the efficiency of sending recall reminders.
  • FIG. 1 is a schematic flowchart of a method for sending vehicle recall prompt information provided by an embodiment of the application
  • FIG. 2 is a schematic diagram of an application scenario of a method for sending vehicle recall prompt information provided by an embodiment of the application
  • FIG. 3 is a schematic diagram of a sub-flow of a method for sending vehicle recall prompt information provided by an embodiment of the application;
  • FIG. 4 is a schematic diagram of another sub-flow of the method for sending vehicle recall prompt information provided by an embodiment of the application;
  • FIG. 5 is a schematic diagram of another flow chart of a method for sending vehicle recall prompt information provided by an embodiment of the application
  • FIG. 6 is a schematic diagram of another sub-flow of the method for sending vehicle recall prompt information according to an embodiment of the application.
  • FIG. 7 is a schematic diagram of another sub-flow of the method for sending vehicle recall prompt information according to an embodiment of the application.
  • FIG. 8 is a schematic block diagram of a device for sending vehicle recall prompt information according to an embodiment of the application.
  • FIG. 9 is a schematic block diagram of a computer device provided by an embodiment of the application.
  • FIG. 1 is a schematic flowchart of a method for sending vehicle recall prompt information provided by an embodiment of the present application
  • FIG. 2 is a schematic diagram of an application scenario of a method for sending vehicle recall prompt information provided by an embodiment of the present application.
  • the method for sending vehicle recall prompt information is applied to the management server 10.
  • the method is executed by the application software installed in the management server 10.
  • the management server 10 communicates with at least one client 20, and the client can use the client 20 to
  • the newly-added vehicle identity information is sent to the management server 10.
  • the management server 10 verifies the newly-added vehicle identity information and adds it to the database after passing.
  • the management server 10 monitors the webpage to be monitored to obtain the new recall notification.
  • the database obtains the target vehicle identity information corresponding to the newly added recall notice and sends the vehicle recall prompt information to the client 20 corresponding to the information receiving address in the target vehicle identity information.
  • the management server 10 can monitor the webpage to be monitored and send the vehicle recall
  • the client terminal 10 may be a terminal device with an information receiving function and an information sending function, such as a desktop computer, a notebook computer, a tablet computer, or a mobile phone.
  • the method includes steps S110 to S140.
  • the recall notice issued in the webpage to be monitored corresponding to the webpage information is periodically monitored according to a preset monitoring period to obtain a new recall notice.
  • the monitoring period is the pre-set time period for periodic monitoring of the webpage to be monitored.
  • the user is also the administrator of the management server.
  • the management server can periodically monitor the webpage to be monitored according to the monitoring period, so as to obtain the current period of time.
  • the issued recall notice is taken as a new recall notice and acquired, and the current acquisition period is the time period between the current time and the last acquisition time.
  • the web address information of the webpage to be monitored is the web address information corresponding to the webpage input by the user to be monitored.
  • the webpage to be monitored can be a news website, an automobile portal website, a government website, etc., which publish notices about automobile recalls on the Internet.
  • the newly-added recall notice can be text, picture or PDF document; if the newly-added recall notice is picture or PDF document, it can be converted into picture or PDF format by OCR recognition (Optical Character Recognition) Corresponding text information.
  • S120 Analyze the newly added recall notice according to a preset analysis rule to obtain corresponding recall analysis information.
  • the analysis rules include item keywords and a defect level matching model; the recall analysis information includes recall range information and defect levels.
  • the parsing rules are the rules for parsing new recall notices recorded in text form. Through parsing, some important information can be obtained from the content contained in the new recall notices.
  • the item keyword is the keyword information for matching the information contained in the newly added recall notice to obtain the corresponding item information, and all the obtained item information can also be used as the recall scope information corresponding to the newly added recall notice; defect level
  • the matching model is the matching model that matches the recall range information to obtain the corresponding defect level, and the defect level is used to indicate the severity of the defect of the recalled vehicle in the new recall notice.
  • step S120 includes sub-steps S121 and S122.
  • the project keywords include but are not limited to: model series, model year, recalled quantity, recall description, production date range, VIN (Vehicle Identification Number, vehicle identification code) range; for new recall notices that are related to the project keywords
  • VIN Vehicle Identification Number, vehicle identification code
  • the matched character is located, and part of the text information from the character to the end symbol is further obtained as the item information corresponding to the item keyword, where the end symbol can be ",", ";” or ".”; the obtained
  • the item information corresponding to each item keyword is composed of the recall scope information of the newly-added recall notice.
  • S122 Acquire a defect level corresponding to the recall range information according to the defect level matching model.
  • the defect level matching model includes item information quantification rules, neural networks, and level matching rules. Specifically, the item information contained in the recall range information can be quantified according to the item information quantification rules to obtain the corresponding quantified value, and the quantified value is input to the nerve The network obtains the corresponding quantitative score, and further obtains the defect level corresponding to the quantitative score according to the level matching rules.
  • the item information corresponding to the model series, recall number, recall description, and production date range can be quantified to obtain the corresponding quantified value, and the quantified value can be input into the trained neural network to obtain the corresponding quantified score, according to the level matching rules Obtain the defect level corresponding to the obtained quantitative score by the classification interval information in, and then obtain the defect level corresponding to the recall range information.
  • the defect level can be divided into minor, severe, severe, and very severe.
  • step S122 includes sub-steps S1221, S1222, and S1223.
  • Item information quantification rules are rules for quantifying multiple item information contained in the recall scope information. If the recall scope information contains multiple items, the item information quantification rules include specific rules for quantifying the item information of each item. .
  • the project information of the model series includes the vehicle brand and vehicle model. The quantitative value corresponding to the vehicle brand and the quantitative value corresponding to the vehicle model can be obtained from the project information quantification rules, and the quantified value corresponding to the vehicle model can be obtained by adding them to the model series. The quantitative value corresponding to this item; the number of recalls is divided by a preset value to obtain the corresponding quantitative value.
  • the item information quantification rule includes multiple recall description keywords, and each recall description keyword corresponds to a quantitative value, which can be obtained from the information Get the recall description keywords that match the recall description in the quantification rules, and add the quantified values of the matching recall description keywords to get the quantified value corresponding to the recall description.
  • the generation date range is obtained by obtaining evidence in months and converting it into years. The corresponding quantized value.
  • the quantization value corresponding to "GXX” in the vehicle series is 1.1, and the quantization value corresponding to "350” is 0.2, then the quantization value of the vehicle series GXX-350 is obtained.
  • the quantitative value corresponding to the number of recalls of 2395 is 2.395; the keywords of the recall description matching the information quantification rules are "turn (1.2), bolt (0.5), corrosion (1.5), fracture (1.8)", then The quantitative value corresponding to the recall description is 5, and the production date range is rounded to 6 months by month, and the corresponding quantitative value is 0.5.
  • the neural network in the project information quantification rule is a trained neural network.
  • the neural network includes multiple input nodes, a fully connected layer, and an output node.
  • An input node corresponds to the quantized value of a project, and an output node corresponds to all
  • the obtained quantitative score the fully connected layer contains multiple feature units, and each feature unit is associated with all input nodes and all output nodes.
  • the feature unit can be used to reflect the difference between the quantitative value corresponding to the recall range information and the quantitative score. connection relation.
  • Training is the process of adjusting the parameters in the calculation formula.
  • the multiple quantized values obtained are input to the corresponding input node as the input value of the neural network, and the output value corresponding to the output node can be calculated through the calculation formula in the trained neural network, and the obtained output value is the quantized score .
  • the level matching rule includes multiple grading intervals, and each grading interval corresponds to a defect level, and the defect level corresponding to the grading interval where the quantitative score is located is obtained as the defect level corresponding to the recall range information.
  • the quantitative score calculated according to the neural network is 7.78; the level matching rule contains three grading intervals: [0, 2]-slight, (2, 5]-medium, (5-10)-severe, corresponding to 7.78 If the grading interval of is (5, 10), the defect level corresponding to the recall range information in Table 1 is obtained as serious.
  • the recall analysis information can be obtained by combining the recall range information and the defect level.
  • S130 Match the vehicle identity information in the pre-stored database according to the recall analysis information, and use the vehicle identity information matching the recall analysis information as the target vehicle identity information.
  • the vehicle identity information in the pre-stored database is matched according to the recall analysis information, and the vehicle identity information that matches the recall analysis information is used as the target vehicle identity information.
  • the recall analysis information includes recall scope information and defect levels.
  • the database is the database pre-stored in the management server to record the vehicle identity information.
  • the vehicle identity information recorded in the database is the information sent to the server by the client and verified.
  • the vehicle identity information contains the vehicle identification code ( Vehicle Identification Number, VIN), vehicle owner information, information receiving address, etc., where the vehicle identification code is the unique identification information corresponding to the vehicle, and the vehicle owner information is the personal identification information of the owner of the vehicle, and the information receiving address That is, the address information filled in by the owner to receive the prompt information sent by the server.
  • the recall range information is matched with the identity information of each vehicle in the database to determine whether each vehicle identity information matches the recall range information, and the vehicle identity that matches the recall range information can be obtained.
  • the information serves as the target vehicle's identity information.
  • step S130 includes sub-steps S131, S132, and S133.
  • S131 Determine whether the vehicle identification code in each of the vehicle identity information is included in the identification code range in the recall range information.
  • the vehicle identification code is a character string containing seventeen characters
  • the steps to determine whether the vehicle identification code belongs to the identification code range include: 1. Obtain the vehicle identification code of a vehicle identity information in the database, and identify the vehicle Determine whether the first eight digits of the code match the first eight digits of the identification code range; 2. If the result of step 1 is a match, then determine whether the last six digits of the vehicle identification code belong to the last six digits of the identification code range. Range; 3. If the judgment result of step 1 is not a match, then judge whether the first six digits of the vehicle identification code match the first six digits of the identification code range; 4.
  • Step 2 execute Step 2; 5. If the judgment result of step 3 does not match, the judgment result that the vehicle identification code is not included in the identification code range is obtained; 6. If the judgment result of step 2 is belonging, the vehicle identification code is obtained The judgment result of the code range; 7. If the judgment result in step 1 is not included, the judgment result that the vehicle identification code is not included in the identification code range is obtained.
  • the vehicle identification code is included in the identification code range, it is judged whether the vehicle identification code matches the production date range in the recall range information.
  • the information represented by the tenth character in the vehicle identification code is the year of production of the vehicle, and 30 years is a cycle, and it is judged whether the tenth character in the vehicle identification code matches the production date range.
  • the corresponding information between the tenth character in the vehicle identification code and the year of production is shown in Table 2.
  • the vehicle identification code and the production in the recall range information Date range matches.
  • the vehicle identification information corresponding to the vehicle identification code is determined as the target vehicle identification information. If the vehicle identification code matches the production date range, the vehicle identification information corresponding to the vehicle identification code is used as the target vehicle identification information that matches the recall range information. If the vehicle identification code is not included in the identification code range or the vehicle identification code does not match the production date range, the vehicle identification information corresponding to the vehicle identification code is not the target vehicle identification information, and the next vehicle identification stored in the database is obtained Code and repeat the above judgment.
  • step S1310 is further included before step S130.
  • S1310 If the newly-added vehicle identity information from the client is received, verify the newly-added vehicle identity information and store the newly-added vehicle identity information in the database after the verification is passed.
  • the newly-added vehicle identity information is received from the client, the newly-added vehicle identity information is verified and the newly-added vehicle identity information is stored in the database after the verification is passed.
  • the vehicle owner of the client can use the client to register in the management server. During the registration process, the vehicle owner needs to fill in the complete vehicle identity information and send it to the management server to complete the registration process.
  • the management server After the management server receives the newly-added vehicle identity information from the client, it can verify whether the newly-added vehicle identity information meets the preset verification rules, and only the newly-added vehicle identity information that meets the verification rules can be stored in the database.
  • step S1310 includes sub-steps S1311 and S1312.
  • the vehicle identification code in the newly added vehicle identity information is verified according to a preset verification rule to obtain a verification result of whether it is passed.
  • the vehicle identification code in the newly added vehicle identity information is verified according to a preset verification rule to obtain a verification result of whether it is passed.
  • the newly-added vehicle identification information includes the vehicle identification code.
  • the ninth character in the vehicle identification code is the check digit of the vehicle identification code.
  • the specific verification rules are: (1) First, use the information in Table 3.
  • the letters in the identification code are correspondingly converted into numbers; (2) According to the weighted value information in Table 4, the number corresponding to each character in the vehicle identification code is multiplied by the weighted value and then added to obtain the weighted calculation value; (3) ) Divide the weighted calculated value by 11 and take the remainder, the remainder is the calculated check value; (4) Determine whether the check value matches the ninth character in the vehicle identification code to obtain the verification result of whether it is passed (If the check value is 10, it is judged whether the ninth character in the vehicle identification code is "X").
  • the newly-added vehicle identity information is added to the database for storage. Only the newly-added vehicle identity information that meets the verification rules can be stored in the database. If the verification result of the newly-added vehicle identity information is verified, it is added to the database for storage.
  • step S1313 is further included after step S1311.
  • S140 According to the information receiving address in the target vehicle identity information, send the vehicle recall prompt information corresponding to the recall analysis information to the client corresponding to the information receiving address.
  • the vehicle recall prompt information corresponding to the recall analysis information is sent to the client corresponding to the information receiving address.
  • the target vehicle identity information contains the information receiving address, and the vehicle recall prompt information corresponding to the recall analysis information can be sent to the client according to the client corresponding to the information receiving address.
  • the recall analysis information can also include the recall time, recall address and other information.
  • the recall time is the time information for the car manufacturer to receive the recalled vehicle
  • the recall address is the address information for the car manufacturer to receive the recalled vehicle.
  • the model series, defect level, recall time, and recall address in the recall analysis information generate corresponding vehicle recall prompt information and send it to the client.
  • the new recall notification is obtained from the web page to be monitored and analyzed to obtain the recall analysis information.
  • the recall analysis information includes the recall scope information and defects Level, obtain the target vehicle identity information matching the recall analysis information from the database, and send the vehicle recall prompt information to the client corresponding to the information receiving address in the target vehicle identity information.
  • the above technical methods also involve big data processing.
  • the new recall notice is obtained through the monitoring webpage and automatically analyzed to obtain the recall analysis information.
  • the vehicle recall reminder information can be sent to the corresponding client in a targeted manner, which can ensure that the vehicle owner can obtain timely and accurate information. Recall information has greatly improved the efficiency of sending recall reminders.
  • An embodiment of the present application also provides a device for sending vehicle recall reminder information.
  • the device for sending vehicle recall reminder information is used to execute any embodiment of the aforementioned method for sending vehicle recall reminder information.
  • FIG. 8 is a schematic block diagram of a device for sending vehicle recall prompt information according to an embodiment of the present application.
  • the sending device of the vehicle recall prompt information may be configured in the management server 10.
  • the device 100 for sending reminder information of vehicle recall includes: a newly-added recall notification acquiring unit 110, a recall notification analyzing unit 120, a matching unit 130, and a reminding information sending unit 140.
  • a new recall notification obtaining unit 110 is added, which is used to periodically monitor the recall notices issued in the webpage to be monitored corresponding to the webpage information according to the preset monitoring period if the webpage information input by the user is received to obtain new information. Increased recall notice.
  • the recall notification analysis unit 120 is configured to analyze the newly added recall notification according to a preset analysis rule to obtain corresponding recall analysis information.
  • the recall notification analysis unit 120 includes: a recall range information acquisition unit and a defect level acquisition unit.
  • the recall range information acquiring unit is used to acquire the recall range information corresponding to the item keyword in the newly added recall notice; the defect level acquiring unit is used to acquire the information corresponding to the recall range according to the defect level matching model The defect level.
  • the defect level acquisition unit includes: an item information quantification unit, a quantitative score acquisition unit, and a defect level matching unit.
  • the item information quantization unit is configured to quantify multiple item information in the recall range information according to the item information quantization rule to obtain corresponding quantized values; the quantized score obtaining unit is configured to use the quantized value as an input value
  • the neural network is input to use the output value as a quantitative score corresponding to the recall range information; a defect level matching unit is used to obtain a defect level matching the quantitative score according to the level matching rule.
  • the matching unit 130 is configured to match the vehicle identity information in the pre-stored database according to the recall analysis information, and use the vehicle identity information matching the recall analysis information as the target vehicle identity information.
  • the matching unit 130 includes: a vehicle identification code judgment unit, a production date range matching unit, and a target vehicle identity information determining unit.
  • the vehicle identification code determination unit is used to determine whether the vehicle identification code in each of the vehicle identification information is included in the identification code range in the recall range information; the production date range matching unit is used to determine whether the vehicle identification code is included in the identification code range of the recall range information; The code is included in the identification code range, and it is judged whether the vehicle identification code matches the production date range in the recall range information; the target vehicle identity information determination unit is configured to determine whether the vehicle identification code matches the production date range in the recall range information. The production date range is matched, and the vehicle identity information corresponding to the vehicle identification code is determined as the target vehicle identity information.
  • the device 100 for sending vehicle recall prompt information includes: a newly added vehicle identity information verification unit.
  • the newly added vehicle identity information verification unit is configured to, if the newly added vehicle identity information from the client is received, verify the newly added vehicle identity information and store the newly added vehicle identity information in the database after the verification is passed.
  • the newly-added vehicle identity information verification unit includes: a vehicle identification code verification unit and a vehicle identity information storage unit.
  • the vehicle identification code verification unit is used to verify the vehicle identification code in the newly added vehicle identity information according to a preset verification rule to obtain a verification result of whether it is passed; the vehicle identity information storage unit is used to verify the verification result In order to pass the verification, the newly-added vehicle identity information is added to the database for storage.
  • the newly added vehicle identity information verification unit further includes: a prompt unit.
  • the prompt unit is configured to, if the verification result is that the verification fails, according to the information receiving address in the newly added vehicle identity information, send a prompt message indicating that the information verification fails to the client corresponding to the information receiving address.
  • the prompt information sending unit 140 is configured to send the vehicle recall prompt information corresponding to the recall analysis information to the client corresponding to the information receiving address according to the information receiving address in the target vehicle identity information.
  • the vehicle recall reminder information sending device applies the aforementioned method for sending vehicle recall reminder information, and obtains the recall analysis information according to the new recall notification obtained from the web page to be monitored and analyzed.
  • the analysis information includes recall scope information and defect level, the target vehicle identity information matching the recall analysis information is obtained from the database, and the vehicle recall prompt information is sent to the client corresponding to the information receiving address in the target vehicle identity information.
  • the above technical methods also involve big data processing.
  • the new recall notice is obtained through the monitoring webpage and automatically analyzed to obtain the recall analysis information.
  • the vehicle recall reminder information can be sent to the corresponding client in a targeted manner, which can ensure that the vehicle owner can obtain timely and accurate information. Recall information has greatly improved the efficiency of sending recall reminders.
  • the foregoing device for sending vehicle recall prompt information may be implemented in the form of a computer program, and the computer program may run on a computer device as shown in FIG. 9.
  • FIG. 9 is a schematic block diagram of a computer device according to an embodiment of the present application.
  • the computer device 500 includes a processor 502, a memory, and a network interface 505 connected through a system bus 501, where the memory may include a non-volatile storage medium 503 and an internal memory 504.
  • the non-volatile storage medium 503 can store an operating system 5031 and a computer program 5032.
  • the processor 502 can execute the method for sending the vehicle recall prompt information.
  • the processor 502 is used to provide calculation and control capabilities, and support the operation of the entire computer device 500.
  • the internal memory 504 provides an environment for the operation of the computer program 5032 in the non-volatile storage medium 503.
  • the processor 502 can execute the method for sending vehicle recall prompt information.
  • the network interface 505 is used for network communication, such as providing data information transmission.
  • the structure shown in FIG. 9 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device 500 to which the solution of the present application is applied.
  • the specific computer device 500 may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.
  • the processor 502 is configured to run a computer program 5032 stored in a memory, so as to implement the corresponding function in the aforementioned method for sending vehicle recall prompt information.
  • the embodiment of the computer device shown in FIG. 9 does not constitute a limitation on the specific configuration of the computer device.
  • the computer device may include more or less components than those shown in the figure. Or some parts are combined, or different parts are arranged.
  • the computer device may only include a memory and a processor. In such embodiments, the structures and functions of the memory and the processor are consistent with the embodiment shown in FIG. 9 and will not be repeated here.
  • the processor 502 may be a central processing unit (Central Processing Unit, CPU), and the processor 502 may also be other general-purpose processors, digital signal processors (Digital Signal Processors, DSPs), Application Specific Integrated Circuit (ASIC), Field-Programmable Gate Array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc.
  • the general-purpose processor may be a microprocessor or the processor may also be any conventional processor.
  • a computer-readable storage medium may be a non-volatile computer-readable storage medium, or may be a volatile computer-readable storage medium.
  • the computer-readable storage medium stores a computer program, where the computer program, when executed by a processor, implements the steps included in the aforementioned method for sending vehicle recall prompt information.
  • the disclosed equipment, device, and method may be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the units is only a logical function division. In actual implementation, there may be other division methods, or the units with the same function may be combined into one. Units, for example, multiple units or components can be combined or integrated into another system, or some features can be omitted or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may also be electrical, mechanical or other forms of connection.
  • the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments of the present application.
  • the functional units in the various embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit can be implemented in the form of hardware or software functional unit.
  • the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.
  • the technical solution of this application is essentially or the part that contributes to the existing technology, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product can be stored in a computer.
  • the read storage medium includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application.
  • the computer-readable storage medium is a tangible, non-transitory storage medium, and the computer-readable storage medium may be an internal storage unit of the aforementioned device, such as a physical storage medium such as a hard disk or a memory of the device.
  • the storage medium may also be an external storage device of the device, such as a plug-in hard disk equipped on the device, a smart memory card (Smart Media Card, SMC), a Secure Digital (SD) card, and a flash memory card. (Flash Card) and other physical storage media.

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Abstract

一种车辆召回提示信息的发送方法、装置及存储介质，其中方法包括：从待监控网页获取新增召回通知（S110）并进行解析得到召回解析信息，召回解析信息包括召回范围信息及缺陷等级（S120），从数据库中获取与召回解析信息相匹配的目标车辆身份信息（S130），发送车辆召回提示信息至与目标车辆身份信息中的信息接收地址对应的客户端（S140）。基于业务过程优化技术，通过监控网页获取新增召回通知并自动解析得到召回解析信息，可针对性地发送车辆召回提示信息至对应的客户端，可确保车辆所有人可以及时、精准获取召回信息，大幅提高了召回提示信息的发送效率。

Description

车辆召回提示信息的发送方法、装置、计算机设备
本申请要求于2020年07月22日提交中国专利局、申请号为202010711395.1，发明名称为“车辆召回提示信息的发送方法、装置、计算机设备”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及人工智能技术领域，尤其涉及一种车辆召回提示信息的发送方法、装置、计算机设备。
背景技术
随着社会经济的快速发展，人民物质生活水平不断提高，越来越多的家庭拥有了属于自己的汽车。然而汽车不同于其他消费品，汽车的质量关乎每一位乘员的安全，汽车完成售卖后，在其使用过程中依然会因各种缺陷而逐步暴露质量问题，为对车辆所有人的安全负责，各汽车厂家会不定时发布召回通知，对存在质量问题的部分汽车实施召回维修。
然而发明人发现，现有的召回通知均是非定向发布于各大新闻网站、汽车门户网站等，由于汽车的所有人无法保证能够随时关注到与该汽车的品牌相关的召回通知，并且该所有人在查看召回通知的过程中还需仔细核对其所拥有的汽车是否包含于召回通知的召回范围内，因此这一发布方式导致汽车的所有人无法及时、精准获取相应的召回信息，也即是无法及时、准确获取其所拥有的汽车是否应当被召回的信息。因而，现有的技术方法中的召回通知发布方式存在车辆所有人无法及时、精准获悉召回信息的问题。
发明内容
本申请实施例提供了一种车辆召回提示信息的发送方法、装置、计算机设备及存储介质，旨在解决现有的现有技术方法中的召回通知发布方式所存在的车辆所有人无法及时、精准获悉召回信息的问题。
第一方面，本申请实施例提供了一种车辆召回提示信息的发送方法，其包括：
若接收到用户所输入的网页信息，根据预置的监控周期对与所述网页信息对应的待监控网页中所发布的召回通知进行周期性监控以获取新增召回通知；
根据预置的解析规则对所述新增召回通知进行解析以得到对应的召回解析信息；
根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将与所述召回解析信息相匹配的车辆身份信息作为目标车辆身份信息；
根据所述目标车辆身份信息中的信息接收地址，向所述信息接收地址对应的客户端发送与所述召回解析信息对应的车辆召回提示信息。
第二方面，本申请实施例提供了一种车辆召回提示信息的发送装置，其包括：
新增召回通知获取单元，用于若接收到用户所输入的网页信息，根据预置的监控周期对与所述网页信息对应的待监控网页中所发布的召回通知进行周期性监控以获取新增召回通知；
召回通知解析单元，用于根据预置的解析规则对所述新增召回通知进行解析以得到对应的召回解析信息；
匹配单元，用于根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将 与所述召回解析信息相匹配的车辆身份信息作为目标车辆身份信息；
提示信息发送单元，用于根据所述目标车辆身份信息中的信息接收地址，向所述信息接收地址对应的客户端发送与所述召回解析信息对应的车辆召回提示信息。
第三方面，本申请实施例又提供了一种计算机设备，其包括存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序，所述处理器执行所述计算机程序时实现上述第一方面所述的车辆召回提示信息的发送方法。
第四方面，本申请实施例还提供了一种计算机可读存储介质，其中所述计算机可读存储介质存储有计算机程序，所述计算机程序当被处理器执行时使所述处理器执行上述第一方面所述的车辆召回提示信息的发送方法。
本申请实施例提供了一种车辆召回提示信息的发送方法、装置、计算机设备及存储介质，涉及人工智能技术。根据从待监控网页获取新增召回通知并进行解析得到召回解析信息，召回解析信息包括召回范围信息及缺陷等级，从数据库中获取与召回解析信息相匹配的目标车辆身份信息，发送车辆召回提示信息至与目标车辆身份信息中的信息接收地址对应的客户端。上述技术方法还涉及大数据处理，通过监控网页获取新增召回通知并自动解析得到召回解析信息，可针对性地发送车辆召回提示信息至对应的客户端，可确保车辆所有人可以及时、精准获取召回信息，大幅提高了召回提示信息的发送效率。
附图说明
为了更清楚地说明本申请实施例技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。
图1为本申请实施例提供的车辆召回提示信息的发送方法的流程示意图；
图2为本申请实施例提供的车辆召回提示信息的发送方法的应用场景示意图；
图3为本申请实施例提供的车辆召回提示信息的发送方法的子流程示意图；
图4为本申请实施例提供的车辆召回提示信息的发送方法的另一子流程示意图；
图5为本申请实施例提供的车辆召回提示信息的发送方法的另一流程示意图；
图6为本申请实施例提供的车辆召回提示信息的发送方法的另一子流程示意图；
图7为本申请实施例提供的车辆召回提示信息的发送方法的另一子流程示意图；
图8为本申请实施例提供的车辆召回提示信息的发送装置的示意性框图；
图9为本申请实施例提供的计算机设备的示意性框图。
具体实施方式
下面将结合本申请实施例中的附图，对本申请实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本申请一部分实施例，而不是全部的实施例。基于本申请中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本申请保护的范围。
应当理解，当在本说明书和所附权利要求书中使用时，术语“包括”和“包含”指示所描述特征、整体、步骤、操作、元素和/或组件的存在，但并不排除一个或多个其它特征、整体、步骤、操作、元素、组件和/或其集合的存在或添加。
还应当理解，在此本申请说明书中所使用的术语仅仅是出于描述特定实施例的目的而并 不意在限制本申请。如在本申请说明书和所附权利要求书中所使用的那样，除非上下文清楚地指明其它情况，否则单数形式的“一”、“一个”及“该”意在包括复数形式。
还应当进一步理解，在本申请说明书和所附权利要求书中使用的术语“和/或”是指相关联列出的项中的一个或多个的任何组合以及所有可能组合，并且包括这些组合。
请参阅图1及图2，图1是本申请实施例提供的车辆召回提示信息的发送方法的流程示意图；图2为本申请实施例提供的车辆召回提示信息的发送方法的应用场景示意图。该车辆召回提示信息的发送方法应用于管理服务器10中，该方法通过安装于管理服务器10中的应用软件进行执行，管理服务器10与至少一台客户端20进行通信，客户可通过客户端20将新增车辆身份信息发送至管理服务器10，管理服务器10对新增车辆身份信息进行验证并在通过后加入至数据库中，管理服务器10对待监控网页进行监控以获取新增召回通知，管理服务器10从数据库获取与新增召回通知对应的目标车辆身份信息后发送车辆召回提示信息至与目标车辆身份信息中的信息接收地址对应的客户端20，管理服务器10即为可监控待监控网页并发送车辆召回提示信息的企业终端，客户端10可以是具有信息接收功能及信息发送功能的终端设备，例如台式电脑、笔记本电脑、平板电脑或手机等。
如图1所示，该方法包括步骤S110～S140。
S110、若接收到用户所输入的网页信息，根据预置的监控周期对与所述网页信息对应的待监控网页中所发布的召回通知进行周期性监控以获取新增召回通知。
若接收到用户所输入的网页信息，根据预置的监控周期对与所述网页信息对应的待监控网页中所发布的召回通知进行周期性监控以获取新增召回通知。其中，监控周期即为预先设置的对待监控网页进行周期性监控的时间周期，用户也即是管理服务器的管理员，管理服务器可根据监控周期对待监控网页进行周期性监控，以将当前获取时段内所发布的召回通知作为新增召回通知并进行获取，当前获取时段即为当前时间与上一次获取时间之间的时间段。其中，待监控网页的网址信息即为用户所输入需进行监控的网页所对应的网址信息，待监控网页可以是新闻网站、汽车门户网站、政府网站等在互联网上发布有关汽车召回通知的网站。新增召回通知可以是文字、图片或PDF文档；若新增召回通知为图片或PDF文档，则可通过OCR识别(Optical Character Recognition，光学字符识别)将图片或PDF格式的新增召回通知转换为对应的文字信息。
S120、根据预置的解析规则对所述新增召回通知进行解析以得到对应的召回解析信息。
根据预置的解析规则对所述新增召回通知进行解析以得到对应的召回解析信息。其中，所述解析规则中包括项目关键字以及缺陷等级匹配模型；所述召回解析信息中包括召回范围信息及缺陷等级。解析规则即为对以文字形式进行记载的新增召回通知进行解析的规则，通过解析即可从新增召回通知所包含的内容中获取部分重要的信息。项目关键字即为对新增召回通知中所包含的信息进行匹配以获取对应的项目信息的关键字信息，所得到的所有项目信息也可作为与新增召回通知对应的召回范围信息；缺陷等级匹配模型即为对召回范围信息进行匹配以获取对应缺陷等级的匹配模型，缺陷等级即是用于表示新增召回通知中召回车辆存在缺陷的严重程度。
在一具体的实施例中，如图3所示，步骤S120包括子步骤S121和S122。
S121、获取所述新增召回通知中与所述项目关键字对应的召回范围信息。
获取所述新增召回通知中与所述项目关键字对应的召回范围信息。具体的，项目关键字包括但不限于：车型系列、年款、召回数量、召回描述、生产日期范围、VIN(Vehicle Identification Number，车辆识别码)范围；对新增召回通知中与项目关键字相匹配的字符进行定位，并进一步获取该字符至结束符号的部分文字信息作为与该项目关键字对应的项目信息，其中，结束符号可以是“，”、“；”或“。”；所得到的与每一项目关键字对应的项目信息组成为该新增召回通知的召回范围信息。
例如，根据上述项目关键字所得到的一份召回范围信息如表1所示。
Figure PCTCN2020131769-appb-000001
表1
S122、根据所述缺陷等级匹配模型获取与所述召回范围信息对应的缺陷等级。
根据所述缺陷等级匹配模型获取与所述召回范围信息对应的缺陷等级。缺陷等级匹配模型包括项目信息量化规则、神经网络及等级匹配规则，具体的，可根据项目信息量化规则对召回范围信息中所包含的项目信息进行量化得到对应的量化值，并将量化值输入神经网络得到对应的量化分数，并根据等级匹配规则进一步获取与量化分数对应的缺陷等级。具体的，可将车型系列、召回数量、召回描述、生产日期范围所对应的项目信息进行量化得到对应的量化值，并将量化值输入经过训练的神经网络得到对应的量化分数，根据等级匹配规则中的分级区间信息获取与所得到的量化分数对应的缺陷等级，即可获取与召回范围信息对应的缺陷等级，缺陷等级可以分为轻微、严重、较严重和十分严重。
在一具体的实施例中，如图4所示，步骤S122包括子步骤S1221、S1222和S1223。
S1221、根据所述项目信息量化规则对所述召回范围信息中的多个项目信息进行量化以得到对应的量化值。
项目信息量化规则即为对召回范围信息中所包含的多个项目信息进行量化的规则，召回范围信息中包含多个项目，则项目信息量化规则包含对每一项目的项目信息进行量化的具体规则。车型系列这一项目的项目信息中包含车辆品牌及车辆型号，可从项目信息量化规则中分别获取与车辆品牌所对应的量化值及与车辆型号所对应的量化值，相加后得到与车型系列这一项目所对应的量化值；召回数量除以一预设数值得到对应的量化值，项目信息量化规则中包括多个召回描述关键字，每一召回描述关键字对应一个量化值，可从信息量化规则中获取与召回描述相匹配的召回描述关键字，并将相匹配的召回描述关键字的量化值相加得到与召回描述对应的量化值，生成日期范围按月数取证并折算成年份得到对应的量化值。
例如，对表1中的项目信息分别进行量化，车辆系列中“GXX”对应的量化值为1.1，“350”对应的量化值为0.2，则车辆系列GXX-350进行量化得到对应的量化值为1.3；召回数量2395对应的量化值为2.395；召回描述与信息量化规则相匹配的召回描述关键字分别为“转向(1.2)、 螺栓(0.5)、腐蚀(1.5)、断裂(1.8)”，则与召回描述对应的量化值为5，生产日期范围按月份取整为6个月，则对应的量化值为0.5。
S1222、将所述量化值作为输入值输入所述神经网络以将输出值作为与所述召回范围信息对应的量化分数。
项目信息量化规则中的神经网络为训练后的神经网络，神经网络中包括多个输入节点、全连接层及一个输出节点，一个输入节点与一个项目的量化值相对应，一个输出节点即对应所得到的量化分数，全连接层中包含多个特征单元，每一个特征单元均与所有输入节点和所有输出节点进行关联，特征单元可用于反映召回范围信息所对应的量化值与量化分数之间的关联关系。特征单元与输入节点及输出节点之间的关联关系可采用计算公式进行体现，计算公式可表示为y i＝a×x i+b；其中，a和b为该公式中的参数，对神经网络进行训练也即是计算公式中参数进行调整的过程。将所得到的多个量化值作为神经网络的输入值输入对应的输入节点，通过训练后的神经网络中的计算公式即可计算得到输出节点对应的输出值，所得到的输出值即为量化分数。
S1223、根据所述等级匹配规则获取与所述量化分数相匹配的缺陷等级。
等级匹配规则中包含多个分级区间，每一分级区间对应一个缺陷等级，获取量化分数所处的分级区间对应的缺陷等级作为与召回范围信息对应的缺陷等级。
例如，根据神经网络计算得到的量化分数为7.78；等级匹配规则中包含三个分级区间：[0，2]–轻微，(2，5]–中等，(5-10]–严重，与7.78对应的分级区间为(5，10]，则得到与表1中的召回范围信息对应的缺陷等级为严重。将召回范围信息及缺陷等级组合即可得到召回解析信息。
S130、根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将与所述召回解析信息相匹配的车辆身份信息作为目标车辆身份信息。
根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将与所述召回解析信息相匹配的车辆身份信息作为目标车辆身份信息。所述召回解析信息中包括召回范围信息及缺陷等级。数据库即为管理服务器中预存的用于对车辆身份信息进行记录的数据库，数据库中所记录的车辆身份信息即为客户端发送至服务器并经过验证后的信息，车辆身份信息中包含车辆识别码(Vehicle Identification Number，VIN)、车辆所有人信息、信息接收地址等，其中，车辆识别码即为与车辆唯一对应的识别信息，车辆所有人信息即为车辆的所有人的个人身份信息，信息接收地址即为该所有人所填写的用于接收服务器所发送的提示信息的地址信息。根据所得到的召回解析信息中的召回范围信息与数据库中的每一车辆身份信息进行匹配，即可确定每一车辆身份信息是否与召回范围信息相匹配，获取与召回范围信息相匹配的车辆身份信息作为目标车辆身份信息。
在一具体的实施例中，如图5所示，步骤S130包括子步骤S131、S132和S133。
S131、对每一所述车辆身份信息中的车辆识别码是否包含于所述召回范围信息中的识别码范围进行判断。
对每一所述车辆身份信息中的车辆识别码是否包含于所述召回范围信息中的识别码范围进行判断。具体的，车辆识别码为一个包含十七位字符的字符串，对车辆识别码是否属于识别码范围进行判断的步骤包括：1、获取数据库中一个车辆身份信息的车辆识别码，对该车辆 识别码的前八位是否与识别码范围的前八位相匹配进行判断；2、若步骤1判断结果为相匹配，则判断该车辆识别码的后六位是否属于识别码范围后六位所限定的范围；3、若步骤1判断结果为不相匹配，则对该车辆识别码的前六位是否与识别码范围的前六位相匹配进行判断；4、若步骤3判断结果为相匹配，则执行步骤2；5、若步骤3判断结果为不相匹配，则得到该车辆识别码不包含于识别码范围的判断结果；6、若步骤2判断结果为属于，则得到该车辆识别码包含于识别码范围的判断结果；7、若步骤1判断结果为不属于，则得到该车辆识别码不包含于识别码范围的判断结果。
S132、若所述车辆识别码包含于所述识别码范围，对所述车辆识别码是否与所述召回范围信息中的生产日期范围相匹配进行判断。
若所述车辆识别码包含于所述识别码范围，对所述车辆识别码是否与所述召回范围信息中的生产日期范围相匹配进行判断。具体的，车辆识别码中的第十位字符所表示的信息即为车辆的生产年份，30年为一个周期，判断车辆识别码中的第十位是否与生产日期范围相匹配。其中，车辆识别码中第十位字符与生产年份的对应信息如表2所示。
生产年份 字符 生产年份 字符 生产年份 字符
1991 M 2001 1 2011 B
1992 N 2002 2 2012 C
1993 P 2003 3 2013 D
1994 R 2004 4 2014 E
1995 S 2005 5 2015 F
1996 T 2006 6 2016 G
1997 V 2007 7 2017 H
1998 W 2008 8 2018 J
1999 X 2009 9 2019 K
2000 Y 2010 A 2020 L
表2
例如，某一车辆识别码中的第十位字符为K，生产日期范围为起：2018-12-17、止：2019-06-19，则判断得到该车辆识别码与召回范围信息中的生产日期范围相匹配。
S133、若所述车辆识别码与所述生产日期范围相匹配，将与所述车辆识别码对应的车辆身份信息确定为目标车辆身份信息。
若所述车辆识别码与所述生产日期范围相匹配，将与所述车辆识别码对应的车辆身份信息确定为目标车辆身份信息。若车辆识别码与生产日期范围相匹配，则该车辆识别码所对应的车辆身份信息即作为与召回范围信息相匹配的目标车辆身份信息。若车辆识别码不包含于识别码范围或者车辆识别码不与生产日期范围相匹配，则该车辆识别码所对应的车辆身份信息不为目标车辆身份信息，获取数据库中所存储的下一车辆识别码并重复进行上述判断。
在一具体的实施例中，如图6所示，步骤S130之前还包括步骤S1310。
S1310、若接收到来自客户端的新增车辆身份信息，验证所述新增车辆身份信息并在验证通过后将所述新增车辆身份信息存储至所述数据库中。
若接收到来自客户端的新增车辆身份信息，验证所述新增车辆身份信息并在验证通过后将所述新增车辆身份信息存储至所述数据库中。客户端的车辆所有人可使用客户端在管理服务器中进行登记注册，在登记注册过程中，该车辆所有人需填写完整的车辆身份信息并发送至管理服务器以完成登记注册的流程。管理服务器接收来自客户端的新增车辆身份信息后，即可对该新增车辆身份信息是否符合预置的验证规则进行验证，只有符合验证规则的新增车辆身份信息才能存储至数据库中。
在一具体的实施例中，步骤S1310包括子步骤S1311和S1312。
S1311、根据预置的验证规则对所述新增车辆身份信息中的车辆识别码进行验证以得到是否通过的验证结果。
根据预置的验证规则对所述新增车辆身份信息中的车辆识别码进行验证以得到是否通过的验证结果。新增车辆身份信息中包括车辆识别码，车辆识别码中的第九位字符即为该车辆识别码的校验位，具体的校验规则为：(1)首先通过表3中的信息将车辆识别码中的字母对应转换为数字；(2)根据表4中的加权值信息，将车辆识别码中每一位字符对应的数字进行与加权值相乘后相加得到加权计算值；(3)将加权计算值除以11并取余，余数即为计算得到的校验值；(4)判断校验值是否与车辆识别码中的第九位字符相匹配即可得到是否通过的验证结果(若校验值为10，则判断车辆识别码中的第九位字符是否为“X”)。
字母 数字 字母 数字 字母 数字 字母 数字
A 1 G 7 N 5 V 5
B 2 H 8 P 7 W 6
C 3 J 1 R 9 X 7
D 4 K 2 S 2 Y 8
E 5 L 3 T 3 Z 9
F 6 M 4 U 4    
表3
位数 一 二 三 四 五 六 七 八
加权值 8 7 6 5 4 3 2 10
位数 十 十一 十二 十三 十四 十五 十六 十七
加权值 9 8 7 6 5 4 3 2
表4
S1312、若所述验证结果为验证通过，将所述新增车辆身份信息添加至所述数据库中进行存储。
若所述验证结果为验证通过，将所述新增车辆身份信息添加至所述数据库中进行存储。只有符合验证规则的新增车辆身份信息才能存储至数据库中，若新增车辆身份信息的验证结果为验证通过，则添加至数据库中进行存储。
在一具体的实施例中，如图7所示，步骤S1311之后还包括步骤S1313。
S1313、若所述验证结果为验证不通过，根据所述新增车辆身份信息中的信息接收地址，向所述信息接收地址对应的客户端发送信息验证不通过的提示信息。
S140、根据所述目标车辆身份信息中的信息接收地址，向所述信息接收地址对应的客户端发送与所述召回解析信息对应的车辆召回提示信息。
根据所述目标车辆身份信息中的信息接收地址，向所述信息接收地址对应的客户端发送与所述召回解析信息对应的车辆召回提示信息。目标车辆身份信息中包含信息接收地址，可根据信息接收地址所对应的客户端，发送与召回解析信息对应的车辆召回提示信息至该客户端。具体的，召回解析信息中还可以包括召回时间、召回地址等信息，召回时间即为汽车生产商接收被召回车辆的时间信息，召回地址即为汽车生产商接收被召回车辆的地址信息，可根据召回解析信息中的车型系列、缺陷等级、召回时间及召回地址等信息生成对应的车辆召回提示信息，并发送至该客户端。
在本申请涉及人工智能技术，在实施例所提供的车辆召回提示信息的发送方法中，根据从待监控网页获取新增召回通知并进行解析得到召回解析信息，召回解析信息包括召回范围信息及缺陷等级，从数据库中获取与召回解析信息相匹配的目标车辆身份信息，发送车辆召回提示信息至与目标车辆身份信息中的信息接收地址对应的客户端。上述技术方法还涉及大数据处理，通过监控网页获取新增召回通知并自动解析得到召回解析信息，可针对性地发送车辆召回提示信息至对应的客户端，可确保车辆所有人可以及时、精准获取召回信息，大幅提高了召回提示信息的发送效率。
本申请实施例还提供一种车辆召回提示信息的发送装置，该车辆召回提示信息的发送装置用于执行前述车辆召回提示信息的发送方法的任一实施例。具体地，请参阅图8，图8是本申请实施例提供的车辆召回提示信息的发送装置的示意性框图。该车辆召回提示信息的发送装置可以配置于管理服务器10中。
如图8所示，车辆召回提示信息的发送装置100包括：新增召回通知获取单元110、召回通知解析单元120、匹配单元130和提示信息发送单元140。
新增召回通知获取单元110，用于若接收到用户所输入的网页信息，根据预置的监控周期对与所述网页信息对应的待监控网页中所发布的召回通知进行周期性监控以获取新增召回通知。
召回通知解析单元120，用于根据预置的解析规则对所述新增召回通知进行解析以得到对应的召回解析信息。
在一具体的实施例中，所述召回通知解析单元120包括：召回范围信息获取单元及缺陷等级获取单元。
召回范围信息获取单元，用于获取所述新增召回通知中与所述项目关键字对应的召回范围信息；缺陷等级获取单元，用于根据所述缺陷等级匹配模型获取与所述召回范围信息对应的缺陷等级。
在一具体的实施例中，所述缺陷等级获取单元包括：项目信息量化单元、量化分数获取单元及缺陷等级匹配单元。
项目信息量化单元，用于根据所述项目信息量化规则对所述召回范围信息中的多个项目信息进行量化以得到对应的量化值；量化分数获取单元，用于将所述量化值作为输入值输入 所述神经网络以将输出值作为与所述召回范围信息对应的量化分数；缺陷等级匹配单元，用于根据所述等级匹配规则获取与所述量化分数相匹配的缺陷等级。
匹配单元130，用于根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将与所述召回解析信息相匹配的车辆身份信息作为目标车辆身份信息。
在一具体的实施例中，所述匹配单元130包括：车辆识别码判断单元、生产日期范围匹配单元及目标车辆身份信息确定单元。
车辆识别码判断单元，用于对每一所述车辆身份信息中的车辆识别码是否包含于所述召回范围信息中的识别码范围进行判断；生产日期范围匹配单元，用于若所述车辆识别码包含于所述识别码范围，对所述车辆识别码是否与所述召回范围信息中的生产日期范围相匹配进行判断；目标车辆身份信息确定单元，用于若所述车辆识别码与所述生产日期范围相匹配，将与所述车辆识别码对应的车辆身份信息确定为目标车辆身份信息。
在一具体的实施例中，所述车辆召回提示信息的发送装置100包括：新增车辆身份信息验证单元。
新增车辆身份信息验证单元，用于若接收到来自客户端的新增车辆身份信息，验证所述新增车辆身份信息并在验证通过后将所述新增车辆身份信息存储至所述数据库中。
在一具体的实施例中，所述新增车辆身份信息验证单元包括：车辆识别码验证单元及车辆身份信息存储单元。
车辆识别码验证单元，用于根据预置的验证规则对所述新增车辆身份信息中的车辆识别码进行验证以得到是否通过的验证结果；车辆身份信息存储单元，用于若所述验证结果为验证通过，将所述新增车辆身份信息添加至所述数据库中进行存储。
在一具体的实施例中，所述新增车辆身份信息验证单元还包括：提示单元。
提示单元，用于若所述验证结果为验证不通过，根据所述新增车辆身份信息中的信息接收地址，向所述信息接收地址对应的客户端发送信息验证不通过的提示信息。
提示信息发送单元140，用于根据所述目标车辆身份信息中的信息接收地址，向所述信息接收地址对应的客户端发送与所述召回解析信息对应的车辆召回提示信息。
在本申请涉及人工智能技术，在实施例所提供的车辆召回提示信息的发送装置应用上述车辆召回提示信息的发送方法，根据从待监控网页获取新增召回通知并进行解析得到召回解析信息，召回解析信息包括召回范围信息及缺陷等级，从数据库中获取与召回解析信息相匹配的目标车辆身份信息，发送车辆召回提示信息至与目标车辆身份信息中的信息接收地址对应的客户端。上述技术方法还涉及大数据处理，通过监控网页获取新增召回通知并自动解析得到召回解析信息，可针对性地发送车辆召回提示信息至对应的客户端，可确保车辆所有人可以及时、精准获取召回信息，大幅提高了召回提示信息的发送效率。
上述车辆召回提示信息的发送装置可以实现为计算机程序的形式，该计算机程序可以在如图9所示的计算机设备上运行。
请参阅图9，图9是本申请实施例提供的计算机设备的示意性框图。
参阅图9，该计算机设备500包括通过系统总线501连接的处理器502、存储器和网络接口505，其中，存储器可以包括非易失性存储介质503和内存储器504。
该非易失性存储介质503可存储操作系统5031和计算机程序5032。该计算机程序5032 被执行时，可使得处理器502执行车辆召回提示信息的发送方法。
该处理器502用于提供计算和控制能力，支撑整个计算机设备500的运行。
该内存储器504为非易失性存储介质503中的计算机程序5032的运行提供环境，该计算机程序5032被处理器502执行时，可使得处理器502执行车辆召回提示信息的发送方法。
该网络接口505用于进行网络通信，如提供数据信息的传输等。本领域技术人员可以理解，图9中示出的结构，仅仅是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的计算机设备500的限定，具体的计算机设备500可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
其中，所述处理器502用于运行存储在存储器中的计算机程序5032，以实现上述的车辆召回提示信息的发送方法中对应的功能。
本领域技术人员可以理解，图9中示出的计算机设备的实施例并不构成对计算机设备具体构成的限定，在其他实施例中，计算机设备可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。例如，在一些实施例中，计算机设备可以仅包括存储器及处理器，在这样的实施例中，存储器及处理器的结构及功能与图9所示实施例一致，在此不再赘述。
应当理解，在本申请实施例中，处理器502可以是中央处理单元(Central Processing Unit，CPU)，该处理器502还可以是其他通用处理器、数字信号处理器(Digital Signal Processor，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、现成可编程门阵列(Field-Programmable Gate Array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。其中，通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
在本申请的另一实施例中提供计算机可读存储介质。该计算机可读存储介质可以为非易失性的计算机可读存储介质，也可以是易失性的计算机可读存储介质。该计算机可读存储介质存储有计算机程序，其中计算机程序被处理器执行时实现上述的车辆召回提示信息的发送方法中所包含的步骤。
所属领域的技术人员可以清楚地了解到，为了描述的方便和简洁，上述描述的设备、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、计算机软件或者二者的结合来实现，为了清楚地说明硬件和软件的可互换性，在上述说明中已经按照功能一般性地描述了各示例的组成及步骤。这些功能究竟以硬件还是软件方式来执行取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
在本申请所提供的几个实施例中，应该理解到，所揭露的设备、装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为逻辑功能划分，实际实现时可以有另外的划分方式，也可以将具有相同功能的单元集合成一个单元，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另外，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口、装置或单元的间接耦合或通信连接，也可以是电的，机械的或其它的形式连接。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本申请实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以是两个或两个以上单元集成在一个单元中。上述集成的单元既可以采用硬件的形式实现，也可以采用软件功能单元的形式实现。
所述集成的单元如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分，或者该技术方案的全部或部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个计算机可读存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请各个实施例所述方法的全部或部分步骤。
所述计算机可读存储介质为实体的、非瞬时性的存储介质，所述计算机可读存储介质可以是前述设备的内部存储单元，例如设备的硬盘或内存等实体存储介质。所述存储介质也可以是所述设备的外部存储设备，例如所述设备上配备的插接式硬盘，智能存储卡(Smart Media Card,SMC)，安全数字(Secure Digital,SD)卡，闪存卡(Flash Card)等实体存储介质。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到各种等效的修改或替换，这些修改或替换都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以权利要求的保护范围为准。

Claims (20)

  1. 一种车辆召回提示信息的发送方法，应用于管理服务器，所述管理服务器与至少一台客户端进行通信，其中，所述方法包括：
    若接收到用户所输入的网页信息，根据预置的监控周期对与所述网页信息对应的待监控网页中所发布的召回通知进行周期性监控以获取新增召回通知；
    根据预置的解析规则对所述新增召回通知进行解析以得到对应的召回解析信息，所述召回解析信息包括召回范围信息及缺陷等级；
    根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将与所述召回解析信息相匹配的车辆身份信息作为目标车辆身份信息；
    根据所述目标车辆身份信息中的信息接收地址，向所述信息接收地址对应的客户端发送与所述召回解析信息对应的车辆召回提示信息。
  2. 根据权利要求1所述的车辆召回提示信息的发送方法，其中，所述解析规则包括项目关键字及缺陷等级匹配模型，所述根据预置的解析规则对所述新增召回通知进行解析以得到对应的召回解析信息，包括：
    获取所述新增召回通知中与所述项目关键字对应的召回范围信息；
    根据所述缺陷等级匹配模型获取与所述召回范围信息对应的缺陷等级。
  3. 根据权利要求1所述的车辆召回提示信息的发送方法，其中，所述根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将与所述召回解析信息相匹配的车辆身份信息作为目标车辆身份信息，包括：
    对每一所述车辆身份信息中的车辆识别码是否包含于所述召回范围信息中的识别码范围进行判断；
    若所述车辆识别码包含于所述识别码范围，对所述车辆识别码是否与所述召回范围信息中的生产日期范围相匹配进行判断；
    若所述车辆识别码与所述生产日期范围相匹配，将与所述车辆识别码对应的车辆身份信息确定为目标车辆身份信息。
  4. 根据权利要求1所述的车辆召回提示信息的发送方法，其中，所述根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将与所述召回解析信息相匹配的车辆身份信息作为目标车辆身份信息之前，还包括：
    若接收到来自客户端的新增车辆身份信息，验证所述新增车辆身份信息并在验证通过后将所述新增车辆身份信息存储至所述数据库中。
  5. 根据权利要求4所述的车辆召回提示信息的发送方法，其中，所述验证所述新增车辆身份信息并在验证通过后将所述新增车辆身份信息存储至所述数据库中，包括：
    根据预置的验证规则对所述新增车辆身份信息中的车辆识别码进行验证以得到是否通过的验证结果；
    若所述验证结果为验证通过，将所述新增车辆身份信息添加至所述数据库中进行存储。
  6. 根据权利要求2所述的车辆召回提示信息的发送方法，其中，所述缺陷等级匹配模型 包括项目信息量化规则、神经网络及等级匹配规则，所述根据所述缺陷等级匹配模型获取与所述召回范围信息对应的缺陷等级，包括：
    根据所述项目信息量化规则对所述召回范围信息中的多个项目信息进行量化以得到对应的量化值；
    将所述量化值作为输入值输入所述神经网络以将输出值作为与所述召回范围信息对应的量化分数；
    根据所述等级匹配规则获取与所述量化分数相匹配的缺陷等级。
  7. 根据权利要求5所述的车辆召回提示信息的发送方法，其中，所述根据预置的验证规则对所述新增车辆身份信息中的车辆识别码进行验证以得到是否通过的验证结果之后，还包括：
    若所述验证结果为验证不通过，根据所述新增车辆身份信息中的信息接收地址，向所述信息接收地址对应的客户端发送信息验证不通过的提示信息。
  8. 一种车辆召回提示信息的发送装置，包括：
    新增召回通知获取单元，用于若接收到用户所输入的网页信息，根据预置的监控周期对与所述网页信息对应的待监控网页中所发布的召回通知进行周期性监控以获取新增召回通知；
    召回通知解析单元，用于根据预置的解析规则对所述新增召回通知进行解析以得到对应的召回解析信息；
    匹配单元，用于根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将与所述召回解析信息相匹配的车辆身份信息作为目标车辆身份信息；
    提示信息发送单元，用于根据所述目标车辆身份信息中的信息接收地址，向所述信息接收地址对应的客户端发送与所述召回解析信息对应的车辆召回提示信息。
  9. 一种计算机设备，包括存储器、处理器及存储在所述存储器上并可在所述处理器上运行的计算机程序，其中，所述处理器执行所述计算机程序时实现以下步骤：
    若接收到用户所输入的网页信息，根据预置的监控周期对与所述网页信息对应的待监控网页中所发布的召回通知进行周期性监控以获取新增召回通知；
    根据预置的解析规则对所述新增召回通知进行解析以得到对应的召回解析信息，所述召回解析信息包括召回范围信息及缺陷等级；
    根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将与所述召回解析信息相匹配的车辆身份信息作为目标车辆身份信息；
    根据所述目标车辆身份信息中的信息接收地址，向所述信息接收地址对应的客户端发送与所述召回解析信息对应的车辆召回提示信息。
  10. 根据权利要求9所述的计算机设备，其中，所述解析规则包括项目关键字及缺陷等级匹配模型，所述根据预置的解析规则对所述新增召回通知进行解析以得到对应的召回解析信息，包括：
    获取所述新增召回通知中与所述项目关键字对应的召回范围信息；
    根据所述缺陷等级匹配模型获取与所述召回范围信息对应的缺陷等级。
  11. 根据权利要求9所述的计算机设备，其中，所述根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将与所述召回解析信息相匹配的车辆身份信息作为目标车 辆身份信息，包括：
    对每一所述车辆身份信息中的车辆识别码是否包含于所述召回范围信息中的识别码范围进行判断；
    若所述车辆识别码包含于所述识别码范围，对所述车辆识别码是否与所述召回范围信息中的生产日期范围相匹配进行判断；
    若所述车辆识别码与所述生产日期范围相匹配，将与所述车辆识别码对应的车辆身份信息确定为目标车辆身份信息。
  12. 根据权利要求9所述的计算机设备，其中，所述根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将与所述召回解析信息相匹配的车辆身份信息作为目标车辆身份信息之前，还包括：
    若接收到来自客户端的新增车辆身份信息，验证所述新增车辆身份信息并在验证通过后将所述新增车辆身份信息存储至所述数据库中。
  13. 根据权利要求12所述的计算机设备，其中，所述验证所述新增车辆身份信息并在验证通过后将所述新增车辆身份信息存储至所述数据库中，包括：
    根据预置的验证规则对所述新增车辆身份信息中的车辆识别码进行验证以得到是否通过的验证结果；
    若所述验证结果为验证通过，将所述新增车辆身份信息添加至所述数据库中进行存储。
  14. 根据权利要求10所述的计算机设备，其中，所述缺陷等级匹配模型包括项目信息量化规则、神经网络及等级匹配规则，所述根据所述缺陷等级匹配模型获取与所述召回范围信息对应的缺陷等级，包括：
    根据所述项目信息量化规则对所述召回范围信息中的多个项目信息进行量化以得到对应的量化值；
    将所述量化值作为输入值输入所述神经网络以将输出值作为与所述召回范围信息对应的量化分数；
    根据所述等级匹配规则获取与所述量化分数相匹配的缺陷等级。
  15. 根据权利要求13所述的计算机设备，其中，所述根据预置的验证规则对所述新增车辆身份信息中的车辆识别码进行验证以得到是否通过的验证结果之后，还包括：
    若所述验证结果为验证不通过，根据所述新增车辆身份信息中的信息接收地址，向所述信息接收地址对应的客户端发送信息验证不通过的提示信息。
  16. 一种计算机可读存储介质，其中，所述计算机可读存储介质存储有计算机程序，所述计算机程序当被处理器执行时使所述处理器执行以下操作：
    若接收到用户所输入的网页信息，根据预置的监控周期对与所述网页信息对应的待监控网页中所发布的召回通知进行周期性监控以获取新增召回通知；
    根据预置的解析规则对所述新增召回通知进行解析以得到对应的召回解析信息，所述召回解析信息包括召回范围信息及缺陷等级；
    根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将与所述召回解析信息相匹配的车辆身份信息作为目标车辆身份信息；
    根据所述目标车辆身份信息中的信息接收地址，向所述信息接收地址对应的客户端发送 与所述召回解析信息对应的车辆召回提示信息。
  17. 根据权利要求16所述的计算机可读存储介质，其中，所述解析规则包括项目关键字及缺陷等级匹配模型，所述根据预置的解析规则对所述新增召回通知进行解析以得到对应的召回解析信息，包括：
    获取所述新增召回通知中与所述项目关键字对应的召回范围信息；
    根据所述缺陷等级匹配模型获取与所述召回范围信息对应的缺陷等级。
  18. 根据权利要求16所述的计算机可读存储介质，其中，所述根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将与所述召回解析信息相匹配的车辆身份信息作为目标车辆身份信息，包括：
    对每一所述车辆身份信息中的车辆识别码是否包含于所述召回范围信息中的识别码范围进行判断；
    若所述车辆识别码包含于所述识别码范围，对所述车辆识别码是否与所述召回范围信息中的生产日期范围相匹配进行判断；
    若所述车辆识别码与所述生产日期范围相匹配，将与所述车辆识别码对应的车辆身份信息确定为目标车辆身份信息。
  19. 根据权利要求16所述的计算机可读存储介质，其中，所述根据所述召回解析信息对预存数据库中的车辆身份信息进行匹配，以将与所述召回解析信息相匹配的车辆身份信息作为目标车辆身份信息之前，还包括：
    若接收到来自客户端的新增车辆身份信息，验证所述新增车辆身份信息并在验证通过后将所述新增车辆身份信息存储至所述数据库中。
  20. 根据权利要求19所述的计算机可读存储介质，其中，所述验证所述新增车辆身份信息并在验证通过后将所述新增车辆身份信息存储至所述数据库中，包括：
    根据预置的验证规则对所述新增车辆身份信息中的车辆识别码进行验证以得到是否通过的验证结果；
    若所述验证结果为验证通过，将所述新增车辆身份信息添加至所述数据库中进行存储。
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