Information processing method and device

Abstract

The invention provides an information processing method and device, and the method comprises the steps: responding to a target request obtained by a target object in a first state, outputting first information, enabling the target object to comprise a target application or target equipment, enabling the first information to be generated by a target model based on application data or equipment data, and obtaining second information, the second information comprises input information for the first information, a second state of the target object is determined based on the second information, and the first state is different from the second state.

Description

Technical Field

[0001] The present disclosure relates to the field of information technology, and in particular to an information processing method and device. Background Art

[0002] Currently, authentication is mainly achieved by setting fixed-mode questions and processing the fixed questions. However, this fixed-mode information processing method has strong dependency and low security. Summary of the invention

[0003] The present disclosure provides an information processing method, device, electronic device and storage medium.

[0004] According to a first aspect of the present disclosure, there is provided an information processing method, comprising:

[0005] In response to the target object obtaining a target request in the first state, outputting first information; the target object includes a target application or a target device, and the first information is generated by a target model based on application data or device data;

[0006] obtaining second information, wherein the second information includes input information for the first information;

[0007] Based on the second information, a second state of the target object is determined; the first state is different from the second state.

[0008] In an implementation of the present application, determining the second state of the target object based on the second information includes:

[0009] If the second information and the third information meet a matching condition, determining a second state of the target object; the target application or the target device can operate normally in the second state;

[0010] The third information is generated by a target model based on target data and the first information, and the first information has a corresponding relationship with the third information.

[0011] In an implementation of the present application, the method further includes:

[0012] parsing the second information and the third information to obtain corresponding semantic features;

[0013] If the semantic features have a matching relationship, it is determined that the matching condition is satisfied.

[0014] In an implementation of the present application, after obtaining the second information, the method further includes:

[0015] Output new first information and obtain new second information;

[0016] Based on all of the first information and all of the second information, a second state of the target object is determined.

[0017] In an implementation of the present application, determining the second state of the target object based on all the first information and all the second information includes:

[0018] If all the first information meets the first quantity condition; the output order of the first information is related to the reference data and / or information complexity of the model when generating the information;

[0019] The output of new first information is stopped, and the second state of the target object is determined based on all the second information.

[0020] In an implementation of the present application, the method further includes:

[0021] The new first information is generated by the target model based on the previous one or more second information and the application data or the device data.

[0022] In an implementation of the present application, the method further includes:

[0023] If there is target second information satisfying the second quantity condition among all the obtained second information, stop generating and outputting new first information, and determine the second state of the target object; the target second information is the second information satisfying the matching condition with the corresponding third information.

[0024] In an implementation of the present application, the method further includes:

[0025] If the second information and the third information do not satisfy the matching condition, determining the third state of the target object; the third state includes any one of the following:

[0026] The third state is the same as the first state;

[0027] The target application or the target device cannot be operated in the third state.

[0028] In an implementation of the present application, the application data or device data includes one or more of registration information, operation information, and running information for a target application or target device within a target time.

[0029] According to a second aspect of the present disclosure, there is provided an information processing device, including:

[0030] A first information processing module, configured to output first information in response to a target object obtaining a target request in a first state; the target object includes a target application or a target device, and the first information is generated by a target model based on application data or device data;

[0031] A second information processing module, used to obtain second information, where the second information includes input information for the first information;

[0032] A state determination module is used to determine a second state of the target object based on the second information; the first state is different from the second state.

[0033] According to a third aspect of the present disclosure, there is provided an electronic device, including:

[0034] at least one processor; and

[0035] a memory communicatively connected to the at least one processor; wherein,

[0036] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method described in the present disclosure.

[0037] According to a fourth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to cause the computer to execute the method described in the present disclosure.

[0038] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The above and other objects, features and advantages of the exemplary embodiments of the present disclosure will become readily understood by reading the detailed description below with reference to the accompanying drawings. In the accompanying drawings, several embodiments of the present disclosure are shown in an exemplary and non-limiting manner, in which:

[0040] In the drawings, the same or corresponding reference numerals represent the same or corresponding parts.

[0041] Figure 1 A schematic diagram of an implementation flow of the information processing method provided in an embodiment of the present application is shown;

[0042] Figure 2 A schematic diagram of an information matching process provided by an embodiment of the present application is shown;

[0043] Figure 3 A schematic diagram of a state determination process provided by an embodiment of the present application is shown;

[0044] Figure 4 A schematic diagram of the structure of an information processing device provided by an embodiment of the present application is shown;

[0045] Figure 5 A schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0046] In order to make the purpose, features, and advantages of the present disclosure more obvious and easy to understand, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present disclosure.

[0047] Since the current information processing method of unlocking devices and applications using fixed questions is highly dependent and has low security. Therefore, in order to improve information processing security and user experience, the present application provides an information processing method, device, electronic device and storage medium. The information processing method provided by the present application can be applied to a client electronic device or a cloud server. The electronic device provided by the present application can be a mobile phone, a computer, a tablet computer and other devices.

[0048] The technical solution of the embodiment of the present application will be described below in conjunction with the drawings in the embodiment of the present application.

[0049] Figure 1 A schematic diagram of an implementation flow of the information processing method provided in an embodiment of the present application is shown. Figure 1 As shown, the method includes:

[0050] S101, in response to a target object obtaining a target request in a first state, output first information; the target object includes a target application or a target device, and the first information is generated by a target model based on application data or device data.

[0051] Target devices include mobile phones, computers, tablets, etc. Target applications are applications or software installed on the device.

[0052] The first state of the target object refers to the target object being in an unusable state. The unusable state includes a locked state or a powered-off state, etc. When the target object is in the first state, the user cannot normally use the functions of the target object. For example, if the target object is a computer, when the computer is in a locked state, the document processing function and multimedia function of the computer cannot be used by the user. For another example, if the target object is a music program in a mobile phone, when the music program is in a locked state, the user does not log in to the music program or does not have the permission of the music program, and the user cannot use the music program to listen to music.

[0053] The first information is a question that can reflect basic information of the target device or target application. The first information includes text information and voice information.

[0054] The target model is a model for generating basic information describing the target device or target application. The target model can be a generative model (generative models), a generative language model (generative language models, GLMs). For example, it can specifically include large language models (LLMs), GPT (Generative Pre-trained Transformer), a large visual model, a multimodal large model, etc. The model involved in the embodiment of the present application can be a general large model, or it can be an expert large model obtained after fine-tuning based on demand, and the embodiment of the present application does not limit this. The target model can be deployed on a client device.

[0055] In the present disclosure, application data may be user usage data in a target application, for example, the user's usage frequency and historical login information of the target application, etc. Device data may be target device hardware data and operating system data, etc.

[0056] In the present disclosure, when the target device or target application is in the first state, the electronic device can monitor whether a trigger operation for the target device or target application is received. The trigger operation may include operations such as clicking a display screen, a keyboard or a target application or voice wake-up.

[0057] If a trigger operation for a target device or a target application is received, a request to change the state of the target device or the target application may be used as a target request. In response to the request to change the state of the target device or the target application, the electronic device outputs first information.

[0058] S102: Obtain second information, where the second information includes input information for the first information.

[0059] In the present disclosure, the second information is explanation information or answer information for the first information. For example, if the first information is a question for a target application or a target device, the second information is the answer to the question; if the first information is functional description information for a target application or a target device, the second information can be extended explanation information for the functional description information.

[0060] In the present disclosure, a user may input second information for a first information by voice or text input. A user may input the second information through an input unit of an electronic device. The input unit includes a keyboard, a virtual keyboard, a microphone, a mouse, etc. In a possible implementation, when the first information is output, a target interface may be displayed on a display screen of the electronic device. The target interface includes a first information output area and a second information input area, and the user may input the second information in the second information input area, and the target interface may be a dialogue window. That is, one or more first information and second information may be presented in a dialogue manner.

[0061] S103: Determine a second state of the target object based on the second information; the first state is different from the second state.

[0062] The second state of the target object refers to the target object being in a usable state. The usable state includes an unlocked state and a normal operating state. When the target object is in the second state, the user can normally access and use the functions of the target object. For example, if the target object is a computer, when the computer is in a usable state, the user can use the document processing function of the computer.

[0063] In the present disclosure, the state of the target device or the target application may be adjusted through the second information, so that the target device or the target application is adjusted from the first state to the second state.

[0064] The information processing method disclosed in the present invention is adopted to respond to the target object obtaining a target request in the first state, output the first information, the target object includes a target application or a target device, the first information is generated by the target model based on the application data or the device data, and the second information is obtained, the second information includes input information for the first information, and the second state of the target object is determined based on the second information, and the first state is different from the second state. The first information can be generated by processing the application data or the device data by the target model, the first information is not fixed, the first information can change with the change of the application data or the device data, the first information can timely reflect the data change of the target object, and the second state of the target object is determined by using the second information obtained by the first information that can reflect the data change of the target object, which is more secure for the target object.

[0065] In a possible implementation, determining the second state of the target object based on the second information includes: if the second information and third information satisfy a matching condition, determining the second state of the target object.

[0066] The target application or the target device can operate normally in the second state. In the second state, the function of the target application or the target device can be used by the user. The third information is generated by the target model based on the target data and the first information, and the first information has a corresponding relationship with the third information.

[0067] In the present disclosure, the target data may include application data of the target application or device data of the target device. The target model may generate questions that can reflect the basic information of the target device or the target application as the first information based on the application data of the target application or the device data of the target device, and generate standard answers corresponding to the questions as the third information. For example, for application A, the application data of application A includes historical login data and registration data of user B, etc. When application A is in a locked state, the target model may generate question Q1 "When was the last time you logged into application A?" as the first information based on the historical login data and registration data of user B, and generate the standard answer A1 "September 5" corresponding to question Q1 as the third information.

[0068] In one embodiment, if there is only one second information, the matching condition may be that the information similarity between the second information and the third information is greater than or equal to a preset similarity threshold. The preset similarity threshold may be set according to application requirements, for example, may be set to 0.95 or 0.96.

[0069] In another possible implementation, if there is more than one second information, each second information corresponds to one third information. The matching condition may be that the number of second information whose information similarity with the corresponding third information is greater than or equal to a preset similarity threshold is greater than or equal to a preset number. The preset number can be set according to application requirements, for example, set to 3 or 4.

[0070] In another possible implementation, if there is more than one second information, the matching condition may also be that the ratio of the number of second information whose information similarity with the corresponding third information is greater than or equal to a preset similarity threshold to the number of all second information is greater than or equal to a preset ratio threshold. The preset ratio threshold may be set according to application requirements, for example, to 0.8 or 0.9.

[0071] When the second information and the third information meet the matching condition, the state of the target program or the target device can be adjusted from the first state to the second state, so that the user can use the target program or the target device.

[0072] In the present disclosure, the cosine similarity or semantic similarity between the second information and the third information may be calculated as the information similarity between the second information and the third information.

[0073] In the present disclosure, the information similarity between the second information and the third information can also be determined by a pre-trained language model. Specifically, a pre-trained language model can be used to generate a semantic vector of the second information and a semantic vector of the third information, and the information similarity between the second information and the third information can be determined by calculating the cosine similarity between the semantic vector of the second information and the semantic vector of the third information.

[0074] In one possible implementation, Figure 2 A schematic diagram of an information matching process provided by an embodiment of the present application is shown. Figure 2 As shown, the method for determining whether the second information and the third information meet the matching condition may include:

[0075] S201, parsing the second information and the third information to obtain corresponding semantic features.

[0076] In the present disclosure, if the second information and the third information are text information, the second information and the third information can be segmented respectively to obtain the text segmentation of the second information and the text segmentation of the third information. The segmentation features corresponding to the text segmentation of the second information are searched through the vocabulary feature library, and the segmentation features corresponding to the text segmentation of the third information are searched. The segmentation features corresponding to the text segmentation of the second information are spliced ​​and normalized to obtain the semantic features corresponding to the second information. The segmentation features corresponding to the text segmentation of the third information are spliced ​​and normalized to obtain the semantic features corresponding to the third information.

[0077] If the second information and / or the third information is voice information, the voice information can be converted into text information, the text information can be segmented and text features can be extracted, and the semantic features corresponding to the second information and the semantic features corresponding to the third information can be determined based on the text features.

[0078] In the present disclosure, a pre-trained semantic feature extraction model may also be used to parse the second information and the third information to obtain corresponding semantic features. For example, a natural language processing model may be used to extract semantic features corresponding to the second information and semantic features corresponding to the third information.

[0079] S202: If the semantic features have a matching relationship, determine that the matching condition is satisfied.

[0080] In the present disclosure, the semantic features corresponding to the extracted second information and the semantic features corresponding to the third information can be converted into feature vectors, and the similarity between the feature vectors is calculated. If the similarity between the feature vectors is greater than or equal to the target similarity, it can be determined that the semantic features have a matching relationship, otherwise, the semantic features do not have a matching relationship. The similarity between the feature vectors can be the cosine similarity or the Euclidean distance between the feature vectors. The target similarity can be set to 0.8 or 0.85, etc.

[0081] In one possible implementation, Figure 3 FIG. 2 shows a schematic diagram of a state determination process provided by an embodiment of the present application. Figure 3 As shown, the method for determining the second state of the target object may include:

[0082] S301, output new first information and obtain new second information.

[0083] In the present disclosure, after receiving a target request, the electronic device can continuously generate multiple first information. After obtaining the second information for the previously generated first information, the electronic device can generate new first information based on the application data or device data by the target model. For example, in the scenario where the computer is locked, the user needs to be authenticated if he wants to log in to the computer. After the computer receives the user's authentication request, the target model can generate authentication question 1 as the first information based on the computer's device data, and the user enters answer information 1 as the second information for authentication question 1. After the computer receives the user's answer information 1, the target model can continue to generate authentication question 2 as the new first information based on the computer's device data, and the user enters answer information 2 as the new second information for authentication question 2.

[0084] Alternatively, if the second information for the previously generated first information is not obtained after a preset time has passed after the previous first information is generated, the electronic device may also generate new first information by the target model based on the application data or device data. For example, in the scenario where the computer is locked, the user needs to be authenticated to log in to the computer. After the computer receives the user's authentication request, the target model may generate authentication question 3 as the first information based on the computer's device data. If the computer does not receive the user's answer to authentication question 3 within the preset time, the answer may be left blank as the second information. Then, the target model continues to generate authentication question 4 as the new first information based on the computer's device data, and the user enters answer information 4 for authentication question 4 as the new second information. The preset time can be set to 1 minute or 2 minutes, etc.

[0085] The new first information is different from the previous first information.

[0086] S302: Determine a second state of the target object based on all the first information and all the second information.

[0087] For each first information, the target model can generate third information corresponding to the first information based on the application data of the target application or the device data of the target device and the first information. The method for generating the third information has been described in detail above and will not be repeated here.

[0088] In the present disclosure, for each first information, the information similarity between the second information and the third information corresponding to the first information can be calculated. If the information similarity is greater than a preset similarity threshold, it can be determined that the second information and the third information corresponding to the first information match.

[0089] In the present disclosure, if the number of first information that matches the corresponding second information and third information reaches a preset number, it can be determined that the target device or target application has reached the second state. Alternatively, if the number of first information that matches the corresponding second information and third information accounts for a proportion of all first information that reaches a preset proportion threshold, it can be determined that the target device or target application has reached the second state.

[0090] In a possible implementation, if all the first information meets the first quantity condition, stop outputting new first information, and determine the second state of the target object based on all the second information. The output order of the first information is related to the reference data and / or information complexity of the model when generating the information.

[0091] In the present disclosure, if the amount of the generated first information reaches the target amount, it can be determined that the first information meets the first amount condition. The target amount can be set to 3 or 4, etc.

[0092] In the present disclosure, the first information may be generated by a target model based on application data or device data.

[0093] Alternatively, the first information may also be generated by the target model based on application data or device data and the previous first information. In the present disclosure, the first information may be divided into information complexity levels. For example, the first information generated based on application data or device data with more refined target applications or target devices has higher information complexity. The sophistication of the data may be measured by data dimension and data span. For example, the higher the data dimension involved, the higher the sophistication of the data. The wider the time span and range span of the data involved, the higher the sophistication of the data. In the present disclosure, the first information may also be divided into types. The types of the first information may include behavior information type and attribute information type, etc.

[0094] When generating new first information, the information complexity level of the next first information may be determined by referring to the type and / or information complexity of the previous first information. The next information complexity level may be greater than or equal to the information complexity level of the previous first information.

[0095] In the present disclosure, if the number of generated first information reaches the target number, the output of new first information is stopped, and the second state of the target object can be determined using the second information corresponding to all the first information currently generated. For example, the information similarity between the second information and the third information corresponding to each first information can be calculated, and the number of matching second information and third information can be determined using the information similarity. The second state of the target program or target application is determined based on the number of matching second information and third information.

[0096] In a possible implementation, the new first information is generated by the target model based on the previous one or more second information and the application data or the device data.

[0097] In the present disclosure, when generating new first information, if the information similarity between the second information and the third information corresponding to the previous first information does not reach the preset similarity threshold, the target model can refer to the previous second information and the application data or the device data to generate the first information of the same type as the previous first information but with higher information complexity. Alternatively, if the information similarity between the second information and the third information corresponding to the previous first information does not reach the preset similarity threshold, the target model can refer to the previous second information and the application data or the device data to generate new first information of a different type from the previous first information but with information complexity not lower than the previous first information.

[0098] For example, the first information is the authentication question Q2 for the target program, the standard answer corresponding to the authentication question Q2 is the third information, and the user's answer to the authentication question Q2 is the second information. If the information similarity between the second information and the third information corresponding to the authentication question Q2 does not reach the preset similarity threshold, that is, the user's answer to the authentication question Q2 does not match the standard answer corresponding to the authentication question Q2. The target model can generate an authentication question Q3 of the same type as the authentication question Q2 but with higher information complexity, or the target model can generate a new authentication question Q4 of a different type from the authentication question Q2 but with information complexity not less than the authentication question Q2.

[0099] Before generating new first information, the target model may refer to the information similarity between the second information and the third information corresponding to all previously generated first information. If the proportion of the number of first information whose information similarity between the corresponding second information and the third information reaches a preset similarity threshold among all previously generated first information is lower than the target proportion, the target model may refer to the application data or device data to generate new first information whose information complexity is much higher than all previously generated first information. If the proportion of the number of first information whose information similarity between the corresponding second information and the third information reaches a preset similarity threshold among all previously generated first information is not lower than the target proportion, the target model may refer to the application data or device data to generate new first information whose information complexity is not higher than all previously generated first information. The target proportion can be set to 0.7 or 0.8.

[0100] In a possible implementation, if there is target second information satisfying the second quantity condition among all the second information obtained, stop generating and outputting new first information, and determine the second state of the target object; the target second information is the second information satisfying the matching condition with the corresponding third information.

[0101] In the present disclosure, the similarity between the second information and the third information corresponding to each first information can be calculated. If the similarity reaches a preset similarity threshold, it can be determined that the second information and the corresponding third information meet the matching condition, and the second information can be determined as the target second information.

[0102] In the present disclosure, if the target second information is greater than or equal to a preset number, it can be determined that the target second information that meets the second quantity condition exists in all the obtained second information. Alternatively, if the ratio between the number of target second information and the number of all second information is greater than or equal to a preset ratio threshold, it can be determined that the target second information that meets the second quantity condition exists in all the obtained second information.

[0103] When there is target second information satisfying the second quantity condition among all the obtained second information, the target device or target program can be adjusted from the first state to the second state. For example, the target device or target program can be adjusted from an unusable locked state to a usable unlocked state.

[0104] In a possible implementation, if the second information and the third information do not satisfy the matching condition, the third state of the target object is determined; the third state includes any one of the following: the third state is the same as the first state; the target application or the target device cannot be operated in the third state.

[0105] In the present disclosure, the third state may be a locked state in which the login interface is maintained, or the third state may be a locked state in which the login interface is not displayed, or the third state may be an alarm state.

[0106] Take the scenario of a user logging in to a computer for authentication as an example. If the user's answer to the first round of authentication questions does not meet the matching condition with the standard answer given by the computer, that is, the user authentication fails, the computer can still maintain the login interface and be locked, and the user can continue the next round of authentication requests.

[0107] If the user fails authentication in the specified rounds, the computer will no longer display the login interface and will be locked. The user can continue authentication after a preset time period, which can be set to 5 minutes or 10 minutes, etc.

[0108] If the user fails authentication in the specified rounds and triggers a new authentication operation, the computer can be in an alarm state, warning the user to continue authentication after a preset time period or sending an alarm signal to reflect that an illegal user is using the device.

[0109] In a possible implementation, the application data or device data includes one or more of registration information, operation information, and running information for a target application or target device within a target time.

[0110] In the present disclosure, the registration information of the target device may include information such as the device identification, user name, registration time, device type, and device operating system. The registration information of the target application may include information such as the user name, registration time, and application version. The operation information of the target device may include historical operation behavior information and device resource usage information, and the operation information of the target application may include information such as the user's historical operation behavior information and application logs. The operation information of the target application may include application startup time and memory usage information, and the operation information of the device may include device startup time, network status, and memory usage information.

[0111] By adopting the information processing method disclosed in the present invention, the first information can be generated by processing the application data or device data through the target model. Since the first information is not fixed, it can change with the change of the application data or device data, and can also change based on the change of one or more previous first information. The first information can timely reflect the situation of the target object, and the second state of the target object can be determined by using the second information and the third information corresponding to the first information to achieve unlocking of the target object, which has higher security and better user experience.

[0112] Based on the same concept, according to the information processing method provided by the above embodiment of the present disclosure, correspondingly, another embodiment of the present disclosure further provides an information processing device, whose structural schematic diagram is shown in FIG. Figure 4As shown, specifically including:

[0113] A first information processing module 401 is used to respond to a target object obtaining a target request in a first state and output first information; the target object includes a target application or a target device, and the first information is generated by a target model based on application data or device data;

[0114] A second information processing module 402, configured to obtain second information, where the second information includes input information for the first information;

[0115] The state determination module 403 is used to determine a second state of the target object based on the second information; the first state is different from the second state.

[0116] The information processing device disclosed in the present invention is used to respond to the target object obtaining a target request in the first state, output the first information, the target object includes a target application or a target device, the first information is generated by the target model based on the application data or the device data, and the second information is obtained. The second information includes input information for the first information, and the second state of the target object is determined based on the second information, and the first state is different from the second state. The first information can be generated by processing the application data or the device data by the target model, the first information is not fixed, and the first information can change with the change of the application data or the device data. The first information can timely reflect the data change of the target object, and the second state of the target object is determined by using the second information obtained by the first information that can reflect the data change of the target object, which is more secure for the target object.

[0117] In one possible implementation, the state determination module 403 is specifically used to determine the second state of the target object if the second information and the third information meet a matching condition; the target application or the target device can operate normally in the second state; the third information is generated by the target model based on the target data and the first information, and the first information and the third information have a corresponding relationship.

[0118] In one possible implementation, the state determination module 403 is further used to parse the second information and the third information to obtain corresponding semantic features; if the semantic features have a matching relationship, it is determined that the matching condition is satisfied.

[0119] In one possible implementation, the state determination module 403 is further configured to output new first information, obtain new second information, and determine the second state of the target object based on all the first information and all the second information.

[0120] In one possible implementation, the state determination module 403 is specifically used to determine if all the first information satisfies the first quantity condition; the output order of the first information is related to the reference data and / or information complexity of the model when generating the information;

[0121] The output of new first information is stopped, and the second state of the target object is determined based on all the second information.

[0122] In one possible implementation, the new first information is generated by the target model based on the previous one or more second information, and the application data or the device data.

[0123] In one possible implementation, the state determination module 403 is also used to stop generating and outputting new first information and determine the second state of the target object if there is target second information that meets the second quantity condition among all the second information obtained; the target second information is the second information that meets the matching condition with the corresponding third information.

[0124] In one embodiment, the state determination module 403 is also used to determine the third state of the target object if the second information and the third information do not meet the matching conditions; the third state includes any one of the following: the third state is the same as the first state; the target application or the target device cannot be operated in the third state.

[0125] In one possible implementation, the application data or device data includes one or more of registration information, operation information, and running information for a target application or target device within a target time.

[0126] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device and a readable storage medium.

[0127] Figure 5 A schematic block diagram of an example electronic device 500 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0128] like Figure 5As shown, the device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 502 or a computer program loaded from a storage unit 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the device 500 can also be stored. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output (I / O) interface 505 is also connected to the bus 504.

[0129] A number of components in the device 500 are connected to the I / O interface 505, including: an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a disk, an optical disk, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0130] The computing unit 501 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 501 performs the various methods and processes described above, such as information processing methods. For example, in some embodiments, the information processing method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 508. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 500 via ROM 502 and / or communication unit 509. When the computer program is loaded into RAM 503 and executed by the computing unit 501, one or more steps of the information processing method described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to perform the information processing method in any other appropriate manner (e.g., by means of firmware).

[0131] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), integrated systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0132] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0133] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0134] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0135] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0136] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0137] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0138] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the present disclosure, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0139] The above is only a specific embodiment of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present disclosure, which should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. An information processing method, comprising: In response to the target object obtaining a target request in a first state, outputting first information; The target object includes a target application or a target device, and the first information is generated by a target model based on application data or device data; obtaining second information, wherein the second information includes input information for the first information; Based on the second information, a second state of the target object is determined; the first state is different from the second state.

2. The method according to claim 1, determining the second state of the target object based on the second information, comprising: If the second information and the third information meet a matching condition, determining a second state of the target object; The target application or the target device can operate normally in the second state; The third information is generated by a target model based on target data and the first information, and the first information has a corresponding relationship with the third information.

3. The method according to claim 2, further comprising: parsing the second information and the third information to obtain corresponding semantic features; If the semantic features have a matching relationship, it is determined that the matching condition is satisfied.

4. The method according to claim 2, after obtaining the second information, the method further comprises: Output new first information and obtain new second information; Based on all of the first information and all of the second information, a second state of the target object is determined.

5. The method according to claim 4, determining the second state of the target object based on all the first information and all the second information, comprising: If all the first information meets the first quantity condition; The output order of the first information is related to the reference data and / or information complexity of the model when generating the information; The output of new first information is stopped, and the second state of the target object is determined based on all the second information.

6. The method according to claim 4, further comprising: The new first information is generated by the target model based on the previous one or more second information and the application data or the device data.

7. The method according to claim 4, further comprising: If there is target second information satisfying the second quantity condition among all the obtained second information, stop generating and outputting new first information, and determine the second state of the target object; The target second information is the second information that satisfies a matching condition with the corresponding third information.

8. The method according to any one of claims 1 to 7, further comprising: If the second information and the third information do not satisfy a matching condition, determining a third state of the target object; The third state includes any of the following: The third state is the same as the first state; The target application or the target device cannot be operated in the third state.

9. The method according to any one of claims 1 to 7, wherein the application data or device data comprises one or more of registration information, operation information, and running information for a target application or target device within a target time.

10. An information processing device, comprising: A first information processing module, configured to respond to a target object obtaining a target request in a first state and output first information; The target object includes a target application or a target device, and the first information is generated by a target model based on application data or device data; A second information processing module, used to obtain second information, where the second information includes input information for the first information; A state determination module is used to determine a second state of the target object based on the second information; the first state is different from the second state.

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