Animal care recommendation providing method, apparatus, device, and storage medium

Abstract

The present application relates to the technical field of information processing, and discloses an animal maintenance suggestion providing method, device, equipment and storage medium, the method comprises the following steps: obtaining the first information of a target animal input by a user currently and the second information about the target animal; if it is determined that the animal maintenance suggestion information cannot be generated based on the first information and the second information, generating the first question information related to the animal state based on the first information and the second information; obtaining the first reply information of the user answering the first question information; if the animal maintenance suggestion information still cannot be generated based on the first reply information, the first information and the second information, continue to generate new first question information and obtain new first reply information until the animal maintenance suggestion information can be generated based on the existing first reply information, the first information and the second information; generating and outputting the animal maintenance suggestion information. The present application can provide more accurate and professional consultation reply or consultation suggestion for the user.

Description

Technical Field

[0001] This invention relates to the field of information processing technology, and specifically to a method, apparatus, equipment, and storage medium for providing animal care advice. Background Technology

[0002] As animals gain greater importance in families and the socio-economic sphere, online animal care services have emerged and become a convenient and popular option. Pet owners can obtain instant care advice through online platforms, saving time and improving the accessibility of care services. However, the online animal care service industry is still in its early stages of development and faces several challenges. For example, online animal care services typically rely on one-on-one consultations with experienced professionals. To ensure service quality, platforms may need to employ a large number of qualified professionals, increasing operating costs. To address this issue, related technologies have proposed using artificial intelligence or other intelligent technologies to replace professionals in providing consultation services. However, current intelligent technologies can only simply identify keywords in user inquiries and then provide corresponding suggestions or answers based on these keywords. Therefore, the accuracy of the suggestions or answers is low, failing to precisely solve customers' problems and resulting in a poor user experience. Summary of the Invention

[0003] In view of this, the present invention provides a method, apparatus, device and storage medium for providing animal care advice, in order to solve the problem of low accuracy in automatically answering user inquiries in online animal care services, which leads to a poor user experience.

[0004] In a first aspect, the present invention provides a method for providing animal care advice, the method comprising:

[0005] Obtain first information about the target animal currently input by the user, and second information about the target animal, wherein the second information includes at least one of the following: basic information of the target animal, historical health information, historical care information, and historical dialogue information about the target animal;

[0006] If it is determined that animal care advice cannot be generated based on the first information and the second information, then a first question related to the animal's status is generated based on the first information and the second information.

[0007] Obtain the user's first response to the first question;

[0008] If the animal care advice information still cannot be generated based on the first response information, the first information, and the second information, then new first question information is generated and new first response information is obtained until the animal care advice information can be generated based on the existing first response information, the first information, and the second information.

[0009] Generate and output the animal care recommendations.

[0010] In one optional implementation, after outputting the animal care advice information, the method further includes:

[0011] Output query information to determine whether the user's problem has been resolved, and obtain feedback information sent by the user based on the query information;

[0012] If it is determined based on the feedback information that the user's problem has been resolved, then the current animal care advice provision process ends.

[0013] If the user's intention is determined to regenerate new animal care advice information based on the feedback information, then the second question information related to the animal's status is generated multiple times, and after each generation of the second question information, the second reply information in which the user answers the second question information is obtained, until new animal care advice information can be generated based on the existing first reply information, second reply information, first information and second information;

[0014] Generate and output new animal care advice information until the user sends feedback indicating that the problem has been resolved, and then end the current animal care advice provision process.

[0015] In one optional implementation, after outputting the query information used to determine whether the user's problem has been resolved and obtaining the feedback information sent by the user based on the query information, the method further includes:

[0016] If the feedback information is further inquiry information from the user, then the correlation between the inquiry information and the historical dialogue information is obtained, and the historical dialogue information includes the first question information and the first answer information;

[0017] If the consultation information is related to the historical dialogue information, then the consultation information and the most recent part of the historical dialogue information are transmitted to the encyclopedia model;

[0018] If the consultation information and the historical dialogue information are unrelated, then the consultation information is transmitted to the encyclopedia model;

[0019] Obtain the output information of the encyclopedia model and output it to the user.

[0020] In one alternative implementation, the animal care recommendations include disease diagnosis recommendations, medication recommendations, or grooming recommendations.

[0021] In one optional implementation, before generating and outputting the animal care recommendation information, the method further includes:

[0022] Based on the first information, determine the clarity of the user's consultation intent;

[0023] Based on the first response information, the first information, and the second information, the completeness of the target animal's status information is determined;

[0024] If, based on the first information, it is determined that the user's consultation intent is unclear, or based on the first response information, the first information, and the second information, it is determined that the status information of the target animal is incomplete, then it is determined that the animal care advice information cannot be generated based on the first information and the second information.

[0025] If, based on the first information, it is determined that the user's consultation intent is clear, and based on the first response information, the first information, and the second information, it is determined that the status information of the target animal is complete, then it is determined that the animal care advice information can be generated based on the first information and the second information.

[0026] In one optional implementation, determining the clarity of the user's consultation intent based on the first information includes:

[0027] The first information is evaluated to obtain an evaluation result, which includes confidence level and semantic accuracy level. The semantic accuracy level indicates whether there is ambiguity or invalidity.

[0028] If the evaluation result indicates that the confidence level is lower than the set threshold, is ambiguous, or is invalid, then it is determined that the user's consultation intention is unclear.

[0029] In one optional implementation, determining the completeness of the target animal's state information based on the first response information, the first information, and the second information includes:

[0030] Obtain key information extracted from the first response information, the first information, and the second information;

[0031] If the extracted key information lacks information about the target dimension, then the state information of the target animal is determined to be incomplete.

[0032] In one optional implementation, generating the first query information related to the animal's state based on the first information and the second information includes:

[0033] Obtain one or more consultation intent categories of the user currently determined based on the first information, wherein the consultation intent categories include at least one of beauty and skincare inquiries, health and skincare inquiries, and drug inquiries;

[0034] Based on the first information and the second information, the first question information related to the animal's state is generated, and the generated first question information is adapted to the user's current consultation intent category.

[0035] In one optional implementation, generating the first query information related to the animal's state based on the first information and the second information includes:

[0036] A first judgment conclusion is determined based on the first information and the second information, and the first judgment conclusion is the initial judgment conclusion;

[0037] The first question information is generated based on the first judgment conclusion.

[0038] In one optional implementation, after obtaining the first response information from the user in response to the first question, the method further includes:

[0039] Obtain the typical cases corresponding to the first judgment conclusion;

[0040] The relevant information of the typical case is matched with the first information and the first response information;

[0041] If the matching degree is lower than a preset threshold, it is determined that the animal care suggestion information that matches the first judgment conclusion cannot be generated based on the first response information, the first information and the second information.

[0042] The step of continuing to generate new information for the first question includes:

[0043] Based on the first response information, one or more initial second judgment conclusions that are different from the first judgment conclusion are obtained;

[0044] Based on the first information, the first response information, and the second information, the first question information related to the animal's state is generated, and the animal state targeted by the first question information matches the animal state corresponding to the second judgment conclusion.

[0045] In one optional implementation, the first question is a guided question, and the first question is in the form of a multiple-choice question, which includes true / false selection, single selection, and multiple selection.

[0046] In a second aspect, the present invention provides an animal care advice providing device, the device comprising:

[0047] The information acquisition module is used to acquire first information about the target animal currently input by the user, and second information about the target animal, wherein the second information includes at least one of the following: basic information of the target animal, historical health information, historical care information, and historical dialogue information about the target animal;

[0048] The question information generation module is used to generate first question information related to the animal's status based on the first information and the second information if it is determined that animal care advice information cannot be generated based on the first information and the second information.

[0049] The response information acquisition module is used to acquire the first response information of the user in response to the first question information;

[0050] The question information generation module is further configured to, if the animal care advice information cannot be generated based on the first response information, the first information, and the second information, continue to generate new first question information and obtain new first response information until the animal care advice information can be generated based on the existing first response information, the first information, and the second information.

[0051] The suggested output module is used to generate and output the animal care suggestion information.

[0052] Thirdly, the present invention provides a computer device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the animal care advice provision method of the first aspect or any corresponding embodiment described above.

[0053] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions for causing a computer to perform the animal care advice provision method described in the first aspect or any corresponding embodiment thereof.

[0054] Fifthly, the present invention provides a computer program product, including computer instructions for causing a computer to execute the animal care advice provision method described in the first aspect or any corresponding embodiment thereof.

[0055] The animal care advice method, apparatus, equipment, and storage medium provided in this invention can automatically provide animal care consultation services to users using artificial intelligence or other intelligent technologies. During the service process, a multi-round follow-up questioning mechanism—specifically, repeatedly asking users questions related to the animal's condition—refines the necessary information, thereby providing more accurate and professional consultation answers or advice based on more comprehensive information, thus precisely solving users' problems and improving user experience. Furthermore, in this invention, each follow-up question (i.e., inquiry information) is generated based on existing information (including the initial information provided by the user when initiating the consultation, the user's previous responses to follow-up questions, and information filled in by the user before initiating the consultation, and information provided by the user in previous consultations, etc.), thereby avoiding asking the user repetitive questions and further improving user experience. Attached Figure Description

[0056] To more clearly illustrate the technical solutions in the specific embodiments or related technologies of the present invention, the drawings used in the description of the specific embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0057] Figure 1 This is a flowchart illustrating a method for providing animal care advice according to an embodiment of the present invention;

[0058] Figure 2 This is a flowchart illustrating another method for providing animal care advice according to an embodiment of the present invention;

[0059] Figure 3 This is a flowchart illustrating another method for providing animal care advice according to an embodiment of the present invention;

[0060] Figure 4 This is a structural block diagram of an animal care advice providing device according to an embodiment of the present invention;

[0061] Figure 5 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. Detailed Implementation

[0062] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0063] In related technologies, online animal care service platforms need to employ a large number of qualified professionals, which not only increases operating costs but also presents the following problems:

[0064] First, due to the lack of an effective regulatory mechanism, some professional animal care workers may not have enough clinical experience or professional knowledge, which affects the quality of their services.

[0065] Second, users may concentrate their inquiries on online animal care service platforms during certain time periods. This could lead to the platform's professional staff being overworked during some periods while remaining idle during others, resulting in a waste of human resources and high operating costs.

[0066] Third, during peak hours when users consult online animal care service platforms, users may have to wait a long time to receive a response due to the excessive workload of professional staff, which affects the user experience.

[0067] Fourth, different professionals may have different consultation and judgment methods, and the lack of unified standards makes it difficult to optimize and manage the entire service process. In cases involving multidisciplinary collaboration (such as internal medicine, surgery, etc.), the absence of a good internal communication mechanism can lead to coordination problems.

[0068] Fifth, limited or inaccurate information provided by users forces animal care professionals to spend extra time clarifying the situation or requesting supplementary materials, thus reducing consultation efficiency. Consequently, the platform needs to hire more professionals, further increasing operating costs.

[0069] According to an embodiment of the present invention, an embodiment of a method for providing animal care advice is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of executable computer instructions. Furthermore, although a logical order is shown in the flowchart, in some cases the steps shown or described may be performed in a different order than that shown here.

[0070] This embodiment provides a method for providing animal care advice, which can be used on various terminals or servers. An online animal care service platform can be deployed on these terminals or servers. Figure 1This is a flowchart of a method for providing animal care advice according to an embodiment of the present invention, such as... Figure 1 As shown, the process includes the following steps:

[0071] Step S101: Obtain first information about the target animal currently input by the user, and second information about the target animal. The second information includes at least one of the following: basic information of the target animal, historical health information, historical care information, and historical dialogue information about the target animal.

[0072] Specifically, the first piece of information can be what the user enters and sends to the online animal care service platform when initiating a consultation. This first piece of information can be one or more pieces of information entered by the user. It can be an animal care-related question, specifically including the current status information of the target animal. The user can be an animal owner.

[0073] The second piece of information can be either currently entered by the user and sent to the online animal care service platform, or it can be information pre-stored by the platform. For example, such as... Figure 2 The diagram shown is a flowchart of an animal care consultation process. Figure 3 The diagram shows another animal care consultation process. The platform can deploy an animal database, which stores secondary information about each animal. Specifically, the target animal's basic information, historical health information, and historical care information can be entered by the user into the online animal care service platform before the consultation, such as when registering an account. Basic information includes the animal's species, age, sex, and weight. Historical health information and historical care information can be provided by the user or extracted from the user's previous consultations on the platform. Historical health information includes past medical records, etc.

[0074] The historical dialogue information for the target animal is obtained through the platform's historical dialogue review function, which allows the platform to review previous conversations between the user and the platform in order to better understand the context of the user's current inquiry.

[0075] In embodiments of the present invention, such as Figure 2 The diagram shown is a flowchart of an animal care consultation process. Figure 3 The diagram shows another animal care consultation process. After receiving the user's initial information about the target animal, the platform filters this information for sensitive words to ensure it does not contain any inappropriate or offensive language. Of course, the platform filters not only the initial information but also all user input, including subsequent questions and responses.

[0076] Step S102: If it is determined that animal care advice information cannot be generated based on the first information and the second information, then a first question related to the animal's status is generated based on the first information and the second information.

[0077] In some optional implementations, step S102, namely generating the first query information related to the animal's state based on the first information and the second information, includes:

[0078] Step S1021: Obtain one or more consultation intent categories of the user currently determined based on the first information. The consultation intent categories include at least one of beauty and skincare inquiries, health and skincare inquiries, and drug inquiries. Specifically, a classifier can be used to identify the user's consultation intent category based on the first information.

[0079] Step S1022: Based on the first information and the second information, generate the first question information related to the animal's state, and the generated first question information is adapted to the user's current consultation intent category. For example, if the user inputs "My dog ​​isn't eating," the platform will determine that it may be a disease consultation, and then ask specific symptoms based on this determination: "Has your dog recently shown signs of vomiting, diarrhea, or lethargy?"

[0080] In this embodiment of the invention, if the user's consultation intent category can be determined based on the first information input by the user, then when asking a question, the question information will be generated based on the user's current consultation intent category, so as to quickly generate animal care advice information for the user's consultation question and improve efficiency.

[0081] Specifically, in this embodiment of the invention, the user's current consultation intent category is determined based on the first information, thereby achieving the triage of user question types. Different consultation intent categories correspond to different platform follow-up questioning logics to ensure the depth of information acquisition. For example, if the user's consultation intent category is beauty and care inquiry, the platform will follow up with questions about animal fur type, daily cleaning frequency, etc. If the platform determines that the user currently has multiple categories of consultation intent, then it needs to conduct follow-up questions for each of those multiple categories of consultation intent.

[0082] In some alternative embodiments, step S102, generating the first query information related to the animal's state based on the first information and the second information, includes:

[0083] Step S102a: Determine a first judgment conclusion based on the first information and the second information. This first judgment conclusion is the initial judgment conclusion. In other embodiments, the first judgment conclusion may also be determined based solely on the first information. When determining the first judgment conclusion based on the first and second information, the user's consultation intent or consultation intent analogy may be determined first based on the first information, or based on the first and second information, and then the first judgment conclusion is generated accordingly. For example, if the first information entered by the user includes "My cat has a runny nose, it must have a cold, what should I do?", then the current first judgment conclusion can be obtained based on the first information: the cat has a cold.

[0084] like Figure 2 The diagram shown is a flowchart of an animal care consultation process. Figure 3 Another animal care consultation flowchart shown above, when the known animal status information is incomplete (i.e. the extracted keywords do not meet the minimum combination for disease judgment or the minimum combination for health advice), first determine the first judgment conclusion (i.e. the suspected disease), and then generate the first question information based on the possible symptoms of the suspected disease.

[0085] Step S102b: Generate the first question information based on the first judgment conclusion. For example, the first judgment conclusion may be one or more suspected diseases, and the first question information is a question generated based on the possible symptoms of the suspected disease. If the first judgment conclusion is a cold, then the first question information may include: whether or not there is a runny nose.

[0086] In other embodiments, when generating the first question information related to the animal's state based on the first information and the second information, the user's current consultation intent category or consultation intent can be determined based on the first information, and a first judgment conclusion can be determined based on the first information or based on the first information and the second information. Then, the first question information is generated based on the determined consultation intent category or consultation intent and the first judgment conclusion, making the generated first question information more targeted.

[0087] In some specific embodiments, the first question is a guiding question, and the first question is in the form of a multiple-choice question, which includes true / false selection, single selection, and multiple selection.

[0088] In this embodiment of the invention, the platform asks users follow-up questions in the form of multiple-choice questions. For example, "yes / no" questions, or regular single-choice or multiple-choice questions. This avoids users inputting overly complex or difficult-to-analyze answers, improving the platform's service efficiency.

[0089] In addition, the platform uses a friendly tone in the questions it generates, enhancing the user experience.

[0090] Step S103: Obtain the first response information from the user in response to the first question. Specifically, after generating the first question, the first question is output through an interactive interface. After seeing the first question on the interactive interface, the user will respond accordingly, and thus the first response information can be obtained.

[0091] Step S104: If the animal care advice information still cannot be generated based on the first response information, the first information, and the second information, then continue to generate new first question information and obtain new first response information until the animal care advice information can be generated based on the existing first response information, the first information, and the second information.

[0092] In this embodiment of the invention, after each question is posed to a user, the platform dynamically adjusts the direction of subsequent follow-up questions based on the user's response, avoiding repetitive or meaningless questions. For example, if a user enters "My dog ​​isn't eating," the platform will determine that this may be a medical inquiry, and based on this determination, it will ask specific symptoms: "Has your dog recently shown signs of vomiting, diarrhea, or lethargy?" After the user answers this follow-up question, the platform can further ask questions based on the user's response: "Has the dog's diet and environment changed? Has it been vaccinated recently?"

[0093] In summary, when the information input by the user is insufficient or ambiguous, the embodiments of the present invention proactively ask the user questions in order to obtain more complete and accurate information.

[0094] In specific embodiments, multiple required questions can be generated at once to improve follow-up questioning efficiency, generate animal care advice information faster, and reduce the time spent by users.

[0095] like Figure 2 The flowchart shown is a process for animal care consultation, which can utilize a consultation model to conduct multiple rounds of follow-up questions.

[0096] In some specific implementations, after step S104 and before step S105 (generating and outputting the animal care suggestion information), the method further includes:

[0097] Step S104a: Based on the first information, determine the clarity of the user's consultation intent;

[0098] Step S104b: Based on the first response information, the first information, and the second information, determine the completeness of the target animal's state information;

[0099] Step S104c: If, based on the first information, it is determined that the user's consultation intent is unclear, or based on the first response information, the first information, and the second information, it is determined that the status information of the target animal is incomplete, then it is determined that the animal care suggestion information cannot be generated based on the first information and the second information.

[0100] Step S104d: If, based on the first information, it is determined that the user's consultation intent is clear, and based on the first reply information, the first information, and the second information, it is determined that the status information of the target animal is complete, then it is determined that the animal care suggestion information can be generated based on the first information and the second information.

[0101] In this embodiment of the invention, when automatically providing animal care consultation services to users using artificial intelligence or other intelligent technologies, not only is a multi-round follow-up questioning mechanism used to ensure the comprehensiveness of animal-related information, but the system also automatically determines whether the user's consultation intent is clear. If the user's consultation intent is unclear, even if the animal-related information is complete and comprehensive, animal care advice matching the user's consultation intent cannot be generated. Furthermore, in some cases, if the user's consultation intent is unclear, it is impossible to determine whether the animal-related information is complete and comprehensive. This is because the demand for animal-related information changes with the user's consultation intent; in other words, different animal care advice requires different animal-related information.

[0102] Specifically, embodiments of the present invention determine the clarity of a user's consultation intent based on first information. The first information may be one or more pieces of information entered by the user when initiating a consultation, which generally includes the user's consultation intent. Of course, in other embodiments, the determination of the user's consultation intent is not limited to the first information, nor is it limited to the determination of the clarity of the user's consultation intent based solely on the first information. For example, the user's consultation intent and corresponding clarity may be obtained by combining the first information, the second information, and the first response information.

[0103] Furthermore, if the user's consultation intent is unclear, a follow-up questioning mechanism can be used to clarify it. For example, the user's consultation intent can be predicted based on existing information (including initial information), and then the user can be asked to confirm whether the predicted intent is correct. For instance, if the predicted intent is: "What disease does your pet have?", then the output would be: "Are you asking about the disease your pet has?" If the user replies "Yes," then the consultation intent is clearly a disease consultation. If the user replies "No," then the user's consultation intent can be re-predicted and confirmed with the user. Alternatively, multiple possible user consultation intents can be predicted from the beginning based on existing information (including initial information), and then confirmed with the user. Even when the user's consultation intent is unclear, the user can be directly asked: "What information do you want to consult about?"

[0104] In summary, before generating and outputting animal care advice, it is necessary to clarify the user's consultation intent and ensure that the animal-related information required to generate the corresponding advice is complete and comprehensive. Only then can accurate advice that meets the user's needs be generated. If the user's consultation intent is unclear or the required animal-related information is incomplete, it is necessary to clarify the user's intent and supplement the required animal-related information by asking the user follow-up questions.

[0105] In addition, before asking the user follow-up questions, if only the first and second information are available, the same method is used to determine whether animal care advice can be generated based on the first and second information.

[0106] The following examples illustrate how to determine the clarity of a user's consultation intent and the completeness of the target animal's status information.

[0107] In some specific implementations, step S104a, determining the clarity of the user's consultation intent based on the first information, includes:

[0108] Step S104a1: Evaluate the first information to obtain an evaluation result. The evaluation result includes confidence level and semantic accuracy. The semantic accuracy indicates whether there is ambiguity or invalidity.

[0109] Specifically, a rule engine can be used in conjunction with rules to determine whether information is ambiguous or invalid.

[0110] Alternatively, the following methods or combinations can be used to determine whether information is ambiguous or invalid:

[0111] 1. Grammatical Analysis: Grammatical analysis can check whether the sentence structure is correct, thus making a preliminary judgment on the validity of the information. Valid sentences usually follow the grammatical rules of a specific language.

[0112] 2. Semantic Analysis: This is to understand the actual meaning of the text. This process attempts to resolve the true meaning of words, phrases, and sentences, as well as the relationships between them. This is crucial for identifying potential ambiguities, as a word or phrase may have multiple meanings depending on the context.

[0113] 3. Entity Recognition: Identifying and classifying important elements in text. Accurately identifying these entities helps in understanding the text content and reduces the possibility of misunderstanding.

[0114] 4. Contextual understanding: Considering the context in which information appears can help eliminate ambiguity.

[0115] 5. Machine Learning Models: Modern Natural Language Processing (NLP) systems widely use machine learning models to evaluate the quality of information. These models are trained on large amounts of data and are able to identify patterns and predict which information is likely to be valid and which may be ambiguous or misleading.

[0116] Regarding confidence level, specifically, a confidence algorithm, such as the Softmax function or the Bayesian method, can be used to score the degree of understanding of the first piece of information to obtain the confidence level. Specifically, the model is pre-trained with a corpus labeled with confidence levels, allowing it to know how to score the information entropy for a given combination of pet information (the more complete the information, the higher the information entropy). During inference, the model's Softmax transforms the pet information combinations (logits) into a confidence probability distribution, representing the model's probability for each category; the higher the probability value, the higher the confidence level. Similarly, the Bayesian method models the uncertainty of model parameters by introducing a probability distribution, using the variance or entropy of the prediction distribution to measure confidence; the larger the variance or the higher the entropy, the lower the confidence level. A threshold could be set, for example, 80%.

[0117] In step S104a2, if the evaluation result is that the confidence level is lower than a set threshold, ambiguous, or invalid, then it is determined that the user's consultation intention is unclear. If the evaluation result is that the confidence level is greater than or equal to the set threshold, unambiguous, and valid, then it is determined that the user's consultation intention is clear.

[0118] As mentioned above, in some embodiments, the determination of the user's consultation intent is not limited to the first information, nor is it limited to the determination of the clarity of the user's consultation intent based on the first information. For example, the evaluation of the first information can be combined with the second information. For example, when the second information includes historical dialogue information, it is necessary to combine the historical dialogue information to evaluate the first information, that is, it is necessary to determine whether the user's current consultation question is clear through contextual information.

[0119] In some specific implementations, step S104b, namely determining the completeness of the target animal's state information based on the first response information, the first information, and the second information, includes:

[0120] Step S104b1: Obtain key information extracted from the first response information, the first information, and the second information. This key information is related to animal care. Specifically, NLP technology can be used to perform semantic analysis on the first and second information, focusing on key information and ignoring invalid parts through an attention mechanism to extract key information. For example, key information could include: "runny nose," "red eyes," and "tangled fur."

[0121] Step S104b2: If the extracted key information lacks information from the target dimension, then the state information of the target animal is determined to be incomplete. The dimensions here include one or more of the following: breed, age, sex, defecation status, mental and appetite status, duration of the animal's state, frequency of occurrence of the animal's state, and accompanying symptoms of the animal's state. The target dimension can be one or more of all dimensions.

[0122] In this embodiment of the invention, the dimensions of the key information required to generate animal care advice information can be determined in advance. After obtaining the key information extracted from the first response information, the first information and the second information, the dimensions corresponding to the extracted key information are compared with the dimensions of the required key information determined in advance. In this way, it can be determined whether the key information obtained at present is missing one or more dimensions of key information.

[0123] Step S104b2 above can be executed by an artificial intelligence model. For example, step S104b2, which determines that the target animal's state information is incomplete if the extracted key information lacks information in the target dimension, includes:

[0124] Obtain one or more categories of the user's current consultation intent, determined based on the first information;

[0125] The dimensions of key information required to generate animal care advice information corresponding to the aforementioned consultation intent category;

[0126] By comparing the dimensions of the key information extracted from the first response information, the first information, and the second information with the dimensions of the required key information, it is determined whether the extracted key information is missing information of the target dimension.

[0127] If the extracted key information is found to lack information in the target dimension, then the state information of the target animal is determined to be incomplete.

[0128] For example, step S104b2, which states that if the extracted key information lacks information about the target dimension, then the state information of the target animal is determined to be incomplete, includes:

[0129] Obtain the user's current judgment conclusion determined based on the first information;

[0130] The dimensions of key information required to generate the animal care advice information corresponding to the judgment conclusion;

[0131] By comparing the dimensions of the key information extracted from the first response information, the first information, and the second information with the dimensions of the required key information, it is determined whether the extracted key information is missing information of the target dimension.

[0132] If the extracted key information is found to lack information in the target dimension, then the state information of the target animal is determined to be incomplete.

[0133] In some optional implementations, if a follow-up question needs to be initiated because the key information extracted from the first response information, the first information, and the second information is missing one or more dimensions of key information, then when generating the question information, it is necessary to target the missing dimensions of key information in order to obtain the corresponding dimensions of key information.

[0134] For example, if a user mentions "What should I do if my cat sneezes?" but doesn't provide other symptom information, the platform will automatically generate a question: "Does the cat have a runny nose or loss of appetite?" Or, for instance, if a user enters "My dog ​​has tear stains," the platform will ask: "Are the tear stains dark brown? Are they accompanied by redness and swelling around the eyes?"

[0135] Before generating the first question and obtaining the first response, when determining whether animal care advice can be generated based on the first and second information, the same method is used to determine whether the target animal's status information is complete. For example, Figure 2 The diagram shown is a flowchart of an animal care consultation process. Figure 3 Another animal care consultation flowchart shown is based on the first information input by the user (i.e., the user's question) and the second information in the animal information database, which extracts symptom keywords (i.e., key information).

[0136] In some optional implementations, after obtaining the first response information from the user in response to the first question, the method further includes:

[0137] Step 1: Obtain the typical cases corresponding to the first judgment conclusion.

[0138] Step 2: Match the relevant information of the typical case with the first information and the first response information; specifically, the relevant information of the typical case and the first information here mainly refer to the animal's status information.

[0139] Step 3: If the matching degree is lower than a preset threshold, it is determined that the animal care advice information that matches the first judgment conclusion cannot be generated based on the first response information, the first information, and the second information. Specifically, each dimension of information corresponds to a matching degree value, and then the total matching degree value can be obtained by weighted summation. Finally, the judgment is made based on the total matching degree.

[0140] The process of generating new first question information includes:

[0141] Step 1: Based on the first response information, obtain one or more initial second judgment conclusions that differ from the first judgment conclusion. Specifically, the second judgment conclusion can be generated by combining the second information. The first response information can be user response information obtained from one round of follow-up questions, or user response information obtained from multiple rounds of follow-up questions. For example, although the first information entered by the user (e.g., the animal owner) indicates that the target animal may have a cold, the platform judges based on the first response information that it may have an allergy. In this case, the first judgment conclusion is a cold, and the second judgment conclusion is an allergy.

[0142] Step 2: Based on the first information, the first response information, and the second information, generate the first question information related to the animal's state, wherein the animal state addressed by the first question information matches the animal state corresponding to the second judgment conclusion. The generated first question information will then be output to the user, and the user's first response information will be obtained.

[0143] Step S105: Generate and output the animal care advice information. Specifically, an artificial intelligence model can be used to generate the animal care advice information. Regarding this AI model: During the training phase, it encounters a large amount of text data covering a wide range of topics, including but not limited to pet care and medical knowledge. By analyzing language patterns and information in this text, the model can learn basic knowledge about different topics. When interacting with users, the model can understand the current topic of discussion based on the context of the conversation and provide relevant answers accordingly. For example, in a multi-turn pet consultation scenario, if a user mentions that their dog has skin problems, the model can infer possible causes (such as allergies, parasite infections, etc.) and provide suggestions based on previously learned information about canine skin problems. The model excels at recognizing patterns in text and generating appropriate responses accordingly. For example, when encountering questions about symptoms and solutions, it might answer according to the pattern of "confirming symptoms - suggesting possible causes - recommending action steps." Although the model lacks long-term memory, it can utilize short-term contextual memory to maintain conversational coherence during a multi-turn dialogue. This means that in the case of pet consultation, the model can remember the information previously provided by the user (such as pet breed, age, weight, etc.) and take these factors into account in subsequent responses.

[0144] Specifically, the animal care advice includes disease diagnosis suggestions, medication recommendations, and grooming advice. It may also include feeding and rehabilitation suggestions. Once the platform collects sufficient information, it will generate animal care advice information and corresponding animal care advice reports.

[0145] Here's an example of how a user gets animal care advice on a consultation platform:

[0146] Animal owner (i.e., user): Hello. I would like to inquire about grooming and health care for my dog.

[0147] Platform: Hello! We're happy to assist you. How old is your dog? What breed is it?

[0148] Animal owner: It is a two-year-old Golden Retriever.

[0149] Platform: Understood. Regular grooming is very important for long-haired dogs like Golden Retrievers. How often do you usually groom your dog?

[0150] Animal owner: About once a week. Is that enough?

[0151] Platform: For Golden Retrievers, it's recommended to brush them at least every 3-4 days to prevent tangles and reduce shedding. Also, how often should they be bathed?

[0152] Animal owner: We take a bath about twice a month.

[0153] Platform: This frequency is appropriate. However, make sure to use shampoo and conditioner specifically formulated for dogs' skin. So, what about ear cleaning and nail trimming?

[0154] Animal owner: We pay close attention to cleaning the ears, about once a week; as for the nails, we trim them as needed.

[0155] Platform: Great, keeping your ears clean can prevent infection. As for your nails, it's recommended to check and trim them monthly to prevent them from growing too long and affecting your walking. Are there any special dietary arrangements?

[0156] Animal owner: Mainly dog ​​food, occasionally some fruits and vegetables.

[0157] Platform: A good choice. Ensure high-quality dog ​​food meets its nutritional needs. As for fruits and vegetables, avoid foods harmful to dogs, such as grapes and chocolate.

[0158] Animal owner: I understand. Are there any other things I need to be aware of?

[0159] Platform: Advice on animal health and wellness:

[0160] In terms of beauty and health, in addition to regular grooming and proper bathing mentioned above, you can also consider professional beauty care, such as regular haircuts and styling.

[0161] Daily care: Paying attention to eye and teeth hygiene is equally important.

[0162] Regarding diet: Ensure your dog gets plenty of water and adjust food portions according to their age and weight to prevent obesity. Adequate exercise is also essential, as it helps maintain a healthy physique and promotes digestion. We hope these suggestions are helpful!

[0163] Another user consultation platform provides an example of how animal care advice is obtained:

[0164] Animal owner: My dog ​​has some red spots on his skin lately.

[0165] Platform: Hello, my dog ​​has recently developed red spots on its skin, which is definitely something to watch out for. To better help my dog, I need some additional information. Has your dog been scratching or licking these red spots recently? This will help us determine if there is any itching.

[0166] Animal owner: Some

[0167] Platform: We understand. The dog is scratching or licking the red spots, which suggests it may be accompanied by itching. Next, could you please tell us where these red spots are mainly located on the dog's body? For example, on the abdomen, back, or limbs? This will help us further determine the possible cause.

[0168] Animal main: back, head

[0169] Platform: Thank you for your detailed description. Red spots on your dog's back and head, accompanied by itching, can be caused by a variety of reasons. Has your dog recently experienced any changes in its living environment, such as moving, getting new furniture, or acquiring new pets? These factors can sometimes affect an animal's skin condition.

[0170] Animal owner: No change

[0171] Platform: Okay, since the living environment hasn't changed, we need to consider other possible factors. Has your dog's diet changed recently, for example, have you switched to a new dog food or added any new food? Dietary changes can sometimes cause skin problems.

[0172] Animal owner: None

[0173] Platform: Understood. Based on the information you provided, the diagnostic summary is as follows:

[0174] Differential diagnosis:

[0175] 1. Superficial pyoderma

[0176] 2. Atopic dermatitis

[0177] 3. Fungal infections: such as Microsporum canis, Malassezia infections, etc.

[0178] 4. External parasite infections: such as fleas, lice, ticks, demodicose mites, scabies mites, etc.

[0179] Treatment recommendations: If you feel that your dog's current overall condition is acceptable, you can try the following measures first:

[0180] 1. Timely external parasite control, prioritizing medications effective against mites.

[0181] 2. Administer fish oil or topical medications to repair the skin's protective barrier.

[0182] 3. Veterinary antibacterial spray can be applied to broken skin areas.

[0183] 4. If necessary, administer oral veterinary antibiotics and anti-inflammatory and antipruritic medications.

[0184] Note: Home treatment and observation usually last 1-2 days. If the dog's symptoms improve significantly after observation, continue treatment until full recovery. If the symptoms do not improve significantly or worsen after observation, please take the dog to a veterinary clinic immediately. The above-suggested medications have no significant side effects on most animals. Please read the instructions carefully before use.

[0185] Medical advice: Choose a nearby hospital with high ratings or a hospital you are familiar with. Cooperate with the doctor for visual, tactile, and auscultatory examinations, which may include skin scrapings, Wood's lamp examination, fungal culture, and allergy testing to find the specific cause. After the basic examinations, the doctor will give a preliminary diagnosis and a preliminary treatment plan.

[0186] Daily care:

[0187] 1. During a skin disease, reduce the dog's diet to a single type or feed it a hypoallergenic prescription dog food.

[0188] 2. During a dog's skin disease, you can increase the frequency of bathing to twice a week, and use a moisturizing and repairing medicated bath for washing and care.

[0189] 3. Perform internal and external deworming treatments on time, once a month.

[0190] I hope these suggestions are helpful. Please feel free to contact me if you have any further questions.

[0191] The animal care advice method provided in this invention can automatically provide users with animal care consultation services using artificial intelligence or other intelligent technologies. During the service process, a multi-round follow-up questioning mechanism is used—specifically, repeatedly asking users questions related to the animal's condition to refine the necessary information. This allows for more comprehensive information to provide users with more accurate and professional consultation answers or advice, thereby precisely solving users' problems and improving user experience. Furthermore, in this invention, each follow-up question (i.e., inquiry information) is generated based on existing information (including the initial information provided by the user when initiating the consultation, the user's previous responses to follow-up questions, and information filled in by the user before initiating the consultation, and information provided by the user in previous consultations). This avoids asking users repetitive questions and further enhances user experience.

[0192] Some optional implementations, such as Figure 2 or Figure 3 As shown, after outputting the animal care suggestion information, the process also includes:

[0193] Step S105: Output inquiry information to determine whether the user's problem has been resolved, and obtain feedback information sent by the user based on the inquiry information.

[0194] Step S106: If it is determined based on the feedback information that the user's problem has been resolved, then the current animal care advice provision process ends. For example, if the consultation service is provided to the user through a dialogue in an interactive interface, then the dialogue ends when the user's feedback information indicates that the user's problem has been resolved.

[0195] Step S107: If the user's intention is to regenerate new animal care advice information based on the feedback information, then the second question information related to the animal's status is generated multiple times, and after each generation of the second question information, the second reply information in which the user answers the second question information is obtained, until new animal care advice information can be generated based on the existing first reply information, second reply information, first information and second information.

[0196] This also involves asking users multiple questions through a series of dialogues to obtain more comprehensive information.

[0197] Specifically, each time a second question is generated, it is based on the existing first response, the second response (except when the second question was generated for the first time), the first information, and the second information. This not only allows for the acquisition of necessary supplementary information but also avoids duplicate questioning.

[0198] Step S108: Generate and output new animal care advice information until the user sends feedback information indicating that the user's problem has been resolved, and end the current animal care advice provision process.

[0199] In other words, this embodiment of the invention provides consultation services to users by generating animal care suggestions in multiple rounds until the user's problem is solved, thereby improving user satisfaction. Furthermore, before generating each new animal care suggestion, the user is asked follow-up questions about the animal in the same or similar manner to obtain more complete and comprehensive information, thereby improving the accuracy of the animal care suggestions, reducing the number of times animal care suggestions are generated, and increasing the efficiency of responding to user inquiries.

[0200] Other alternative implementations, such as Figure 2 or Figure 3 As shown, after step S105, which involves outputting the query information used to determine whether the user's problem has been resolved and obtaining the feedback information sent by the user based on the query information, the method further includes:

[0201] Step S109, if the feedback information is further inquiry information from the user (i.e. Figure 2 or Figure 3 shown If further questions are asked, the correlation between the consultation information and the historical dialogue information is obtained, and the historical dialogue information includes the first question information and the first answer information.

[0202] Specifically, keywords from the user's current inquiry information and keywords from historical dialogue information can be extracted and sent to Softmax. Softmax performs domain similarity calculation on the keywords and converts the results into a confidence probability distribution, which is used to represent the probability that the user's further inquiry information is not related to historical dialogue information. The higher the probability value, the more relevant it is.

[0203] Step S110: If the consultation information and the historical dialogue information are related, then the consultation information and the most recent portion of the historical dialogue information are transmitted to the encyclopedia model. The most recent portion of the historical dialogue information may, for example, be the historical dialogue information from the most recent 5 rounds.

[0204] Step S111: If the consultation information and the historical dialogue information are not related, then the consultation information is transmitted to the encyclopedia model.

[0205] Step S112: Obtain the output information of the encyclopedia model and output it to the user.

[0206] The animal care advice method provided in this embodiment can provide users with accurate, professional, and targeted animal care advice.

[0207] The animal care advice method provided in this embodiment can simultaneously generate independent questions and care suggestions for multiple different users' inquiries, without time constraints, minimizing user waiting time and improving user experience. It also avoids the problem of insufficient professional resources during peak hours and wasted resources during off-peak hours.

[0208] The animal care advice method provided in this embodiment follows a standardized consultation process, ensuring consistency and accuracy in each consultation, and the entire service process is easy to optimize and manage.

[0209] The animal care advice method provided in this embodiment introduces an advanced artificial intelligence agent. Relying on a rich disease database and advanced algorithms, it accurately analyzes animal symptoms. When pet owners describe their animal's symptoms, the AI ​​agent can quickly integrate multiple factors to determine the potential disease type, providing a scientific basis for subsequent treatment. The AI ​​agent is online 24 / 7, ready to answer any questions pet owners may have, whether it's confusion about daily animal care or concerns about certain disease symptoms, providing rapid and professional answers to alleviate pet owners' anxiety.

[0210] The animal care advice method provided in this embodiment can generate scientifically sound and personalized treatment plans based on the animal's individual characteristics such as age, weight, and breed. For example, for minor skin diseases in small dogs, the artificial intelligence system can recommend suitable topical ointments and application frequencies, and provide detailed precautions. This avoids adverse consequences caused by improper medication and improves treatment effectiveness.

[0211] The animal care advice method provided in this embodiment can quickly understand the symptoms described by the user, reducing the time spent on clarification and supplementary materials. Utilizing efficient backend support, it rapidly analyzes user-uploaded images and videos, improving diagnostic efficiency. The entire process, from user input to diagnostic result generation, is highly automated, reducing errors and time consumption from manual operations. It can integrate multidisciplinary knowledge, providing interdisciplinary preliminary diagnostic suggestions when needed, reducing difficulties in internal coordination.

[0212] The animal care advice method provided in this embodiment establishes a unique health record for each animal, recording information such as vaccinations, physical examination data, and medical history. Furthermore, based on the data in the health record, the system regularly pushes personalized health monitoring plans to animal owners, including dietary adjustment suggestions, exercise programs, and preventative healthcare measures, ensuring the animal maintains optimal health.

[0213] The animal care advice method provided in this embodiment offers a user-friendly interface design, an intuitive functional layout, and a timely user feedback mechanism. It improves interface usability: users can easily get started and quickly find the functions they need; enhances interactivity: the AI ​​doctor can interact with users in real time, answer questions, and improve user satisfaction; and provides a comprehensive feedback mechanism: through user feedback collection and improvement mechanisms, the performance and service quality of the AI ​​doctor are continuously optimized.

[0214] The animal care advice method provided in this invention not only enables online animal consultation services, but also deeply integrates with animal hospitals, animal insurance, and smart animal hardware, providing pet owners with a comprehensive service experience.

[0215] This embodiment also provides an animal care advice providing device, which is used to implement the above embodiments and preferred embodiments, and will not be repeated as already described. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0216] This embodiment provides an animal care advice provision device, such as... Figure 4 As shown, it includes:

[0217] The information acquisition module 401 is used to acquire first information about the target animal currently input by the user, and second information about the target animal, wherein the second information includes at least one of the following: basic information of the target animal, historical health information, historical care information, and historical dialogue information about the target animal;

[0218] The question information generation module 402 is used to generate first question information related to the animal status based on the first information and the second information if it is determined that animal care advice information cannot be generated based on the first information and the second information.

[0219] The response information acquisition module 403 is used to acquire the first response information of the user in response to the first question information;

[0220] The question information generation module 402 is further configured to, if the animal care advice information cannot be generated based on the first response information, the first information and the second information, continue to generate new first question information and obtain new first response information until the animal care advice information can be generated based on the existing first response information, the first information and the second information.

[0221] The suggested output module 404 is used to generate and output the animal care suggestion information.

[0222] In some optional embodiments, the animal care advice providing device also includes:

[0223] The query information output module is used to output query information to determine whether the user's problem has been resolved, and to obtain feedback information sent by the user based on the query information;

[0224] The termination module is used to end the current animal care advice provision process if it is determined based on the feedback information that the user's problem has been resolved.

[0225] The follow-up question module is used to generate a second question related to the animal's status multiple times if the user's intention is to regenerate new animal care advice information based on the feedback information. After each generation of the second question information, the module obtains a second reply information from the user in response to the second question information, until new animal care advice information can be generated based on the existing first reply information, second reply information, first information, and second information.

[0226] The suggestion generation module is used to generate and output new animal care suggestion information until the user sends feedback information indicating that the user's problem has been resolved, and then ends the current animal care suggestion provision process.

[0227] In some optional embodiments, the animal care advice providing device also includes:

[0228] The relevance acquisition module is used to acquire the relevance between the inquiry information and the historical dialogue information if the feedback information is further inquiry information of the user, wherein the historical dialogue information includes the first question information and the first answer information;

[0229] The first transmission module is used to transmit the consultation information and the most recent part of the historical dialogue information to the encyclopedia model if the consultation information is related to the historical dialogue information.

[0230] The second transmission module is used to transmit the consultation information to the encyclopedia model if the consultation information and the historical dialogue information are not related.

[0231] The output module is used to obtain the output information of the encyclopedia model and output it to the user.

[0232] In some optional embodiments, the animal care advice includes disease diagnosis advice, medication advice, or grooming advice.

[0233] In some optional embodiments, the animal care advice providing device also includes:

[0234] The clarity determination module is used to determine the clarity of the user's consultation intent based on the first information;

[0235] The completeness determination module is used to determine the completeness of the target animal's state information based on the first response information, the first information, and the second information;

[0236] The judgment module is configured to determine that the animal care advice information cannot be generated based on the first information and the second information if, based on the first information, it is determined that the user's consultation intention is unclear, or based on the first response information, the first information, and the second information, it is determined that the target animal's status information is incomplete; and if, based on the first information, it is determined that the user's consultation intention is clear, and based on the first response information, the first information, and the second information, it is determined that the target animal's status information is complete, then it is determined that the animal care advice information can be generated based on the first information and the second information.

[0237] In some optional implementations, the clarity determination module is specifically used to evaluate the first information and obtain an evaluation result. The evaluation result includes confidence level and semantic accuracy. The semantic accuracy indicates whether there is ambiguity or invalidity. If the evaluation result is that the confidence level is lower than a set threshold, there is ambiguity, or it is invalid, then it is determined that the user's consultation intent is unclear.

[0238] In some optional implementations, the completeness determination module is specifically used to obtain key information extracted from the first response information, the first information, and the second information; if the extracted key information lacks information of the target dimension, then it is determined that the state information of the target animal is incomplete.

[0239] In some optional implementations, the question information generation module 402 is specifically used to obtain one or more consultation intent categories of the user currently determined based on the first information, wherein the consultation intent categories include at least one of beauty and care inquiry, health care inquiry, and drug inquiry; and generate the first question information related to the animal's state based on the first information and the second information, wherein the generated first question information is adapted to the user's current consultation intent category.

[0240] In some optional implementations, the question information generation module 402 is specifically used to determine a first judgment conclusion based on the first information and the second information, wherein the first judgment conclusion is an initial judgment conclusion; and to generate the first question information based on the first judgment conclusion.

[0241] In some optional embodiments, the animal care advice providing device also includes:

[0242] The typical case acquisition module is used to acquire typical cases corresponding to the first judgment conclusion;

[0243] The matching module is used to match the relevant information of the typical case with the first information and the first response information;

[0244] The determination module is used to determine that if the matching degree is lower than a preset threshold, the animal care suggestion information that matches the first determination conclusion cannot be generated based on the first response information, the first information and the second information.

[0245] The question information generation module 402 includes:

[0246] The second judgment conclusion acquisition unit is used to obtain one or more initial second judgment conclusions that are different from the first judgment conclusion based on the first response information;

[0247] The question generation unit is used to generate the first question information related to the animal state based on the first information, the first response information and the second information, and the animal state targeted by the first question information matches the animal state corresponding to the second judgment conclusion.

[0248] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0249] In this embodiment, the animal care advice providing device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0250] This invention also provides a computer device having the above-described features. Figure 4 The animal care recommendations shown provide the device.

[0251] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of the present invention, such as... Figure 5 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 5 Take a processor 10 as an example.

[0252] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GPA), or any combination thereof.

[0253] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0254] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0255] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0256] The computer device also includes an input device 30 and an output device 40. The processor 10, memory 20, input device 30, and output device 40 can be connected via a bus or other means. Figure 5 Taking the example of a connection between China and Israel via a bus.

[0257] Input device 30 can receive input numerical or character information, and generate key signal inputs related to user settings and function control of the computer device, such as a touchscreen, keypad, mouse, trackpad, touchpad, joystick, one or more mouse buttons, trackball, joystick, etc. Output device 40 may include display devices, auxiliary lighting devices (e.g., LEDs), and haptic feedback devices (e.g., vibration motors). The aforementioned display devices include, but are not limited to, liquid crystal displays, light-emitting diodes, displays, and plasma displays. In some alternative embodiments, the display device may be a touchscreen.

[0258] The computer device also includes a communication interface for communicating with other devices or communication networks.

[0259] This invention also provides a computer-readable storage medium. The methods described above according to embodiments of the invention can be implemented in hardware or firmware, or implemented as computer code that can be recorded on a storage medium, or implemented as computer code downloaded via a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and then stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code, which, when accessed and executed by the computer, processor, or hardware, implements the methods shown in the above embodiments.

[0260] A portion of this invention can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to the invention through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0261] Although embodiments of the invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the invention, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for providing animal care advice, characterized in that, The method includes: Obtain first information about the target animal currently input by the user, and second information about the target animal, wherein the second information includes at least one of the following: basic information of the target animal, historical health information, historical care information, and historical dialogue information about the target animal; If it is determined that animal care advice cannot be generated based on the first information and the second information, then a first question related to the animal's status is generated based on the first information and the second information. Obtain the user's first response to the first question; If the animal care advice information cannot be generated based on the first response information, the first information, and the second information, then a new first question information is generated and a new first response information is obtained until the animal care advice information can be generated based on the existing first response information, the first information, and the second information. Generate and output the animal care recommendations.

2. The method according to claim 1, characterized in that, After outputting the animal care advice information, the method further includes: Output query information to determine whether the user's problem has been resolved, and obtain feedback information sent by the user based on the query information; If it is determined based on the feedback information that the user's problem has been resolved, then the current animal care advice provision process ends. If the user's intention is determined to regenerate new animal care advice information based on the feedback information, then the second question information related to the animal's status is generated multiple times, and after each generation of the second question information, the second reply information in which the user answers the second question information is obtained, until new animal care advice information can be generated based on the existing first reply information, second reply information, first information and second information; Generate and output new animal care advice information until the user sends feedback indicating that the problem has been resolved, and then end the current animal care advice provision process.

3. The method according to claim 2, characterized in that, The output includes an inquiry message used to determine whether the user's problem has been resolved, and after obtaining feedback information sent by the user based on the inquiry message, it also includes: If the feedback information is further inquiry information from the user, then the correlation between the inquiry information and the historical dialogue information is obtained, and the historical dialogue information includes the first question information and the first answer information; If the consultation information is related to the historical dialogue information, then the consultation information and the most recent part of the historical dialogue information are transmitted to the encyclopedia model; If the consultation information and the historical dialogue information are unrelated, then the consultation information is transmitted to the encyclopedia model; Obtain the output information of the encyclopedia model and output it to the user.

4. The method according to any one of claims 1-3, characterized in that, The animal care recommendations include disease diagnosis recommendations, medication recommendations, or grooming recommendations.

5. The method according to claim 1, characterized in that, Before generating and outputting the animal care advice information, the process also includes: Based on the first information, determine the clarity of the user's consultation intent; Based on the first response information, the first information, and the second information, the completeness of the target animal's status information is determined; If, based on the first information, it is determined that the user's consultation intent is unclear, or based on the first response information, the first information, and the second information, it is determined that the status information of the target animal is incomplete, then it is determined that the animal care advice information cannot be generated based on the first information and the second information. If, based on the first information, it is determined that the user's consultation intent is clear, and based on the first response information, the first information, and the second information, it is determined that the status information of the target animal is complete, then it is determined that the animal care advice information can be generated based on the first information and the second information.

6. The method according to claim 5, characterized in that, Determining the clarity of the user's consultation intent based on the first information includes: The first information is evaluated to obtain an evaluation result, which includes confidence level and semantic accuracy level. The semantic accuracy level indicates whether there is ambiguity or invalidity. If the evaluation result indicates that the confidence level is lower than the set threshold, is ambiguous, or is invalid, then it is determined that the user's consultation intention is unclear.

7. The method according to claim 5, characterized in that, The step of determining the completeness of the target animal's status information based on the first response information, the first information, and the second information includes: Obtain key information extracted from the first response information, the first information, and the second information; If the extracted key information lacks information about the target dimension, then the state information of the target animal is determined to be incomplete.

8. The method according to claim 1, characterized in that, The generation of first query information related to the animal's state based on the first information and the second information includes: Obtain one or more consultation intent categories of the user currently determined based on the first information, wherein the consultation intent categories include at least one of beauty and skincare inquiries, health and skincare inquiries, and drug inquiries; Based on the first information and the second information, the first question information related to the animal's state is generated, and the generated first question information is adapted to the user's current consultation intent category.

9. The method according to claim 1, characterized in that, The generation of first query information related to the animal's state based on the first information and the second information includes: A first judgment conclusion is determined based on the first information and the second information, and the first judgment conclusion is the initial judgment conclusion; The first question information is generated based on the first judgment conclusion.

10. The method according to claim 9, characterized in that, After obtaining the first response information from the user in response to the first question, the method further includes: Obtain the typical cases corresponding to the first judgment conclusion; The relevant information of the typical case is matched with the first information and the first response information; If the matching degree is lower than a preset threshold, it is determined that the animal care suggestion information that matches the first judgment conclusion cannot be generated based on the first response information, the first information and the second information. The step of continuing to generate new information for the first question includes: Based on the first response information, one or more initial second judgment conclusions that are different from the first judgment conclusion are obtained; Based on the first information, the first response information, and the second information, the first question information related to the animal's state is generated, and the animal state targeted by the first question information matches the animal state corresponding to the second judgment conclusion.

11. The method according to claim 1, characterized in that, The first question is a guided question, and the first question is in the form of a multiple-choice question, which includes true / false selection, single selection, and multiple selection.

12. An animal care advice providing device, characterized in that, The device includes: The information acquisition module is used to acquire first information about the target animal currently input by the user, and second information about the target animal, wherein the second information includes at least one of the following: basic information of the target animal, historical health information, historical care information, and historical dialogue information about the target animal; The question information generation module is used to generate first question information related to the animal's status based on the first information and the second information if it is determined that animal care advice information cannot be generated based on the first information and the second information. The response information acquisition module is used to acquire the first response information of the user in response to the first question information; The question information generation module is further configured to, if the animal care advice information cannot be generated based on the first response information, the first information, and the second information, continue to generate new first question information and obtain new first response information until the animal care advice information can be generated based on the existing first response information, the first information, and the second information. The suggested output module is used to generate and output the animal care suggestion information.

13. A computer device, characterized in that, include: A memory and a processor are communicatively connected, the memory storing computer instructions, and the processor executing the computer instructions to perform the method for providing animal care advice as described in any one of claims 1 to 11.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a computer to perform the method of providing animal care advice as described in any one of claims 1 to 11.

15. A computer program product, characterized in that, Includes computer instructions for causing a computer to perform the method of providing animal care advice as described in any one of claims 1 to 11.

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