Intelligent quotation method and device, electronic equipment and storage medium

Abstract

The invention provides an intelligent quotation method, and relates to the technical field of automobile insurance digitization and the like. The method comprises the following steps: in response to a quotation instruction received in a chat interface, acquiring insurance demand information and image data corresponding to a to-be-insured vehicle; according to the similarity between the insurance demand information and description information of each candidate package in a database, determining a target package; identifying and extracting text contents in the image data to obtain parameter information of the to-be-insured vehicle; and determining a quotation result according to a quotation algorithm corresponding to the target package and the parameter information, and displaying the quotation result on a chat interface. Therefore, the operation process of quotation can be simplified, the flexibility and efficiency of vehicle insurance quotation can be improved, the use scene of quotation service can be expanded, and the user experience can be optimized.

Description

Technical Field

[0001] This application relates to technical fields such as digitalization of auto insurance, and particularly relates to an intelligent quotation method, device, electronic device, and storage medium. Background Art

[0002] Auto insurance is an important means to protect the rights and interests of vehicles and vehicle owners. With the continuous increase in the number of automobiles in use, the demand in the auto insurance market is growing day by day. Improving the simplicity and flexibility of auto insurance quotations is the key to enhancing the competitiveness of insurance companies and improving customer satisfaction. Summary of the Invention

[0003] This application aims to solve at least one of the technical problems in the related art to some extent.

[0004] To this end, the first object of this application is to propose an intelligent quotation method to realize the automatic selection of preset packages that meet the insurance needs by using optical character recognition technology and text similarity algorithms, obtain the parameters of the vehicle to be quoted, and then obtain the quotation result, so as to improve the efficiency of auto insurance quotations.

[0005] The second object of this application is to propose an intelligent quotation device.

[0006] The third object of this application is to propose an electronic device.

[0007] The fourth object of this application is to propose a computer-readable storage medium.

[0008] The fifth object of this application is to propose a computer program product.

[0009] To achieve the above object, an intelligent quotation method according to an embodiment of the first aspect of this application includes:

[0010] Respond to the quotation instruction received in the chat interface, and obtain the insurance demand information and the image data corresponding to the vehicle to be insured;

[0011] Determine the target package according to the similarity between the insurance demand information and the description information of each candidate package in the database;

[0012] Identify and extract the text content in the image data to obtain the parameter information of the vehicle to be insured;

[0013] Determine the quotation result according to the quotation algorithm corresponding to the target package and the parameter information, and display it in the chat interface.

[0014] To achieve the above object, an intelligent quotation device according to an embodiment of the second aspect of this application includes:

[0015] A first acquisition module, configured to acquire insurance demand information and image data corresponding to a vehicle to be insured in response to a quotation instruction received in a chat interface;

[0016] A first determination module, configured to determine a target package according to the similarity between the insurance demand information and the description information of each candidate package in a database;

[0017] A second acquisition module, configured to identify and extract text content in the image data to obtain parameter information of the vehicle to be insured;

[0018] A second determination module, configured to determine a quotation result according to a quotation algorithm corresponding to the target package and the parameter information, and display the quotation result in the chat interface.

[0019] To achieve the above object, an embodiment of the third aspect of the present application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0020] The memory stores computer-executable instructions;

[0021] The processor executes the computer-executable instructions stored in the memory to implement the intelligent quotation method according to the embodiment of the first aspect.

[0022] To achieve the above object, an embodiment of the fourth aspect of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, they are used to implement the intelligent quotation method according to the embodiment of the first aspect.

[0023] To achieve the above object, an embodiment of the fifth aspect of the present application provides a computer program product, including a computer program, and when the computer program is executed by a processor, it implements the intelligent quotation method according to the embodiment of the first aspect.

[0024] The intelligent quotation method, device, electronic device and storage medium provided by the present application can send a quotation demand and image data of a quotation vehicle in a chat window interaction manner, and use a target package matching the quotation demand and information extracted from the image data to complete the automatic quotation of vehicle insurance, which can simplify the quotation operation process, improve the flexibility and efficiency of vehicle insurance quotation, expand the usage scenarios of quotation services, and optimize the user experience.

[0025] Additional aspects and advantages of the present application will be given in part in the following description, become apparent in part from the following description, or be learned through the practice of the present application. Description of the Drawings

[0026] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description of embodiments in conjunction with the accompanying drawings, where:

[0027] Figure 1 It is a schematic flowchart of an intelligent quotation method provided by an embodiment of the present application;

[0028] Figure 2 It is a schematic flowchart of another intelligent quotation method provided by an embodiment of the present application;

[0029] Figure 3 It is a schematic flowchart of another intelligent quotation method provided by an embodiment of the present application; and

[0030] Figure 4 It is a schematic structural diagram of an intelligent quotation device provided by an embodiment of the present application. Detailed Description of the Embodiment

[0031] The embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the accompanying drawings are exemplary and are intended to explain the present application, and should not be construed as limiting the present application.

[0032] The intelligent quotation method and device of the embodiments of the present application will be described below with reference to the accompanying drawings.

[0033] Existing vehicle insurance quotation technologies mainly operate on the client side of software or applications running on a personal computer (PC). Users can obtain quotations by inputting vehicle information, selecting insurance types, etc. In terms of insurance type selection and insured amount setting, existing vehicle insurance quotations require users to manually check a large number of options, with a relatively high operation complexity and a long quotation time, which cannot meet the user's need for quick quotation.

[0034] In addition, the usage scenario of the PC side is relatively fixed, and users need to be in a specific environment (such as an office or at home) to operate, which to a certain extent limits the flexibility and immediacy of quotation.

[0035] Therefore, the present application provides an intelligent quotation method, which can obtain preset insurance packages in the database through an interactive manner in a mobile terminal and a small program on an enterprise-level application platform, realizing fast and instant insurance for vehicle insurance packages, and improving the automation and flexibility of quotation. The intelligent quotation method mentioned in the embodiments of the present application is executed by a quotation robot provided by an application program.

[0036] Figure 1 It is a schematic flowchart of an intelligent quotation method provided by an embodiment of the present application.

[0037] As Figure 1 shown, the intelligent quotation method includes the following steps:

[0038] Step 101, in response to receiving a quotation instruction in the chat interface, obtain the insurance demand information and the image data corresponding to the vehicle to be insured.

[0039] Among them, the insurance demand information is the content used to describe the current insurance demand in the quotation instruction, and may include at least one of the name of the target insurance package, the preferred insurance items and types, etc.

[0040] Among them, the image data corresponding to the vehicle may include at least one of the insured's ID card photo, vehicle purchase invoice, driver's license photo, etc.

[0041] In the embodiment of the present application, the user (i.e., the insurance salesman) can send a quotation instruction in the chat interface of any application program that can provide a quotation robot interface in the mobile terminal. In this way, the quotation robot can, in response to the quotation instruction received in the chat interface, obtain the insurance demand information and the image data corresponding to the vehicle to be insured from the quotation instruction.

[0042] It should be noted that after receiving the quotation instruction, it is also necessary to check the content in the quotation instruction, because the quotation instruction may not include the image data corresponding to the vehicle to be insured, and it is impossible to obtain the image data for quotation. In this case, the user needs to be prompted to supplement and upload the image data.

[0043] Optionally, it can be detected first whether the quotation instruction includes the image data corresponding to the vehicle to be insured. In the case where the quotation instruction does not include the image data, a prompt message for uploading the image data is sent to the chat interface. Then, the image data uploaded in the chat interface is received.

[0044] In the embodiment of the present application, if no image data is detected, the quotation robot can automatically prompt the user in the chat interface to upload the image data of relevant vehicle materials to ensure the smooth progress of the subsequent steps of obtaining the quotation parameters related to the vehicle. Then, when an image is uploaded, the image data corresponding to the vehicle to be insured is obtained.

[0045] Step 102, determine the target package according to the similarity between the insurance demand information and the description information of each candidate package in the database.

[0046] In the embodiments of the present application, an insurance agent can preset or select different insurance packages in the database of the application platform mini-program as candidate packages, and these packages can be customized according to various factors such as vehicle type, usage nature, and user preferences. Thus, the quotation robot can determine the target package for each insurance application in combination with the package data configuration in the mini-program.

[0047] In the embodiments of the present application, the quotation robot can analyze the insurance application requirement information input by the user through a text similarity algorithm, identify the package names mentioned in the insurance application requirement information, and determine the candidate package corresponding to the identified package name as the target package. Alternatively, according to the requirements described by the user, the candidate package with the most matching corresponding description information and requirements can be recommended to determine the target package.

[0048] Step 103: Identify and extract the text content in the image data to obtain the parameter information of the vehicle to be insured.

[0049] Among them, the parameter information of the vehicle can include at least one of the vehicle basic information (such as vehicle identification code, model, purchase date, etc.), vehicle usage, and driver's ID number, etc.

[0050] In the embodiments of the present application, through the link of the image data, Java technology can be used to extract the data stream and convert it into the base64 format for in-depth optical character recognition (OCR) processing. That is, high-precision OCR technology can be used to identify and extract the text content in the image data to obtain the parameter information of the vehicle to be insured, so as to accurately complete the subsequent quotation calculation.

[0051] It should be noted that the image data can include different types of photos, and in different types of photos (such as certificates, invoices, etc.), the position of the text content and the content to be extracted are also different. Then, in the present application, after obtaining the image data, the image data can be classified first, and then for each type of image data, the corresponding extraction mode can be used to determine which positions of the text content in the image data need to be extracted to obtain the parameter information of the vehicle to be insured.

[0052] Step 104: Determine the quotation result according to the quotation algorithm corresponding to the target package and the parameter information, and display it on the chat interface.

[0053] In the embodiments of the present application, the insurance quotation of the vehicle to be insured can be calculated according to the quotation algorithm corresponding to the target package built in the quotation robot in combination with the parameter information, and the quotation result can be displayed on the chat interface in real time and sent to the salesman.

[0054] Optionally, before determining the quotation result according to the quotation algorithm and parameter information corresponding to the target package, the parameter information obtained in step 103 can be first displayed in the chat interface, and then, when a confirmation instruction for the parameter information is received, the quotation robot automatically starts the quotation calculation process. Thus, further manual correction can be performed on the parameter information extracted from the image data to ensure accurate data support for quotation confirmation.

[0055] It should be noted that the confirmation instruction for the parameter information can be to reply with a preset content, such as "confirm", "1", etc. in the dialog box containing the parameter information in the chat interface.

[0056] In this embodiment, first, in response to a quotation instruction received in the chat interface, the insurance application requirement information and the image data corresponding to the vehicle to be insured are obtained. Then, according to the similarity between the insurance application requirement information and the description information of each candidate package in the database, the target package is determined, and the text content in the image data is recognized and extracted to obtain the parameter information of the vehicle to be insured. After that, according to the quotation algorithm corresponding to the target package and the parameter information, the quotation result is determined and displayed in the chat interface. Thus, by means of interaction in the chat window, the quotation requirement and the image data of the vehicle to be insured are sent, and the automatic quotation of vehicle insurance is completed by using the target package matching the quotation requirement and the information extracted from the image data, which can simplify the operation process of quotation, improve the flexibility and efficiency of vehicle insurance quotation, expand the usage scenarios of the quotation service, and optimize the user experience.

[0057] This embodiment provides another intelligent quotation method. Figure 2 It is a schematic flowchart of an intelligent quotation method provided by an embodiment of the present application.

[0058] As Figure 2 shown, the intelligent quotation method may include the following steps:

[0059] Step 201, in response to a quotation instruction received in the chat interface, obtain the insurance application requirement information and the image data corresponding to the vehicle to be insured.

[0060] For a detailed description of the above step 201, reference can be made to other embodiments of the present application, which will not be elaborated here.

[0061] Step 202, extract at least one type of first information from the insurance application requirement information.

[0062] Among them, the types of the first information can be vehicle type, vehicle usage nature, or preferred insurance types, etc.

[0063] In the embodiment of the present application, existing text processing technologies can be used to extract information in a specific format from the insurance application requirement information to obtain at least one type of first information.

[0064] Step 203: Match the first information with the second information in the description information of each candidate package to determine the similarity between the insurance application requirement information and the description information.

[0065] Among them, the second information may be information such as vehicle type, vehicle usage nature, or insurance types included in the package (such as compulsory traffic insurance, vehicle damage insurance, third-party liability insurance, on-board personnel liability insurance, etc.). The first information and the second information are of the same type of information.

[0066] In the embodiment of the present application, a text similarity algorithm can be used to match the first information with the second information in the description information of each candidate package in the database, and determine the matching degree between all the first information in the insurance application requirement information and all the second information corresponding to a candidate package as the similarity between the insurance application requirement information and the description information of the candidate package.

[0067] Step 204: Determine the candidate package corresponding to the description information with the highest similarity as the target package.

[0068] In the embodiment of the present application, after obtaining the similarity corresponding to the description information of each candidate package, it can be determined that the candidate package with the highest corresponding similarity is more in line with the insurance application intention of the salesman. Therefore, this candidate package can be determined as the target package for the current quotation basis.

[0069] Optionally, after determining the similarity between the insurance application requirement information and the description information, the similarities corresponding to all candidate packages can also be sorted, and at least one candidate package with a similarity greater than the similarity threshold can be displayed in the chat interface. Then, when a selection instruction for any candidate package is received, that any candidate package is determined as the target package.

[0070] Among them, the similarity threshold can be determined according to the actual accuracy requirements of package matching, etc., and the present application does not limit this.

[0071] In the embodiment of the present application, there may be situations where the candidate package with the highest similarity does not meet the user's budget, etc., resulting in the package with the highest similarity not being able to be used as the target package for quotation. Therefore, at least one candidate package with a similarity greater than the similarity threshold can be displayed in the chat interface, so that the user can intuitively obtain the quotation schemes corresponding to the at least one candidate package respectively in the chat interface, and then select a package as the target package according to the needs. This can make the selection of the target package more in line with the user's needs and provide conditions for improving the reliability and efficiency of subsequent quotations.

[0072] It should be noted that after determining the target package, it is possible that the target package is a package for quoting for a transferred vehicle. In addition to the insurance information such as vehicle damage insurance and third-party liability insurance in this package, other information such as the transfer time, start date of insurance, and customer phone number also need to be obtained when issuing the policy. Then, the requirements for these information can be fed back to the salesman in the chat interface.

[0073] Step 205: Identify and extract the text content in the image data to obtain the parameter information of the vehicle to be insured.

[0074] Step 206: Determine the quotation result according to the quotation algorithm corresponding to the target package and the parameter information, and display it in the chat interface.

[0075] For the detailed description of the above steps 205 and 206, reference can be made to other embodiments of the present application, which will not be elaborated here.

[0076] In this embodiment, by matching the same type of information in the insured demand information and the description information of the candidate packages, the similarity corresponding to the description information of all packages is determined. Then, the package corresponding to the description information with the highest similarity is determined as the target package for quotation. Thereby, the reliability of the package for quotation can be improved, making the selection of the package more in line with the user's intention, and further improving the efficiency of providing quotations and optimizing the usage experience.

[0077] This embodiment provides another intelligent quotation method. Figure 3 It is a schematic flowchart of an intelligent quotation method provided by an embodiment of the present application.

[0078] As Figure 3 shown, the intelligent quotation method may include the following steps:

[0079] Step 301: In response to receiving a quotation instruction in the chat interface, obtain the insured demand information and the image data corresponding to the vehicle to be insured.

[0080] Step 302: Determine the target package according to the similarity between the insured demand information and the description information of each candidate package in the database.

[0081] Step 303: Identify and extract the text content in the image data to obtain the parameter information of the vehicle to be insured.

[0082] Step 304: Determine the quotation result according to the quotation algorithm corresponding to the target package and the parameter information, and display it in the chat interface.

[0083] For the detailed description of the above steps 301 to 304, reference can be made to other embodiments of the present application, which will not be elaborated here.

[0084] Step 305: Receive a modification instruction for the quotation algorithm, and determine the modified quotation algorithm based on the modification instruction.

[0085] In the embodiments of the present application, in order to meet the requirements of increasing the business volume of insurance companies and enhancing market competitiveness, etc., it is usually necessary to adjust the quotation parameters and algorithms of preset packages during certain periods. Therefore, the quotation robot can receive the modification instruction for the quotation algorithm of the target package from the salesman, and adjust the quotation parameters and calculation methods according to the indication of the modification instruction to obtain the modified quotation algorithm.

[0086] Step 306: Update the quotation result according to the modified quotation algorithm and parameter information, and display it on the chat interface.

[0087] In the embodiments of the present application, the modified quotation algorithm can be used to substitute the parameter information of the vehicle to be insured, recalculate the quotation result, and update the quotation result in the chat interface.

[0088] It should be noted that after displaying the quotation result, it is also possible to receive and store the feedback information from the salesman or the customer, and then periodically identify the improvement points of the preset package for the feedback information, and complete the update based on the improvement points to maintain the efficiency and accuracy of the quotation robot.

[0089] In this embodiment, by adjusting the package quotation parameters according to the package modification instruction of the salesman, and then completing the update of the quotation result, the quotation parameters can be flexibly adjusted according to the actual quotation needs, the flexibility of the quotation can be improved, the personalized needs of customers can be met, and the usage experience can be optimized.

[0090] To implement the above embodiments, the present application also proposes an intelligent quotation device.

[0091] Figure 4 The following is a schematic structural diagram of an intelligent quotation device provided by an embodiment of the present application.

[0092] As Figure 4 shown, the intelligent quotation device 400 includes:

[0093] A first acquisition module 401, configured to acquire the insurance demand information and the image data corresponding to the vehicle to be insured in response to receiving a quotation instruction in the chat interface;

[0094] A first determination module 402, configured to determine the target package according to the similarity between the insurance demand information and the description information of each candidate package in the database;

[0095] A second acquisition module 403, configured to identify and extract the text content in the image data to obtain the parameter information of the vehicle to be insured;

[0096] The second determination module 404 is configured to determine a quotation result according to the quotation algorithm and parameter information corresponding to the target package, and display it in the chat interface.

[0097] Further, the first acquisition module 401 may also be configured to:

[0098] Detect whether the quotation instruction contains the image data corresponding to the vehicle to be insured;

[0099] In the case that the quotation instruction does not contain image data, send a prompt message for uploading image data to the chat interface;

[0100] Receive the image data uploaded in the chat interface.

[0101] Further, the first determination module 402 may specifically be configured to:

[0102] Extract at least one type of first information from the insurance demand information;

[0103] Match the first information with the second information in the description information of each candidate package to determine the similarity between the insurance demand information and the description information, wherein the first information and the second information are of the same type of information;

[0104] Determine the candidate package corresponding to the description information with the highest similarity as the target package.

[0105] Further, the first determination module 402 may also be configured to:

[0106] Sort the similarities corresponding to all candidate packages, and display at least one candidate package with a similarity greater than the similarity threshold in the chat interface;

[0107] In the case of receiving a selection instruction for any candidate package, determine any candidate package as the target package.

[0108] Further, the second determination module 404 may also be configured to:

[0109] Display the parameter information in the chat interface, and receive a determination instruction for the parameter information.

[0110] Further, the second determination module 404 may also be configured to:

[0111] Receive a modification instruction for the quotation algorithm, and determine the quotation algorithm modified based on the modification instruction;

[0112] Update the quotation result according to the modified quotation algorithm and parameter information, and display it in the chat interface.

[0113] It should be noted that the foregoing explanation of the embodiments of the intelligent quotation method also applies to the intelligent quotation device of this embodiment, and will not be elaborated here.

[0114] In the embodiments of the present application, by means of interaction in the chat window, the quotation requirement and the image data of the quoted vehicle are sent, and the automatic quotation of vehicle insurance is completed by using the target package that matches the quotation requirement and the information extracted from the image data, which can simplify the operation process of quotation, improve the flexibility and efficiency of vehicle insurance quotation, expand the usage scenarios of quotation services, and optimize the user experience.

[0115] To implement the above embodiments, the present application also proposes an electronic device, including: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided in the foregoing embodiments.

[0116] To implement the above embodiments, the present application also proposes a computer-readable storage medium, in which computer-executable instructions are stored, and when the computer-executable instructions are executed by a processor, they are used to implement the method provided in the foregoing embodiments.

[0117] To implement the above embodiments, the present application also proposes a computer program product, including a computer program, which when executed by a processor, implements the method provided in the foregoing embodiments.

[0118] The collection, storage, use, processing, transmission, provision, and disclosure of the user's personal information involved in the present application and other processing all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0119] It should be noted that personal information from users should be collected for legal and reasonable purposes and should not be shared or sold outside of these legitimate uses. In addition, such collection / sharing should be carried out after obtaining the informed consent of the user, including but not limited to notifying the user to read the user agreement / user notice and signing an agreement / authorization including authorizing relevant user information before the user uses this function. In addition, any necessary steps should be taken to protect and safeguard access to such personal information data and ensure that others with access to personal information data comply with their privacy policies and procedures.

[0120] The present application anticipates providing an implementation plan for users to selectively block the use or access of personal information data. That is, the present disclosure anticipates providing hardware and / or software to prevent or block access to such personal information data. Once personal information data is no longer needed, the risk can be minimized by restricting data collection and deleting data. In addition, when applicable, personal identifiers are removed from such personal information to protect the privacy of users.

[0121] In the descriptions of the foregoing embodiments, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0122] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of the features. In the description of the present application, "a plurality of" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0123] Any process or method description shown in a flowchart or described in other ways herein may be understood to represent a module, segment, or portion of code including one or more executable instructions for implementing a customized logic function or process, and the scope of the preferred embodiments of the present application includes additional implementations, where the functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0124] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definable sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or in conjunction with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer-readable media include the following: electrical connection parts with one or more wirings (electronic devices), portable computer disk cartridges (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other suitable processing as necessary, and then storing it in a computer memory.

[0125] It should be understood that various parts of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits with logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits with suitable combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0126] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the methods of the above embodiments can be completed by instructing relevant hardware through a program, and the said program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0127] In addition, each functional unit in various embodiments of the present application may be integrated into one processing module, or each unit may exist physically alone, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0128] The above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. An intelligent quotation method, characterized in that: include: In response to receiving a quotation instruction in the chat interface, obtaining insurance demand information and image data corresponding to the vehicle to be insured; Determine the target package according to the similarity between the insurance demand information and the description information of each candidate package in the database; Identify and extract text content in the image data to obtain parameter information of the vehicle to be insured; The quotation result is determined according to the quotation algorithm corresponding to the target package and the parameter information, and is displayed on the chat interface.

2. The method according to claim 1, characterized in that After receiving the quotation instruction in response to the chat interface, the method further includes: Detecting whether the quotation instruction contains image data corresponding to the vehicle to be insured; When the quotation instruction does not include image data, sending a prompt message for uploading image data to the chat interface; Receive the image data uploaded in the chat interface.

3. The method according to claim 1, characterized in that The step of determining the target package according to the similarity between the insurance demand information and the description information of each candidate package in the database comprises: Extracting at least one type of first information from the insurance demand information; Matching the first information with the second information in the description information of each candidate package to determine the similarity between the insurance demand information and the description information, wherein the first information and the second information are of the same type; The candidate package corresponding to the description information with the highest similarity is determined as the target package.

4. The method according to claim 3, characterized in that After determining the similarity between the insurance demand information and the description information, the method further includes: sorting the similarities corresponding to all the candidate packages, and displaying at least one candidate package having a similarity greater than a similarity threshold in the chat interface; When a selection instruction for any candidate package is received, the any candidate package is determined as a target package.

5. The method according to claim 1, characterized in that: Before determining the quotation result according to the quotation algorithm corresponding to the target package and the parameter information, the method further includes: The parameter information is displayed in the chat interface, and a confirmation instruction for the parameter information is received.

6. The method according to any one of claims 1 to 4, characterized in that: After determining the quotation result according to the quotation algorithm corresponding to the target package and the parameter information and displaying it on the chat interface, the method further includes: receiving a modification instruction for the quotation algorithm, and determining a modified quotation algorithm based on the modification instruction; According to the modified quotation algorithm and the parameter information, the quotation result is updated and displayed on the chat interface.

7. An intelligent quotation device, characterized in that: include: A first acquisition module, for acquiring insurance demand information and image data corresponding to the vehicle to be insured in response to receiving a quotation instruction in the chat interface; A first determination module, configured to determine a target package according to the similarity between the insurance demand information and the description information of each candidate package in the database; A second acquisition module is used to recognize and extract text content in the image data to obtain parameter information of the vehicle to be insured; The second determination module is used to determine the quotation result according to the quotation algorithm corresponding to the target package and the parameter information, and display it on the chat interface.

8. An electronic device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the intelligent quotation method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the intelligent quotation method according to any one of claims 1 to 6.

10. A computer program product, characterized in that It includes a computer program, which, when executed by a processor, implements the intelligent quotation method described in any one of claims 1 to 6.

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