Methods, devices, electronic equipment and storage media for generating control information

Abstract

This application relates to a method, apparatus, electronic device, and storage medium for generating control information. The method includes: acquiring target control information, wherein the target control information includes first device information and first operation information, the first device information representing a target device, and the first operation information representing a target operation on the target device; determining target information from the first device information and the first operation information, wherein the target information is used to generate associative control information based on the target control information; and generating the associative control information based on the target information. Therefore, even when a user is unfamiliar with the device's control methods, associative control information can be generated based on the target information determined from the first device information and the first operation information included in the target control information, thereby helping and guiding the user to control the device, reducing the number of operations required by the user, and improving the user's control efficiency.

Description

Technical Field

[0001] This application relates to the field of the Internet of Things, and more particularly to a method, apparatus, electronic device, and storage medium for generating control information. Background Technology

[0002] Currently, the Internet of Things (IoT) is developing rapidly, but this rapid technological advancement has not translated into widespread user adoption. Many users are unfamiliar with how to control IoT devices. For example, in scenarios where users control devices via voice, if they are unfamiliar with the control methods, they may need to input voice commands multiple times to achieve the desired control, resulting in low efficiency in user control.

[0003] It is evident that improving user control efficiency when users are unfamiliar with the device's control methods is a technical issue worthy of attention. Summary of the Invention

[0004] In view of this, in order to solve some or all of the above-mentioned technical problems, embodiments of this application provide a method, apparatus, electronic device and storage medium for generating control information.

[0005] In a first aspect, embodiments of this application provide a method for generating control information, the method comprising:

[0006] Acquire target control information, wherein the target control information includes first device information and first operation information, the first device information representing a target device, and the first operation information representing a target operation on the target device;

[0007] Target information is determined from the first device information and the first operation information, wherein the target information is used to generate associative control information for the target control information;

[0008] Based on the target information, the associative control information is generated.

[0009] In one possible implementation, determining the target information from the first device information and the first operation information includes:

[0010] The first device information is identified as the target information; and

[0011] The generation of the associative control information based on the target information includes:

[0012] From a pre-constructed first knowledge graph, determine the second device information of the associated devices of the target device represented by the first device information, wherein the nodes of the first knowledge graph represent device information and the edges of the first knowledge graph represent the degree of association between the two devices;

[0013] Based on the second device information, the association control information is generated.

[0014] In one possible implementation, generating the association control information based on the second device information includes:

[0015] Determine a first quantity of the second device information identified from the first knowledge graph;

[0016] Based on the first quantity, the association control information is generated.

[0017] In one possible implementation, generating the association control information based on the first quantity includes:

[0018] If the first quantity is greater than the preset quantity, select the preset quantity of second device information from the first quantity of second device information;

[0019] The preset number of second device information items are combined with the first operation information to obtain the association control information.

[0020] In one possible implementation, generating the association control information based on the first quantity includes:

[0021] If the first quantity is less than the preset threshold, the second operation information of the associated operation of the target operation represented by the first operation information is determined from the pre-constructed second knowledge graph, wherein the nodes of the second knowledge graph represent operation information and the edges of the second knowledge graph represent the degree of association between the two operations.

[0022] Based on the second operation information, the association control information is generated.

[0023] In one possible implementation, generating the associative control information based on the second operation information includes:

[0024] For each determined piece of the second operation information, the second operation information is combined with the first number of pieces of the second device information to obtain the association control information.

[0025] In one possible implementation, determining the target information from the first device information and the first operation information includes:

[0026] The first operation information is determined as the target information; and

[0027] The generation of the associative control information based on the target information includes:

[0028] From a pre-constructed second knowledge graph, determine the second operation information of the associated operation of the target operation represented by the first operation information, wherein the nodes of the second knowledge graph represent operation information, and the edges of the second knowledge graph represent the degree of association between the two operations;

[0029] Based on the second operation information, the association control information is generated.

[0030] In one possible implementation, generating the associative control information based on the second operation information includes:

[0031] The second device information is combined with each of the generated second operation information to obtain the association control information.

[0032] In one possible implementation, determining the target information from the first device information and the first operation information includes:

[0033] Determine the control result information corresponding to the target control information, wherein the control result information indicates whether the target device has completed the target operation;

[0034] Based on the control result information, target information is determined from the first device information and the first operation information.

[0035] In one possible implementation, determining the target information from the first device information and the first operation information based on the control result information includes:

[0036] If the control result information indicates that the target device has not completed the target operation, influencing factor information is determined, wherein the influencing factor information represents the factors that cause the target device to fail to complete the target operation;

[0037] When the influencing factor information represents equipment factors, the first equipment information is determined as the target information;

[0038] When the influencing factor information represents operational factors, the first operational information is determined as the target information;

[0039] If the control result information indicates that the target device has completed the target operation, the first operation information is determined as the target information.

[0040] Secondly, embodiments of this application provide a control information generation apparatus, the apparatus comprising:

[0041] An acquisition unit is used to acquire target control information, wherein the target control information includes first device information and first operation information, the first device information representing a target device, and the first operation information representing a target operation on the target device;

[0042] The determining unit is configured to determine target information from the first device information and the first operation information, wherein the target information is used to generate associative control information of the target control information;

[0043] The generation unit is used to generate the associative control information based on the target information.

[0044] In one possible implementation, determining the target information from the first device information and the first operation information includes:

[0045] The first device information is identified as the target information; and

[0046] The generation of the associative control information based on the target information includes:

[0047] From a pre-constructed first knowledge graph, determine the second device information of the associated devices of the target device represented by the first device information, wherein the nodes of the first knowledge graph represent device information and the edges of the first knowledge graph represent the degree of association between the two devices;

[0048] Based on the second device information, the association control information is generated.

[0049] In one possible implementation, generating the association control information based on the second device information includes:

[0050] Determine a first quantity of the second device information identified from the first knowledge graph;

[0051] Based on the first quantity, the association control information is generated.

[0052] In one possible implementation, generating the association control information based on the first quantity includes:

[0053] If the first quantity is greater than the preset quantity, select the preset quantity of second device information from the first quantity of second device information;

[0054] The preset number of second device information items are combined with the first operation information to obtain the association control information.

[0055] In one possible implementation, generating the association control information based on the first quantity includes:

[0056] If the first quantity is less than the preset threshold, the second operation information of the associated operation of the target operation represented by the first operation information is determined from the pre-constructed second knowledge graph, wherein the nodes of the second knowledge graph represent operation information and the edges of the second knowledge graph represent the degree of association between the two operations.

[0057] Based on the second operation information, the association control information is generated.

[0058] In one possible implementation, generating the associative control information based on the second operation information includes:

[0059] For each determined piece of the second operation information, the second operation information is combined with the first number of pieces of the second device information to obtain the association control information.

[0060] In one possible implementation, determining the target information from the first device information and the first operation information includes:

[0061] The first operation information is determined as the target information; and

[0062] The generation of the associative control information based on the target information includes:

[0063] From a pre-constructed second knowledge graph, determine the second operation information of the associated operation of the target operation represented by the first operation information, wherein the nodes of the second knowledge graph represent operation information, and the edges of the second knowledge graph represent the degree of association between the two operations;

[0064] Based on the second operation information, the association control information is generated.

[0065] In one possible implementation, generating the associative control information based on the second operation information includes:

[0066] The second device information is combined with each of the generated second operation information to obtain the association control information.

[0067] In one possible implementation, determining the target information from the first device information and the first operation information includes:

[0068] Determine the control result information corresponding to the target control information, wherein the control result information indicates whether the target device has completed the target operation;

[0069] Based on the control result information, target information is determined from the first device information and the first operation information.

[0070] In one possible implementation, determining the target information from the first device information and the first operation information based on the control result information includes:

[0071] If the control result information indicates that the target device has not completed the target operation, influencing factor information is determined, wherein the influencing factor information represents the factors that cause the target device to fail to complete the target operation;

[0072] When the influencing factor information represents equipment factors, the first equipment information is determined as the target information;

[0073] When the influencing factor information represents operational factors, the first operational information is determined as the target information;

[0074] If the control result information indicates that the target device has completed the target operation, the first operation information is determined as the target information.

[0075] Thirdly, embodiments of this application provide an electronic device, including:

[0076] Memory, used to store computer programs;

[0077] A processor is configured to execute a computer program stored in the memory, and when the computer program is executed, to implement the method of any embodiment of the control information generation method of the first aspect of this application.

[0078] Fourthly, embodiments of this application provide a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the method of any embodiment of the control information generation method of the first aspect described above.

[0079] Fifthly, embodiments of this application provide a computer program comprising computer-readable code, which, when executed on a device, causes a processor in the device to implement the method of any embodiment of the control information generation method of the first aspect described above.

[0080] The control information generation method provided in this application can obtain target control information, wherein the target control information includes first device information and first operation information. The first device information represents a target device, and the first operation information represents a target operation on the target device. Then, target information is determined from the first device information and the first operation information, wherein the target information is used to generate associative control information of the target control information. Finally, the associative control information is generated based on the target information. Therefore, even when the user is unfamiliar with the device's control methods, associative control information can be generated based on the target information determined from the first device information and the first operation information included in the target control information. This helps and guides the user to control the device, reduces the number of operations required by the user, and improves the user's control efficiency. Attached Figure Description

[0081] Figure 1 A flowchart illustrating a method for generating control information provided in an embodiment of this application;

[0082] Figure 2 A flowchart illustrating another method for generating control information provided in an embodiment of this application;

[0083] Figure 3A A flowchart illustrating another method for generating control information provided in an embodiment of this application;

[0084] Figure 3B for Figure 3A A flowchart illustrating the process of determining objects based on knowledge graph A.

[0085] Figure 3C for Figure 3A A schematic diagram of the process for determining intent based on knowledge graph B;

[0086] Figure 4 This is a schematic diagram of the structure of a control information generation device provided in an embodiment of this application;

[0087] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0088] Various exemplary embodiments of this application will now be described in detail with reference to the accompanying drawings. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps set forth in these embodiments do not limit the scope of this application.

[0089] Those skilled in the art will understand that the terms "first" and "second" in the embodiments of this application are only used to distinguish different steps, devices or modules, and do not represent any specific technical meaning, nor do they indicate the logical order between them.

[0090] It should also be understood that in this embodiment, "multiple" can refer to two or more, and "at least one" can refer to one, two or more.

[0091] It should also be understood that any component, data or structure mentioned in the embodiments of this application can generally be understood as one or more unless explicitly defined or given contrary guidance in the context.

[0092] Furthermore, the term "and / or" in this application is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this application generally indicates that the preceding and following related objects have an "or" relationship.

[0093] It should also be understood that the description of the various embodiments in this application emphasizes the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described in detail.

[0094] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the scope of this application and its application or use.

[0095] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and equipment should be considered part of the specification.

[0096] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0097] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. To facilitate understanding of the embodiments of this application, the application will be described in detail below with reference to the accompanying drawings and embodiments. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0098] Figure 1 This is a flowchart illustrating a method for generating control information provided in an embodiment of this application.

[0099] like Figure 1 As shown, the method specifically includes:

[0100] Step 101: Obtain target control information, wherein the target control information includes first device information and first operation information, the first device information represents a target device, and the first operation information represents a target operation on the target device.

[0101] In this embodiment, the first device information may be the control information included in the target control information.

[0102] The first operational information can be the operational information included in the target control information.

[0103] The target device can be the device represented by the first device information.

[0104] The target operation can be the operation represented by the first operation information.

[0105] As an example, target control information can be a voice control command issued by the user. For instance, target control information could be the voice command "washing machine purifies the air." In this case, the target device represented by the first device information is "washing machine," and the target operation represented by the first operation information is "purify the air." As another example, target control information could be the voice command "turn on the air conditioner." In this case, the target device represented by the first device information is "air conditioner," and the target operation represented by the first operation information is "turn on."

[0106] Step 102: Determine target information from the first device information and the first operation information, wherein the target information is used to generate associative control information for the target control information.

[0107] In this embodiment, the first device information can be determined as the target information. Alternatively, the first operation information can be determined as the target information. Or, both the first device information and the first operation information can be determined as the target information.

[0108] Step 103: Generate the association control information based on the target information.

[0109] In this embodiment, when the first device information is determined to be the target information, the associative control information can be generated as follows: First, determine the operation information with the highest similarity (or correlation) to the first operation information from a pre-determined set of operation information. Then, combine the first device information and the determined operation information to obtain the associative control information.

[0110] When the first operation information is determined to be the target information, the associative control information can be generated as follows: First, determine the device information with the highest similarity (or correlation) to the first device information from a pre-determined set of device information. Then, combine the determined device information and the first operation information to obtain the associative control information.

[0111] When the first device information and the first operation information are identified as target information, the associative control information can be generated as follows: First, determine the operation information with the highest similarity (or correlation) to the first operation information from a pre-determined set of operation information, and determine the device information with the highest similarity (or correlation) to the first device information from a pre-determined set of device information. Then, combine the determined device information and the determined operation information to obtain the associative control information.

[0112] The similarity (or correlation) between two pieces of operational information in a predetermined set of operational information can be preset. Similarly, the similarity (or correlation) between two pieces of device information in a predetermined set of device information can also be preset.

[0113] Here, the number of association control information can be one or more.

[0114] Optionally, after performing step 103 above, the association control information can be displayed or played, or the association control information can be sent to the corresponding device to perform the corresponding operation.

[0115] In some optional implementations of this embodiment, step 102 can be performed as follows: the first operation information is determined as the target information.

[0116] Based on this, step 103 can also be performed in the following manner (including steps one and two) to generate the associative control information based on the target information:

[0117] Step 1: From the pre-constructed second knowledge graph, determine the second operation information of the associated operation of the target operation represented by the first operation information.

[0118] In this context, the nodes of the second knowledge graph represent operation information, and the edges of the second knowledge graph represent the degree of association between two operations.

[0119] The degree of association information represented by the edges in the second knowledge graph can be numerically represented. For example, a larger numerical value indicates a higher degree of association between the operations indicated by the two operation information represented by the two nodes connected by the edge.

[0120] As an example, two nodes in the second knowledge graph can represent the operation information "on" and "off" respectively. The edge connecting the two nodes can represent the degree of association between "on" and "off". For example, the edge connecting the two nodes can represent the degree of association information "10". As another example, two nodes in the second knowledge graph can represent the operation information "on" and "heating up" respectively. The edge connecting the two nodes can represent the degree of association between "on" and "heating up". For example, the edge connecting the two nodes can represent the degree of association information "5".

[0121] In some cases, the number of second operation information points determined from a pre-constructed second knowledge graph can be a fixed value. Alternatively, the degree of correlation between the operation indicated by the second operation information determined from the pre-constructed second knowledge graph and the operation indicated by the aforementioned first operation information can be greater than a preset value.

[0122] Step two: Based on the second operation information, generate the association control information.

[0123] As an example, the device information with the highest similarity (or correlation) to the first device information can be identified first from a pre-defined set of device information. Then, the identified device information and the second operation information are combined to obtain the associative control information.

[0124] It is understood that, among the above-mentioned optional implementation methods, associative control information can be generated based on the second operation information determined from the pre-constructed second knowledge graph, thereby improving the correlation between the generated associative control information and the target control information. When using the generated associative control information to control the device, the control of the device can be more in line with the user's expectations, thereby improving the control efficiency of the device.

[0125] In some application scenarios of the above optional implementation methods, step two can be performed in the following way to generate the associative control information based on the second operation information:

[0126] The second device information is combined with each of the generated second operation information to obtain the association control information.

[0127] Therefore, the number of associative control information obtained can be equal to the number of second operation information.

[0128] It is understood that in the above application scenarios, each piece of associative control information obtained includes the second device information and the second operation information, thereby improving the correlation between the generated associative control information and the target control information. When using the generated associative control information to control the device, the control of the device can better meet the user's expectations, thereby improving the control efficiency of the device.

[0129] In some optional implementations of this embodiment, step 102 can be performed in the following manner (including step one and step two) to determine the target information from the first device information and the first operation information:

[0130] Step 1: Determine the control result information corresponding to the target control information.

[0131] The control result information indicates whether the target device has completed the target operation. For example, the control result information may indicate whether the target device has successfully executed the target operation.

[0132] Step two: Based on the control result information, determine the target information from the first device information and the first operation information.

[0133] As an example, if the control result information indicates that the target device has completed the target operation, the first device information can be identified as the target information. Subsequently, the following text regarding... Figure 2 The association control information is generated in the manner described in the corresponding embodiments. Please refer to the following description for details, which will not be repeated here.

[0134] As another example, when the control result information indicates that the target device has not completed the target operation, the influencing factor information of the target device's failure to complete the target operation can be determined first. Here, the influencing factor information represents the factors affecting the target device's failure to complete the target operation. If the influencing factor information indicates a device factor, the first device information is determined as the target information. If the influencing factor information indicates an operational factor, the first operational information is determined as the target information. If the control result information indicates that the target device has completed the target operation, the first operational information is determined as the target information.

[0135] It is understood that, among the above optional implementation methods, the target information can be determined from the first device information and the first operation information based on the control result information corresponding to the target control information. In this way, different methods can be used to generate the target information for different control result information.

[0136] In some application scenarios of the above-mentioned optional implementation methods, step two can be performed in the following way to determine the target information from the first device information and the first operation information based on the control result information:

[0137] First, if the control result information indicates that the target device has not completed the target operation, then influencing factor information is determined. This influencing factor information represents the factors that caused the target device to fail to complete the target operation.

[0138] Subsequently, if the influencing factor information represents equipment factors, the first equipment information is determined as the target information.

[0139] Then, if the influencing factor information represents operational factors, the first operational information is determined as the target information.

[0140] It is understandable that in the above application scenario, by using different methods to determine the target information based on different influencing factors when the control result information indicates that the target device has not completed the target operation, the correlation between the generated associative control information and the target control information is improved. When using the generated associative control information to control the device, the control of the device can be more in line with the user's expectations, thereby improving the control efficiency of the device.

[0141] In some of the above application scenarios, when the control result information indicates that the target device has completed the target operation, the first operation information can also be determined as the target information.

[0142] It is understood that, under the above circumstances, when the control result information indicates that the target device has completed the target operation, by determining the first operation information as the target information and then using the target information to generate associative control information, the user's familiarity with device control can be improved, thereby improving the user's subsequent control efficiency of the device and increasing the user's frequency of device use.

[0143] The control information generation method provided in this application can obtain target control information, wherein the target control information includes first device information and first operation information. The first device information represents a target device, and the first operation information represents a target operation on the target device. Then, target information is determined from the first device information and the first operation information, wherein the target information is used to generate associative control information of the target control information. Finally, the associative control information is generated based on the target information. Therefore, even when the user is unfamiliar with the device's control methods, associative control information can be generated based on the target information determined from the first device information and the first operation information included in the target control information. This helps and guides the user to control the device, reduces the number of operations required by the user, and improves the user's control efficiency.

[0144] Figure 2 This is a flowchart illustrating another method for generating control information provided in an embodiment of this application. Figure 2 As shown, the method specifically includes:

[0145] Step 201: Obtain target control information, wherein the target control information includes first device information and first operation information, the first device information represents a target device, and the first operation information represents a target operation on the target device.

[0146] In this embodiment, step 201 and Figure 1 Step 101 in the corresponding embodiment is basically the same, and will not be repeated here.

[0147] Step 202: Determine the first device information as the target information.

[0148] Step 203: Determine the second device information of the associated devices of the target device represented by the first device information from the pre-constructed first knowledge graph, wherein the nodes of the first knowledge graph represent device information and the edges of the first knowledge graph represent the degree of association between the two devices.

[0149] In this embodiment, the association information represented by the edges of the first knowledge graph can be numerically represented. For example, a larger numerical value indicates a higher degree of association between the devices indicated by the two device information represented by the two nodes connected by the edge.

[0150] As an example, two nodes in the first knowledge graph can represent device information "air conditioner" and device information "electric fan," respectively. The edge connecting the two nodes can represent the degree of association between "air conditioner" and "electric fan." For example, the edge connecting the two nodes can represent the degree of association information "10." As another example, two nodes in the first knowledge graph can represent device information "air conditioner" and device information "refrigerator," respectively. The edge connecting the two nodes can represent the degree of association between "air conditioner" and "refrigerator." For example, the edge connecting the two nodes can represent the degree of association information "5."

[0151] In some cases, the number of second device information points determined from the pre-built first knowledge graph can be a fixed value. Alternatively, the degree of association between the device indicated by the second device information determined from the pre-built first knowledge graph and the device indicated by the aforementioned first device information can be greater than a preset value.

[0152] Step 204: Generate the association control information based on the second device information.

[0153] In this embodiment, the operation information with the highest similarity (or correlation) to the first operation information from a pre-determined set of operation information can be determined first. Then, the determined operation information and the second device information are combined to obtain the associative control information.

[0154] In some optional implementations of this embodiment, step 204 can be performed in the following manner to generate the association control information based on the second device information:

[0155] Step 1: Determine the first quantity of the second device information identified from the first knowledge graph.

[0156] The first quantity may be the number of the second device information determined from the first knowledge graph.

[0157] Step two: Based on the first quantity, generate the association control information.

[0158] The specific execution method of step two above can be found in the following description, and will not be repeated here.

[0159] It is understandable that, among the above optional implementation methods, different methods can be used to generate associative control information based on different initial quantities.

[0160] In some application scenarios of the above optional implementation methods, step two can be performed in the following way to generate the association control information based on the first quantity:

[0161] The first step is to select the preset number of second device information from the first number of second device information if the first number is greater than the preset number.

[0162] As an example, a preset number of second device information items can be randomly selected from the first number of second device information items, or the preset number of second device information items can be selected from the first number of second device information items in descending order of relevance.

[0163] The second step is to combine the preset number of second device information items with the first operation information to obtain the association control information.

[0164] Therefore, the number of associative control information obtained can be a preset number.

[0165] It is understood that in the above application scenario, each piece of associative control information obtained includes the second device information and the first operation information, thereby improving the correlation between the generated associative control information and the target control information. When using the generated associative control information to control the device, the control of the device can better meet the user's expectations, thereby improving the control efficiency of the device.

[0166] In some application scenarios of the above optional implementation methods, step two can also be performed in the following way to generate the association control information based on the first quantity:

[0167] The first step involves determining, from a pre-constructed second knowledge graph, the second operation information of the associated operations of the target operation represented by the first operation information, when the first quantity is less than the preset threshold. Nodes in the second knowledge graph represent operation information, and edges in the second knowledge graph represent the degree of association between the two operations.

[0168] In this context, the nodes of the second knowledge graph represent operation information, and the edges of the second knowledge graph represent the degree of association between two operations.

[0169] The degree of association information represented by the edges in the second knowledge graph can be numerically represented. For example, a larger numerical value indicates a higher degree of association between the operations indicated by the two operation information represented by the two nodes connected by the edge.

[0170] As an example, two nodes in the second knowledge graph can represent the operation information "on" and "off" respectively. The edge connecting the two nodes can represent the degree of association between "on" and "off". For example, the edge connecting the two nodes can represent the degree of association information "10". As another example, two nodes in the second knowledge graph can represent the operation information "on" and "heating up" respectively. The edge connecting the two nodes can represent the degree of association between "on" and "heating up". For example, the edge connecting the two nodes can represent the degree of association information "5".

[0171] In some cases, the number of second operation information points determined from a pre-constructed second knowledge graph can be a fixed value. Alternatively, the degree of correlation between the operation indicated by the second operation information determined from the pre-constructed second knowledge graph and the operation indicated by the aforementioned first operation information can be greater than a preset value.

[0172] The second step is to generate the association control information based on the second operation information.

[0173] As an example, the device information with the highest similarity (or correlation) to the first device information can be identified first from a pre-defined set of device information. Then, the identified device information and the second operation information are combined to obtain the associative control information.

[0174] It is understandable that in the above application scenarios, associative control information can be generated based on the second operation information determined from the pre-constructed second knowledge graph, thereby improving the correlation between the generated associative control information and the target control information. When using the generated associative control information to control the device, the control of the device can be more in line with the user's expectations, thereby improving the control efficiency of the device.

[0175] In some of the above application scenarios, the second step can be performed in the following way to generate the associative control information based on the second operation information:

[0176] For each determined piece of the second operation information, the second operation information is combined with the first number of pieces of the second device information to obtain the association control information.

[0177] It is understandable that, under the above circumstances, the number of associative control information obtained can be the product of the number of determined second operation information and the first number. Therefore, by increasing the number of generated associative control information, the user's familiarity with device control can be improved, thereby improving the control efficiency of the device and increasing the frequency of user use of the device.

[0178] It should be noted that, in addition to the contents described above, this embodiment may also include... Figure 1 The corresponding technical features described in the corresponding embodiments, thereby achieving Figure 1 For details on the technical effects of the control information generation method shown, please refer to [link / reference]. Figure 1 The relevant descriptions are presented concisely and will not be elaborated upon here.

[0179] The control information generation method provided in this application can generate associative control information based on the second device information determined from the pre-constructed first knowledge graph, thereby improving the correlation between the generated associative control information and the target control information. When using the generated associative control information to control the device, the control of the device can better meet the user's expectations, thereby improving the control efficiency of the device.

[0180] Figure 3A This is a flowchart illustrating another method for generating control information provided in an embodiment of this application. This method can be applied to one or more electronic devices such as smartphones, laptops, desktop computers, portable computers, and servers. Furthermore, the executing entity of this method can be hardware or software. When the executing entity is hardware, it can be one or more of the aforementioned electronic devices. For example, a single electronic device can execute this method, or multiple electronic devices can cooperate with each other to execute this method. When the executing entity is software, this method can be implemented as multiple software programs or software modules, or as a single software program or software module. No specific limitations are made here.

[0181] The embodiments of this application are described below by way of example. However, it should be noted that the embodiments of this application may have the features described below, but the following description does not constitute a limitation on the protection scope of the embodiments of this application.

[0182] Specifically, such as Figure 3A As shown, this method constructs an object-related knowledge graph A (i.e., the first knowledge graph mentioned above) and an object intent-related knowledge graph B (i.e., the second knowledge graph mentioned above). The construction of the knowledge graphs will not be described in detail here, but will be used directly.

[0183] This example uses voice-activated air conditioning control. In each voice control interaction (e.g., the target control information mentioned above), the system analyzes the target device (which device, such as the target device or the device indicated by the device information) and the user's intent (what to do, i.e., the target operation or the operation indicated by the operation information). The voice service then sends the voice control command to the corresponding device (i.e., the target device) and provides feedback on the processing result (success / failure, and the reason for failure, i.e., the control result information). Afterwards, analysis is performed based on the control result; the target device and intent obtained above will be used subsequently.

[0184] Figure 3A In this context, N represents the number of associated words (i.e., the aforementioned association control information) that we want to output (i.e., the aforementioned preset threshold); a represents the number of objects with high relevance to the current object (i.e., the aforementioned target device) retrieved from the object-related knowledge graph (i.e., the aforementioned first knowledge graph) each time; b represents the number of objects with high relevance to the current intent retrieved from the intent-related knowledge graph (i.e., the aforementioned second knowledge graph) each time. This ensures that N associated words are ultimately obtained.

[0185] The control result (i.e., the control result information mentioned above) indicates whether the control was successful (i.e., whether the target device completed the target operation). If the control was successful, first consider b intentions (an array sorted from highest to lowest correlation) related to the same object (i.e., the target device). Determine if b < N. If b ≥ N, combine the N intentions (the N most correlated among the b intentions) with the current object to generate N related words. If b < N is not yet satisfied, proceed to A (i.e., the first knowledge graph mentioned above). Based on the object association knowledge graph, obtain a objects (an array sorted from highest to lowest correlation), and combine each of the a objects with b intentions. If the logic is correct (the logic of a sentence), they can be combined into related words. These are accumulated sequentially until N related words are reached, satisfying the requirement.

[0186] If control fails, the cause can be analyzed, which can be mainly divided into three factors: object factors (i.e., the equipment factors mentioned above), unrecognized intent (i.e., the operational factors mentioned above), and others.

[0187] If the factor is "object not found," for voice-activated air conditioners, it could be due to factors such as the device being offline or the device not being found. In this case, the relevant online devices can be found by associating object A with a knowledge graph, and related keywords can be generated based on the intent.

[0188] If the factor is that the intent is not recognized, then for voice-activated air conditioners, different air conditioners may support different control skills or not support the current intent function, etc. We can use the intent-related knowledge graph of object B to find other related supporting intents under the same object, and generate associated words in combination with the object.

[0189] If the factor is otherwise, no object or intent may be identified, and the conversation will fall into small talk. Normal chat-related suggested words can be recommended, but voice control-related suggested words will not be recommended.

[0190] Among them, knowledge graph A, also known as the first knowledge graph mentioned above, can determine objects through the following process: Figure 3B As shown; Knowledge Graph B, also known as the second knowledge graph mentioned above, has the following process for determining intent: Figure 3C As shown in the diagram. Here, since the devices installed in each household are different, a knowledge graph A and a knowledge graph B can be constructed for each household. The knowledge graph A constructed for different households can be different, and the knowledge graph B constructed for different households can also be different. The nodes of knowledge graph A can represent the devices installed in a single household, such as IoT devices that are online in a single household.

[0191] It should be noted that, in addition to the contents described above, this embodiment may also include the technical features described in the above embodiments, thereby achieving the technical effect of the control information generation method shown above. Please refer to the above description for details. For the sake of brevity, it will not be elaborated here.

[0192] The control information generation method provided in this application recommends related words to the user based on three aspects: the object, intent, and control result of the user's voice control. Depending on the result, the user's intent and the targeted object can be comprehensively analyzed, and different methods can be used to generate related words, ultimately obtaining a combination of the relevant object and intent. Based on this information, the generated related words are displayed to the user, who can refer to them for dialogue interaction, improving the user's usability. This can help users solve problems such as incomplete functionality and complex dialogue in voice product control, recommending usable dialogue based on the user's control, thus improving the user experience.

[0193] Figure 4 This is a schematic diagram of the structure of a control information generation device provided in an embodiment of this application.

[0194] Specifically, it includes:

[0195] The acquisition unit 401 is used to acquire target control information, wherein the target control information includes first device information and first operation information, the first device information represents a target device, and the first operation information represents a target operation on the target device;

[0196] The determining unit 402 is configured to determine target information from the first device information and the first operation information, wherein the target information is used to generate associative control information of the target control information;

[0197] The generation unit 403 is used to generate the association control information based on the target information.

[0198] In one possible implementation, determining the target information from the first device information and the first operation information includes:

[0199] The first device information is identified as the target information; and

[0200] The generation of the associative control information based on the target information includes:

[0201] From a pre-constructed first knowledge graph, determine the second device information of the associated devices of the target device represented by the first device information, wherein the nodes of the first knowledge graph represent device information and the edges of the first knowledge graph represent the degree of association between the two devices;

[0202] Based on the second device information, the association control information is generated.

[0203] In one possible implementation, generating the association control information based on the second device information includes:

[0204] Determine a first quantity of the second device information identified from the first knowledge graph;

[0205] Based on the first quantity, the association control information is generated.

[0206] In one possible implementation, generating the association control information based on the first quantity includes:

[0207] If the first quantity is greater than the preset quantity, select the preset quantity of second device information from the first quantity of second device information;

[0208] The preset number of second device information items are combined with the first operation information to obtain the association control information.

[0209] In one possible implementation, generating the association control information based on the first quantity includes:

[0210] If the first quantity is less than the preset threshold, the second operation information of the associated operation of the target operation represented by the first operation information is determined from the pre-constructed second knowledge graph, wherein the nodes of the second knowledge graph represent operation information and the edges of the second knowledge graph represent the degree of association between the two operations.

[0211] Based on the second operation information, the association control information is generated.

[0212] In one possible implementation, generating the associative control information based on the second operation information includes:

[0213] For each determined piece of the second operation information, the second operation information is combined with the first number of pieces of the second device information to obtain the association control information.

[0214] In one possible implementation, determining the target information from the first device information and the first operation information includes:

[0215] The first operation information is determined as the target information; and

[0216] The generation of the associative control information based on the target information includes:

[0217] From a pre-constructed second knowledge graph, determine the second operation information of the associated operation of the target operation represented by the first operation information, wherein the nodes of the second knowledge graph represent operation information, and the edges of the second knowledge graph represent the degree of association between the two operations;

[0218] Based on the second operation information, the association control information is generated.

[0219] In one possible implementation, generating the associative control information based on the second operation information includes:

[0220] The second device information is combined with each of the generated second operation information to obtain the association control information.

[0221] In one possible implementation, determining the target information from the first device information and the first operation information includes:

[0222] Determine the control result information corresponding to the target control information, wherein the control result information indicates whether the target device has completed the target operation;

[0223] Based on the control result information, target information is determined from the first device information and the first operation information.

[0224] In one possible implementation, determining the target information from the first device information and the first operation information based on the control result information includes:

[0225] If the control result information indicates that the target device has not completed the target operation, influencing factor information is determined, wherein the influencing factor information represents the factors that cause the target device to fail to complete the target operation;

[0226] When the influencing factor information represents equipment factors, the first equipment information is determined as the target information;

[0227] When the influencing factor information represents operational factors, the first operational information is determined as the target information;

[0228] If the control result information indicates that the target device has completed the target operation, the first operation information is determined as the target information.

[0229] The control information generation device provided in this embodiment can be as follows: Figure 4 The control information generation device shown can execute all the steps of the control information generation methods described above, thereby achieving the technical effects of the control information generation methods described above. For details, please refer to the relevant descriptions above. For the sake of brevity, it will not be elaborated here.

[0230] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 5 The illustrated electronic device 500 includes at least one processor 501, a memory 502, at least one network interface 504, and other user interfaces 503. The various components in the electronic device 500 are coupled together via a bus system 505. It is understood that the bus system 505 is used to implement communication between these components. In addition to a data bus, the bus system 505 also includes a power bus, a control bus, and a status signal bus. However, for clarity, ... Figure 5 The general designated all buses as Bus System 505.

[0231] The user interface 503 may include a display, keyboard, or clicking device (e.g., mouse, trackball, touchpad, or touchscreen).

[0232] It is understood that the memory 502 in the embodiments of this application can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of RAM are available, such as Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced Synchronous DRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory 502 described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0233] In some implementations, memory 502 stores elements, executable units or data structures, or subsets thereof, or extended sets thereof: operating system 5021 and application program 5022.

[0234] The operating system 5021 includes various system programs, such as the framework layer, core library layer, and driver layer, used to implement various basic business functions and handle hardware-based tasks. The application program 5022 includes various applications, such as a media player and a browser, used to implement various application functions. Programs implementing the methods of this application embodiment can be included in application program 5022.

[0235] In this embodiment, by calling the program or instructions stored in memory 502, specifically the program or instructions stored in application program 5022, processor 501 executes the method steps provided in each method embodiment, including, for example:

[0236] Acquire target control information, wherein the target control information includes first device information and first operation information, the first device information representing a target device, and the first operation information representing a target operation on the target device;

[0237] Target information is determined from the first device information and the first operation information, wherein the target information is used to generate associative control information for the target control information;

[0238] Based on the target information, the associative control information is generated.

[0239] The methods disclosed in the embodiments of this application can be applied to or implemented by processor 501. Processor 501 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in processor 501 or by instructions in the form of software. The processor 501 may be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this application. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this application can be directly embodied in the execution of a hardware decoding processor, or executed by a combination of hardware and software units in the decoding processor. The software units may be located in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. The storage medium is located in memory 502. Processor 501 reads the information in memory 502 and, in conjunction with its hardware, completes the steps of the above method.

[0240] It is understood that the embodiments described herein can be implemented in hardware, software, firmware, middleware, microcode, or a combination thereof. For hardware implementation, the processing unit can be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers, microprocessors, other electronic units for performing the functions described above in this application, or combinations thereof.

[0241] For software implementation, the techniques described herein can be implemented by units that perform the functions described above. The software code can be stored in memory and executed by a processor. The memory can be implemented within the processor or external to the processor.

[0242] The electronic device provided in this embodiment may be as follows: Figure 5 The electronic device shown can execute all the steps of the above-described methods for generating control information, thereby achieving the technical effects of the above-described methods for generating control information. For details, please refer to the above descriptions. For the sake of brevity, further details are omitted here.

[0243] This application also provides a storage medium (computer-readable storage medium). This storage medium stores one or more programs. The storage medium may include volatile memory, such as random access memory; it may also include non-volatile memory, such as read-only memory, flash memory, hard disk, or solid-state drive; and it may also include combinations of the above types of memory.

[0244] When one or more programs in the storage medium can be executed by one or more processors to implement the above-described method for generating control information executed on the electronic device side.

[0245] The processor described above is used to execute a program for generating control information stored in memory, in order to implement the following steps of a control information generation method executed on the electronic device side:

[0246] Acquire target control information, wherein the target control information includes first device information and first operation information, the first device information representing a target device, and the first operation information representing a target operation on the target device;

[0247] Target information is determined from the first device information and the first operation information, wherein the target information is used to generate associative control information for the target control information;

[0248] Based on the target information, the associative control information is generated.

[0249] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0250] The steps of the methods or algorithms described in conjunction with the embodiments disclosed herein can be implemented in hardware, a software module executed by a processor, or a combination of both. The software module can be located in random access memory (RAM), main memory, read-only memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, removable disk, CD-ROM, or any other form of storage medium known in the art.

[0251] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of this application. It should be understood that the above descriptions are merely specific embodiments of this application and are not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this application should be included within the scope of protection of this application. Furthermore, for the foregoing embodiments, for the sake of simplicity, they are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to the present invention.

Claims

1. A method for generating control information, characterized in that, The method includes: Acquire target control information, wherein the target control information includes first device information and first operation information, the first device information representing a target device, and the first operation information representing a target operation on the target device; Target information is determined from the first device information and the first operation information, wherein the target information is used to generate associative control information for the target control information; Based on the target information, the associative control information is generated; Determining the target information from the first device information and the first operation information includes: Determine the control result information corresponding to the target control information, wherein the control result information indicates whether the target device has completed the target operation; Based on the control result information, target information is determined from the first device information and the first operation information; The step of determining the target information from the first device information and the first operation information based on the control result information includes: If the control result information indicates that the target device has not completed the target operation, influencing factor information is determined, wherein the influencing factor information represents the factors that cause the target device to fail to complete the target operation; When the influencing factor information represents equipment factors, the first equipment information is determined as the target information; When the influencing factor information represents operational factors, the first operational information is determined as the target information.

2. The method according to claim 1, characterized in that, Determining the target information from the first device information and the first operation information includes: The first device information is identified as the target information; and The generation of the associative control information based on the target information includes: From a pre-constructed first knowledge graph, determine the second device information of the associated devices of the target device represented by the first device information, wherein the nodes of the first knowledge graph represent device information and the edges of the first knowledge graph represent the degree of association between the two devices; Based on the second device information, the association control information is generated.

3. The method according to claim 2, characterized in that, The step of generating the association control information based on the second device information includes: Determine a first quantity of the second device information identified from the first knowledge graph; Based on the first quantity, the association control information is generated.

4. The method according to claim 3, characterized in that, The generation of the association control information based on the first quantity includes: If the first quantity is greater than the preset quantity, select the preset quantity of second device information from the first quantity of second device information; The preset number of second device information items are combined with the first operation information to obtain the association control information.

5. The method according to claim 3, characterized in that, The generation of the association control information based on the first quantity includes: If the first quantity is less than a preset threshold, the second operation information of the associated operation of the target operation represented by the first operation information is determined from the pre-constructed second knowledge graph, wherein the nodes of the second knowledge graph represent operation information and the edges of the second knowledge graph represent the degree of association between the two operations. Based on the second operation information, the association control information is generated.

6. The method according to claim 5, characterized in that, The generation of the associative control information based on the second operation information includes: For each determined piece of the second operation information, the second operation information is combined with the first number of pieces of the second device information to obtain the association control information.

7. The method according to claim 1, characterized in that, Determining the target information from the first device information and the first operation information includes: The first operation information is determined as the target information; and The generation of the associative control information based on the target information includes: From a pre-constructed second knowledge graph, determine the second operation information of the associated operation of the target operation represented by the first operation information, wherein the nodes of the second knowledge graph represent operation information, and the edges of the second knowledge graph represent the degree of association between the two operations; Based on the second operation information, the association control information is generated.

8. The method according to claim 7, characterized in that, The generation of the associative control information based on the second operation information includes: The second device information is combined with each of the generated second operation information to obtain the association control information.

9. The method according to claim 1, characterized in that, The step of determining the target information from the first device information and the first operation information based on the control result information includes: If the control result information indicates that the target device has completed the target operation, the first operation information is determined as the target information.

10. A control information generation device, characterized in that, The device includes: An acquisition unit is used to acquire target control information, wherein the target control information includes first device information and first operation information, the first device information representing a target device, and the first operation information representing a target operation on the target device; The determining unit is configured to determine target information from the first device information and the first operation information, wherein the target information is used to generate associative control information of the target control information; A generation unit is used to generate the associative control information based on the target information; Determining the target information from the first device information and the first operation information includes: Determine the control result information corresponding to the target control information, wherein the control result information indicates whether the target device has completed the target operation; Based on the control result information, target information is determined from the first device information and the first operation information; The step of determining the target information from the first device information and the first operation information based on the control result information includes: If the control result information indicates that the target device has not completed the target operation, influencing factor information is determined, wherein the influencing factor information represents the factors that cause the target device to fail to complete the target operation; When the influencing factor information represents equipment factors, the first equipment information is determined as the target information; When the influencing factor information represents operational factors, the first operational information is determined as the target information.

11. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing a computer program stored in the memory, wherein when the computer program is executed, it implements the method described in any one of claims 1-9.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1-9.

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