A communication delay processing method based on virtual reality

Abstract

A method for processing communication delay based on virtual reality provided by this application selects reference communication description content to be processed from a cluster of sample communication description content to be processed based on the moment of the communication description content to be processed, which can reduce the interval time of the communication cycle, thereby improving the recognition rate of communication interaction data. Further, multiple communication cycle features are extracted from the communication description content to be processed and the reference communication description content to be processed. Based on the association between the key information clusters including communication tags and the types of target communication interaction data, the association of communication interaction data corresponding to the communication cycle can be accurately realized, so that the communication data difference caused by communication delay can be accurately obtained, and the difference can be optimized, effectively reducing the interference caused by communication delay.

Description

Technical Field

[0001] This application relates to the technical field of data latency processing. Specifically, it relates to a communication latency processing method based on virtual reality. Background Art

[0002] Virtual reality technology has a virtuality that transcends reality. It is a new computer technology developed along with the development of multimedia technology. It uses three-dimensional graphics generation technology, multi-sensor interaction technology, and high-resolution display technology to generate a three-dimensional realistic virtual environment, and users need to enter the virtual environment through special interaction devices.

[0003] Currently, the technical fields to which virtual reality technology is applied are becoming more and more extensive. When virtual reality technology is specifically combined with communication technology, due to problems such as slow network speed or poor information in the network, communication data latency may occur. Therefore, a technical solution is urgently needed to improve the above technical problems. Summary of the Invention

[0004] To improve the technical problems existing in the related art, this application provides a communication latency processing method based on virtual reality.

[0005] In a first aspect, a communication latency processing method based on virtual reality is provided. The method at least includes: obtaining a to-be-processed communication description content covering target communication interaction data; obtaining associated reference to-be-processed communication description content from a sample to-be-processed communication description content cluster in combination with the attribute information of the to-be-processed communication description content; the sample to-be-processed communication description content in the sample to-be-processed communication description content cluster covers target communication interaction data; performing convolution processing on the to-be-processed communication description content and the reference to-be-processed communication description content to generate a first key information cluster corresponding to the to-be-processed communication description content and a second key information cluster corresponding to the reference to-be-processed communication description content; both the first key information cluster and the second key information cluster include communication tags and important indications of the types of target communication interaction data. The important indication of the communication tag in the first key information cluster and the second key information cluster is obtained by determining the to-be-processed communication description content and the reference to-be-processed communication description content as the input information latency optimization thread of the to-be-processed communication description content binary group and obtaining the transitional processing result of the information latency optimization thread. The information latency optimization thread is configured based on the configuration communication cycles with the same information difference and different information differences; determining the correlation degree between the first key information cluster and the second key information cluster, and determining the information similarity of the target communication interaction data in the to-be-processed communication description content and the reference to-be-processed communication description content in combination with the correlation degree; determining the information latency optimization result of the target communication interaction data in the to-be-processed communication description content in combination with the information similarity.

[0006] In an independently implemented embodiment, obtaining the associated reference communication description content to be processed from the sample communication description content cluster for the attribute information of the communication description content to be processed includes: determining the time difference between the attribute information of the communication description content to be processed and the attribute information of each sample communication description content to be processed; and determining the sample communication description content to be processed with a time difference lower than the specified determination value as the reference communication description content to be processed.

[0007] In an independently implemented embodiment, performing convolution processing on the communication description content to be processed and the reference communication description content to be processed to generate a first key information cluster corresponding to the communication description content to be processed and a second key information cluster corresponding to the reference communication description content to be processed includes: inputting the communication description content to be processed and the reference communication description content to be processed into a configured communication cycle information difference convolution processing sub-thread, performing convolution processing on the communication description content to be processed based on the first convolution processing method of the communication cycle information difference convolution processing sub-thread to obtain a corresponding first information difference feature, and loading the first information difference feature into the first key information cluster; performing convolution processing on the reference communication description content to be processed based on the second convolution processing method of the communication cycle information difference convolution processing sub-thread to obtain a corresponding second information difference feature, and loading the second information difference feature into the second key information cluster; the communication cycle information difference convolution processing sub-thread is a sub-thread in the information delay optimization thread, and the information delay optimization thread is used to determine the communication cycle information difference association result according to the important indication information output by the communication cycle information difference convolution processing sub-thread.

[0008] In an independently implemented embodiment, each convolution processing method includes a number of convolution processing units, and each convolution processing unit in the same convolution processing method is combined in sequence. The data processing process of the convolution processing method is implemented through the following steps: obtaining the information difference feature corresponding to the real-time input communication cycle based on the important indication communication cycle output by each convolution processing unit; the input data of the real-time convolution processing unit includes the real-time input communication cycle and the important indication communication cycle output by each convolution processing unit before the real-time convolution processing unit.

[0009] In an independently implemented embodiment, the configuration process of the information delay optimization thread is achieved through the following steps: obtaining a configuration example cluster; the configuration example cluster includes a configuration communication cycle pair and a corresponding configuration indication, the configuration communication cycle pair includes a first configuration communication cycle and a second configuration communication cycle, and the configuration indication includes the same information difference and different information differences; respectively determining the first configuration communication cycle and the second configuration communication cycle as the inputs of the corresponding convolution processing methods in the information delay optimization thread to be configured, generating a first configuration information difference feature corresponding to the first configuration communication cycle and a second configuration information difference feature corresponding to the second configuration communication cycle; determining the important indication difference between the first configuration information difference feature and the second configuration information difference feature; combining the configuration indication and the feature difference to determine a quantization evaluation vector, and debugging the thread variables of the information delay optimization thread in combination with the quantization evaluation vector until the specified requirements are met, obtaining the configured information delay optimization thread.

[0010] In an independently implemented embodiment, the convolution processing of the to-be-processed communication description content and the reference to-be-processed communication description content to generate a first key information cluster corresponding to the to-be-processed communication description content and a second key information cluster corresponding to the reference to-be-processed communication description content includes: loading the to-be-processed communication description content and the reference to-be-processed communication description content into the configured target communication interaction data convolution processing thread one by one, generating target communication interaction data features corresponding to the to-be-processed communication description content and the reference to-be-processed communication description content respectively; loading the target communication interaction data feature corresponding to the to-be-processed communication description content into the first key information cluster, and loading the target communication interaction data feature corresponding to the reference to-be-processed communication description content into the second key information cluster.

[0011] In an independently implemented embodiment, the method further includes: loading the to-be-processed communication description content and the reference to-be-processed communication description content into the configured derivative communication data convolution processing thread one by one, generating derivative communication data features corresponding to the to-be-processed communication description content and the reference to-be-processed communication description content respectively; generating matching derivative features of the corresponding target communication interaction data features based on the derivative communication data features corresponding to the same to-be-processed communication description content, generating matching derivative features corresponding to the to-be-processed communication description content and the reference to-be-processed communication description content respectively; loading the matching derivative feature corresponding to the to-be-processed communication description content into the first key information cluster, and loading the matching derivative feature corresponding to the reference to-be-processed communication description content into the second key information cluster.

[0012] In an independently implemented embodiment, the target communication interaction data features include at least one first cycle feature of the target communication interaction data, and the derived communication data features include at least one reference cycle feature of the derived communication data. Generating a matching derived feature of the corresponding target communication interaction data feature based on the derived communication data features corresponding to the same communication description content to be processed includes: distinguishing the real-time communication description content to be processed based on the reference cycle feature of each derived communication data corresponding to the real-time communication description content to be processed, to obtain each pending semantic segment and the corresponding segment cycle feature; the real-time communication description content to be processed is the communication description content to be processed or the reference communication description content to be processed; associating the first cycle feature of each target communication interaction data in the real-time communication description content to be processed with the segment cycle feature of each pending semantic segment, and determining the pending semantic segment corresponding to each target communication interaction data according to the association result; generating a second cycle feature of each target communication interaction data based on the segment cycle feature of the pending semantic segment corresponding to each target communication interaction data; combining the second cycle features of each target communication interaction data in the real-time communication description content to be processed to generate a matching derived feature of the corresponding target communication interaction data feature.

[0013] In an independently implemented embodiment, performing convolution processing on the communication description content to be processed and the reference communication description content to be processed to generate a first key information cluster corresponding to the communication description content to be processed and a second key information cluster corresponding to the reference communication description content to be processed includes: generating a first communication cycle feature corresponding to the communication description content to be processed in combination with the communication cycle label of the communication description content to be processed, and loading the first communication cycle feature into the first key information cluster; generating a second communication cycle feature corresponding to the reference communication description content to be processed in combination with the communication cycle label of the reference communication description content to be processed, and loading the second communication cycle feature into the second key information cluster.

[0014] In an independently implemented embodiment, determining the correlation degree between the first key information cluster and the second key information cluster, and determining the information similarity of the target communication interaction data in the communication description content to be processed and the reference communication description content to be processed in combination with the correlation degree includes: inputting the first key information cluster and the second key information cluster into a configured correlation degree evaluation thread to generate the correlation degree; when the correlation degree is greater than the correlation degree determination value, determining that the information similarity is the same; when the correlation degree is lower than the correlation degree determination value, determining that the information similarity is different.

[0015] In an independently implemented embodiment, when there are no less than two pieces of reference communication description content to be processed, for each second key information cluster having a mapping relationship with the reference communication description content to be processed, the information similarity between the communication description content to be processed and each piece of reference communication description content to be processed, and determining the information delay optimization result of the target communication interaction data in the communication description content to be processed by combining the information similarity includes: when no less than one information similarity is the same, determining that the information delay optimization result is that the target communication interaction data remains unchanged; otherwise, determining that the information delay optimization result is that the target communication interaction data changes.

[0016] A communication delay processing method based on virtual reality provided by an embodiment of the present application obtains the communication description content to be processed covering the target communication interaction data, obtains the associated reference communication description content to be processed from the sample communication description content cluster to be processed based on the attribute information of the communication description content to be processed, the sample communication description content in the sample communication description content cluster to be processed covers the target communication interaction data, performs convolution processing on the communication description content to be processed and the reference communication description content to be processed to obtain the first key information cluster corresponding to the communication description content to be processed and the second key information cluster corresponding to the reference communication description content to be processed. Both the first key information cluster and the second key information cluster include communication tags and important indications of the types of target communication interaction data, determine the correlation degree between the first key information cluster and the second key information cluster, determine the information similarity of the target communication interaction data in the communication description content to be processed and the reference communication description content to be processed based on the correlation degree, and determine the information delay optimization result of the target communication interaction data in the communication description content to be processed based on the information similarity. In this way, selecting the reference communication description content to be processed from the sample communication description content cluster according to the time of the communication description content to be processed can reduce the interval time of the communication cycle, thereby improving the recognition rate of communication interaction data. Further, extracting the characteristics of multiple communication cycles from the communication description content to be processed and the reference communication description content to be processed, and based on the correlation between the key information clusters including communication tags and the types of target communication interaction data, the communication interaction data corresponding to the communication cycle can be accurately associated, so that the communication data difference caused by communication delay can be accurately obtained and optimized, and the interference caused by communication delay can be effectively reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0018] Figure 1 The flowchart of a communication latency processing method provided by an embodiment of the present application based on virtual reality. Specific implementation manners

[0019] In order to better understand the above technical solution, the technical solution of the present application will be described in detail below through the accompanying drawings and specific embodiments. It should be understood that the embodiments of the present application and the specific features in the embodiments are detailed descriptions of the technical solution of the present application, rather than limitations on the technical solution of the present application. Without conflict, the technical features in the embodiments of the present application and the embodiments can be combined with each other.

[0020] Please refer to Figure 1 , which shows a communication latency processing method based on virtual reality. The method may include the technical solutions described in the following steps S202 - step S210.

[0021] Step S202, obtain the to-be-processed communication description content covering the target communication interaction data.

[0022] Exemplarily, the communication interaction data is communication information transmitted in bytes.

[0023] Step S204, obtain the associated reference to-be-processed communication description content from the sample to-be-processed communication description content cluster based on the attribute information of the to-be-processed communication description content; the sample to-be-processed communication description content in the sample to-be-processed communication description content cluster covers the target communication interaction data.

[0024] Exemplarily, the attribute information refers to the time information collected for the to-be-processed communication description content. The sample to-be-processed communication description content cluster includes several sample to-be-processed communication description contents covering the target communication interaction data. The sample to-be-processed communication description content refers to the to-be-processed communication description content collected at the sample time. It can be understood that the relevant information of the target communication interaction data covered in the sample to-be-processed communication description content represents past information, and the relevant information of the target communication interaction data covered in the to-be-processed communication description content represents current information. The relevant information of the target communication interaction data covered in the to-be-processed communication description content and the sample to-be-processed communication description content may be the same or different.

[0025] For example, in order to improve the recognition rate of the target communication interaction data, the associated reference to-be-processed communication description content can be obtained from the sample to-be-processed communication description content cluster based on the attribute information of the to-be-processed communication description content. The sample to-be-processed communication description content with a time difference lower than the specified determination value from the attribute information of the to-be-processed communication description content is determined as the associated reference to-be-processed communication description content, thereby reducing the associated period of the communication cycle, reducing the number of subsequent associated communication cycles, and avoiding meaningless communication cycle associations.

[0026] In a possible embodiment, obtaining associated reference communication description content to be processed from a cluster of sample communication description content to be processed based on the attribute information of the communication description content to be processed includes: determining the time difference between the attribute information of the communication description content to be processed and the attribute information of each sample communication description content to be processed; and determining the sample communication description content to be processed with a time difference lower than a specified determination value as the reference communication description content to be processed.

[0027] For example, the sample communication description content in the cluster of sample communication description content to be processed also has corresponding attribute information. Based on the attribute information of the communication description content to be processed and the attribute information of the sample communication description content to be processed, the time difference between the communication description content to be processed and the sample communication description content to be processed can be determined, that is, the acquisition difference between the communication description content to be processed and the sample communication description content to be processed, and the time differences between the communication description content to be processed and each sample communication description content to be processed are obtained. When the time difference between the communication description content to be processed and the sample communication description content to be processed is lower than the specified determination value, it indicates that the transmission times of the communication description content to be processed and the sample communication description content to be processed are relatively close. Therefore, the sample communication description content to be processed can be determined as the reference communication description content to be processed corresponding to the communication description content to be processed. It can be understood that there can be no less than one reference communication description content to be processed corresponding to a communication description content to be processed.

[0028] Step S206: Perform convolution processing on the communication description content to be processed and the reference communication description content to be processed to obtain a first key information cluster corresponding to the communication description content to be processed and a second key information cluster corresponding to the reference communication description content to be processed; both the first key information cluster and the second key information cluster include communication tags and important indications of the types of target communication interaction data.

[0029] For example, convolution processing can be performed on the communication description content to be processed covering the target communication interaction data to obtain a key information cluster corresponding to the communication description content to be processed. The key information cluster corresponding to the communication description content to be processed is the first key information cluster, and the key information cluster corresponding to the reference communication description content to be processed is the second key information cluster. The key information cluster corresponding to the communication description content to be processed includes no less than two features, specifically including communication tags, types of target communication interaction data, and important indications of other types. The important indication of the communication tag represents the information difference feature of the communication description content to be processed. The important indication of the type of target communication interaction data represents the real-time feature of the communication description content to be processed, and specifically is an important indication related to the target communication interaction data.

[0030] Step S208: Determine the correlation degree between the first key information cluster and the second key information cluster, and determine the information similarity of the target communication interaction data in the to-be-processed communication description content and the reference to-be-processed communication description content based on the correlation degree.

[0031] Exemplarily, the information similarity is used to determine whether the information of the target communication interaction data in the to-be-processed communication description content is the same as that of the target communication interaction data in the reference to-be-processed communication description content, and whether the to-be-processed communication description content and the target communication interaction data cover the same target communication interaction data.

[0032] For example, after obtaining the first key information cluster and the second key information cluster, the correlation degree between the first key information cluster and the second key information cluster can be determined, and the information similarity of the target communication interaction data in the to-be-processed communication description content and the reference to-be-processed communication description content can be determined based on the correlation degree. The correlation degree between the first key information cluster and the second key information cluster can be determined. For example, the similarity between the first key information cluster and the second key information cluster can be determined and the similarity can be determined as the correlation degree. Alternatively, the first key information cluster and the second key information cluster can be input into an artificial intelligence thread, and the artificial intelligence thread outputs the correlation degree between the first key information cluster and the second key information cluster. It can be understood that the higher the correlation degree between the first key information cluster and the second key information cluster, the more relevant the to-be-processed communication description content and the reference to-be-processed communication description content are. When the correlation degree is greater than the correlation degree determination value, it is determined that the information similarity of the target communication interaction data in the to-be-processed communication description content and the reference to-be-processed communication description content is the same. When the correlation degree is lower than the correlation degree determination value, it is determined that the information similarity of the target communication interaction data in the to-be-processed communication description content and the reference to-be-processed communication description content is different. The information similarity includes the same and different.

[0033] Step S210: Determine the information delay optimization result of the target communication interaction data in the to-be-processed communication description content based on the information similarity.

[0034] For example, the information delay optimization result of the target communication interaction data in the to-be-processed communication description content can be determined according to the information similarity. The information delay optimization result refers to the change situation of the target communication interaction data in the to-be-processed communication description content relative to the past. The information delay optimization result includes that the target communication interaction data remains unchanged and the target communication interaction data changes.

[0035] In a possible embodiment, when there is one reference to-be-processed communication description content, if the information similarity is the same, it can be determined that the information delay optimization result is that the target communication interaction data remains unchanged. If the information similarity is different, it can be determined that the information delay optimization result is that the target communication interaction data changes.

[0036] In a possible embodiment, when there are no less than two reference communication descriptions to be processed, for each second key information cluster having a mapping relationship with the reference communication descriptions to be processed, the information similarity between the communication description to be processed and each reference communication description to be processed, and based on the information similarity, determining the information delay optimization result of the target communication interaction data in the communication description to be processed, including: when no less than one information similarity is the same, determining that the information delay optimization result is that the target communication interaction data remains unchanged; otherwise, determining that the information delay optimization result is that the target communication interaction data changes.

[0037] For example, when there are no less than two reference communication descriptions to be processed, one reference communication description binary group corresponds to one second key information cluster, that is, each second key information cluster having a mapping relationship with the reference communication descriptions to be processed. Correspondingly, each round of a communication description to be processed is associated with one reference communication description to be processed. Therefore, there is a corresponding information similarity between a communication description to be processed and one reference communication description to be processed, that is, the information similarity between the communication description to be processed and each reference communication description to be processed. When there are no less than two reference communication descriptions to be processed, as long as there is no less than one information similarity that is the same among all the information similarities, it can be determined that the information delay optimization result is that the target communication interaction data remains unchanged; if all the information similarities are different, it can be determined that the information delay optimization result is that the target communication interaction data changes.

[0038] Further, after recording a set of communication descriptions to be processed, a communication description cluster to be processed is obtained.

[0039] In the above communication latency processing method based on virtual reality, by obtaining the communication description content to be processed covering the target communication interaction data, obtaining the associated reference communication description content to be processed from the sample communication description content clusters to be processed based on the attribute information of the communication description content to be processed, the sample communication description content in the sample communication description content clusters to be processed covers the target communication interaction data, performing convolution processing on the communication description content to be processed and the reference communication description content to be processed to obtain the first key information cluster corresponding to the communication description content to be processed and the second key information cluster corresponding to the reference communication description content to be processed, both the first key information cluster and the second key information cluster include communication tags and important indications of the types of target communication interaction data, determining the degree of association between the first key information cluster and the second key information cluster, determining the information similarity of the target communication interaction data in the communication description content to be processed and the reference communication description content to be processed based on the degree of association, and determining the information latency optimization result of the target communication interaction data in the communication description content to be processed based on the information similarity. In this way, selecting the reference communication description content to be processed from the sample communication description content clusters to be processed based on the time of the communication description content to be processed can reduce the interval time of the communication cycle, thereby improving the recognition rate of communication interaction data. Further, extracting the characteristics of multiple communication cycles for the communication description content to be processed and the reference communication description content to be processed, and based on the association between the key information clusters including communication tags and the types of target communication interaction data, the association of the communication interaction data corresponding to the communication cycle can be accurately realized, so that the communication data difference caused by communication latency can be accurately obtained and the difference can be optimized, effectively reducing the interference caused by communication latency.

[0040] In a possible embodiment, performing convolution processing on the communication description content to be processed and the reference communication description content to be processed to obtain the first key information cluster corresponding to the communication description content to be processed and the second key information cluster corresponding to the reference communication description content to be processed includes: inputting the communication description content to be processed and the reference communication description content to be processed into the configured communication cycle information difference convolution processing sub-thread, performing convolution processing on the communication description content to be processed through the first convolution processing method of the communication cycle information difference convolution processing sub-thread to obtain the corresponding first information difference feature, and loading the first information difference feature into the first key information cluster; performing convolution processing on the reference communication description content to be processed through the second convolution processing method of the communication cycle information difference convolution processing sub-thread to obtain the corresponding second information difference feature, and loading the second information difference feature into the second key information cluster; the communication cycle information difference convolution processing sub-thread is a sub-thread in the information latency optimization thread, and the information latency optimization thread is used to determine the communication cycle information difference association result according to the important indication information output by the communication cycle information difference convolution processing sub-thread.

[0041] Furthermore, the information delay optimization thread is an artificial intelligence thread used to determine the communication cycle information difference correlation result of a communication cycle pair. The input data of the information delay optimization thread is the communication cycle pair, and the output data is the communication cycle information difference correlation result. The information delay optimization thread includes a communication cycle information difference convolution processing sub-thread and an output unit. The communication cycle information difference convolution processing sub-thread is used to extract the information difference features of the communication cycle. The communication cycle information difference convolution processing sub-thread includes a first convolution processing method and a second convolution processing method, and different convolution processing methods are used to extract different information difference features of the communication cycle. The communication cycle information difference convolution processing sub-thread can output the information difference features of each communication cycle in the communication cycle pair, that is, the important indication information output by the communication cycle information difference convolution processing sub-thread includes the information difference features of each communication cycle in the communication cycle pair. The output unit is used to determine the communication cycle information difference correlation result according to the information difference features of each communication cycle in the communication cycle pair. The communication cycle information difference correlation result can be a specific correlation score or a correlation label.

[0042] For example, the information delay optimization thread is configured in advance. After determining the communication description content to be processed and the reference communication description content to be processed, the communication description content to be processed and the reference communication description content to be processed can be input into the communication cycle information difference convolution processing sub-thread in the information delay optimization thread. The communication cycle information difference convolution processing sub-thread can output the information difference features corresponding to the communication description content to be processed and the reference communication description content to be processed respectively. In the communication cycle information difference convolution processing sub-thread, the communication description content to be processed can be specifically input into the first convolution processing method of the communication cycle information difference convolution processing sub-thread, and the communication description content to be processed is convolved through the first convolution processing method of the communication cycle information difference convolution processing sub-thread to obtain the information difference feature of the communication description content to be processed, that is, the first information difference feature. The reference communication description content to be processed can be specifically input into the second convolution processing method of the communication cycle information difference convolution processing sub-thread, and the reference communication description content to be processed is convolved through the second convolution processing method of the communication cycle information difference convolution processing sub-thread to obtain the information difference feature of the reference communication description content to be processed, that is, the second information difference feature. Without obtaining the final output communication cycle information difference correlation result of the information delay optimization thread, only the intermediate processing results of the information delay optimization thread, that is, the first information difference feature and the second information difference feature, are needed for subsequent communication cycle association through the key information cluster.

[0043] In this embodiment, the communication cycle information difference convolution processing sub-thread can extract the information difference features of the communication description content to be processed and the reference communication description content to be processed at the same time, improving the convolution processing efficiency of the communication cycle, and thus helping to improve the communication interaction data recognition rate.

[0044] In a possible embodiment, each convolution processing method includes a number of convolution processing units. Each convolution processing unit in the same convolution processing method is combined in sequence. The data processing process of the convolution processing method is realized through the following steps: obtaining the information difference feature corresponding to the real-time input communication cycle based on the important indication communication cycle output by each convolution processing unit; the input data of the real-time convolution processing unit includes the real-time input communication cycle and the important indication communication cycle output by each convolution processing unit before the real-time convolution processing unit.

[0045] Furthermore, the real-time input communication cycle is the communication description content to be processed or the reference communication description content to be processed. When the convolution processing method is the first convolution processing method, the real-time input communication cycle is the communication description content to be processed. When the convolution processing method is the second convolution processing method, the real-time input communication cycle is the reference communication description content to be processed.

[0046] In this embodiment, obtaining the information difference feature corresponding to the real-time input communication cycle based on the important indication communication cycle output by each convolution processing unit, wherein the input data of the real-time convolution processing unit includes the real-time input communication cycle and the important indication communication cycle output by each convolution processing unit before the real-time convolution processing unit can improve the extraction accuracy of the information difference feature.

[0047] In a possible embodiment, the configuration process of the information delay optimization thread is realized through the following steps: obtaining a configuration example cluster; the configuration example cluster includes configuration communication cycle pairs and corresponding configuration indications. The configuration communication cycle pair includes a first configuration communication cycle and a second configuration communication cycle. The configuration indication includes information difference being the same and information difference being different; respectively determining the first configuration communication cycle and the second configuration communication cycle as the inputs of the corresponding convolution processing method in the information delay optimization thread to be configured, obtaining the first configuration information difference feature corresponding to the first configuration communication cycle and the second configuration information difference feature corresponding to the second configuration communication cycle; determining the important indication difference between the first configuration information difference feature and the second configuration information difference feature; determining a quantization evaluation vector based on the configuration indication and the feature difference, and debugging the thread variables of the information delay optimization thread based on the quantization evaluation vector until meeting the specified requirements to obtain the configured information delay optimization thread.

[0048] For example, the communication cycle information difference convolution processing sub-thread is determined to be part of the information delay optimization thread, and the precise communication cycle information difference convolution processing sub-thread can only be obtained by configuring the information delay optimization thread. The information delay optimization thread is obtained through detection configuration. When performing detection configuration, a configuration example cluster needs to be obtained, and thread configuration is performed based on the configuration example cluster. The configuration example cluster includes multiple groups of configuration communication cycle pairs and corresponding configuration indicators. A group of configuration communication cycle pairs includes a first configuration communication cycle and a second configuration communication cycle, and the configuration indicator includes information difference being the same and information difference being different. The first configuration communication cycle and the second configuration communication cycle can be input into the information delay optimization thread to be configured together. The first configuration communication cycle is determined as the input of the first convolution processing method in the information delay optimization thread to be configured, and the second configuration communication cycle is determined as the input of the second convolution processing method in the information delay optimization thread to be configured. The first convolution processing method can output the first configuration information difference feature corresponding to the first configuration communication cycle, and the second convolution processing method can output the second configuration information difference feature corresponding to the second configuration communication cycle. It can be understood that for the configuration communication cycle pair with the configuration indicator of information difference being the same, the more similar the important indication differences are, the better. For the configuration communication cycle pair with the configuration indicator of information difference being different, the greater the important indication differences are, the better. Therefore, the important indication differences between the first configuration information difference feature and the second configuration information difference feature can be determined, the quantization evaluation vector is determined based on the configuration indicator and the feature difference, and processing is performed based on the quantization evaluation vector to debug the thread variables of the information delay optimization thread until the specified requirements are met, and the configured information delay optimization thread is obtained. In this way, there is no need to configure the information difference convolution processing thread based on the communication cycle with the information difference area accurately marked. Based on the configuration communication cycle pair simply marked with the same or different communication cycle information differences, the information delay optimization thread can be configured, and different convolution processing methods in the information delay optimization thread can simultaneously complete the information difference convolution processing of different communication cycles.

[0049] The information delay optimization thread includes an information difference convolution processing sub-thread and a loss unit. The information difference convolution processing sub-thread includes a first convolution processing method and a second convolution processing method. When configuring the information delay optimization thread, the first configuration communication cycle and the second configuration communication cycle are loaded into the first convolution processing method and the second convolution processing method one by one. The first convolution processing method and the second convolution processing method respectively output a first configuration information difference feature corresponding to the first configuration communication cycle and a second configuration information difference feature corresponding to the second configuration communication cycle. The first configuration information difference feature and the second configuration information difference feature are input into the loss unit, and the configuration instruction is also input into the loss unit. The loss unit determines a quantization evaluation vector based on the first configuration information difference feature, the second configuration information difference feature and the configuration instruction, and reversely debugs the thread variables based on the quantization evaluation vector until the specified requirements are met to obtain the configured information delay optimization thread. When the information delay optimization thread configuration is completed, the loss unit can be determined as an output unit to output an evaluation label corresponding to the input communication cycle pair. Based on the configuration communication cycle pair, the thread variables of the first convolution processing method and the second convolution processing method are jointly debugged. The optimal thread variables finally obtained by the first convolution processing method and the second convolution processing method are different, but the information differences of the communication cycle pairs can be accurately judged based on the information difference features respectively output by the first convolution processing method and the second convolution processing method.

[0050] In a possible embodiment, convolution processing is performed on the communication description content to be processed and the reference communication description content to be processed to obtain a first key information cluster corresponding to the communication description content to be processed and a second key information cluster corresponding to the reference communication description content to be processed, including: loading the communication description content to be processed and the reference communication description content to be processed into the configured target communication interaction data convolution processing thread one by one to obtain target communication interaction data features respectively corresponding to the communication description content to be processed and the reference communication description content to be processed, loading the target communication interaction data feature corresponding to the communication description content to be processed into the first key information cluster, and loading the target communication interaction data feature corresponding to the reference communication description content to be processed into the second key information cluster.

[0051] Furthermore, the target communication interaction data convolution processing thread is an artificial intelligence thread for extracting important indication information of the target communication interaction data in the communication description content to be processed.

[0052] For example, a target communication interaction data convolution processing thread is configured in advance. After determining the communication description content to be processed and the reference communication description content to be processed, the communication description content to be processed can be input into the configured target communication interaction data convolution processing thread to obtain the target communication interaction data features corresponding to the communication description content to be processed, and the reference communication description content to be processed can be input into the configured target communication interaction data convolution processing thread to obtain the target communication interaction data features corresponding to the reference communication description content to be processed.

[0053] In this embodiment, through the artificial intelligence thread, important indication information of the target communication interaction data in the communication description content to be processed can be quickly extracted, improving the speed and accuracy of convolution processing, thereby helping to improve the accuracy of communication interaction data detection.

[0054] In a possible embodiment, the method further includes the following steps.

[0055] Step S502: Load the communication description content to be processed and the reference communication description content to be processed into the configured derivative communication data convolution processing thread one by one to obtain the derivative communication data features corresponding to the communication description content to be processed and the reference communication description content to be processed respectively.

[0056] Furthermore, the derivative communication data convolution processing thread is an artificial intelligence thread for extracting important indication information of the derivative communication data in the communication description content to be processed.

[0057] For example, a derivative communication data convolution processing thread is configured in advance. After determining the communication description content to be processed and the reference communication description content to be processed, the communication description content to be processed can be input into the configured derivative communication data convolution processing thread to obtain the derivative communication data features corresponding to the communication description content to be processed, and the reference communication description content to be processed can be input into the configured derivative communication data convolution processing thread to obtain the derivative communication data features corresponding to the reference communication description content to be processed.

[0058] Step S504: Generate matching derivative features of the corresponding target communication interaction data features based on the derivative communication data features corresponding to the same communication description content to be processed, to obtain the matching derivative features corresponding to the communication description content to be processed and the reference communication description content to be processed respectively.

[0059] For example, according to the derivative communication data features corresponding to the communication description content to be processed, matching derivative features of the target communication interaction data features corresponding to the communication description content to be processed can be generated, and according to the derivative communication data features corresponding to the reference communication description content to be processed, matching derivative features of the target communication interaction data features corresponding to the reference communication description content to be processed can be generated.

[0060] Step S506: Load the matching derivative features corresponding to the communication description content to be processed into the first key information cluster, and load the matching derivative features corresponding to the reference communication description content to be processed into the second key information cluster.

[0061] For example, the important indicators of the target communication interaction data type include the target communication interaction data features and the matching derivative features. The matching derivative features corresponding to the communication description content to be processed can be loaded into the first key information cluster, and the matching derivative features corresponding to the reference communication description content to be processed can be loaded into the second key information cluster.

[0062] In a possible embodiment, the target communication interaction data features include the first cycle features of not less than one target communication interaction data, the derivative communication data features include the reference cycle features of not less than one derivative communication data, and the matching derivative features of the target communication interaction data features corresponding to the same communication description content to be processed are generated. Specifically, it may include the following steps.

[0063] Step S602: Distinguish the real-time communication description content to be processed based on the reference cycle features of each derivative communication data corresponding to the real-time communication description content to be processed, and obtain each pending semantic segment and the corresponding segment cycle feature; the real-time communication description content to be processed is the communication description content to be processed or the reference communication description content to be processed.

[0064] Among them, the derivative communication data features include the reference cycle features of not less than one derivative communication data. The reference cycle feature refers to the attribute information of the derivative communication data.

[0065] For example, based on the reference cycle features of each derivative communication data in the communication description content to be processed, the communication description content to be processed can be differentiated by communication cycle, and several communication cycle subsets are obtained. One communication cycle subset is determined as one pending semantic segment. Thus, each pending semantic segment and the corresponding segment cycle feature of the communication description content to be processed or the reference communication description content to be processed can be obtained.

[0066] Step S604: Associate the first cycle features of each target communication interaction data in the real-time communication description content to be processed with the segment cycle features of each pending semantic segment, and determine the pending semantic segment corresponding to each target communication interaction data according to the association result.

[0067] For example, the target communication interaction data features include the first cycle features of no less than one target communication interaction data. The first cycle features of each target communication interaction data in the same communication description content to be processed can be associated with the segment cycle features of each semantic segment to be determined, so as to determine which semantic segment to be determined each target communication interaction data is located in, and thus determine the semantic segment to be determined corresponding to each target communication interaction data. If a target communication interaction data is located in a semantic segment to be determined, the semantic segment to be determined corresponding to the target communication interaction data is the semantic segment to be determined.

[0068] Step S606: Generate the second cycle features of each target communication interaction data based on the segment cycle features of the semantic segment to be determined corresponding to each target communication interaction data.

[0069] For example, the segment cycle features further include the sequence order between semantic segments to be determined. Step S608: Generate the matching derivative features of the corresponding target communication interaction data features based on the second cycle features of each target communication interaction data in the real-time communication description content to be processed.

[0070] In a possible embodiment, perform convolution processing on the communication description content to be processed and the reference communication description content to be processed to obtain the first key information cluster corresponding to the communication description content to be processed and the second key information cluster corresponding to the reference communication description content to be processed, including: generating the first communication cycle feature corresponding to the communication description content to be processed based on the communication cycle label of the communication description content to be processed, and loading the first communication cycle feature into the first key information cluster; generating the second communication cycle feature corresponding to the reference communication description content to be processed based on the communication cycle label of the reference communication description content to be processed, and loading the second communication cycle feature into the second key information cluster.

[0071] For example, in addition to the communication label and the important indication of the type of target communication interaction data in the key information cluster, it may also include the important indication related to the communication cycle acquisition device. The first communication cycle feature corresponding to the communication description content to be processed can be generated based on the communication cycle label of the communication description content to be processed, and the first communication cycle feature is loaded into the first key information cluster. The second communication cycle feature corresponding to the reference communication description content to be processed is generated based on the communication cycle label of the reference communication description content to be processed, and the second communication cycle feature is loaded into the second key information cluster.

[0072] In a possible embodiment, the correlation degree between the first key information cluster and the second key information cluster is determined, and the information similarity of the target communication interaction data in the communication description content to be processed and the reference communication description content to be processed is determined based on the correlation degree, including: inputting the first key information cluster and the second key information cluster into a configured correlation degree evaluation thread to obtain the correlation degree; when the correlation degree is greater than the correlation degree determination value, determining that the information similarity is the same; when the correlation degree is lower than the correlation degree determination value, determining that the information similarity is different.

[0073] Wherein, the correlation degree evaluation thread is an artificial intelligence thread for determining the correlation degree between the first key information cluster and the second key information cluster.

[0074] For example, the correlation degree evaluation thread is configured in advance. After determining the first key information cluster and the second key information cluster, the first key information cluster and the second key information cluster can be input into the configured correlation degree evaluation thread to obtain the correlation degree between the first key information cluster and the second key information cluster. When the correlation degree is greater than the correlation degree determination value, it can be determined that the information similarity is the same; when the correlation degree is lower than the correlation degree determination value, it can be determined that the information similarity is different.

[0075] In this embodiment, the artificial intelligence thread can quickly determine the correlation degree between the first key information cluster and the second key information cluster, improve the efficiency and accuracy of determining the correlation degree, and thus help improve the accuracy of communication interaction data recognition.

[0076] On the above basis, a communication delay processing device based on virtual reality is provided, which is applied to a communication delay processing system based on virtual reality. The device includes:

[0077] A content acquisition module, configured to acquire the communication description content to be processed covering the target communication interaction data;

[0078] A data interaction module, configured to obtain the associated reference communication description content to be processed from the sample communication description content clusters to be processed in combination with the attribute information of the communication description content to be processed; the sample communication description content in the sample communication description content clusters to be processed covers the target communication interaction data;

[0079] A difference acquisition module is configured to perform convolution processing on the to-be-processed communication description content and the reference to-be-processed communication description content, and generate a first key information cluster corresponding to the to-be-processed communication description content and a second key information cluster corresponding to the reference to-be-processed communication description content; both the first key information cluster and the second key information cluster include communication tags and important indications of target communication interaction data types. The important indications of the communication tags in the first key information cluster and the second key information cluster are obtained by determining the to-be-processed communication description content and the reference to-be-processed communication description content as the input information delay optimization thread of the to-be-processed communication description content binary group, and obtaining the transition processing result of the information delay optimization thread. The information delay optimization thread is configured based on the configured communication cycles with the same information difference and different information differences.

[0080] A result determination module is configured to determine the correlation degree between the first key information cluster and the second key information cluster, and determine the information similarity of the target communication interaction data in the to-be-processed communication description content and the reference to-be-processed communication description content in combination with the correlation degree; and determine the information delay optimization result of the target communication interaction data in the to-be-processed communication description content in combination with the information similarity.

[0081] On the above basis, a communication delay processing system based on virtual reality is shown, including a processor and a memory that communicate with each other. The processor is configured to read a computer program from the memory and execute it to implement the above method.

[0082] On the above basis, a computer-readable storage medium is further provided, and the computer program stored thereon implements the above method when running.

[0083] In summary, based on the above solution, by obtaining the to-be-processed communication description content covering the target communication interaction data, obtaining the associated reference to-be-processed communication description content from the sample to-be-processed communication description content clusters based on the attribute information of the to-be-processed communication description content, where the sample to-be-processed communication description content in the sample to-be-processed communication description content clusters covers the target communication interaction data, performing convolution processing on the to-be-processed communication description content and the reference to-be-processed communication description content to obtain the first key information cluster corresponding to the to-be-processed communication description content and the second key information cluster corresponding to the reference to-be-processed communication description content, both the first key information cluster and the second key information cluster include communication tags and important indications of the types of target communication interaction data, determining the correlation degree between the first key information cluster and the second key information cluster, determining the information similarity of the target communication interaction data in the to-be-processed communication description content and the reference to-be-processed communication description content based on the correlation degree, and determining the information delay optimization result of the target communication interaction data in the to-be-processed communication description content based on the information similarity. In this way, by selecting the reference to-be-processed communication description content from the sample to-be-processed communication description content clusters based on the time of the to-be-processed communication description content, the interval time of the communication cycle can be reduced, thereby improving the recognition rate of communication interaction data. Further, extracting the characteristics of multiple communication cycles from the to-be-processed communication description content and the reference to-be-processed communication description content, and based on the correlation between the key information clusters including communication tags and the types of target communication interaction data, the association of the communication interaction data corresponding to the communication cycle can be accurately realized, so that the communication data difference caused by communication delay can be accurately obtained and optimized, and the interference caused by communication delay can be effectively reduced.

[0084] It should be understood that the systems and their modules shown above can be implemented in various ways. For example, in some embodiments, the systems and their modules can be implemented through hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated designed hardware. Those skilled in the art can understand that the above methods and systems can be implemented using computer-executable instructions and / or included in the processor control code. For example, such code is provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The systems and their modules of the present application can be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also by software implemented by various types of processors, or by a combination of the above hardware circuits and software (e.g., firmware).

[0085] It should be noted that the beneficial effects that may be produced by different embodiments are different. In different embodiments, the beneficial effects that may be produced may be any one or several combinations of the above, or any other beneficial effects that may be obtained.

[0086] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only an example and does not constitute a limitation to this application. Although not explicitly stated here, those skilled in the art may make various modifications, improvements, and corrections to this application. Such modifications, improvements, and corrections are proposed in this application, so such modifications, improvements, and corrections still fall within the spirit and scope of the exemplary embodiments of this application.

[0087] At the same time, this application uses specific terms to describe the embodiments of this application. Such as "one embodiment", "an embodiment", and / or "some embodiments" mean a certain feature, structure, or characteristic related to at least one embodiment of this application. Therefore, it should be emphasized and noted that the "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more at different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures, or characteristics in one or more embodiments of this application can be appropriately combined.

[0088] In addition, those skilled in the art can understand that various aspects of this application can be described and illustrated by several patentable types or situations, including any new and useful processes, machines, products, or combinations of substances, or any new and useful improvements to them. Accordingly, various aspects of this application can be executed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above hardware or software can all be referred to as "data blocks", "modules", "engines", "units", "components", or "systems". In addition, various aspects of this application may be embodied as a computer product located in one or more computer-readable media, which includes computer-readable program codes.

[0089] A computer storage medium may contain a propagated data signal containing computer program codes, such as on a baseband or as part of a carrier wave. This propagated signal may have various forms of manifestation, including electromagnetic form, optical form, etc., or a suitable combination of forms. A computer storage medium can be any computer-readable medium other than a computer-readable storage medium, which can be connected to an instruction execution system, device, or equipment to realize communication, propagation, or transmission for use of the program. The program codes located on the computer storage medium can be propagated through any suitable medium, including radio, cable, fiber optic cable, RF, or similar media, or any combination of the above media.

[0090] The computer program code required for the operations of various parts of this application can be written in any one or more programming languages, including object-oriented programming languages such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, Python, etc., conventional procedural programming languages such as C language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages such as Python, Ruby, and Groovy, or other programming languages. This program code can run entirely on the user's computer, or run on the user's computer as an independent software package, or run partially on the user's computer and partially on a remote computer, or run entirely on a remote computer or server. In the latter case, the remote computer can be connected to the user's computer through any network form, such as a local area network (LAN) or a wide area network (WAN), or connected to an external computer (e.g., through the Internet), or in a cloud computing environment, or used as a service such as software as a service (SaaS).

[0091] In addition, unless clearly stated in the claims, the order of the processing elements and sequences, the use of numerical letters, or the use of other names in this application is not used to limit the order of the processes and methods of this application. Although some currently considered useful embodiments of the invention are discussed through various examples in the above disclosure, it should be understood that such details only serve the purpose of illustration, and the appended claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that conform to the essence and scope of the embodiments of this application. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only through software solutions, such as installing the described system on an existing server or mobile device.

[0092] Similarly, it should be noted that, in order to simplify the expression of the disclosure of this application and thus help the understanding of one or more embodiments of the invention, in the previous description of the embodiments of this application, sometimes multiple features are merged into one embodiment, drawing, or description thereof. However, this disclosure method does not mean that the features required by the object of this application are more than those mentioned in the claims. In fact, the features of the embodiments are less than all the features of the individual embodiments disclosed above.

[0093] In some embodiments, numbers are used to describe components and the quantity of attributes. It should be understood that such numbers used in the description of embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the said numbers allow for adaptive variations. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, and such approximate values may vary according to the characteristics required by individual embodiments. In some embodiments, the numerical parameters should consider the specified significant digits and adopt the method of retaining the general number of digits. Although the numerical ranges and parameters used in some embodiments of the present application to confirm the breadth of their scope are approximate values, in specific embodiments, such numerical settings are as precise as possible within the feasible range.

[0094] For each patent, patent application, patent application publication, and other materials cited in the present application, such as articles, books, specifications, publications, documents, etc., their entire contents are hereby incorporated into the present application by reference. Except for the application history documents that are inconsistent with or conflict with the content of the present application, and except for the documents that limit the broadest scope of the claims of the present application (currently or subsequently attached to the present application). It should be noted that if there are inconsistencies or conflicts between the descriptions, definitions, and / or uses of terms in the attached materials of the present application and the content described in the present application, the descriptions, definitions, and / or uses of terms in the present application shall prevail.

[0095] Finally, it should be understood that the embodiments described in the present application are only used to illustrate the principles of the embodiments of the present application. Other variations may also fall within the scope of the present application. Therefore, by way of example and not limitation, alternative configurations of the embodiments of the present application may be considered to be consistent with the teachings of the present application. Accordingly, the embodiments of the present application are not limited to the embodiments explicitly introduced and described in the present application.

[0096] The above are only the embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. A method for processing communication delay based on virtual reality, characterized in that, the method at least includes: obtaining the to-be-processed communication description content covering the target communication interaction data; obtaining the associated reference to-be-processed communication description content from the sample to-be-processed communication description content clusters in combination with the attribute information of the to-be-processed communication description content; the sample to-be-processed communication description content in the sample to-be-processed communication description content clusters covers the target communication interaction data; performing convolution processing on the to-be-processed communication description content and the reference to-be-processed communication description content to generate a first key information cluster corresponding to the to-be-processed communication description content and a second key information cluster corresponding to the reference to-be-processed communication description content; both the first key information cluster and the second key information cluster include communication tags and important indications of the types of target communication interaction data. The important indications of the communication tags in the first key information cluster and the second key information cluster are obtained by determining the to-be-processed communication description content and the reference to-be-processed communication description content as the input information delay optimization thread of the to-be-processed communication description content binary group and obtaining the transition processing result of the information delay optimization thread. The information delay optimization thread is configured based on the communication cycles with the same information difference and different information differences; determining the correlation degree between the first key information cluster and the second key information cluster, and determining the information similarity of the target communication interaction data in the to-be-processed communication description content and the reference to-be-processed communication description content in combination with the correlation degree; determining the information delay optimization result of the target communication interaction data in the to-be-processed communication description content in combination with the information similarity.

2. The method according to claim 1, characterized in that, the obtaining the associated reference to-be-processed communication description content from the sample to-be-processed communication description content clusters in combination with the attribute information of the to-be-processed communication description content includes: determining the time difference between the attribute information of the to-be-processed communication description content and the attribute information of each sample to-be-processed communication description content; determining the sample to-be-processed communication description content with the time difference lower than the specified determination value as the reference to-be-processed communication description content.

3. The method according to claim 1, characterized in that, the performing convolution processing on the to-be-processed communication description content and the reference to-be-processed communication description content to generate a first key information cluster corresponding to the to-be-processed communication description content and a second key information cluster corresponding to the reference to-be-processed communication description content includes: inputting the to-be-processed communication description content and the reference to-be-processed communication description content into the configured communication cycle information difference convolution processing sub-thread, performing convolution processing on the to-be-processed communication description content based on the first convolution processing method of the communication cycle information difference convolution processing sub-thread to obtain the corresponding first information difference feature, and loading the first information difference feature into the first key information cluster; Performing convolution processing on the reference communication description content to be processed according to the second convolution processing method of the communication cycle information difference convolution processing sub-thread to obtain a corresponding second information difference feature, and loading the second information difference feature into the second key information cluster; The communication cycle information difference convolution processing sub-thread is a sub-thread in the information delay optimization thread, and the information delay optimization thread is used to determine the communication cycle information difference association result according to the important indication information output by the communication cycle information difference convolution processing sub-thread.

4. The method according to claim 3, wherein, Each convolution processing method includes a number of convolution processing units. Each convolution processing unit in the same convolution processing method is combined in sequence, and the data processing process of the convolution processing method is realized through the following steps: Obtaining the information difference feature corresponding to the real-time input communication cycle based on the important indication communication cycle output by each convolution processing unit; The input data of the real-time convolution processing unit includes the real-time input communication cycle and the important indication communication cycle output by each convolution processing unit before the real-time convolution processing unit.

5. The method according to claim 3, wherein, The configuration process of the information delay optimization thread is realized through the following steps: Obtaining a configuration example cluster; The configuration example cluster includes a configuration communication cycle pair and a corresponding configuration indication. The configuration communication cycle pair includes a first configuration communication cycle and a second configuration communication cycle, and the configuration indication includes information difference being the same and information difference being different; Determining the first configuration communication cycle and the second configuration communication cycle as the inputs of the corresponding convolution processing methods in the information delay optimization thread to be configured respectively, and generating a first configuration information difference feature corresponding to the first configuration communication cycle and a second configuration information difference feature corresponding to the second configuration communication cycle; Determining the important indication difference between the first configuration information difference feature and the second configuration information difference feature; Combining the configuration indication and the feature difference to determine a quantization evaluation vector, and debugging the thread variables of the information delay optimization thread in combination with the quantization evaluation vector until the specified requirements are met, so as to obtain the configured information delay optimization thread.

6. The method according to claim 1, wherein, The performing convolution processing on the communication description content to be processed and the reference communication description content to be processed to generate a first key information cluster corresponding to the communication description content to be processed and a second key information cluster corresponding to the reference communication description content to be processed includes: Loading the communication description content to be processed and the reference communication description content to be processed into the configured target communication interaction data convolution processing thread one by one to generate target communication interaction data features corresponding to the communication description content to be processed and the reference communication description content to be processed respectively; Loading the target communication interaction data feature corresponding to the communication description content to be processed into the first key information cluster, and loading the target communication interaction data feature corresponding to the reference communication description content to be processed into the second key information cluster.

7. The method according to claim 6, wherein, The method further includes: Loading the to-be-processed communication description content and the reference to-be-processed communication description content into a configured convolution processing thread for derivative communication data one by one, to generate derivative communication data features corresponding to the to-be-processed communication description content and the reference to-be-processed communication description content respectively; Generating matching derivative features of corresponding target communication interaction data features based on the derivative communication data features corresponding to the same to-be-processed communication description content, to generate matching derivative features corresponding to the to-be-processed communication description content and the reference to-be-processed communication description content respectively; Loading the matching derivative features corresponding to the to-be-processed communication description content into the first key information cluster, and loading the matching derivative features corresponding to the reference to-be-processed communication description content into the second key information cluster; Wherein, the target communication interaction data features include at least one first cycle feature of target communication interaction data, the derivative communication data features include at least one reference cycle feature of derivative communication data, and generating matching derivative features of corresponding target communication interaction data features based on the derivative communication data features corresponding to the same to-be-processed communication description content includes: Differentiating the real-time to-be-processed communication description content based on the reference cycle feature of each derivative communication data corresponding to the real-time to-be-processed communication description content, to obtain each to-be-determined semantic segment and the corresponding segment cycle feature; The real-time to-be-processed communication description content is the to-be-processed communication description content or the reference to-be-processed communication description content; Associating the first cycle feature of each target communication interaction data in the real-time to-be-processed communication description content with the segment cycle feature of each to-be-determined semantic segment, and determining the to-be-determined semantic segment corresponding to each target communication interaction data according to the association result; Generating a second cycle feature of each target communication interaction data based on the segment cycle feature of the to-be-determined semantic segment corresponding to each target communication interaction data; Combining the second cycle features of each target communication interaction data in the real-time to-be-processed communication description content to generate matching derivative features of corresponding target communication interaction data features.

8. The method according to claim 1, characterized in that The convolving the to-be-processed communication description content and the reference to-be-processed communication description content to generate a first key information cluster corresponding to the to-be-processed communication description content and a second key information cluster corresponding to the reference to-be-processed communication description content includes: Combining the communication cycle label of the to-be-processed communication description content to generate a first communication cycle feature corresponding to the to-be-processed communication description content, and loading the first communication cycle feature into the first key information cluster; Combining the communication cycle label of the reference to-be-processed communication description content to generate a second communication cycle feature corresponding to the reference to-be-processed communication description content, and loading the second communication cycle feature into the second key information cluster.

9. The method according to claim 1, characterized in that Determining the correlation degree between the first key information cluster and the second key information cluster, and determining the information similarity of the target communication interaction data in the communication description content to be processed and the reference communication description content to be processed in combination with the correlation degree, includes: Inputting the first key information cluster and the second key information cluster into a configured correlation degree evaluation thread to generate the correlation degree; When the correlation degree is greater than the correlation degree determination value, determining that the information similarity is the same; When the correlation degree is lower than the correlation degree determination value, determining that the information similarity is different.

10. The method according to claim 1, wherein, when there are no less than two reference communication description contents to be processed, for the second key information clusters having a mapping relationship with each reference communication description content to be processed, and the information similarity between the communication description content to be processed and each reference communication description content to be processed, determining the information delay optimization result of the target communication interaction data in the communication description content to be processed in combination with the information similarity, includes: when no less than one information similarity is the same, determining that the information delay optimization result is that the target communication interaction data remains unchanged; otherwise, determining that the information delay optimization result is that the target communication interaction data changes.

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