User feature determination method and electronic equipment

Abstract

The invention provides a user feature determination method and electronic equipment, and relates to the technical field of medical treatment. The method comprises the following steps: acquiring behavior data of a target user generated in a target application; the target application is an application related to medical diagnosis; determining a target label corresponding to the behavior data in the label set by using a preset label model; the target label is used for representing portrait features of the target user; and taking the target tag as a feature tag of the target user.

Description

Technical Field

[0001] The present disclosure relates to the field of medical technology, and in particular to a method for determining user characteristics and an electronic device. Background Art

[0002] In the relevant technology, medical institutions currently only have the basic information and case information of patients. These data can only be used as basic information for diagnosis of the disease, resulting in a relatively single and inaccurate patient portrait, which is not conducive to doctors' understanding of the patient's condition. Summary of the invention

[0003] The present disclosure provides a method for determining user characteristics and an electronic device, which can help shorten the time for obtaining the database language statement, thereby improving the efficiency of generating a report to be generated.

[0004] In a first aspect, the present disclosure provides a method for determining user characteristics, which is applied to an electronic device, and the method includes: obtaining behavioral data of a target user generated in a target application; the target application is an application related to medical diagnosis; using a preset label model to determine a target label in a label set that corresponds to the behavioral data; the target label is used to represent the portrait characteristics of the target user; and the target label is used as a feature label of the target user.

[0005] In some embodiments, the tag set includes personalized tags, and the method also includes: collecting behavioral data of multiple visiting users generated in the target application; using a tag generation model to obtain a personalized tag corresponding to the behavioral data of each visiting user based on the behavioral data of multiple visiting users; the personalized tag is used to represent the portrait characteristics of the visiting user.

[0006] In some embodiments, the personalized tag is determined by the tag generation model to have a tag level, wherein a superior tag is associated with at least one subordinate tag, and the portrait feature represented by the subordinate tag is a sub-feature of the portrait feature represented by the superior tag.

[0007] In some embodiments, the tag set also includes basic tags, which are determined based on basic information and case information of users accessing the target application.

[0008] In some embodiments, a preset label model is used to output target data according to a preset format template and input behavior data. The data format of the target data conforms to the preset format template, and the target data includes a target label.

[0009] In some embodiments, obtaining the behavior data of the target user generated in the target application includes: receiving the behavior data sent by the second terminal, where the behavior data is determined by the target application in response to a touch operation of the target user.

[0010] In some embodiments, the method further includes: sending a feature tag related to the target user to the first terminal.

[0011] In a second aspect, the present disclosure provides a method for generating a user portrait, which is applied to a first terminal, and the method includes: receiving a feature tag of a target user sent by an electronic device; the feature tag is a tag corresponding to the behavior data of the target user in a tag set determined using a preset tag model; based on the feature tag, generating a user portrait of the target user; and displaying the user portrait on a display page of the first terminal.

[0012] In some embodiments, the user portrait includes a tag forest consisting of multiple tag trees, and the tag data in each tag tree includes at least one feature tag.

[0013] In a third aspect, the present disclosure provides a communication method, applied to a second terminal, the method comprising: determining behavior data of a target user in response to a touch operation of the target user on a target application; the target application is an application related to medical diagnosis; and sending the behavior data to an electronic device.

[0014] In a fourth aspect, the present disclosure provides a device for determining user characteristics, which is applied to an electronic device, and the device includes: an acquisition unit and a processing unit; the acquisition unit is used to acquire the behavior data of the target user generated in the target application; the target application is an application related to medical diagnosis; the processing unit is used to use a preset label model to determine the target label corresponding to the behavior data in the label set; the target label is used to represent the portrait characteristics of the target user; and the target label is used as the feature label of the target user.

[0015] In some embodiments, the tag set includes personalized tags, and the processing unit is also used to collect behavioral data of multiple visiting users generated in the target application; using the tag generation model, based on the behavioral data of multiple visiting users, the personalized tags corresponding to the behavioral data of each visiting user are obtained; the personalized tags are used to represent the portrait characteristics of the visiting users.

[0016] In some embodiments, the personalized tag is determined by the tag generation model to have a tag level, wherein a superior tag is associated with at least one subordinate tag, and the portrait feature represented by the subordinate tag is a sub-feature of the portrait feature represented by the superior tag.

[0017] In some embodiments, the tag set also includes basic tags, which are determined based on basic information and case information of users accessing the target application.

[0018] In some embodiments, a preset label model is used to output target data according to a preset format template and input behavior data. The data format of the target data conforms to the preset format template, and the target data includes a target label.

[0019] In some embodiments, the acquisition unit is specifically configured to receive behavior data sent by the second terminal, where the behavior data is determined by the target application in response to a touch operation of the target user.

[0020] In some embodiments, the processing unit is further configured to send a feature tag related to the target user to the first terminal.

[0021] In a fifth aspect, the present disclosure provides a device for generating a user portrait, which is applied to a first terminal. The device includes a processing unit, which is used to receive a feature tag of a target user sent by an electronic device; the feature tag is a tag corresponding to the behavior data of the target user in a tag set determined by a preset tag model; based on the feature tag, a user portrait of the target user is generated; the user portrait is displayed on a display page of the first terminal.

[0022] In some embodiments, the user portrait includes a tag forest consisting of multiple tag trees, and the tag data in each tag tree includes at least one feature tag.

[0023] In a sixth aspect, the present disclosure provides a communication device, applied to a second terminal, the device comprising a processing unit and a communication unit; the processing unit is used to determine the behavior data of the target user in response to the touch operation of the target user in the target application; the target application is an application related to medical diagnosis; the communication unit is used to send the behavior data to the electronic device.

[0024] In a seventh aspect, the present disclosure provides a user portrait generation system, which includes a first terminal, a second terminal, and an electronic device; the second terminal is used to determine the behavior data of the target user in response to the touch operation of the target user in the target application; and send the behavior data to the electronic device.

[0025] The electronic device is used to obtain the behavior data of the target user generated in the target application; the target application is an application related to medical diagnosis; a preset label model is used to determine the target label corresponding to the behavior data in the label set; the target label is used as a characteristic label of the target user, and the characteristic label of the target user is sent to the first terminal.

[0026] The first terminal is used to receive a feature tag of a target user sent by an electronic device, and generate a user portrait of the target user based on the feature tag; the user portrait is displayed on a display page of the first terminal.

[0027] In an eighth aspect, the present disclosure provides an electronic device, comprising: a memory and a processor; the memory is used to store computer instructions; the processor is used to implement any one of the optional methods in the above-mentioned first aspect when executing the computer instructions.

[0028] In a ninth aspect, the present disclosure provides a computer-readable storage medium, in which a computer program or instruction is stored. When the computer program or instruction is executed by a processing device, any optional method in the first aspect is implemented.

[0029] In a tenth aspect, the present disclosure provides a computer program product, including a computer program or instructions, which, when executed by a processing device, implements any one of the optional methods in the first aspect above.

[0030] The user feature determination method provided by the present disclosure can efficiently and in real time obtain various types of behavior data generated by the target user (i.e., the patient) in applications related to medical diagnosis. By continuously collecting and analyzing the behavior data, the health information changes of the target user can be dynamically updated to ensure that the user status mastered is the latest and comprehensive. Then, the collected behavior data is parsed using a preset tag model to determine the target tag corresponding to the current behavior data, and the target tag is stored and managed as the feature tag of the target user. Doctors can timely understand the latest changes in the patient's health status based on these real-time updated feature tags, so as to make more accurate diagnostic decisions, formulate personalized treatment plans, or adjust existing treatment plans.

[0031] In addition, this feature label can not only be easily and quickly accessed by doctors, but can also be presented to users themselves in a visual way, enhancing their ability to understand and manage their own health conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0033] Figure 1 A schematic diagram of a user portrait generation system architecture provided in an embodiment of the present disclosure;

[0034] Figure 2 A schematic diagram of the composition of a terminal device provided in an embodiment of the present disclosure;

[0035] Figure 3 A schematic diagram of the composition of an electronic device provided in an embodiment of the present disclosure;

[0036] Figure 4 A flowchart of a method for determining user characteristics provided by an embodiment of the present disclosure;

[0037] Figure 5 A flowchart of another method for determining user characteristics provided by an embodiment of the present disclosure;

[0038] Figure 6 A flowchart of a method for generating a user portrait provided in an embodiment of the present disclosure;

[0039] Figure 7 A schematic block diagram of a user portrait provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present disclosure to clearly and completely describe the technical solutions in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present disclosure.

[0041] In the description of the present disclosure, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present disclosure. In addition, the terms "first", "second", and "third" are used only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, the features defined as "first", "second", and "third" may explicitly or implicitly include one or more features. In the description of the present disclosure, the meaning of "multiple" is two or more, unless otherwise clearly and specifically defined.

[0042] In the description of the present disclosure, the word "exemplary" is used to mean "used as an example, illustration, or illustration". Any embodiment described in the present disclosure as "exemplary" is not necessarily to be construed as being preferred or advantageous over other embodiments. The following description is given to enable any technician in the field to implement and use the present disclosure. In the following description, details are listed for the purpose of explanation. It should be understood that a person of ordinary skill in the art can recognize that the present disclosure can be implemented without using these specific details. In other examples, well-known structures and processes will not be elaborated in detail to avoid obscuring the description of the present disclosure with unnecessary details. Therefore, the present disclosure is not intended to be limited to the embodiments shown, but is consistent with the widest scope consistent with the principles and features disclosed in the present disclosure.

[0043] In current medical technology and practice, the patient data held by medical institutions is mainly limited to basic identity information (such as name, age, gender, contact information, etc.) and case information (including past medical history, diagnosis results, treatment records, drug use history, etc.). Although this information plays a fundamental role in the initial diagnosis of the disease, its scope is relatively narrow, and its depth and breadth are insufficient. Therefore, the constructed patient portraits often appear single and inaccurate.

[0044] Specifically, this limitation is reflected in many aspects: First, important information such as patients' physiological parameters (such as real-time monitoring data of blood pressure, blood sugar, heart rate, etc.), living habits (such as dietary preferences, exercise habits, sleep quality), genetic factors (family medical history, genetic test results) and mental health status (stress level, mood changes, history of mental illness) are often ignored or not effectively integrated into the patient portrait. This information is crucial for comprehensively assessing the patient's health status, predicting the development trend of the disease, and formulating personalized treatment plans.

[0045] Secondly, with the development of medical information technology and big data technology, the sources of medical data are becoming increasingly diverse, including but not limited to wearable devices, remote monitoring systems, electronic health record systems, social media health-related data, etc. However, many medical institutions have not yet established an effective mechanism to collect, integrate and analyze these massive data from different channels, resulting in a significant reduction in the richness and accuracy of patient portraits.

[0046] Furthermore, the singleness of patient portraits is also reflected in the lack of tracking and updating of patients' dynamic changes. The development of diseases is dynamic, and the patient's physical and psychological state will also change over time. However, the existing patient information update mechanism is often lagging behind and cannot reflect the patient's latest condition in a timely manner, thus affecting the doctor's comprehensive understanding of the patient's condition.

[0047] In summary, the problems that exist in the construction of patient portraits in current medical institutions not only limit doctors' in-depth understanding of patients' health conditions and accurate treatment, but also hinder the personalized and intelligent development of medical services. Therefore, exploring and implementing more comprehensive, accurate and dynamic patient portrait construction methods has become the key to improving the quality and efficiency of medical services.

[0048] Based on the above technical problems, the disclosed embodiment provides a method for determining user characteristics, which can efficiently and in real time obtain various types of behavior data generated by the target user (i.e., the patient) in applications related to medical diagnosis. By continuously collecting and analyzing the behavior data, the health information changes of the target user can be dynamically updated to ensure that the user status is up-to-date and comprehensive. Then, the collected behavior data is parsed using a preset label model to determine the target label corresponding to the current behavior data, and the target label is stored and managed as the characteristic label of the target user. Doctors can timely understand the latest changes in the patient's health status based on these real-time updated characteristic labels, so as to make more accurate diagnostic decisions, formulate personalized treatment plans, or adjust existing treatment plans.

[0049] In addition, this feature label can not only be easily and quickly accessed by doctors, but can also be presented to users themselves in a visual way, enhancing their ability to understand and manage their own health conditions.

[0050] In order to facilitate understanding of the embodiments of the present disclosure, the following points are explained before introducing the embodiments of the present disclosure.

[0051] 1. In the embodiments of the present disclosure, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain information is called information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated, such as but not limited to, directly indicating the information to be indicated, such as the information to be indicated itself or the index of the information to be indicated. The information to be indicated may also be indirectly indicated by indicating other information, wherein the other information is associated with the information to be indicated. It is also possible to indicate only a part of the information to be indicated, while the other parts of the information to be indicated are known or agreed in advance.

[0052] 2. “Pre-setting” can be achieved by pre-saving corresponding codes, tables or other methods that can be used to indicate relevant information in a device (for example, a client device or a server device). The embodiments of the present disclosure do not limit the specific implementation method.

[0053] 3. In the embodiments of the present disclosure, descriptions such as "in the case of ...", "if" and "if" all mean that under certain objective circumstances, the device (such as a client device or a server device) will make corresponding processing, which does not limit the time, nor does it require the device (such as a client device or a server device) to make a judgment action when implementing it, nor does it mean that there are other limitations.

[0054] In addition, the system architecture and business scenarios described in the embodiments of the present disclosure are intended to more clearly illustrate the technical solutions of the embodiments of the present disclosure, and do not constitute a limitation on the technical solutions provided by the embodiments of the present disclosure. A person of ordinary skill in the art can appreciate that with the evolution of the system architecture and the emergence of new business scenarios, the technical solutions provided by the embodiments of the present disclosure are equally applicable to similar technical problems.

[0055] In addition, the actions, terms, etc. involved in the various embodiments of the present disclosure can refer to each other without limitation. The message name or parameter name in the message exchanged between the various devices in the embodiments of the present disclosure is only an example, and other names can also be used in the specific implementation without limitation.

[0056] The following is an exemplary introduction to the system architecture of the embodiments of the present disclosure.

[0057] In some embodiments, the method for determining user characteristics provided by the embodiments of the present disclosure can be applied to Figure 1 In the system architecture shown. For example, Figure 1 A schematic diagram of a user portrait generation system architecture provided by an embodiment of the present disclosure. Figure 1 , the system architecture may include: a first terminal 101, a second terminal 102 and a server 103. The first terminal 101, the second terminal 102 and the server 103 may be in different locations, such as in different cities. The first terminal 101, the second terminal 102 and the server 103 may communicate through a network 104. The network 104 may be the Internet, or other networks (such as Ethernet). The network 104 may include one or more network devices, such as a network device may be a router or a switch. A database is created on both the first terminal 101 and the server 103, and the database may be a relational database, a non-relational database, a graph database, a time series database, etc.

[0058] The first terminal 101 and the second terminal 102 may be installed on a client device, such as a terminal device. In some embodiments, the client device is at least one of a smart phone, a smart watch, a printer, a desktop computer, a laptop computer, a virtual reality terminal, an augmented reality terminal, a wireless terminal, and a laptop computer.

[0059] In some embodiments, the first terminal 101 may be a terminal used by a doctor. The first terminal 101 has a communication function and can access a wired network or a wireless network.

[0060] In the disclosed embodiment, the first terminal 101 may receive a feature tag of a target user (ie, a patient) sent by the server 103 , and then generate a user profile of the target user based on the feature tag.

[0061] The user portrait is displayed on a display page of the first terminal; the feature tag is a tag corresponding to the behavior data of the target user in a tag set determined by a preset tag model.

[0062] In some embodiments, the second terminal 102 may be a terminal used by a target user (ie, a patient). The second terminal 102 has a communication function and can access a wired network or a wireless network.

[0063] In the disclosed embodiment, the second terminal 102 may determine the behavior data of the target user in response to the touch operation of the target user on the target application, and send the behavior data to the server 103 .

[0064] Among them, the target applications are those related to medical diagnosis.

[0065] In some embodiments, the server 103 can be installed on an electronic device, such as a server. In some embodiments, the electronic device can be an independent physical server, or a server cluster or distributed file system composed of multiple physical servers, or at least one of cloud servers that provide basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content distribution networks, and big data or artificial intelligence platforms, etc., which are not limited in the embodiments of the present disclosure. Of course, the server 103 can also include other functions to provide more comprehensive and diversified services.

[0066] In the disclosed embodiment, the server 103 receives the behavior data of the target user sent by the second terminal, and uses a preset tag model to determine the target tag corresponding to the behavior data in the tag set, and then uses the target tag as a feature tag of the target user.

[0067] Among them, the behavior data is determined by the target application in response to the touch operation of the target user; the target application is an application related to medical diagnosis; and the target tag is used to represent the portrait characteristics of the target user.

[0068] In a possible implementation, the relevant functions in the embodiments of the present disclosure may be implemented by one device, or by multiple devices together, or by one or more functional modules in one device, and the embodiments of the present disclosure do not specifically limit this. It is understandable that the above functions may be network elements in hardware devices, or software functions running on dedicated hardware, or a combination of hardware and software, or virtualization functions instantiated on a platform (e.g., a cloud platform).

[0069] When implementing it specifically, Figure 1 The first terminal and the second terminal shown can both adopt Figure 2The structure shown, or including Figure 2 Parts shown. Figure 2 A schematic diagram of the composition of a terminal device provided in an embodiment of the present disclosure includes at least one processor 201, a communication line 202, and at least one communication interface 204, and may also include a memory 203. The processor 201, the memory 203, and the communication interface 204 may be connected via the communication line 202.

[0070] The processor 201 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application, such as one or more digital signal processors (DSP), or one or more field programmable gate arrays (FPGA).

[0071] The communication link 202 may include a pathway for transmitting information between the above-mentioned components.

[0072] The communication interface 204 is used to communicate with other devices or communication networks, and can use any transceiver-like device, such as Ethernet, radio access network (RAN), wireless local area network (WLAN), etc.

[0073] The memory 203 may be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), a magnetic disk storage medium or other magnetic storage device, or any other medium that can be used to include or store desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited to these.

[0074] In one possible design, the memory 203 can exist independently of the processor 201, that is, the memory 203 can be a memory outside the processor 201. In this case, the memory 203 can be connected to the processor 201 through the communication line 202, and is used to store execution instructions or application code, and the processor 201 controls the execution to implement the document generation method provided in the following embodiment of the present application. In another possible design, the memory 203 can also be integrated with the processor 201, that is, the memory 203 can be the internal memory of the processor 201, for example, the memory 203 is a high-speed cache, which can be used to temporarily store some data and instruction information, etc.

[0075] As a possible implementation, the processor 201 may include one or more CPUs, for example Figure 2 As another possible implementation, the electronic device may include multiple processors, such as Figure 2 As another possible implementation, the electronic device may further include an output device 205 and an input device 206.

[0076] In an example of the present application, the hardware structure diagram of the server 103 (ie, the electronic device) is as follows: Figure 3 shown. Figure 3 A schematic diagram of the composition of an electronic device provided in an embodiment of the present disclosure, the electronic device includes a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 302 or a computer program loaded from a storage unit 308 to a random access memory (RAM) 303. In RAM303, various programs and data required for the operation of the electronic device 300 can also be stored. The computing unit 301, ROM302 and RAM303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0077] Multiple components in the electronic device 300 are connected to the input / output interface 305, including: an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the electronic device 300 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0078] The computing unit 301 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit, a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors, and any appropriate processors, controllers, microcontrollers, etc. The computing unit 301 performs the various methods and processes described above, such as the data matching method. For example, in one embodiment, the data matching method may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 308. In one embodiment, part or all of the computer program may be loaded and / or installed on the electronic device 300 via ROM 702 and / or the communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of the data matching method described above may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the data matching method in any other appropriate manner (e.g., by means of firmware).

[0079] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays, application specific integrated circuits, application specific standard parts (ASSPs), system on chip systems (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0080] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0081] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of machine-readable storage media may include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories, read-only memories, erasable programmable read-only memories, optical fibers, portable compact disk read-only memories, optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0082] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user, such as a cathode ray tube (CRT) or a liquid crystal display (LCD) monitor; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and the input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0083] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: Local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.

[0084] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0085] It should be noted that the electronic device described in the embodiment of the present disclosure is for more clearly illustrating the technical solution of the embodiment of the present disclosure, and does not constitute a limitation on the technical solution provided by the embodiment of the present disclosure. A person skilled in the art can appreciate that with the evolution of the report generating device and the emergence of other report generating devices, the technical solution provided by the embodiment of the present disclosure is also applicable to similar technical problems.

[0086] Combine the following Figure 1 , a method for determining user characteristics provided by an embodiment of the present disclosure is described. Figure 4 A flowchart of a method for determining user characteristics provided by an embodiment of the present disclosure is shown in FIG. Figure 4 As shown, the method includes:

[0087] S401, the electronic device obtains the behavior data of the target user generated in the target application.

[0088] In the disclosed embodiment, the target application is an application related to medical diagnosis.

[0089] In some embodiments, the second terminal may determine the behavior data of the target user in response to the touch operation of the target user on the target application, and send the behavior data to the electronic device.

[0090] For example, the target user visits the tumor science page in the mini program once every half an hour or so, and stays on the tumor science page for up to 40 minutes each time. The second terminal can determine that the target user's behavior data is "frequently log in to the mini program, stay for more than 40 minutes, and frequently visit the tumor science page", and send the behavior data to the electronic device.

[0091] S402: The electronic device uses a preset tag model to determine a target tag in the tag set that corresponds to the behavior data.

[0092] In the disclosed embodiment, the target tag is used to represent the portrait features of the target user.

[0093] In some embodiments, the preset label model can be used to output target data according to a preset format template and input behavior data, the data format of the target data conforms to the preset format template, and the target data includes a target label.

[0094] In combination with the example in S401, the electronic device inputs the behavior data "frequently log in to the mini program, stay for more than 40 minutes, and frequently visit tumor science pages" and the required format template into the preset label model, and the preset label model extracts the associated information of the behavior data, and matches and analyzes the label set with the associated information of the behavior data to be classified, accurately identifying and determining which one or several labels in the label set have the highest correlation or match with the behavior data, thereby designating these labels as target labels corresponding to the behavior data.

[0095] It should be understood that this process aims to effectively expand and optimize the correspondence between labels and target behavior data through the intelligent analysis capabilities of the preset label model, ensure the accuracy and efficiency of the classification results, and provide accurate and valuable label information for subsequent data processing, analysis or decision support.

[0096] For example, the default format template is:

[0097] {"tagCode":"XXXX","tagName":"XXXX","tagDesc":"XXXX","tagReason":"XXXXX"};{"tagCode":"XXXX","tagName":"XXXX","tagDesc":"XXXX","tagReason":"XXXX".

[0098] The tag set is:

[0099] [{"deleteFlag":false,"tagCode":"JKGZD-ZLGZZ","tagDesc":"Frequently visit cancer science pages","tagId":"1","tagName":"Tumor focus","tagReason":"Frequently visit pages starting with pagesPopularization"},{"deleteFlag":false,"tagCode":"JKGZD-JCJYZSZ","tagDesc":"Frequently check inspection and testing pages","tagId":"2","tagName":"Inspection and testing focus","tagReason":"Frequently check pages starting with pagesInspection"},{"delete Flag":false,"tagCode":"JKGZD-FYMGYH","tagDesc":"Pay attention to pages related to expense bills","tagId":"3","tagName":"Expense-sensitive users","tagReason":"Frequently check pagesBill"},{"deleteFlag":false,"tagCode":"XXXQ-ZSYQZ","tagDesc":"Frequently browse pages related to popular science and medical advice","tagId":"4","tagName":"Knowledge seekers","tagReason":"Frequently check pagesInspection-science-mian, pages starting withPopularization."}], etc.

[0100] The preset label model can match and analyze the behavior data "frequently log in to the mini program, stay for more than 40 minutes, and frequently visit cancer science pages" to determine that the target user is a cancer follower, frequently visits cancer science pages, has an anxious tendency and frequently visits, and is an active user. Accordingly, the preset label model generates a target label corresponding to the behavior data according to the preset format template:

[0101] {tagCode: ZZGGZ, tagName: Tumor follower, tagDesc: Frequently visits tumor science pages, tagReason: Frequently visits pages starting with pagesPopularization}; {tagCode: JLQX, tagName: Anxiety tendency, tagDesc: Frequent visits to tumor science pages may indicate excessive concern about health, tagReason: Frequent visits to pages starting with pagesPopularization}; {tagCode: HYYH, tagName: Active user, tagDesc: Long usage time, tagReason: Usage time is counted based on entryTime and exitTime}.

[0102] It should be understood that the preset format template can be updated and replaced according to needs, and the tag set can be expanded by updating the attributes (extraTags) to expand the original tag set.

[0103] S403: The electronic device uses the target tag as a characteristic tag of the target user.

[0104] Exemplarily, the electronic device uses the target tags: {tagCode: ZZGGZ, tagName: tumor follower, tagDesc: frequently visits tumor science pages, tagReason: frequently visits pages starting with pagesPopularization}; {tagCode: JLQX, tagName: anxiety tendency, tagDesc: frequently visits tumor science pages, may show excessive concern for health, tagReason: frequently visits pages starting with pagesPopularization}; {tagCode: HYYH, tagName: active user, tagDesc: long usage time, tagReason: usage time is counted according to entryTime and exitTime} as feature tags of the target user, so as to facilitate the subsequent display of the target user's information through different dimensions.

[0105] In addition, the electronic device of the embodiment of the present disclosure can realize the process of automated and intelligent labeling through Python language.

[0106] The disclosed embodiments can efficiently and in real time acquire various types of behavior data generated by target users (i.e., patients) in applications related to medical diagnosis. By continuously collecting and analyzing the behavior data, the health information changes of the target users can be dynamically updated to ensure that the acquired user status is up-to-date and comprehensive. The collected behavior data can then be parsed using a preset tag model to determine the target tag corresponding to the current behavior data, and the target tag is stored and managed as a feature tag of the target user. Doctors can timely understand the latest changes in the patient's health status based on these real-time updated feature tags, thereby making more accurate diagnostic decisions, formulating personalized treatment plans, or adjusting existing treatment plans.

[0107] In addition, this feature label can not only be easily and quickly accessed by doctors, but can also be presented to users themselves in a visual way, enhancing their ability to understand and manage their own health conditions.

[0108] A method for determining user characteristics provided by an embodiment of the present disclosure also includes a process of constructing a personalized tag in a tag set, which can be specifically referred to in the following S501-S502. Figure 5 As shown, the method includes:

[0109] S501, the electronic device collects behavior data of multiple access users generated in the target application.

[0110] In some embodiments, the second terminal may determine behavior data of the multiple accessing users in response to touch operations of the multiple accessing users on the target application, and send the behavior data of the multiple accessing users to the electronic device.

[0111] For example, when one of multiple visiting users visits page A of the mini program (e.g., the inspection report page) and jumps from page A to page B (e.g., the chat page), the electronic device can determine that the data information at this time is page A jumping to page B (e.g., {json:A TO B}), and replace the data information with a text description of "conducting manual consultation after viewing the inspection report", thereby achieving light processing of the user behavior.

[0112] For example, the user performs a jump operation on page A of the mini program (i.e., the inspection report page), and the target is page B (i.e., the chat page). The electronic device can set anchor points on page A and page B respectively to identify the page status and the location information before and after the jump. When page B is loaded, the second terminal can call a predefined interface, which can be used to receive data information transmitted by page A, and the data information includes JSON format data carrying a jump instruction (i.e., A TO B), and the data information identifies the behavior of jumping from page A to page B. The second terminal converts the JSON format data into a preset language description (i.e., manual consultation after viewing the inspection report) and sends the language description to the electronic device.

[0113] In another example, one of the multiple access users accesses the mini program once every two hours or so, stays on the mini program page for more than 20 minutes each time, and pays close attention to the information in the inspection report. The second terminal can determine that the data information at this time is "frequently log in to the mini program, stay for more than 20 minutes, and frequently access the inspection report", and send the data information to the electronic device.

[0114] S502, the electronic device uses a label generation model to obtain a personalized label corresponding to the behavior data of each visiting user according to the behavior data of multiple visiting users.

[0115] In the disclosed embodiment, the personality tag is used to represent the profile features of the visiting user.

[0116] In some embodiments, the electronic device inputs the behavior data of a user among multiple visiting users into a label generation model, and the label generation model generates a corresponding code and name label (ie, a personalized label) based on the input behavior data through its internal algorithm analysis.

[0117] In combination with the example in S501, the electronic device inputs the text description of the replaced behavior data (i.e., manual consultation after viewing the inspection report) into the label generation model, and the label generation model extracts the key information of the behavior data and generates a personalized label corresponding to the behavior data.

[0118] For example, the behavioral data of "seeking manual consultation after viewing the inspection report" is identified as a consultation category, and the corresponding tag code (e.g., tagCode: ZX) and tag name (e.g., tagName: consultation) are returned, thereby generating tag information with practical application value, providing strong support for subsequent personalized recommendations, user behavior analysis, etc.

[0119] Among them, ZX is the capital letter of the label name "consulting".

[0120] In another example, the electronic device inputs the text description of the behavior data "frequently log in to the mini-program, stay for more than 20 minutes, and frequently access the inspection report" into the label generation model, and the label generation model extracts the key information of the behavior data and generates a personalized label corresponding to the behavior data.

[0121] For example, according to "frequently log in to the mini program, stay for more than 20 minutes, and frequently visit the inspection report", generate corresponding personalized tags (such as tagCode: HYYH, tagName: active user, childTag: [{tagCode: PFFW, tagName: frequent visits, childTag: [{tagCode: TLSCC20FZ, tagName, stay time exceeds 20 minutes).

[0122] It should be understood that the personalized tag can be determined by the tag generation model.

[0123] Among them, one upper-level tag is associated with at least one lower-level tag, and the image feature represented by the lower-level tag is a sub-feature of the image feature represented by the upper-level tag.

[0124] For example, take personalized tags (tagCode: HYYH, tagName: active user, childTag: [{tagCode: PFFW, tagName: frequent visit, childTag: [{tagCode: TLSCC20FZ, tagName, stay time exceeds 20 minutes) as an example.

[0125] Among them, HYYH refers to the first letter of the tag name "active users" in capital letters; PFFW refers to the first letter of the tag name "frequent visits" in capital letters; TLSCC20FZ refers to the first letter of the tag name "staying for more than 20 minutes" in capital letters. As the name implies, childTag refers to a child tag (i.e., a subordinate tag), and the corresponding frequent visits are the subordinate tags of active users, and the stay time of more than 20 minutes is the subordinate tag of frequent visits.

[0126] In addition, the electronic device can also store the generated personalized labels in a database for later use in labeling different patients.

[0127] It should be noted that the tag set also includes basic tags, which are determined based on the basic information and case information of the accessing user of the target application.

[0128] Exemplarily, the basic tags may be as shown in Table 1 below.

[0129] Table 1

[0130]

[0131] In addition, the disclosed embodiments can query, add, modify, delete and other operations on the tag set through the Java programming language, and maintain the tag set in the electronic device according to the tree hierarchical structure. At the same time, the electronic device is used as the root system to send the tag set to the first terminal and the second terminal, so as to always keep the tag set as the most complete data.

[0132] At the same time, the embodiment of the present disclosure can use MySQL as a storage tool for tag sets and cleaned data.

[0133] The method for determining user characteristics provided in the embodiments of the present disclosure aims to achieve a comprehensive and accurate characterization of user characteristics by comprehensively analyzing and processing the user's basic information, case information, and behavior data. Specifically, the method can not only preliminarily determine a series of basic tags based on the user's basic information (including but not limited to age, gender, occupation, etc.) and case information (such as past medical history, diagnosis records, treatment conditions, etc.), but also construct a basic framework for user characteristics.

[0134] Furthermore, this method can also deeply mine and continuously track users' behavioral data in various scenarios, including but not limited to access records, interactive behaviors, preference choices, etc., and continuously expand and improve the user's personalized label system based on this.

[0135] It should be understood that after determining the characteristic tag of the target user, the electronic device can send the characteristic tag to the first terminal (i.e., the terminal used by the doctor), so that the first terminal generates a user portrait for the target user based on the characteristic tag.

[0136] Combine the following Figure 1 , a method for generating a user portrait provided by an embodiment of the present disclosure is described. Figure 6 A flowchart of a method for generating a user portrait provided in an embodiment of the present disclosure is shown in FIG. Figure 6 As shown, the method includes:

[0137] S601: The electronic device sends a feature tag of a target user to the first terminal. Correspondingly, the first terminal receives the feature tag of the target user sent by the electronic device.

[0138] In the disclosed embodiment, the feature tag is a tag in a tag set determined by using a preset tag model and corresponding to the behavior data of the target user.

[0139] S602: The first terminal generates a user portrait of the target user based on the feature tag.

[0140] In an embodiment of the present disclosure, a user portrait is displayed on a display page of a first terminal, and the user portrait includes a tag forest composed of a plurality of tag trees, and the tag data in each tag tree includes at least one feature tag.

[0141] In some embodiments, the large screen of the medical data center (first terminal) constructs a detailed health portrait of the target user based on the characteristic tags of the target user, and displays the portrait data of the user on the large screen, and displays it on the large screen in an intuitive and easy-to-understand manner (such as charts, curves, color coding, etc.), thereby realizing efficient generation and real-time display of the health portrait of the target user, greatly improving the doctor's ability to grasp the overall health status of the patient during the diagnosis and treatment process, and providing strong support for the formulation of precision medicine and personalized treatment plans.

[0142] For example, Figure 7 As shown, the large screen of the medical data center displays various contents related to tag management (such as tag overview, hot recommendations, tag definition, tag configuration, operation management, tag service, tag declaration, tag analysis, approval management, data source management, customer management, etc.) and tag overview content (such as user portrait of target users, tag service analysis, tag tree tag ranking, tag usage trend, TOP10 tag usage popularity report, etc.).

[0143] Among them, the portrait of the target user includes a label forest composed of multiple label trees. For example, the first label tree is academic qualifications-graduate students-doctoral students; the second label tree is body mass index-underweight-thin; the third label tree is tumor followers-frequently visit tumor science pages; the fourth label tree is anxiety tendency-may show excessive concern for health.

[0144] It should be understood that the tag data in each tag tree is a characteristic tag of the target user.

[0145] It should be noted that a label set is also stored in the first terminal. The first terminal can manually label the target user in response to the doctor's touch operation, and then the doctor can view the target user's comprehensive portrait information and usage statistics of various labels through the first terminal.

[0146] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of this disclosure can be achieved, and this document is not limited here.

[0147] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for determining user characteristics, characterized in that: Applied to electronic equipment, the method comprises: Acquire behavior data of a target user generated in a target application; the target application is an application related to medical diagnosis; Using a preset tag model, determining a target tag in a tag set corresponding to the behavior data; the target tag is used to represent a profile feature of the target user; The target tag is used as a feature tag of the target user.

2. The method according to claim 1, characterized in that The tag set includes a personalized tag, and the method further includes: Collecting behavioral data of multiple access users generated in the target application; A label generation model is used to obtain a personality label corresponding to the behavior data of each visiting user based on the behavior data of the multiple visiting users; the personality label is used to represent the portrait features of the visiting user.

3. The method according to claim 2, characterized in that The personalized tag is determined to have a tag level by the tag generation model, wherein a superior tag is associated with at least one subordinate tag, and the image feature represented by the subordinate tag is a sub-feature of the image feature represented by the superior tag.

4. The method according to claim 2 or 3, characterized in that The tag set also includes basic tags, which are determined based on basic information and case information of the user accessing the target application.

5. The method according to claim 1, characterized in that The preset label model is used to output target data according to a preset format template and input behavior data, wherein the data format of the target data conforms to the preset format template, and the target data includes the target label.

6. The method according to claim 1, characterized in that The step of obtaining the target user's behavior data generated in the target application includes: The behavior data sent by the second terminal is received, where the behavior data is determined by the target application in response to a touch operation of the target user.

7. The method according to any one of claims 1 to 3, characterized in that The method further comprises: Sending the characteristic tag of the target user to the first terminal.

8. A method for generating a user portrait, characterized in that: Applied to a first terminal, the method includes: Receiving a characteristic tag of a target user sent by an electronic device; the characteristic tag is a tag corresponding to the behavior data of the target user in a tag set determined by a preset tag model; Based on the feature tag, a user portrait of the target user is generated; and the user portrait is displayed on a display page of the first terminal.

9. The method according to claim 8, characterized in that The user portrait includes a tag forest composed of multiple tag trees, and the tag data in each tag tree includes at least one feature tag.

10. An electronic device, characterized in that: The electronic device comprises: a memory and a processor; the memory is used to store computer instructions; the processor is used to implement the method according to any one of claims 1 to 7 when executing the computer instructions.

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