Resume generation method, intelligent terminal and storage medium

Abstract

The invention provides a resume generation method, an intelligent terminal and a storage medium, the resume generation method can be applied to the intelligent terminal, and comprises the following steps: S11: in response to input of personal basic information, obtaining a corresponding information acquisition table through an AI model; and S12, in response to an interaction operation for the information acquisition table, generating a target resume according to an information acquisition result corresponding to the interaction operation and / or the personal basic information. Through the technical scheme of the invention, the generation of the resume can be simplified in a model-assisted manner so as to adapt to the crowd with relatively weak resume compiling ability, and the operation is simple and convenient.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of artificial intelligence, in particular to a resume generation method, an intelligent terminal and a storage medium. BACKGROUND

[0002] In today's job environment, a resume is a core tool for job seekers to demonstrate their own abilities and experiences. There are currently three ways to write a resume: manually, in a word document, or in a webpage / APP provided page. The main content filled in the resume includes personal information, position, work experience, skill expertise and / or self-introduction, etc.

[0003] In the process of conceiving and implementing the present application, the inventors found that at least the following problem exists: how to simplify the generation of a resume through an assisted manner to adapt to people with weaker resume compilation abilities.

[0004] The foregoing narrative is to provide general background information and does not necessarily constitute the prior art. SUMMARY

[0005] To solve the above technical problems, the present application provides a resume generation method, an intelligent terminal and a storage medium, so that users can simplify the generation of a resume through a model-assisted manner to adapt to people with weaker resume compilation abilities, which is simple and convenient to operate.

[0006] The present application provides a resume generation method, which can be applied to an intelligent terminal, including the steps of: S11: in response to the input of personal basic information, acquiring a corresponding information collection table through an AI model; S12: in response to an interactive operation on the information collection table, generating a target resume according to the information collection result corresponding to the interactive operation and / or the personal basic information.

[0007] Optionally, the way of acquiring the corresponding information collection table through the AI model includes at least one of the following: generating a first information collection table corresponding to the position information in the personal basic information through a first special generative model; generating a second information collection table corresponding to the position information in the personal basic information through a general generative model; acquiring the information collection table according to the first information collection table and / or the second information collection table.

[0008] Optionally, the interactive operation on the information collection table includes at least one of the following: performing a selection operation on the options in the displayed information collection table; performing a voice reply to the question voice output according to the information collection table.

[0009] Optionally, the step S12 comprises: obtaining, by the AI model, the resume skill content corresponding to the information collection result; and generating the target resume according to the resume skill content and the personal basic information.

[0010] Optionally, the manner of obtaining, by the AI model, the resume skill content corresponding to the information collection result comprises at least one of the following: generating, by a second special generative model, the first resume skill content corresponding to the information collection result; generating, by a general generative model, the second resume skill content corresponding to the information collection result; obtaining the resume skill content according to the first resume skill content and / or the second resume skill content.

[0011] Optionally, the method further comprises at least one of the following: performing a supplementary guiding operation in response to meeting a first preset condition; updating the target resume according to the resume supplementary content corresponding to the supplementary guiding operation; generating the target resume according to the resume skill content, the personal basic information and the resume supplementary content; performing a duplicate checking process on the resume skill content; generating the target resume according to the resume skill content after the duplicate checking process, the personal basic information and / or the resume supplementary content.

[0012] Optionally, the method further comprises at least one of the following: obtaining employment location information; obtaining cultural custom information corresponding to the employment location information; performing a content optimization process on the resume skill content or the target resume according to the cultural custom information.

[0013] Optionally, the step of generating the target resume according to the resume skill content and the personal basic information comprises: obtaining language type information corresponding to the employment location information; and generating the target resume according to the resume skill content, the personal basic information and the language type information.

[0014] Optionally, the method further comprises: collecting recruitment response information after the target resume is published in response to meeting a second preset condition; and performing a recall calculation process according to the recruitment response information to adjust and update the AI model and / or the knowledge base corresponding thereto.

[0015] The application also provides an intelligent terminal, comprising a memory and a processor, wherein the memory stores a computer program, and the computer program is executed by the processor to implement the steps of the resume generation method described in any one of the above.

[0016] The application further provides a storage medium storing a computer program, which, when executed by a processor, implements the steps of the resume generation method described in any one of the above.

[0017] As described above, the resume generation method of the application can be applied to a smart terminal, including the steps of: S11: in response to input of personal basic information, acquiring a corresponding information collection table through an AI model; S12: in response to an interactive operation on the information collection table, generating a target resume according to information collection results corresponding to the interactive operation and / or the personal basic information. Through the technical solution of the application, after inputting the personal basic information of the user, the information collection table for determining the skills of the user can be acquired or generated through the AI model, so that the user can obtain the information collection results through simple interactive operations on the information collection table, and then generate a resume including personal basic information and / or skill content. In this way, the technical solution of the application can simplify the generation of the resume through the model-assisted manner, so as to adapt to the population with weak resume compiling ability, and the operation is simple and convenient. BRIEF DESCRIPTION OF DRAWINGS

[0018] The accompanying drawings, which are incorporated into and form part of the specification, illustrate embodiments consistent with the application and, together with the specification, serve to explain the principles of the application. In order to more clearly illustrate the technical solutions of the embodiments of the application, the drawings needed to be used in the embodiment description will be briefly introduced as follows. Obviously, for those of ordinary skill in the art, no creative work is needed to obtain other drawings from these drawings.

[0019] Figure 1 A hardware structure schematic diagram of a mobile terminal for implementing various embodiments of the application.

[0020] Figure 2 A communication network system architecture diagram provided by the embodiments of the application.

[0021] Figure 3 is a first flowchart of the resume generation method shown in the first embodiment of the application.

[0022] Figure 4 is a second flowchart of the resume generation method shown in the first embodiment of the application.

[0023] Figure 5 is a schematic diagram of the resume generation system shown in the second embodiment of the application.

[0024] Figure 6 is a flowchart of the recruitment APP shown in the application.

[0025] The objectives, features and advantages of the present application will be further illustrated by the following embodiments in conjunction with the accompanying drawings. The above-mentioned drawings have shown the specific embodiments of the present application, and will be described in more detail hereinafter. These drawings and the written description are not intended to restrict the scope of the present application in any way, but to illustrate the concept of the present application by referring to specific embodiments. DETAILED DESCRIPTION

[0026] The exemplary embodiments will be described in detail herein with reference to the attached drawings. The same reference numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all the implementations consistent with the present application. Instead, they only describe example devices and methods consistent with some aspects of the present application, as detailed in the appended claims.

[0027] It should be noted that, in this document, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without more limitations, an element defined by the statement "comprising a" does not exclude the existence of additional identical elements in the process, method, article, or apparatus that includes the element. In addition, components, features, elements with the same name in different embodiments of the present application can have the same meaning or different meanings, and the specific meaning thereof should be determined in the explanation of the specific embodiment or further in conjunction with the context of the specific embodiment.

[0028] It should be understood that, although terms, first, second, third, etc. can be used herein to describe various information, these terms are not intended to denote a particular order or hierarchy among the information. These terms are used only to distinguish one category of information from another category of information. For example, a first information can be termed a second information, and similarly, a second information can be termed a first information without departing from the scope hereof. The word "if' as used herein, depending on the context in which it is used, can be interpreted to mean "when" or "upon" or "in response to determining" or "in response to detecting." Also, the word "comprise" or "comprising" as used herein, can be interpreted as meaning "comprising but not limited to." It will be further understood that the terms "comprises" "comprising," "includes" "including," "has" "having," "contains" "containing," or the like, are inclusive in a manner similar to the terms "comprise" "comprising," "includes" "including," "has" "having," "contains" "containing," or the like. The terms "plurality" and "a plurality" as used herein can be interpreted to mean "two or more." The term "coupled" as used herein, can be interpreted in a manner similar to the term "connected." Also, the term "coupled" can be interpreted as meaning "connected," although not necessarily directly. The term "circuit" as used herein, can be interpreted as meaning either an individual component or a combination of separate components, whether or not the components are physically connected together. The term "circuitry" as used herein, can be interpreted as meaning a combination of circuits, sub-circuits, and / or sub-circuitries. In addition, it should be understood that the application can be implemented in a variety of forms; therefore, exclusive, specific

[0029] It should be understood that, although various steps in the flowcharts of the embodiments of the present application are shown in a sequential order, these steps are not necessarily performed in the order shown. Unless explicitly stated, the steps of the flowcharts are not necessarily performed in the order shown. Moreover, at least some of the steps shown in the flowcharts can include multiple sub-steps or multiple stages, which are not necessarily performed in the same order as shown, and which can be performed at different times.

[0030] The word "if' as used herein, depending on the context in which it is used, can be interpreted to mean "when" or "upon" or "in response to determining" or "in response to detecting." Similarly, the phrase "if determined" or "if detecting (a stated condition or event)" can be interpreted to mean "when determined" or "in response to determining" or "when detecting (a stated condition or event)" or "in response to detecting (a stated condition or event)," depending on the context in which it is used.

[0031] It should be noted that, in the present document, step codes such as S11, S12, etc. are adopted for the purpose of more clearly and concisely expressing the corresponding content, and do not constitute substantial limitations in order, and a person skilled in the art may perform S12 before S11, etc. in specific implementation, but these should be within the protection scope of the present application.

[0032] It should be understood that the specific embodiments described herein are merely intended to explain the present application, and are not intended to limit the present application.

[0033] In the following description, the suffixes used for elements, such as "module", "part", or "unit", are used only for convenience of explanation of the present application, and have no specific meaning by themselves. Thus, "module", "part", or "unit" can be mixedly used.

[0034] The smart terminal can be implemented in various forms. For example, the smart terminal described in the present application can include a smart terminal such as a mobile phone, a tablet computer, a notebook computer, a palmtop computer, a Personal Digital Assistant (PDA), a Portable Media Player (PMP), a navigation device, a wearable device, a smart band, a pedometer, and the like, and a fixed terminal such as a digital TV, a desktop computer, and the like.

[0035] In the following description, a mobile terminal will be exemplified, and a person skilled in the art will understand that the configuration according to the embodiments of the present application can be applied to a terminal of a fixed type, except for elements particularly used for mobile purposes.

[0036] Referring to Figure 1 , which is a hardware structure diagram of a mobile terminal according to an embodiment of the present application, the mobile terminal 100 can include an RF (Radio Frequency) unit 101, a WiFi module 102, an audio output unit 103, an A / V (audio / video) input unit 104, a sensor 105, a display unit 106, a user input unit 107, an interface unit 108, a storage 109, a processor 110, and a power supply 111, etc. A person skilled in the art can understand that the mobile terminal structure shown in Figure 1 The mobile terminal structure shown in

[0037] The following will be described in detail with reference to Figure 1 The components of the mobile terminal will be described in detail. The radio frequency unit 101 can be used for receiving and transmitting signals in the process of information or communication. Specifically, the radio frequency unit 101 receives the downlink information of the base station and provides the received information to the processor 110 for processing. In addition, the radio frequency unit 101 transmits the uplink data to the base station. Generally, the radio frequency unit 101 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, etc. In addition, the radio frequency unit 101 can also communicate with the network and other devices through wireless communication. The above wireless communication can use any communication standard or protocol, including but not limited to GSM (Global System of Mobile communication), GPRS (General Packet Radio Service), CDMA2000 (Code Division Multiple Access 2000), WCDMA (Wideband Code Division Multiple Access), TD-SCDMA (Time Division-Synchronous Code Division Multiple Access), FDD-LTE (Frequency Division Duplexing-Long Term Evolution), TDD-LTE (Time Division Duplexing-Long Term Evolution), 5G and 6G, etc.

[0038] The WiFi belongs to a short-range wireless transmission technology. The WiFi module 102 can help the user to send and receive e-mails, browse web pages, and access streaming media, etc. It provides the user with wireless broadband Internet access. Although Figure 1 The WiFi module 102 is shown, but it can be understood that it does not belong to the necessary components of the mobile terminal, and can be omitted as needed without changing the essence of the application.

[0039] The audio output unit 103 can convert audio data, which is received by the radio frequency unit 101 or the WiFi module 102 or stored in the memory 109, into an audio signal and output it as sound when the mobile terminal 100 is in a call signal receiving mode, a call mode, a recording mode, a voice recognition mode, a broadcast reception mode, etc. Moreover, the audio output unit 103 can also provide audio output related to a particular function performed by the mobile terminal 100 (e.g., a call signal reception sound, a message reception sound, etc.). The audio output unit 103 can include a speaker, a buzzer, etc.

[0040] The A / V input unit 104 is configured to receive audio or video signals. The A / V input unit 104 can include a graphics processor (GPU) 1041 and a microphone 1042. The graphics processor 1041 processes image data of a still picture or a video obtained by an image capture device (e.g., a camera) in a video call mode or an image call mode. Processed image frames can be displayed on the display unit 106. Processed image frames can be stored in the memory 109 (or other storage medium) or transmitted via the radio frequency unit 101 or the WiFi module 102. The microphone 1042 can receive sound (audio data) via the microphone 1042 in a phone call mode, a recording mode, a voice recognition mode, and the like, and can process such sound into audio data. Processed audio (voice) data can be converted into a format transmittable to a mobile communication base station via the radio frequency unit 101 in the case of the phone call mode. The microphone 1042 can implement various types of noise cancellation (or suppression) algorithms to cancel (or suppress) noise or interference generated in the process of receiving and transmitting audio signals.

[0041] The mobile terminal 100 also includes at least one sensor 105, such as a light sensor, a motion sensor, and other sensors. The light sensor includes an ambient light sensor and a proximity sensor, which can optionally adjust the brightness of the display panel 1061 according to the brightness of ambient light, and turn off the display panel 1061 and / or the backlight when the mobile terminal 100 is moved to the ear. As one of the motion sensors, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), and detect the magnitude and direction of gravity when at rest, which can be used for applications that recognize the posture of the mobile terminal (such as switching between landscape and portrait screens, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometers, tapping), and the like. The mobile terminal can also be configured with a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, and other sensors, which will not be described here.

[0042] The display unit 106 is configured to display information input by a user or information provided to the user. The display unit 106 can include a display panel 1061, which can be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.

[0043] The user input unit 107 can be used to receive input numerals or character information, and to generate key signal inputs related to user settings of the mobile terminal and control of functions. Optionally, the user input unit 107 can include a touch panel 1071 and other input devices 1072. The touch panel 1071, also called a touch screen, can collect touch operations of a user on or proximity thereto (e.g., operations by the user using a finger, a touch pen, or any suitable object or accessory on or in proximity to the touch panel 1071) and drive corresponding connection devices according to a pre-set program. The touch panel 1071 can include two parts, a touch detecting device and a touch controller. The touch detecting device detects the user's touch position and detects a signal resulting from the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detecting device and converts it into touch coordinates, which are then transmitted to the processor 110, and can receive commands from the processor 110 and execute them. In addition, the touch panel 1071 can be implemented in various types such as a resistive type, a capacitive type, an infrared type, and a surface acoustic wave type. In addition to the touch panel 1071, the user input unit 107 can include other input devices 1072. Optionally, the other input devices 1072 can include one or more of, but are not limited to, a physical keyboard, function keys (e.g., a volume control button, a switch button, etc.), a trackball, a mouse, a joystick, etc.

[0044] Optionally, the touch panel 1071 can cover the display panel 1061, and when the touch panel 1071 detects a touch operation on or in proximity thereto, it transmits the information to the processor 110 to determine the type of touch event, and then the processor 110 provides a corresponding visual output on the display panel 1061 according to the type of touch event. Although in the above description, the touch panel 1071 and the display panel 1061 are implemented as two separate components to achieve the input and output functions of the mobile terminal, in some embodiments, the touch panel 1071 and the display panel 1061 can be integrated to achieve the input and output functions of the mobile terminal, without being limited in this regard. Figure 1

[0045] The interface unit 108 serves as an interface through which at least one external device can be connected with the mobile terminal 100. For example, the external device can include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device having an identification module, an audio I / O (input / output) port, a video I / O port, an earphone port, etc. The interface unit 108 can be used to receive input (e.g., data information, power, etc.) from an external device and to transmit the received input to one or more elements within the mobile terminal 100, or can be used to transmit data between the mobile terminal 100 and the external device. ​

[0046] The memory 109 can be used to store software programs and various data. The memory 109 can mainly include a program storage area and a data storage area, and the program storage area can store an operating system, application programs required by at least one function (such as a sound playing function, an image playing function, etc.), and the like; and the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), and the like. In addition, the memory 109 can include a high-speed random access memory, and can also include a nonvolatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state memory device.

[0047] The processor 110 is the control center of the mobile terminal, connects all parts of the mobile terminal through various interfaces and lines, executes various functions of the mobile terminal and processes data by running or executing software programs and / or modules stored in the memory 109 and calling data stored in the memory 109, and thus monitors the mobile terminal as a whole. The processor 110 can include one or more processing units; preferably, the processor 110 can integrate an application processor and a modem processor, and the application processor can mainly process an operating system, a user interface, and application programs, and the like, and the modem processor can mainly process wireless communication. It can be understood that the above-mentioned modem processor can also not be integrated into the processor 110.

[0048] The mobile terminal 100 can also include a power supply 111 (such as a battery) for supplying power to various components; preferably, the power supply 111 can be logically connected to the processor 110 through a power management system, so as to realize the functions of managing charging, discharging, and power consumption management, and the like through the power management system.

[0049] Although Figure 1 The mobile terminal 100 can also include a Bluetooth module and the like, which are not described herein.

[0050] In order to facilitate the understanding of the embodiments of the present application, the communication network system based on the mobile terminal of the present application is described below.

[0051] Please refer to Figure 2 , Figure 2 A communication network system architecture diagram provided by the embodiments of the present application, the communication network system is a LTE system of general mobile communication technology, the LTE system includes a UE (User Equipment, user equipment) 201, an E-UTRAN (Evolved UMTS Terrestrial Radio Access Network, evolved UMTS terrestrial radio access network) 202, an EPC (Evolved Packet Core, evolved packet core network) 203 and an operator's IP service 204 which are sequentially connected in communication.

[0052] Optionally, the UE 201 can be the terminal 100 described above, which will not be repeated here.

[0053] The E-UTRAN 202 includes eNode B 2021 and other eNode Bs 2022. Optionally, the eNode B 2021 can be connected with the other eNode Bs 2022 through backhaul (for example, X2 interface), the eNode B 2021 is connected to the EPC 203, and the eNode B 2021 can provide access for the UE 201 to the EPC 203.

[0054] The EPC 203 can include MME (Mobility Management Entity) 2031, HSS (Home Subscriber Server) 2032, other MMEs 2033, SGW (Serving GateWay) 2034, PGW (PDN Gate Way) 2035, and PCRF (Policy and Charging Rules Function) 2036. Optionally, the MME 2031 is a control node for processing signaling between the UE 201 and the EPC 203, and provides bearer and connection management. The HSS 2032 is used to provide some registers to manage functions such as a home location register (not shown in the figure), and to save some user-specific information about service features, data rates, etc. All user data can be transmitted through the SGW 2034, the PGW 2035 can provide IP address allocation for the UE 201 and other functions, and the PCRF 2036 is a policy and charging control policy decision point for service data flow and IP bearer resources, which selects and provides available policy and charging control decisions for policy and charging enforcement function units (not shown in the figure).

[0055] The IP service 204 can include the Internet, an intranet, an IMS (IP Multimedia Subsystem), or other IP services.

[0056] Although the above describes the LTE system as an example, those skilled in the art should know that the present application is not only applicable to the LTE system, but also applicable to other wireless communication systems, such as GSM, CDMA2000, WCDMA, TD-SCDMA, 5G, and future new network systems (such as 6G), etc., which are not limited here.

[0057] Based on the above mobile terminal hardware structure and communication network system, various embodiments of the present application are proposed.

[0058] Referring to Figures 3 to 4 , Figure 3 is a first flowchart of a resume generation method according to a first embodiment of the present application; Figure 4 is a second flowchart of a resume generation method according to the first embodiment of the present application.

[0059] The resume generation method of the present embodiment can be applied to a smart terminal (such as a mobile phone), including the following steps (for example, steps S11 to S12 in FIG. 1): Figure 1 S11: In response to the input of personal basic information, an information collection table corresponding to the AI model is obtained.

[0060] Optionally, the personal basic information can represent various information content that can indicate specific characters and / or job requirements in the resume.

[0061] Optionally, the personal basic information can include personal information and / or job information indicating specific characters.

[0062] Optionally, the personal information includes but is not limited to at least one of the following: name, gender, age, contact information, work experience, etc. For example, it can also include family information, address information, religious beliefs, nationality, etc.

[0063] Optionally, the job information can represent the job and / or the type of work.

[0064] Optionally, the information collection table can represent a tool for collecting or organizing skill information related to a specific job. Optionally, the display form of the information collection table includes but is not limited to the form of voice question and answer, the form of questionnaire, the form of options, etc.

[0065] Optionally, the input method of the personal basic information can be in the form of voice and / or text, or it can be obtained from a specific platform or a specific file (such as the registration information of a recruitment software or the initial resume uploaded by the user to the recruitment software).

[0066] Optionally, the AI model can be a generative model. Optionally, the AI model can generate or obtain an information collection table that matches the content theme or direction determined by the personal basic information and is targeted at the user's skills.

[0067] Optionally, the generative model is a class of artificial intelligence models that can generate new data samples. They learn the distribution of training data and generate new data similar to but not identical to the training data.

[0068] ​Optionally, the AI model can include a special-purpose generative model and / or a general-purpose generative model that is customized according to specific needs. Optionally, the general-purpose generative model can represent a generative large model on the market that is not targeted at specific users or specific needs, such as openAi, deepSeek, and the like, which are generative large models targeting a wide range of users.

[0069] Optionally, the special-purpose generative model can include a first special-purpose generative model that is mainly used to generate or obtain an information collection table for determining user skills. Compared with the general-purpose generative model, the information collection table generated or obtained by the first special-purpose generative model can be more closely related to actual business needs. Optionally, the first special-purpose generative model can be a special-purpose post-requirement model that is mainly used to obtain or generate an information collection table for determining user skills according to post information in personal basic information. The knowledge base of the special-purpose post-requirement model can be obtained by data processing on specific post recruitment information published in a recruitment system or an existing resume set for a specific post; optionally, the content of the knowledge base of the special-purpose post-requirement model (such as specific post recruitment information published in a recruitment system or an existing resume set for a specific post, etc.) can also be obtained from the knowledge base of the general-purpose generative model by calling the API interface of the general-purpose generative model.

[0070] Optionally, the technical solution of the present embodiment can generate an information collection table through the first special-purpose generative model described above, which can not only ensure the authenticity of the target resume generated subsequently, but also reduce the operation difficulty of information collection. Optionally, the combination of the first special-purpose generative model and its knowledge base can generate an information collection table that is more in line with the requirements of a specific post in the current recruitment system according to the related content of the type of work / post in the knowledge base.

[0071] Optionally, the method of obtaining a corresponding information collection table through an AI model can include, but is not limited to, at least one of the following: generating a first information collection table corresponding to the post information in the personal basic information through the first special-purpose generative model; generating a second information collection table corresponding to the post information in the personal basic information through the general-purpose generative model; obtaining an information collection table according to the first information collection table and / or the second information collection table.

[0072] Optionally, the present embodiment can use the first information collection table generated by the first special-purpose generative model as the basis for performing step S12 (i.e., as the aforementioned information collection table). In this way, the first special-purpose generative model can generate an information collection table for determining user skills, so as to obtain a high-quality resume after performing step S12.

[0073] Optionally, the embodiment can generate the second information collection table generated by the general generative model as the basis for performing step S12 (i.e., as the aforementioned information collection table). In this way, by generating the information collection table that determines the user's skills through the general generative model, the model development and model maintenance costs can be saved, so as to realize the assisted resume generation function in a low-cost manner.

[0074] Optionally, when the first special generative model cannot output the first information collection table according to the personal basic information including the type of work / post, the general generative model is called to output the second information collection table as the basis for performing step S12 (i.e., as the aforementioned information collection table). In this way, the embodiment can adopt a combination of special generative models and general generative models, which not only guarantees the high availability of large models, but also reduces the refinement and construction cost of special generative large models, thereby improving the stability of the assisted resume generation function.

[0075] Optionally, the embodiment can obtain the first information collection table and the second information collection table through the first special generative model and the general generative model respectively, so as to analyze and merge the first information collection table and the second information collection table to obtain a more reasonable, comprehensive or simplified comprehensive information collection table as the basis for performing step S12 (i.e., as the aforementioned information collection table). In this way, the first special generative model and the general generative model can better generate the information collection table that determines the user's skills, so as to obtain a high-quality resume after performing step S12.

[0076] Optionally, when the corresponding information collection table is obtained through the AI model, the number of fields and / or categories in the information collection table can be constrained or limited. Optionally, by limiting the number of fields and / or categories, the technical solution of the embodiment can avoid including too much irrelevant or redundant information in the information collection table, help improve the purity of the content in the information collection table, make the data collected through the information collection table more focused on the part directly related to the post skills, and improve the convenience of the user's operation on the information collection table, so that the subsequent information collection result can reflect the core skills and needs of the user.

[0077] S12: In response to the interactive operation on the information collection table, generating a target resume according to the information collection result corresponding to the interactive operation and / or the personal basic information.

[0078] Optionally, the information collection result obtained by the interactive operation on the information collection table can explicitly indicate the post demand and / or quantify the skill level.

[0079] Optionally, the interactive operation on the information collection table can represent any operation of determining the user's skills or the post demand based on the information collection table.

[0080] Optionally, the interactive operation for the information collection form includes, but is not limited to, at least one of the following: selecting an option in the displayed information collection form; voice answering the voice question output according to the information collection form.

[0081] Optionally, the information collection form includes a preset number of categories, and each category includes at least one option for determining the skill condition of a specific user or the demand of a specific post, so that the preset number of categories and their corresponding options can be displayed one by one or simultaneously for the user to select, so that the information collection result can be obtained after receiving the selection operation of the user. In this way, the technical solution of the embodiment can guide the user to select in the form of a selection question, so as to quickly obtain the information collection result reflecting the post skill and expertise of the user.

[0082] Optionally, the information collection form includes a preset number of categories, so that a prompt voice can be output according to each category to guide the user to voice answer the post skill and / or expertise, and thus the information collection result is obtained in the form of question and answer. In this way, the technical solution of the embodiment can conveniently obtain the information collection result reflecting the post skill and expertise of the user, and is more suitable for the elderly, people with low education, people not familiar with electronic products, etc.

[0083] Optionally, the form and content of the target resume can meet the resume delivery standard.

[0084] Optionally, the content in the target resume can include personal basic information, resume skill content, etc. Optionally, the resume skill content is generated according to the information collection result and reflects the post skill and expertise of the user. Optionally, the resume skill content includes, but is not limited to, at least one of personal introduction, skill label, skill introduction, education introduction, work experience, etc.

[0085] Optionally, referring to Figure 4 , step S12 includes the steps of: S200: obtaining an information collection result corresponding to the interactive operation in response to the interactive operation for the information collection form; S201: obtaining resume skill content corresponding to the information collection result by an AI model; S202: generating a target resume according to the resume skill content and the personal basic information.

[0086] Optionally, step S202 can also be implemented by an AI model.

[0087] Optionally, the embodiment can first generate an information collection table corresponding to the personal basic information by means of the AI model, so as to realize simple interactive operation on the information collection table to obtain an information collection result of the post skills and expertise of the user, and then directly or indirectly generate the target resume according to the information collection result and the personal basic information by means of the AI model.

[0088] Optionally, the special generation model in the AI model can further include a second special generation model mainly used for generating or obtaining the resume skill content according to the information collection result. Compared with the general generation model, the resume skill content generated or obtained by the second special generation model can be more in line with the preferences of most employers.

[0089] Optionally, the second special generation model can be a special resume generation model, which can not only generate or obtain the resume skill content according to the information collection result, but also generate the target resume based on the resume skill content and the personal basic information. Optionally, the content in the knowledge base of the special resume generation model can be obtained after processing or training the published recruitment information or the resume in the recruitment system, so that the resume skill content generated or obtained by the special resume generation model can be more in line with the preferences of most employers or the resume skill content generated or obtained by the special resume generation model can have a higher post fit degree.

[0090] Optionally, the way of obtaining the resume skill content corresponding to the information collection result by the AI model includes but is not limited to at least one of the following: generating first resume skill content corresponding to the information collection result by the second special generation model; generating second resume skill content corresponding to the information collection result by the general generation model; obtaining the resume skill content according to the first resume skill content and / or the second resume skill content.

[0091] Optionally, the embodiment can take the first resume skill content generated by the second special generation model as the resume skill content added to the target resume, so that the resume skill content generated by the second special generation model can have a higher post fit degree.

[0092] Optionally, the embodiment can take the second resume skill content generated by the general generation model as the resume skill content added to the target resume, so that the resume skill content generated by the general generation model can save the model development and model maintenance cost, so as to further realize the assisted resume generation function in a low-cost manner.

[0093] Optionally, when the first resume skill content cannot be output according to the information collection result, the embodiment initiates a second inquiry session to the special resume generation model, and calls the general generation model to output the first resume skill content as the resume skill content of the target resume. In this way, the embodiment can further improve the stability of the assisted generation function of the resume.

[0094] Optionally, the embodiment can obtain the first resume skill content and the second resume skill content through the second special generation model and the general generation model, so as to analyze and merge the first resume skill content and the second resume skill content to obtain more suitable resume skill content.

[0095] Optionally, the method of the embodiment further includes at least one of the following: in response to the first preset condition, performing a supplementary guidance operation; updating the target resume according to the resume supplement content corresponding to the supplementary guidance operation; generating the target resume according to the resume skill content, the personal basic information and the resume supplement content; performing duplicate checking on the resume skill content; generating the target resume according to the resume skill content, the personal basic information and / or the resume supplement content after duplicate checking.

[0096] Optionally, the first preset condition represents a situation in which the content supplement demand is determined according to the personal basic information and the resume skill content.

[0097] Optionally, the supplementary guidance operation is used to guide the user to supplement the information according to the content supplement demand, so as to perfect the content in the resume and obtain a complete resume meeting the resume delivery standard.

[0098] Optionally, the resume supplement content includes but is not limited to at least one of the following: photo, educational certificate, avatar, professional certificate, etc.

[0099] Optionally, the duplicate checking on the resume skill content can be to compare all or part of the content in the resume skill content with the published resumes obtained through various channels, and if there is content duplication, the description of the duplicated content is adjusted to avoid duplication. For example, the personal introduction in the resume skill content is compared with the personal introduction of the published resumes obtained through various channels, and if there is content duplication, the description of the duplicated content is adjusted to avoid duplication.

[0100] Optionally, the resume skill content can also be processed by the AI model. Optionally, the AI model can also include a special resume detection model for processing the resume skill content to obtain the resume skill content after the duplicate checking processing. Optionally, the special resume generation model and the special resume detection model can independently cooperate to effectively ensure the integrity of the resume and reduce the duplication of the resume.

[0101] Optionally, the method of the embodiment can further include at least one of the following: Obtaining employment location information; Obtaining cultural custom information corresponding to the employment location information; Optimizing the resume skill content or the target resume according to the cultural custom information.

[0102] Optionally, the employment location information can be obtained from the personal basic information (for example, the personal basic information includes the employment location information or is determined according to the current address in the personal basic information). Optionally, the employment location information can also be set and guided to guide the user to set. Optionally, the employment location information can also be processed by positioning, and the positioning information obtained by the positioning processing is determined. Optionally, the cultural custom information includes but is not limited to a set of words that infringe on local religious beliefs, a set of words that have ambiguity in the local area, a set of words that are prohibited by local laws, and the like.

[0103] Optionally, the resume skill content or the target resume is optimized according to the cultural custom information, for example, the words that infringe on local religious beliefs, the words that have ambiguity in the local area, the words that are prohibited by local laws, and the like in the resume skill content or the target resume are removed or replaced.

[0104] Optionally, the employment location information corresponding to the cultural custom information, and the resume skill content or the target resume are optimized according to the cultural custom information, can also be realized by the AI model (for example, the special resume detection model described above). In this way, the technical solution of the embodiment can effectively ensure the integrity of the resume and reduce the duplication of the resume, and ensure that the resume content meets the cultural and legal requirements.

[0105] Optionally, the embodiment can perform content screening on the target resume according to the cultural custom information to obtain cultural risk content in the target resume, and optimize the cultural risk content to update the target resume.

[0106] Optionally, the embodiment can perform content screening on the resume skill content according to the cultural custom information, to obtain cultural risk content in the resume skill content, and perform optimization processing on the cultural risk content, to update the resume skill content, so as to generate the target resume according to the updated resume skill content and the personal basic information.

[0107] Optionally, according to the resume skill content and the personal basic information, the step of generating the target resume comprises: obtaining language type information corresponding to the employment location information; and generating the target resume according to the resume skill content, the personal basic information and the language type information. In this way, the technical solution of the embodiment can generate the target resume according to the language of the employment location, thereby improving the user experience.

[0108] Optionally, the technical solution of the embodiment can also generate multiple language versions of the target resume according to the preset multiple language type information, the resume skill content and the personal basic information, for the user to select.

[0109] Optionally, the method of the embodiment further comprises: in response to meeting a second preset condition, collecting recruitment response information after the target resume is published; and performing recall calculation processing according to the recruitment response information, to adjust and update the AI model and / or the knowledge base corresponding thereto. The technical solution of the embodiment can have a resume recall function, which can automatically detect the quality of the generated target resume, so that the quality of the target resume can trigger the resume to be regenerated (for example, the personal introduction and skill label are regenerated), and in addition, the iteration update of the knowledge base of the AI model can be triggered, to ensure the availability of the resume generated by the AI model.

[0110] Optionally, the second preset condition can represent various scenarios triggering the recall calculation.

[0111] Optionally, the recruitment response information can represent information reflecting the degree of fit between the target resume and the recruitment demand of the employing unit after the target resume is published.

[0112] Optionally, the recruitment response information includes at least one of, but is not limited to, the number of views, the number of invitations, the number of rejections, the number of interview rounds, etc.

[0113] Optionally, when the recruitment software or platform is opened or logged in, the collection of the number of views and the number of invitations within a preset time period after the publication of the target resume is triggered, and recall calculation is performed to achieve: when the number of invitations / number of views is too low (e.g., lower than a first preset value), the entries in the information collection table corresponding to the target resume are lowered in priority in the knowledge base of the AI model, and / or the step of obtaining the corresponding information collection table through the AI model is returned to obtain a new information collection table (e.g., new entries are selected from the corresponding knowledge base of the AI model to obtain a new information collection table); when the number of invitations / number of views is too high (e.g., higher than the first preset value or a second preset value, the second preset value being higher than the first preset value), the entries in the information collection table corresponding to the target resume are raised in priority in the knowledge base of the AI model.

[0114] The resume generation method provided by the embodiment can be applied to a smart terminal and includes the steps of: S11, obtaining a corresponding information collection table through an AI model in response to the input of personal basic information; and S12, generating a target resume according to the information collection result corresponding to the interactive operation and / or the personal basic information in response to the interactive operation on the information collection table. Through the technical solution of the embodiment, the information collection table for determining the skills of a user can be obtained or generated through the AI model after the input of the personal basic information of the user, so that the information collection result obtained by the user through simple interactive operation on the information collection table is used to generate a resume including personal basic information and / or skill content. In this way, the technical solution of the embodiment can simplify the generation of a resume in a model-assisted manner to adapt to a group of people with weak resume compiling ability, and the operation is simple and convenient.

[0115] Second embodiment Based on the inventive concept of the resume generation method provided by the first embodiment of the present application, referring to Figure 5 The embodiment provides a resume generation system, which includes a client and a server. The client includes an information input module, a work information collection module, and a resume display module. The server is configured with a general generation model, a special post-requirement model, a special resume generation model, and a special resume detection model. The server further includes a resume recall module.

[0116] The information input module is configured to provide an input interface to enable a user to input personal basic information, and transmit the personal basic information to the server through an API interface after the input of the personal basic information is completed, so that the server invokes the special post-requirement model to generate a corresponding information collection table, and feeds back the information collection table to the work information collection module.

[0117] Optionally, the personal basic information includes personal information, work experience, and post information.

[0118] Optionally, the knowledge base of the dedicated post-requirement model is trained by the post published in the recruitment system, and is continuously fine-tuned according to the resume recall module. For example, the resume recall module can increase the priority of the content with a high invitation / preview ratio. The content of the knowledge base of the dedicated post-requirement model can be obtained by calling the API interface of the general generative model and then stored. When the dedicated post-requirement model cannot provide the information collection form of the post, the information collection form is obtained by calling the general generative model.

[0119] The work information collection module is configured to display the information collection form to guide the user to check by selecting the question form, and to obtain and send the information collection result to the server after the user checks all the selected questions corresponding to the information collection form, so that the server calls the dedicated resume generation model to generate the personal introduction and the ability label in the resume, and generates and outputs the basic resume to the resume display module according to the personal introduction, the ability label and the personal basic information.

[0120] Optionally, the ability label includes an experience label, a skill label, etc.

[0121] Optionally, the basic resume can include a personal information, a job type / post, an expected salary, a personal introduction and an ability label.

[0122] Optionally, the information collection form can only need pure selection and almost no input of text, so as to effectively reduce the difficulty of resume writing.

[0123] Optionally, the information collection form is displayed in the form of a selection question questionnaire, the dedicated post-requirement model selects 7 skill description selection questions from the knowledge base of the dedicated post-requirement model, the user checks the skill description options, and the information collection result is obtained.

[0124] Optionally, the dedicated resume generation model can generate the personal introduction and the ability label content of the resume according to the information collection result. When the dedicated resume generation model cannot provide the personal introduction and the ability label content of the specific post, the general generative model is called to generate the personal introduction and the ability label content. In addition, the keywords of the personal introduction and the ability label content in the knowledge base of the dedicated resume generation model can be derived from the general generative model and the recruitment system. When the knowledge base content of the dedicated resume generation model is trained from the posts published in the recruitment system, the personal introduction and the ability label content generated by the dedicated resume generation model have high post matching degree.

[0125] The resume display module includes a resume preview function and a guided editing function to realize content detection optimization and supplementary information guidance of the basic resume by calling the dedicated resume detection model of the server.

[0126] Optionally, the content check optimization can implement description adjustment of the content repeated with others in the basic resume to avoid repetition, and content optimization of the content violating cultural customs to avoid cultural custom risks, for example, there are multiple religions in the Bangladesh region, and optimization needs to be performed according to religious customs.

[0127] Optionally, the supplementary information guidance can implement checking of missing content in the basic resume, and guiding the user to optimize, which can include guiding the user to upload pictures / qualification certificates.

[0128] Optionally, the resume display module can also perform translation for multilingual regions. For example, when the Bangladesh region supports Bengali and English, various processed basic resumes are translated into Bengali version and English version to obtain target resumes.

[0129] Among them, the resume recall module can record the invitation / preview of the resume, to implement fine-tuning of the AI model (for example, at least one of the general generative model, the dedicated post-demand model, the dedicated resume generation model, etc.) and its corresponding knowledge base.

[0130] Optionally, when the specific APP in the client is opened every day, the recall calculation process is triggered once to calculate the invitation / preview in a preset time period, and when the invitation / preview is too low, a new information collection table (the dedicated post-demand model selects new 7 questions from the numerous skill descriptions in its knowledge base) corresponding to the post information in the aforementioned personal basic information is triggered to pop up, and after the user completes the check of the selection questions in the information collection table, the new information collection result is reacquired, and then the dedicated resume generation model is called to generate the personal introduction and the ability label according to the new information collection result, and the priority of the 7 selection questions in the previous information collection table is reduced; or when the invitation / preview is too high, the selection questions in the information collection table corresponding to the current target resume are promoted in the priority in the database in the dedicated post-demand model under the specific post category.

[0131] The technical solution of the embodiment can generate an information collection table for the user to check off according to the user's personal basic information (for example, the post information therein) with the aid of one or more AI models, and after the user checks off the information table and obtains the information collection result, the resume can be generated with the aid of one or more AI models, thereby realizing the simplification of resume generation in a model-assisted manner. In addition, the technical solution of the embodiment can also verify the generated resume, thereby guiding the user to complete the information and / or avoiding cultural custom risks; in addition, the technical solution of the embodiment can perform recall calculation processing on the acceptance, rejection and interview round of the resume, thereby realizing the updating of the resume and / or the optimization of the AI model and the corresponding knowledge base, and therefore, the technical solution of the embodiment can automatically detect the quality of the generated resume, trigger the process of regenerating the personal introduction and the ability label of the client, and at the same time, trigger the iterative updating of the knowledge base, thereby ensuring the availability of the resume generated by the AI model, so as to facilitate the generation of a resume that is more in line with the recruitment requirements of the employing unit in the future. The technical solution of the embodiment adopts a combination of a special-purpose model and a general-purpose generative model, which can reduce the cost of building a special-purpose model, ensure high availability through a general-purpose generative model, and ensure the authenticity of the resume and reduce the operation difficulty through the post requirement model in the special-purpose model. The post information table generated by the special-purpose post requirement model and the knowledge content of the job type post in the special-purpose post requirement model and the knowledge base derived from the recruitment system can make the special-purpose post requirement model generate an information collection table that is more in line with the requirements of the post in the current recruitment system. The special-purpose resume generation model and the special-purpose resume detection model in the special-purpose model can effectively ensure the integrity of the resume and reduce the repetition of the resume, and ensure that the content of the resume meets the cultural customs and legal requirements.

[0132] Optionally, taking blue-collar workers as an example, blue-collar workers generally have low education, and it is difficult for them to operate documents of electronic products such as mobile phones and computers. Due to the low culture and expression barriers of blue-collar workers with varying levels of education, they often feel at a loss when writing a resume, especially in the skills, personal introduction and work experience introduction, and thus their enthusiasm and efficiency in the job-hunting process are affected. Therefore, the technical solution of the embodiment can be applied to a recruitment APP for blue-collar workers, so that the blue-collar workers can input simple personal basic information (such as name, contact information and job type) and perform simple selection and check-off operations according to the guidance of the recruitment APP, so that the recruitment APP can know the user's selection of relevant skills, work fields and post expectations, and thus based on this information, the recruitment APP can call an AI model to quickly generate a resume that meets the user's post requirements and personal expectations. Referring to Figure 6 , the process of generating a resume through the recruitment APP includes: Step 1: Enter personal information and post information; Second step: generating an information collection table from the model; Third step: generating a resume from the model according to the information collection result.

[0133] The personal information includes at least one of name, age, gender, contact information, etc.

[0134] The post information can represent post, work, industry, etc.

[0135] After completing the first step, Prompt+ inquiry words can be generated according to the entered personal information and post information to call the model, wherein the Prompt+ inquiry words are, for example, "I am a blue-collar worker, male, 45 years old, if I want to find a quality inspector job in manufacturing industry, but my cultural level is not high, what information do I need to provide, preferably in the form of choices, reduce the difficulty, to help the employer quickly understand me, help me find a job faster, please design an information collection table", wherein "male, 45 years old", "quality inspector in manufacturing industry" are the information entered by the user in the first step.

[0136] In the second step, the model can generate an information collection table according to the Prompt+ inquiry words, and the information collection table presents options of skill requirements, job types, salary requirements, etc. in a formatted form, so that after displaying the information collection table, the user can obtain the information collection result through pure check.

[0137] After completing the second step, the model can be called according to the information collection result combined with the Prompt+ inquiry words, wherein the Prompt+ inquiry words are, for example, "generate a 100-word introduction, divided into 5 parts" and / or "generate experience tags, skill tags, time adaptation tags".

[0138] In the third step, the model can generate a personal introduction and ability tags (i.e. experience tags, skill tags, time adaptation tags) according to the information collection result combined with the Prompt+ inquiry words, and when the personal introduction and ability tags contain contents such as education background, professional skills, company, etc., the user can be guided to adjust the proof documents (such as photos, certificates and other attachments, etc.), so that the resume can be generated according to the above contents in the subsequent step.

[0139] Optionally, the model generates a self-introduction of 100 words or less in 5 parts according to the instructions obtained from the information collection results and the Prompt+ inquiry words, for example: 1. Quality inspection tool usage (multiple choice): simple measuring instruments; 2. Work ability (multiple choice): quality problem identification; 3. Past experience industry: mechanical manufacturing; please help me generate a self-introduction of 100 words or less in 5 parts. Subsequently, the model generates a personal introduction according to the aforementioned instructions, for example: 1. I am an experienced quality inspector proficient in using simple measuring instruments; 2. I have accumulated rich quality inspection experience in the mechanical manufacturing industry; 3. I am good at identifying and solving quality problems to ensure that products meet standards; 4. I have good team cooperation ability and can effectively communicate and cooperate; 5. I look forward to continuing to exert my professional skills in a new work environment.

[0140] Thus, the technical solution of the present example can realize a brand-new resume generation method, effectively reduce the threshold for blue-collar workers to write resumes, provide a simple and convenient resume generation method for blue-collar workers, and thereby significantly improve the job-seeking efficiency of blue-collar workers, help them better showcase themselves, and stand out in the fierce job market competition.

[0141] The embodiments of the present application also provide an intelligent terminal, including a memory and a processor, the memory stores a computer program, and the computer program is executed by the processor to realize the steps of the resume generation method in any of the above embodiments.

[0142] The embodiments of the present application also provide a storage medium, the storage medium stores a computer program, and the computer program is executed by the processor to realize the steps of the resume generation method in any of the above embodiments.

[0143] In the embodiments of the intelligent terminal and the storage medium provided by the present application, all technical features of any of the above resume generation method embodiments can be included, and the description and explanation content is basically the same as that of the above method embodiments, which will not be repeated here.

[0144] The embodiments of the present application also provide a computer program product, which includes computer program code, when the computer program code runs on a computer, so that the computer executes the method in various possible embodiments as above.

[0145] The embodiments of the present application also provide a chip, including a memory and a processor, the memory is used to store a computer program, and the processor is used to call and run the computer program from the memory, so that the device installed with the chip executes the method in various possible embodiments as above.

[0146] It can be understood that the above scenarios are only as examples and do not constitute a limitation on the application scenarios of the technical solutions provided by the embodiments of the present application. The technical solutions provided by the embodiments of the present application are also applicable to other scenarios. For example, those skilled in the art can know that with the evolution of system architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present application are also applicable to similar technical problems.

[0147] The sequence numbers of the above embodiments of the present application are only for description and do not represent the advantages and disadvantages of the embodiments.

[0148] The steps in the method of the embodiments of the present application can be adjusted, combined and reduced in sequence according to actual needs.

[0149] The units in the device of the embodiments of the present application can be combined, divided and reduced according to actual needs.

[0150] In the present application, for the same or similar term concept, technical solution and / or application scenario description, generally only the first time is described in detail, and the repeated description is not repeated in order to be brief. When understanding the technical solutions of the present application, the same or similar term concept, technical solution and / or application scenario description, etc. which are not described in detail later can refer to the relevant description before.

[0151] In the present application, the description of each embodiment has its own focus, and the parts not described or recorded in a certain embodiment can be referred to the relevant description of other embodiments.

[0152] Each technical feature of the technical solutions of the present application can be combined arbitrarily. In order to make the description simple, not all possible combinations of each technical feature in the above embodiments are described. However, as long as the combinations of these technical features do not exist contradictory, they should be considered as the scope of the present application.

[0153] From the above description of the embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment method can be realized by means of software and necessary general hardware platform, of course, it can also be realized by hardware, but in many cases the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a software product, which is stored in a storage medium (such as a ROM / RAM, a magnetic disk, an optical disk) as above, and includes a plurality of instructions to make a terminal device (which can be a mobile phone, a computer, a server, a controlled terminal, or a network device, etc.) execute the method of each embodiment of the present application.

[0154] In the above embodiments, all or part of the embodiments can be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments can be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions according to the embodiments of the present application are generated. The computer can be a general purpose computer, a special purpose computer, a computer network, or other programmable apparatus. The computer instructions can be stored in a storage medium or transferred from one storage medium to another storage medium, for example, the computer instructions can be transferred from one website, computer, server or data center to another website, computer, server or data center through wired (for example, coaxial cable, optical fiber, digital subscriber line) or wireless (for example, infrared, wireless, microwave, etc.). The storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, data center, etc. integrated with one or more available media. The available media can be magnetic media (for example, floppy disk, storage disk, magnetic tape), optical media (for example, DVD), or semiconductor media (for example, solid state disk (SSD)) and the like.

[0155] The above is only the preferred embodiment of the present application, and does not limit the patent scope of the present application, and any equivalent structure or equivalent process transformation using the content of the specification and drawings of the present application, or direct or indirect application in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A resume generation method, characterized in that, Including the following steps: S11: In response to the input of basic personal information, the corresponding information collection form is obtained through the AI ​​model; S12: In response to an interactive operation on the information collection form, generate a target resume based on the information collection result corresponding to the interactive operation and / or the personal basic information.

2. The resume generation method according to claim 1, characterized in that, The methods for obtaining the corresponding information collection form through AI models include at least one of the following: A first information collection table corresponding to the job information in the personal basic information is generated by a first dedicated generative model; A second information collection form corresponding to the job information in the personal basic information is generated using a general generative model; The information collection table is obtained based on the first information collection table and / or the second information collection table.

3. The resume generation method according to claim 1, characterized in that, Interactive operations on the information collection form include at least one of the following: Select an option from the displayed information collection form; Provide voice responses to the questions output from the information collection form.

4. The resume generation method according to any one of claims 1 to 3, characterized in that, Step S12 includes: The AI ​​model is used to obtain the resume skills content corresponding to the information collection results. The target resume is generated based on the skills described in the resume and the individual's basic information.

5. The resume generation method according to claim 4, characterized in that, The method of obtaining resume skills content corresponding to the information collection results through an AI model includes at least one of the following: The first resume skills content corresponding to the information collection results is generated by a second dedicated generative model; A second resume with skills content corresponding to the information collection results is generated using a general generative model; The resume skills content is obtained based on the skills content of the first resume and / or the skills content of the second resume.

6. The resume generation method according to claim 4, characterized in that, It also includes at least one of the following: In response to meeting the first preset condition, perform supplementary guidance operations; Update the target resume according to the supplementary resume content corresponding to the supplementary guidance operation; The target resume is generated based on the skills described in the resume, the basic personal information, and the supplementary information provided in the resume. The skills section of the resume was checked for plagiarism. The target resume is generated based on the skills content of the resume after plagiarism detection, the personal basic information, and / or the supplementary content of the resume.

7. The resume generation method according to claim 4, characterized in that, It also includes at least one of the following: Obtain information on employment locations; Obtain cultural and custom information corresponding to the employment location information; Based on the cultural and customary information, the resume skills content or the target resume is optimized. The step of generating the target resume based on the skills content of the resume and the personal basic information includes: Obtain language type information corresponding to the employment location information; The target resume is generated based on the skills described in the resume, the personal basic information, and the language type information.

8. The resume generation method according to claim 4, characterized in that, Also includes: In response to meeting the second preset condition, collect recruitment response information after the target resume is published; Recall calculations are performed based on the recruitment response information to adjust and update the AI ​​model and / or its corresponding knowledge base.

9. A smart terminal, characterized in that, include: A memory and a processor, wherein the memory stores a computer program, and the computer program, when executed by the processor, implements the steps of the resume generation method as described in any one of claims 1 to 8.

10. A storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the steps of the resume generation method as described in any one of claims 1 to 8.

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