A virtual pet doctor matching method based on virtual pets and related products

Abstract

The present application provides a virtual pet doctor matching method based on a virtual pet and related products, wherein the implementation of the method includes: receiving a pre-diagnosis request sent by a target user terminal under a target display interface; obtaining social data of a target user and at least one virtual pet doctor corresponding to the target user terminal and pet information data of a target virtual pet according to the pre-diagnosis request; determining a target virtual pet doctor with a target matching degree higher than a first preset matching degree from at least one virtual pet doctor according to the user social data and the pet information data; and pushing the character image of the target virtual pet doctor to the target display interface. The method of the embodiment of the present application is adopted to determine a virtual pet doctor with a high matching degree for the virtual pet, so that the virtual pet can cooperate with the virtual pet doctor to complete the treatment plan, making the user's treatment process of the virtual pet more personalized and targeted.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a virtual pet-based virtual pet doctor matching method and related products. Background Art

[0002] With the rapid development of computer technology and the increasing variety of software programs, people can perform more and more functions on smart devices. Nowadays, raising virtual pets using virtual pet systems on smart devices has become a popular form of entertainment.

[0003] The current virtual pet system has a relatively simple interactive process for virtual pets to seek medical treatment. For example, users only need to click "treat" or "buy medicine" for virtual pets in the virtual pet system to restore the health of virtual pets. However, this is far from the process of treating real pets in reality. For example, in the process of treating real pets, the pet doctor needs to diagnose the pet's condition, prescribe medicine, and perform other treatment operations to restore the pet's health. In the process of treating virtual pets, the treatment process can be completed without even contacting the pet doctor. It can be seen that the current interactive process of virtual pet treatment is relatively short and lacks an obvious feedback mechanism. For users who raise virtual pets, the immersive experience needs to be improved. Summary of the invention

[0004] The embodiment of the present application provides a virtual pet doctor matching method based on a virtual pet and related products. By implementing the embodiment of the present application, a virtual pet doctor with a high matching degree is determined for the virtual pet.

[0005] In a first aspect, an embodiment of the present application provides a virtual pet-based virtual pet doctor matching method, the method comprising:

[0006] Receiving a pre-diagnosis request sent by a target user terminal in a target display interface, the pre-diagnosis request is used to request a matching virtual pet doctor to perform diagnosis and treatment for the target virtual pet, and the character image of the target virtual pet is displayed in the target display interface;

[0007] According to the pre-diagnosis request, obtaining social data between the target user and at least one virtual pet doctor corresponding to the target user terminal, and pet information data of the target virtual pet;

[0008] According to the user social data and the pet information data, determining a target virtual pet doctor with a target matching degree higher than a first preset matching degree from at least one virtual pet doctor;

[0009] The target virtual pet doctor's character image is pushed to the target display interface.

[0010] In a possible example, the above-mentioned determining, based on the user social data and the pet information data, a target virtual pet doctor having a target matching degree higher than a first preset matching degree from at least one virtual pet doctor includes:

[0011] Acquire historical pet cure information data corresponding to each virtual pet doctor in at least one virtual pet doctor, the historical pet cure information data including breed information and personality characteristic information of a plurality of historical pet cures;

[0012] According to the historical pet treatment information data corresponding to each virtual pet doctor, determine the type of pets that each virtual pet doctor is good at treating;

[0013] Analyze the degree of matching between the pet information data and the type of pets that each virtual pet doctor is good at curing, and determine the recommended matching degree between each virtual pet doctor and the target virtual pet;

[0014] Determine the target matching degree of each virtual pet doctor according to the friendliness between each virtual pet doctor and the target user, as well as the recommended matching degree;

[0015] The virtual pet doctor whose target matching degree is higher than the first preset matching degree is determined as the target virtual pet doctor.

[0016] It can be seen that in the embodiment of the present application, by combining the types of pets that the virtual pet doctor is good at curing and the friendliness between the target users of the virtual pet doctor, a virtual pet doctor with a high degree of match is matched for the target virtual pet. Since the matching process not only uses the pet information data as the basis for analysis and matching, but also uses the user's social data as the basis for analysis and matching, the user's treatment process of the virtual pet is more personalized and targeted.

[0017] In a possible example, if there is no target virtual pet doctor with a target matching degree higher than the first preset matching degree, the method further includes:

[0018] Obtaining historical social interactions between the target virtual pet and other characters other than the target user, as well as the character image corresponding to each virtual pet doctor;

[0019] Analyze the historical social interactions between the target virtual pet and other characters other than the target user to determine the preferred character image of the target virtual pet;

[0020] Determine the image matching degree of each virtual pet doctor according to the character image corresponding to each virtual pet doctor and the similarity between the preferred character images;

[0021] According to the user social data, the pet information data and the image matching degree, a target virtual pet doctor whose target matching degree is higher than a first preset matching degree is determined from at least one virtual pet doctor.

[0022] It can be seen that in the embodiment of the present application, when the target virtual pet doctor cannot be matched for the target user based on the user-friendliness (target user preference) and the type of treatment that the pet doctor is good at (system parameters), the virtual pet doctor image can be matched for the target user with further reference to the situation of other users selecting the virtual pet doctor character image. In this way, the target virtual pet doctor can be matched in combination with the preferences of other users. While providing personalized services to the target users, the user's pursuit of group recognition needs is also taken into account, and the interactive feedback mechanism of the process of matching virtual pets with virtual pet doctors for treatment is strengthened, thereby optimizing the immersive experience of the target users.

[0023] In a possible example, the method further includes receiving a diagnosis request message sent by a target user terminal to a selected pet doctor, and generating a pet diagnosis result according to the diagnosis request message, wherein the selected pet doctors include a target virtual pet doctor and other virtual pet doctors except the target virtual pet doctor. After generating the pet diagnosis result, the method further includes:

[0024] If the virtual pet doctor is selected as the target virtual pet doctor, a first training degree gain value corresponding to the pet diagnosis result is generated;

[0025] If the selected virtual pet doctor is another virtual pet doctor, a second training degree gain value corresponding to the pet diagnosis result is generated, wherein the first training degree gain value is greater than the second training degree gain value.

[0026] It can be seen that in the embodiment of the present application, by generating a training gain value corresponding to the pet diagnosis result according to the virtual pet doctor selected by the target user terminal, when the virtual pet doctor selected by the target user terminal is a target virtual pet doctor with a higher matching degree, the corresponding training gain value will be higher, thereby strengthening the interactive feedback mechanism of the process of matching the virtual pet with the virtual pet doctor for treatment, and then encouraging the target user to select the target virtual pet doctor customized and pushed by the server to treat the target virtual pet, thereby ensuring a benign interaction between the user and the pet system.

[0027] In a possible example, after receiving a diagnosis request message for a selected virtual pet doctor sent by a target user terminal and generating a pet diagnosis result according to the diagnosis request message, the method further includes:

[0028] According to the pet diagnosis result, determine whether the target disease corresponding to the target virtual pet belongs to the target type disease, and the target type disease includes diseases that need to be re-examined at a preset time and long-term diseases that are prone to recurrence;

[0029] If yes, a target association record is generated between the target virtual pet and the selected virtual pet doctor, and the target association record is used for the selected virtual pet doctor to re-examine the target virtual pet for the target disease after a preset time;

[0030] The selected virtual pet doctor image is pushed to the target user terminal after a preset time.

[0031] It can be seen that in the embodiment of the present application, by simulating the treatment process of a specific type of disease in reality that requires regular follow-up and reexamination by the same doctor, the interactive feedback mechanism of the process of matching a virtual pet with a virtual pet doctor for treatment is strengthened, so that the target virtual pet can obtain a more standardized, more coherent, and better treatment effect, thereby making the process of treating the virtual pet more realistic and targeted, thereby optimizing the immersive experience of the target user.

[0032] In a possible example, the virtual pet doctor is a user-controlled character and / or a non-user-controlled character, and the friendship between the target user and the virtual pet doctor is determined by historical interaction data between the target user and the virtual pet doctor.

[0033] It can be seen that in the embodiment of the present application, a virtual pet doctor who has a better historical interaction status with the target user is pushed to the target display interface of the target user terminal, making the matching process of the virtual pet with the virtual pet doctor more personalized and targeted, and optimizing the immersive experience of the target user by strengthening the feedback mechanism given to the target user terminal.

[0034] In a second aspect, an embodiment of the present application provides a virtual pet-based virtual pet doctor matching device, the device comprising:

[0035] A receiving unit, used for receiving a pre-diagnosis request sent by a target user terminal in a target display interface, wherein the pre-diagnosis request is used for requesting a matching virtual pet doctor to perform diagnosis and treatment for a target virtual pet, and a character image of the target virtual pet is displayed in the target display interface;

[0036] An acquisition unit, configured to acquire, according to the pre-diagnosis request, social data between a target user and at least one virtual pet doctor corresponding to the target user terminal, and pet information data of a target virtual pet;

[0037] A determination unit, configured to determine, based on the user social data and the pet information data, a target virtual pet doctor whose target matching degree is higher than a first preset matching degree from at least one virtual pet doctor;

[0038] The push unit is used to push the character image of the target virtual pet doctor to the target display interface.

[0039] In a third aspect, an embodiment of the present application provides an electronic device, comprising a processor, a memory, and computer execution instructions stored in the memory and executable on the processor, wherein when the computer execution instructions are executed, the electronic device executes part or all of the steps described in any method of the first aspect of the embodiment of the present application.

[0040] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer instructions are stored. When the computer instructions are executed on a communication device, the communication device executes part or all of the steps described in any method of the first aspect of the embodiment of the present application.

[0041] In a fifth aspect, an embodiment of the present application provides a computer program product, wherein the computer program product includes a computer program, and the computer program is operable to cause a computer to execute some or all of the steps described in any method of the first aspect of the embodiment of the present application. The computer program product can be a software installation package.

[0042] It can be seen that in the embodiment of the present application, a pre-diagnosis request sent by the target user terminal under the target display interface is received, and the pre-diagnosis request is used to request a matching virtual pet doctor to perform diagnosis and treatment for the target virtual pet, and the character image of the target virtual pet is displayed in the target display interface; according to the pre-diagnosis request, the social data of the target user and at least one virtual pet doctor corresponding to the target user terminal and the pet information data of the target virtual pet are obtained; according to the user social data and the pet information data, a target virtual pet doctor with a target matching degree higher than a first preset matching degree is determined in at least one virtual pet doctor; and the character image of the target virtual pet doctor is pushed to the target display interface. The method of the embodiment of the present application is adopted to determine a virtual pet doctor with a high matching degree for the virtual pet, so that the virtual pet can cooperate with the virtual pet doctor to complete the treatment plan, and by enhancing the interaction between the user and the virtual pet, the user's treatment process of the virtual pet is more personalized and targeted, providing a personal immersive experience for the user to raise a virtual pet. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 It is a structural deployment diagram of a virtual pet system provided by an embodiment of the present application;

[0045] Figure 2 It is a flowchart of a virtual pet doctor matching method based on a virtual pet provided in an embodiment of the present application;

[0046] Figure 3 It is a structural deployment diagram of a virtual pet system to which a virtual pet doctor matching method based on a virtual pet is applied, provided in an embodiment of the present application;

[0047] Figure 4 is an example schematic diagram of a virtual pet doctor matching method based on a virtual pet provided in an embodiment of the present application;

[0048] Figure 5 is an example schematic diagram of a virtual pet doctor matching method based on a virtual pet provided in an embodiment of the present application;

[0049] Figure 6 It is a structural schematic diagram of a virtual pet doctor matching device based on a virtual pet provided in an embodiment of the present application;

[0050] Figure 7 This is a method provided by the embodiment of the present application. Figure 6 A schematic diagram of the structure of a determination unit of the device described in the embodiment;

[0051] Figure 8 It is a schematic diagram of the server structure of the hardware operating environment of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0052] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0053] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0054] The application scenarios involved in the embodiments of the present application are introduced below with reference to the accompanying drawings.

[0055] Figure 1 : is a structural deployment diagram of a virtual pet system provided by an embodiment of the present application. Figure 1 As shown, the first end of the system is connected to a user terminal.

[0056] The user terminal refers to a terminal used by a user who raises a virtual pet on the virtual pet system. When the health of the virtual pet is low, i.e., it is in a sick state, the user issues an operation instruction to "treat" the virtual pet on the user terminal, so that the user terminal sends a "treat" operation request corresponding to the "treat" operation instruction to the virtual pet system;

[0057] Wherein, after receiving the "treatment" operation request from the user terminal, the virtual pet system sends a "treatment" operation response to the user terminal, and the "treatment" operation response is used to improve the health of the virtual pet;

[0058] In the process of the above system treating the virtual pet, after the virtual pet system receives the "treatment" operation request from the user terminal, it only sends a "treatment" operation response to the user terminal to improve the health of the virtual pet, thereby completing the entire treatment operation of the virtual pet. It can be seen that the above process has a short interaction process with the user terminal and no obvious feedback signal, making it difficult to provide users with an immersive experience in raising virtual pets.

[0059] Based on this, the embodiment of the present application provides a virtual pet doctor matching method based on a virtual pet, please refer to Figure 2 , Figure 2 is a flow chart of a virtual pet doctor matching method based on a virtual pet provided in an embodiment of the present application, such as Figure 2 As shown, the method comprises the following steps:

[0060] 101: receiving a pre-diagnosis request sent by a target user terminal in a target display interface, wherein the pre-diagnosis request is used to request a matched virtual pet doctor to perform diagnosis and treatment for a target virtual pet, and a character image of the target virtual pet is displayed in the target display interface.

[0061] Among them, the method provided in the embodiment of the present application can be applied to a virtual pet system provided with a virtual pet, and the virtual pet system includes a server for communicating and interacting with a virtual pet client installed in a target user terminal, and a database storing target user data corresponding to the target user terminal and target virtual pet information data. Furthermore, the virtual pet system can provide a social interaction function, and the social interaction can include interaction between the target user and the virtual pet, interaction between other users and the virtual pet, and interaction between the target user and other users.

[0062] The target user terminal may be a smart phone, tablet computer, personal digital assistant, wearable device or other electronic device.

[0063] The target display interface refers to a display interface of a user terminal in a virtual pet client that displays a character image of a target virtual pet.

[0064] Among them, the target virtual pets, in specific implementation, include cats of different breeds, dogs of different breeds or other pets.

[0065] 102: According to the pre-diagnosis request, obtain social data between the target user and at least one virtual pet doctor corresponding to the target user terminal, and pet information data of the target virtual pet.

[0066] Among them, the virtual pet doctor, in a specific implementation, can be a user-controlled role and / or a non-user-controlled role.

[0067] Among them, the social data between the target user and at least one virtual pet doctor, in a specific implementation, may be the friendship data between the target user and each virtual pet doctor in the at least one virtual pet doctor, and the friendship data is determined by the interaction between the target user and the virtual pet doctor.

[0068] Among them, the pet information data of the target virtual pet may include the animal species, breed type, individual size, etc. of the target virtual pet in a specific implementation.

[0069] 103: Determine, based on the user social data and the pet information data, a target virtual pet doctor whose target matching degree is higher than a first preset matching degree from at least one virtual pet doctor.

[0070] In a specific implementation, the matching degree can be expressed in the form of a percentage of 0 to 100%, or in the form of a numerical value of 0 to 1. Furthermore, if the matching degree is expressed in the form of a percentage of 0 to 100%, the first preset matching degree can be 75%, 80% or other percentages.

[0071] 104: Pushing the target virtual pet doctor's character image to the target display interface.

[0072] Among them, the character images of different virtual pet doctors can be determined according to different physical characteristics, voice characteristics, and temperament characteristics.

[0073] Among them, the character image of the target virtual pet doctor is pushed to the target display interface. In a specific implementation, the target virtual pet doctor can be directly displayed near the target virtual pet in the target display interface; or a selection window can be popped up in the target display interface for the user terminal to select and confirm, and the target virtual pet doctor is displayed in the selection window.

[0074] For example, see Figure 3 , Figure 3 is a structural deployment diagram of a virtual pet system that applies a virtual pet-based virtual pet doctor matching method provided in an embodiment of the present application, such as Figure 3 As shown, the first end of the system is connected to the target user terminal, and the system includes a server and a database, wherein the server is used to communicate and interact with the virtual pet client installed in the target user terminal, and the database is used to store the target user data and the target virtual pet information data corresponding to the target user terminal. The server receives a pre-diagnosis request sent under the target display interface in the virtual pet client of the target user terminal, and the server obtains the social data between the target user and N virtual pet doctors and the pet information data of the target virtual pet corresponding to the target user terminal from the database according to the pre-diagnosis request, wherein the social data between the target user and the N virtual pet doctors is the target user The server determines, based on the friendship data between the target user and the N virtual pet doctors and the information data that the target virtual pet is a medium-sized dog breed, a target virtual pet doctor who has a high friendship with the target user and is good at treating medium-sized dog breeds, so that the target matching degree is higher than the first preset matching degree. The server then pushes the character image of the target virtual pet doctor to the target display interface, so that the target user corresponding to the target user terminal can confirm and select the target virtual pet doctor to complete the treatment process of the target virtual pet.

[0075] It can be seen that in the embodiment of the present application, a pre-diagnosis request sent by the target user terminal under the target display interface is received, and the pre-diagnosis request is used to request a matching virtual pet doctor to perform diagnosis and treatment for the target virtual pet, and the character image of the target virtual pet is displayed in the target display interface; according to the pre-diagnosis request, the social data of the target user and at least one virtual pet doctor corresponding to the target user terminal and the pet information data of the target virtual pet are obtained; according to the user social data and the pet information data, a target virtual pet doctor with a target matching degree higher than a first preset matching degree is determined in at least one virtual pet doctor; and the character image of the target virtual pet doctor is pushed to the target display interface. The method of the embodiment of the present application is adopted to determine a virtual pet doctor with a high matching degree for the virtual pet, so that the virtual pet can cooperate with the virtual pet doctor to complete the treatment plan, and by enhancing the interaction between the user and the virtual pet, the user's treatment process of the virtual pet is more personalized and targeted, providing a personal immersive experience for the user to raise a virtual pet.

[0076] In a possible example, the above-mentioned determining, based on the user social data and the pet information data, a target virtual pet doctor having a target matching degree higher than a first preset matching degree from at least one virtual pet doctor includes:

[0077] Acquire historical pet cure information data corresponding to each virtual pet doctor in at least one virtual pet doctor, the historical pet cure information data including breed information and personality characteristic information of a plurality of historical pet cures;

[0078] According to the historical pet treatment information data corresponding to each virtual pet doctor, determine the type of pets that each virtual pet doctor is good at treating;

[0079] Analyze the degree of matching between the pet information data and the type of pets that each virtual pet doctor is good at curing, and determine the recommended matching degree between each virtual pet doctor and the target virtual pet;

[0080] Determine the target matching degree of each virtual pet doctor according to the friendliness between each virtual pet doctor and the target user, as well as the recommended matching degree;

[0081] The virtual pet doctor whose target matching degree is higher than the first preset matching degree is determined as the target virtual pet doctor.

[0082] Among them, based on the historical pet healing information data corresponding to each virtual pet doctor, the type of pets that each virtual pet doctor is good at healing is determined. In a specific implementation, the historical pet healing information data corresponding to each virtual pet doctor can be analyzed, and the breed information and personality characteristic information in the historical pet healing information data can be classified and statistically sorted, so as to determine the type of pets that each virtual pet doctor is good at healing.

[0083] Among them, the type matching degree between the pet information data and the type of pets that each virtual pet doctor is good at curing is analyzed to determine the recommended matching degree between each virtual pet doctor and the target virtual pet. In a specific implementation, the higher the type matching degree between the pet information data and the type of pets that the virtual pet doctor is good at curing, the higher the recommended matching degree between the virtual pet doctor and the target virtual pet is determined. For example, the target virtual pet is a medium-sized dog with a lively personality, the type of pets that virtual pet doctor 1 is good at curing is a large dog with a lively personality, and the type of pets that virtual pet doctor 2 is good at curing is a large dog with a docile personality. The information consistency between the pet information data of the target virtual pet and the type of pets that virtual pet doctor 1 is good at curing is high, that is, the type matching degree is high, and therefore, the recommended matching degree 1 between virtual pet doctor 1 and the target virtual pet is greater than the recommended matching degree 2 between virtual pet doctor 2 and the target virtual pet.

[0084] Among them, the friendliness between each virtual pet doctor and the target user can be determined according to the interaction between the virtual pet doctor and the target user in a specific implementation. The more frequent the interaction between the virtual pet doctor and the target user, the higher the friendliness.

[0085] For example, in reality, pets will be closer to their owners if they are more friendly to them, and pet doctors will have better healing effects on pets that they are good at curing. Therefore, in a specific implementation, the target matching degree of each virtual pet doctor is determined based on the friendship between each virtual pet doctor and the target user, and the recommended matching degree. It is only necessary to satisfy that the friendship between the virtual pet doctor and the target user, the recommended matching degree, and the target matching degree between each virtual pet doctor are positively correlated. For example, the friendship between each virtual pet doctor and the target user, the recommended matching degree, and the target matching degree between each virtual pet doctor can satisfy: target matching degree = friendship between the virtual pet doctor and the target user + recommended matching degree; it can also be based on the actual application scenario, and weights can be assigned to the friendship between the virtual pet doctor and the target user and the recommended matching degree, and then weighted calculation can be performed to obtain the target matching degree.

[0086] It can be seen that in the embodiment of the present application, the type of pets that each virtual pet doctor is good at curing is determined based on the historical pet information data corresponding to each virtual pet doctor, and then the type matching degree between the pet information data and the type of pets that each virtual pet doctor is good at curing is analyzed to determine the recommended matching degree between each virtual pet doctor and the target virtual pet. The target matching degree of each virtual pet doctor is determined based on the friendliness between each virtual pet doctor and the target user, as well as the recommended matching degree, and finally the virtual pet doctor corresponding to the target matching degree higher than the first preset matching degree is determined as the target virtual pet doctor. By combining the type of pets that the virtual pet doctor is good at curing and the friendliness between the virtual pet doctor and the target user, a virtual pet doctor with a high matching degree is matched for the target virtual pet. Since the matching process not only uses the pet information data as the basis for analysis and matching, but also uses the user's social data as the basis for analysis and matching, the user's treatment of the virtual pet is more personalized and targeted.

[0087] In some application scenarios, there may be no target virtual pet doctor with a target matching degree higher than the first preset matching degree. In this case, considering that the virtual pet itself may have some subjective preferences for human character images, and the virtual pet's preference for human character images is often affected by the social preferences of its owner, the virtual pet's character image preference can also be used as an analysis and evaluation factor in the process of determining the matching degree of the virtual pet doctor, making the process of matching virtual pets with virtual pet doctors more personalized and targeted.

[0088] Therefore, for the above application scenarios, the embodiment of the present application provides another virtual pet doctor matching method based on a virtual pet, which is as follows:

[0089] In a possible example, if there is no target virtual pet doctor with a target matching degree higher than the first preset matching degree, the method further includes:

[0090] Obtaining historical social interactions between the target virtual pet and other characters other than the target user, as well as the character image corresponding to each virtual pet doctor;

[0091] Analyze the historical social interactions between the target virtual pet and other characters other than the target user to determine the preferred character image of the target virtual pet;

[0092] Determine the image matching degree of each virtual pet doctor according to the character image corresponding to each virtual pet doctor and the similarity between the preferred character images;

[0093] According to the user social data, the pet information data and the image matching degree, a target virtual pet doctor whose target matching degree is higher than a first preset matching degree is determined from at least one virtual pet doctor.

[0094] Among them, the character image can include physical characteristics, voice characteristics, temperament characteristics, etc.

[0095] Based on the above exemplary embodiments, since pets tend to have a higher willingness to interact with characters with images preferred by themselves or their owners, therefore, in a specific implementation, based on the user social data, pet information data and image matching, a target virtual pet doctor with a target matching degree higher than a first preset matching degree is determined in at least one virtual pet doctor. It is only necessary to satisfy that the user social data, pet information data and image matching degree are positively correlated. For example, when the user social data is the friendliness between each virtual pet doctor and the target user, and the pet information data is used to derive the recommended matching degree between each virtual pet doctor and the target virtual pet, it can be satisfied that: target matching degree = friendliness between the virtual pet doctor and the target user + recommended matching degree + image matching degree; it can also be based on the actual application scenario, and weights can be assigned to the friendliness, recommended matching degree and image matching degree between the virtual pet doctor and the target user, and then weighted calculation can be performed to obtain the target matching degree.

[0096] It can be seen that in the embodiment of the present application, when there is no target virtual pet doctor with a target matching degree higher than the first preset matching degree, the historical social interactions between the target virtual pet and other characters other than the target user, and the character image corresponding to each virtual pet doctor are obtained, and the preferred character image of the target virtual pet is determined by analyzing the historical social interactions between the target virtual pet and other characters other than the target user, and then the image matching degree of each virtual pet doctor is determined based on the character image corresponding to each virtual pet doctor and the similarity between the preferred character images, and finally, based on the user social data, pet information data and image matching degree, a target virtual pet doctor with a target matching degree higher than the first preset matching degree is determined from at least one virtual pet doctor. Therefore, when the target virtual pet doctor cannot be matched for the target user based on user-friendliness (target user preference) and the type of treatment that the pet doctor is good at (system parameters), the virtual pet doctor image can be matched for the target user with further reference to the selection of virtual pet doctor character images by other users. In this way, the target virtual pet doctor can be matched based on the preferences of other users. While providing personalized services to the target users, the user's pursuit of group recognition needs is also taken into account, and the interactive feedback mechanism of the process of matching virtual pets with virtual pet doctors for treatment is strengthened, thereby optimizing the immersive experience of the target users.

[0097] In some application scenarios, when the server pushes the character image of the target virtual pet doctor to the target display interface, it can also simultaneously push other virtual pet doctors whose matching degree does not reach the first preset matching degree or whose matching degree is lower than that of the target virtual pet doctor. In this case, the target user can also confirm other virtual pet doctors as selected virtual pet doctors on the target user terminal. In order to motivate the target user to select the target virtual pet doctor pushed by the server, a training incentive mechanism can be introduced to guide the target user to confirm the target virtual pet doctor as the selected virtual pet doctor.

[0098] Therefore, for the above application scenarios, the embodiment of the present application provides another virtual pet doctor matching method based on a virtual pet, which is as follows:

[0099] In a possible example, the method further includes receiving a diagnosis request message sent by a target user terminal to a selected pet doctor, and generating a pet diagnosis result according to the diagnosis request message, wherein the selected pet doctors include a target virtual pet doctor and other virtual pet doctors except the target virtual pet doctor. After generating the pet diagnosis result, the method further includes:

[0100] If the virtual pet doctor is selected as the target virtual pet doctor, a first training degree gain value corresponding to the pet diagnosis result is generated;

[0101] If the selected virtual pet doctor is another virtual pet doctor, a second training degree gain value corresponding to the pet diagnosis result is generated, wherein the first training degree gain value is greater than the second training degree gain value.

[0102] Among them, in a specific implementation, the pet diagnosis result can be presented in the target display interface in the form of "the target virtual pet has recovered" or "the health of the target virtual pet has increased by XX points" to be fed back to the target user terminal.

[0103] The degree of cultivation refers to the degree of cultivation of the target virtual pet by the target user. In a specific implementation, the degree of cultivation can be determined based on the interaction frequency and interaction conditions between the target user and the target virtual pet, as well as the physiological state parameters of the target virtual pet.

[0104] Among them, the first cultivation degree gain value is greater than the second cultivation degree gain value. In a specific implementation, the first cultivation degree gain value and the second cultivation degree gain value may be fixed values ​​and the former may be greater than the latter; or the first cultivation degree gain value may be a random additional value added to the second cultivation degree gain value. The random additional value may be any value as long as the condition that the former is greater than the latter is satisfied, which may depend on the actual application scenario.

[0105] Furthermore, in a specific implementation, the higher the training degree of the target virtual pet is, the higher the interaction tendency between the target virtual pet and the target user is.

[0106] For example, the pet diagnosis result is presented in the target display interface in the form of "the health of the target virtual pet is improved by XX points". At the same time, the target display interface will display the cultivation index after the cultivation gain value is updated. Assuming that the initial cultivation degree of the target virtual pet before the pet diagnosis result is generated is A, the first cultivation gain value is M, and the second cultivation gain value is N, please refer to Figure 4 , Figure 4 is an example schematic diagram of a virtual pet doctor matching method based on a virtual pet provided in an embodiment of the present application, such as Figure 4 As shown in (a) in the figure, when the virtual pet doctor is selected as the target virtual pet doctor, the pet diagnosis result 1 is "the health of the target virtual pet is increased by 20 points", and the cultivation degree 1 after the cultivation degree gain value is updated is = initial cultivation degree + first cultivation degree gain value = A + M, and the pet diagnosis result 1 and the cultivation degree 1 are displayed in the target display interface, such as Figure 4 As shown in (b), when the selected virtual pet doctor is another virtual pet doctor, the pet diagnosis result 2 is "the health of the target virtual pet is increased by 10 points", and the cultivation degree 2 after the cultivation degree gain value is updated is = initial cultivation degree + second cultivation degree gain value = A + N, and the pet diagnosis result 2 and cultivation degree 2 are displayed in the target display interface. Since the target matching degree of the target virtual pet doctor is better than that of other virtual pet doctors, and the cultivation degree gain value of the target virtual pet doctor is higher than that of other virtual pet doctors, thus cultivation degree 1> cultivation degree 2, it can be seen that confirming the target virtual pet doctor as the selected virtual pet doctor will have better data feedback, thereby encouraging the target user to select the target virtual pet doctor customized and pushed by the server for the treatment of the target virtual pet.

[0107] It can be seen that in the embodiment of the present application, when receiving the diagnosis request message sent by the target user terminal for the selected pet doctor, and generating the pet diagnosis result according to the diagnosis request message, the selected pet doctors include the target virtual pet doctor and other virtual pet doctors except the target virtual pet doctor. After generating the pet diagnosis result, if the selected virtual pet doctor is the target virtual pet doctor, a first cultivation gain value corresponding to the pet diagnosis result is generated, and if the selected virtual pet doctor is other virtual pet doctors, a second cultivation gain value corresponding to the pet diagnosis result is generated, and the first cultivation gain value is greater than the second cultivation gain value. By generating the cultivation gain value corresponding to the pet diagnosis result according to the virtual pet doctor selected by the target user terminal, when the virtual pet doctor selected by the target user terminal is the target virtual pet doctor with a higher matching degree, the corresponding cultivation gain value will be higher, thereby strengthening the interactive feedback mechanism of the process of matching the virtual pet with the virtual pet doctor for treatment, and then encouraging the target user to select the target virtual pet doctor customized and pushed by the server for the target virtual pet for treatment, thereby ensuring the benign interaction between the user and the pet system.

[0108] In some application scenarios, the disease corresponding to the target virtual pet may be a disease that needs to be re-examined at preset time intervals and a long-term disease that is prone to recurrence, so the same disease needs to be re-examined after a certain period of time. In reality, whether it is the treatment of long-term diseases for humans or pets, they are often treated by the same doctor, so that the doctor can have a better grasp of the patient's disease condition and thus have a better treatment effect.

[0109] Therefore, for the above application scenarios, the embodiment of the present application provides another virtual pet doctor matching method based on a virtual pet, which is as follows:

[0110] In a possible example, after receiving a diagnosis request message for a selected virtual pet doctor sent by a target user terminal and generating a pet diagnosis result according to the diagnosis request message, the method further includes:

[0111] According to the pet diagnosis result, determine whether the target disease corresponding to the target virtual pet belongs to the target type disease, and the target type disease includes diseases that need to be re-examined at a preset time and long-term diseases that are prone to recurrence;

[0112] If yes, a target association record is generated between the target virtual pet and the selected virtual pet doctor, and the target association record is used for the selected virtual pet doctor to re-examine the target virtual pet for the target disease after a preset time;

[0113] The selected virtual pet doctor image is pushed to the target user terminal after a preset time.

[0114] When the target user terminal selects the target virtual pet doctor pushed to the target display interface, the target virtual pet doctor is the selected virtual pet doctor.

[0115] Among them, after generating the target association record between the target virtual pet and the target virtual pet doctor, the server can store the target association record in the database, so that when the selected virtual pet doctor image needs to be pushed to the target user terminal after a preset time, the server can retrieve the corresponding target association record from the database to obtain the corresponding selected virtual pet doctor, thereby improving the server's response efficiency when conducting follow-up examinations for the target virtual pet.

[0116] The preset time may be the next occurrence time of the target type of disease, or a fixed time such as one week later or one month later.

[0117] For example, see Figure 5 , Figure 5 is an example schematic diagram of a virtual pet doctor matching method based on a virtual pet provided in an embodiment of the present application, such as Figure 5 As shown, after the server receives a diagnosis request message sent by the target user terminal for the selected virtual pet doctor and generates a pet diagnosis result according to the diagnosis request message, if it is determined according to the pet diagnosis result that the target disease corresponding to the target virtual pet belongs to the target type disease, a target association record between the target virtual pet and the selected virtual pet doctor is generated, and the target association record is sent to the database for storage. When the target virtual pet needs to be treated again after a preset time, the server retrieves the target association record associated with the target virtual pet from the database, and determines the selected virtual pet doctor based on the target association record. The server then pushes the selected virtual pet doctor image to the target user terminal.

[0118] It can be seen that in the embodiment of the present application, after receiving the diagnosis request message sent by the target user terminal for the selected virtual pet doctor and generating the pet diagnosis result according to the diagnosis request message, if the pet diagnosis result indicates that the target disease corresponding to the target virtual pet belongs to the target type disease, a target association record between the target virtual pet and the target virtual pet doctor is generated, and the selected virtual pet doctor image is pushed to the target user terminal after a preset time, so that the target virtual pet doctor can re-examine the target virtual pet for the target disease. By simulating the treatment process of a specific type of disease in reality that requires regular re-examination and re-examination by the same doctor, the interactive feedback mechanism of the process of matching virtual pets with virtual pet doctors for treatment is strengthened, so that the target virtual pet can obtain a more standardized, more coherent, and better treatment effect, thereby making the process of treating the virtual pet more realistic and targeted, thereby optimizing the immersive experience of the target user.

[0119] In some application scenarios, if the virtual pet system, in addition to providing the function of allowing users to interact with virtual pets, also provides users with the simulation function of taking on a certain position in the pet community, then the virtual pet doctor can also be controlled and operated by other users, that is, the virtual pet doctor can be a user-controlled role or a non-user-controlled role.

[0120] Therefore, for the above application scenarios, the embodiment of the present application provides another virtual pet doctor matching method based on a virtual pet, which is as follows:

[0121] In a possible example, the virtual pet doctor is a user-controlled character and / or a non-user-controlled character, and the friendship between the target user and the virtual pet doctor is determined by historical interaction data between the target user and the virtual pet doctor.

[0122] Among them, the user-controlled role refers to the role that the corresponding virtual pet doctor is operated and controlled by users other than the target user; the non-user-controlled role refers to the non-manually controlled role that the corresponding virtual pet doctor is pre-set by the server.

[0123] Among them, the friendliness between the target user and the virtual pet doctor is determined by the historical interaction data between the target user and the virtual pet doctor. In a specific implementation, the more frequent the interactions between the target user and the virtual pet doctor and the better the interaction conditions, the higher the friendliness between the target user and the virtual pet doctor. That is to say, the friendliness between the target user and the virtual pet doctor is positively correlated with the historical interaction data between the target user and the virtual pet doctor.

[0124] It can be seen that in the embodiment of the present application, the virtual pet doctor is a user-controlled character and / or a non-user-controlled character, and the friendliness between the target user and the virtual pet doctor is determined by the historical interaction data between the target user and the virtual pet doctor, thereby achieving the goal of pushing the virtual pet doctor who has a better historical interaction status with the target user to the target display interface of the target user terminal, making the matching process of matching the virtual pet doctor for the virtual pet more personalized and targeted, and optimizing the immersive experience of the target user by strengthening the feedback mechanism given to the target user terminal.

[0125] With the above Figure 2 For details on the embodiments shown in the drawings, please refer to Figure 6 , Figure 6 is a structural diagram of a virtual pet doctor matching device based on a virtual pet provided in an embodiment of the present application, such as Figure 6 As shown:

[0126] A virtual pet doctor matching device based on a virtual pet, the device comprising:

[0127] 201: a receiving unit, configured to receive a pre-diagnosis request sent by a target user terminal in a target display interface, wherein the pre-diagnosis request is used to request a matched virtual pet doctor to perform diagnosis and treatment for a target virtual pet, and the character image of the target virtual pet is displayed in the target display interface;

[0128] 202: an acquisition unit, configured to acquire, according to the pre-diagnosis request, social data between a target user and at least one virtual pet doctor corresponding to the target user terminal, and pet information data of a target virtual pet;

[0129] 203: A determination unit, configured to determine, based on the user social data and the pet information data, a target virtual pet doctor whose target matching degree is higher than a first preset matching degree from at least one virtual pet doctor;

[0130] 204: a push unit, used for pushing the character image of the target virtual pet doctor to the target display interface.

[0131] It can be seen that in the device provided by the embodiment of the present application, a pre-diagnosis request sent by the target user terminal under the target display interface is received, and the pre-diagnosis request is used to request a matching virtual pet doctor to perform diagnosis and treatment for the target virtual pet, and the character image of the target virtual pet is displayed in the target display interface; according to the pre-diagnosis request, the social data of the target user and at least one virtual pet doctor corresponding to the target user terminal and the pet information data of the target virtual pet are obtained; according to the user social data and the pet information data, a target virtual pet doctor with a target matching degree higher than a first preset matching degree is determined from at least one virtual pet doctor; and the character image of the target virtual pet doctor is pushed to the target display interface. The device of the embodiment of the present application is used to determine a virtual pet doctor with a high matching degree for the virtual pet, so that the virtual pet can cooperate with the virtual pet doctor to complete the treatment plan. By enhancing the interaction between the user and the virtual pet, the user's treatment process for the virtual pet is more personalized and targeted, providing a personal immersive experience for the user to raise a virtual pet.

[0132] Specifically, the embodiment of the present application can divide the functional units of the virtual pet doctor matching device based on the virtual pet according to the above method example. For example, each functional unit can be divided corresponding to each function, or two or more functions can be integrated into one processing unit. The above integrated unit can be implemented in the form of hardware or in the form of software functional units. It should be noted that the division of units in the embodiment of the present application is schematic and is only a logical functional division. There may be other division methods in actual implementation.

[0133] See also Figure 7 , Figure 7 This is a method provided by the embodiment of the present application. Figure 6 A schematic diagram of the structure of the determination unit of the device described in Figure 7 As shown, in a possible example, the above-mentioned determination unit further includes:

[0134] 2031: an information module, used to obtain historical cured pet information data corresponding to each virtual pet doctor in at least one virtual pet doctor, the historical cured pet information data including breed information and personality characteristic information of multiple historical cured pets;

[0135] 2032: a type module, used to determine the type of pets that each virtual pet doctor is good at curing according to the historical pet curing information data corresponding to each virtual pet doctor;

[0136] 233: an analysis module, used to analyze the degree of matching between the pet information data and the type of pets that each virtual pet doctor is good at curing, and determine the recommended matching degree between each virtual pet doctor and the target virtual pet;

[0137] 2034: a matching module, used to determine the target matching degree of each virtual pet doctor according to the friendliness between each virtual pet doctor and the target user, and the recommended matching degree;

[0138] 2035: A target module, used to determine a virtual pet doctor whose target matching degree is higher than a first preset matching degree as a target virtual pet doctor.

[0139] In the several embodiments provided in this application, it should be understood that the disclosed device can be implemented in other ways. For example, the device implementation described above is only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the device or unit can be electrical or other forms.

[0140] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of this embodiment.

[0141] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of a software program module.

[0142] If the above-mentioned integrated unit is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0143] With the above Figure 2 The embodiment shown is consistent with the embodiment shown in the figure. The embodiment of the present application provides an electronic device. Figure 8 , Figure 8 is a schematic diagram of a server structure of a hardware operating environment of an electronic device provided by an embodiment of the present application, such as Figure 8 As shown, the electronic device includes a processor, a memory, and computer execution instructions stored in the memory and executable on the processor. When the computer execution instructions are executed, the electronic device executes instructions including any step of the virtual pet doctor matching method based on a virtual pet.

[0144] Among them, the processor is CPU (Central Processing Unit).

[0145] Among them, the memory, optionally, the memory can be a high-speed RAM memory, or a stable memory, such as a disk memory.

[0146] Those skilled in the art will understand that Figure 8 The structure of the server shown in the figure does not constitute a limitation thereto, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0147] like Figure 8As shown, the memory may include an operating system, a network communication module, and a computer-executable instruction of a virtual pet doctor matching method based on a virtual pet. The operating system is used to manage and control server hardware and software resources and support the operation of computer-executable instructions. The network communication module is used to realize communication between components inside the memory, as well as communication with other hardware and software inside the server. 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), etc.

[0148] exist Figure 8 In the server shown, the processor is used to execute computer-executable instructions for personnel management stored in the memory to implement the following steps: receiving a pre-diagnosis request sent by a target user terminal on a target display interface, the pre-diagnosis request being used to request a matched virtual pet doctor to perform diagnosis and treatment for a target virtual pet, with the character image of the target virtual pet being displayed in the target display interface; obtaining, based on the pre-diagnosis request, social data of a target user and at least one virtual pet doctor corresponding to the target user terminal, and pet information data of the target virtual pet; determining, based on the user social data and the pet information data, a target virtual pet doctor whose target matching degree is higher than a first preset matching degree from at least one virtual pet doctor; and pushing the character image of the target virtual pet doctor to the target display interface.

[0149] The specific implementation of the server involved in this application can be found in the various embodiments of the virtual pet doctor matching method based on virtual pets mentioned above, which will not be described in detail here.

[0150] The embodiment of the present application provides a computer-readable storage medium, in which computer instructions are stored. When the computer instructions are executed on a communication device, the communication device performs the following steps: receiving a pre-diagnosis request sent by a target user terminal in a target display interface, the pre-diagnosis request is used to request a matching virtual pet doctor to perform diagnosis and treatment for a target virtual pet, and the character image of the target virtual pet is displayed in the target display interface; according to the pre-diagnosis request, obtaining social data of a target user and at least one virtual pet doctor corresponding to the target user terminal, and pet information data of the target virtual pet; according to the user social data and pet information data, determining a target virtual pet doctor with a target matching degree higher than a first preset matching degree in at least one virtual pet doctor; and pushing the character image of the target virtual pet doctor to the target display interface. The above-mentioned computer includes an electronic device.

[0151] Among them, electronic terminal devices include mobile phones, tablet computers, personal digital assistants, wearable devices, etc.

[0152] Among them, the computer-readable storage medium can be an internal storage unit of the electronic device described in the above embodiment, such as a hard disk or memory of the electronic device. The computer-readable storage medium can also be an external storage device of the above electronic device, such as a plug-in hard disk equipped on the electronic device, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. Further, the computer-readable storage medium can also include both an internal storage unit of the electronic device and an external storage device. The computer-readable storage medium is used to store computer-executable instructions and other computer-executable instructions and data required by the electronic device. The computer-readable storage medium can also be used to temporarily store data that has been output or is to be output.

[0153] The specific implementation of the computer-readable storage medium involved in the present application can be found in the various embodiments of the virtual pet doctor matching method based on the virtual pet mentioned above, which will not be described in detail here.

[0154] An embodiment of the present application provides a computer program product, wherein the computer program product includes a computer program, and the computer program is operable to cause a computer to perform part or all of the steps of any one of the virtual pet-based virtual pet doctor matching methods recorded in the above method embodiments. The computer program product can be a software installation package.

[0155] It should be noted that, for any of the aforementioned embodiments of the virtual pet-based virtual pet doctor matching method, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the described order of actions, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by this application.

[0156] The above is a detailed introduction to the embodiments of the present application. This article uses specific examples to illustrate the principles and implementation methods of a virtual pet doctor matching method based on a virtual pet in the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, based on the idea of ​​a virtual pet doctor matching method based on a virtual pet in the present application, there will be changes in the specific implementation method and scope of application. In summary, the content of this specification should not be understood as a limitation on the present application.

[0157] Although the present application is described herein in conjunction with various embodiments, in the process of implementing the claimed application, those skilled in the art may understand and implement other variations of the disclosed embodiments by viewing the drawings, the disclosure, and the appended claims. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "one" does not exclude multiple situations. Certain measures are recorded in different dependent claims, but this does not mean that these measures cannot be combined to produce good results.

[0158] A person skilled in the art may understand that all or part of the steps in the various methods of any of the above-mentioned methods of the virtual pet doctor matching method based on virtual pets may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable memory, and the memory may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc.

[0159] Obviously, those skilled in the art can make various changes and modifications to the virtual pet doctor matching method based on virtual pets provided by the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A virtual pet doctor matching method based on a virtual pet, characterized in that: The method comprises: Receiving a pre-diagnosis request sent by a target user terminal in a target display interface, wherein the pre-diagnosis request is used to request a matching virtual pet doctor to perform diagnosis and treatment for a target virtual pet, wherein a character image of the target virtual pet is displayed in the target display interface; According to the pre-diagnosis request, obtaining social data between the target user and at least one virtual pet doctor corresponding to the target user terminal, and pet information data of the target virtual pet; According to the user social data and the pet information data, determining a target virtual pet doctor with a target matching degree higher than a first preset matching degree from the at least one virtual pet doctor; Pushing the character image of the target virtual pet doctor to the target display interface; Wherein, determining a target virtual pet doctor having a target matching degree higher than a first preset matching degree from the at least one virtual pet doctor according to the user social data and the pet information data comprises: Acquire historical pet cure information data corresponding to each virtual pet doctor in the at least one virtual pet doctor, wherein the historical pet cure information data includes breed information and personality characteristic information of a plurality of historical pet cures; Determine the type of pets that each virtual pet doctor is good at curing based on the historical pet curing information data corresponding to each virtual pet doctor; Analyzing the degree of matching between the pet information data and the type of pets that each virtual pet doctor is good at curing, and determining a recommended matching degree between each virtual pet doctor and the target virtual pet; Determining the target matching degree of each virtual pet doctor according to the friendship degree between each virtual pet doctor and the target user, and the recommended matching degree; Determine that the virtual pet doctor whose target matching degree is higher than the first preset matching degree is the target virtual pet doctor; Wherein, if there is no target virtual pet doctor whose target matching degree is higher than the first preset matching degree, the method further includes: Acquire historical social interactions between the target virtual pet and other characters other than the target user, and character images corresponding to each virtual pet doctor; Analyze the historical social interactions between the target virtual pet and other characters except the target user to determine the preferred character image of the target virtual pet; Determining the image matching degree of each virtual pet doctor according to the similarity between the character image corresponding to each virtual pet doctor and the preferred character image; According to the user social data, the pet information data and the image matching degree, a target virtual pet doctor having a target matching degree higher than a first preset matching degree is determined from the at least one virtual pet doctor.

2. The method according to claim 1, characterized in that The method further includes receiving a diagnosis request message sent by the target user terminal to a selected pet doctor, and generating a pet diagnosis result according to the diagnosis request message, wherein the selected pet doctor includes the target virtual pet doctor and other virtual pet doctors except the target virtual pet doctor. After generating the pet diagnosis result, the method further includes: If the selected virtual pet doctor is the target virtual pet doctor, generating a first training degree gain value corresponding to the pet diagnosis result; If the selected virtual pet doctor is the other virtual pet doctor, a second training degree gain value corresponding to the pet diagnosis result is generated, wherein the first training degree gain value is greater than the second training degree gain value.

3. The method according to any one of claims 1 to 2, characterized in that: After receiving a diagnosis request message sent by the target user terminal for the selected virtual pet doctor and generating a pet diagnosis result according to the diagnosis request message, the method further includes: According to the pet diagnosis result, determining whether the target disease corresponding to the target virtual pet belongs to a target type disease, wherein the target type disease includes diseases that need to be re-examined at a preset time and long-term diseases that are prone to recurrence; If yes, a target association record is generated between the target virtual pet and the selected virtual pet doctor, wherein the target association record is used for the selected virtual pet doctor to reexamine the target virtual pet for the target disease after the preset time; The selected virtual pet doctor image is pushed to the target user terminal after the preset time.

4. The method according to any one of claims 1 to 2, characterized in that: The virtual pet doctor is a user-controlled character and / or a non-user-controlled character, and the friendship between the target user and the virtual pet doctor is determined by historical interaction data between the target user and the virtual pet doctor.

5. A virtual pet doctor matching device based on a virtual pet, characterized in that: The device comprises: A receiving unit, configured to receive a pre-diagnosis request sent by a target user terminal in a target display interface, wherein the pre-diagnosis request is used to request a matching virtual pet doctor to perform diagnosis and treatment for a target virtual pet, wherein a character image of the target virtual pet is displayed in the target display interface; an acquisition unit, configured to acquire, according to the pre-diagnosis request, social data between a target user and at least one virtual pet doctor corresponding to the target user terminal, and pet information data of the target virtual pet; A determination unit, configured to determine, based on the user social data and the pet information data, a target virtual pet doctor having a target matching degree higher than a first preset matching degree from the at least one virtual pet doctor; A pushing unit, used for pushing the character image of the target virtual pet doctor to the target display interface; Wherein, the determining unit includes: An information module, used for obtaining historical cured pet information data corresponding to each virtual pet doctor in the at least one virtual pet doctor, wherein the historical cured pet information data includes breed information and personality characteristic information of a plurality of historically cured pets; A type module, used to determine the type of pets that each virtual pet doctor is good at curing according to the historical pet curing information data corresponding to each virtual pet doctor; An analysis module, for analyzing the degree of matching between the pet information data and the type of pets that each virtual pet doctor is good at curing, and determining a recommended matching degree between each virtual pet doctor and the target virtual pet; A matching module, for determining a target matching degree of each virtual pet doctor according to the friendliness between each virtual pet doctor and the target user and the recommended matching degree; A target module, used to determine the virtual pet doctor whose target matching degree is higher than the first preset matching degree as the target virtual pet doctor; in, If there is no target virtual pet doctor with a target matching degree higher than the first preset matching degree, The determination unit can also be used to obtain historical social interactions between the target virtual pet and other characters except the target user, and the character image corresponding to each virtual pet doctor; analyze the historical social interactions between the target virtual pet and other characters except the target user to determine the preferred character image of the target virtual pet; determine the image matching degree of each virtual pet doctor based on the similarity between the character image corresponding to each virtual pet doctor and the preferred character image; and determine a target virtual pet doctor with a target matching degree higher than a first preset matching degree from the at least one virtual pet doctor based on the user social data, the pet information data and the image matching degree.

6. An electronic device, characterized in that: The electronic device comprises a processor, a memory, and computer-executable instructions stored in the memory and executable on the processor. When the computer-executable instructions are executed, the electronic device executes the method according to any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and when the computer instructions are executed on the communication device, the communication device executes the method according to any one of claims 1 to 4.

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