Internet television program source poor quality positioning method and device

Abstract

The invention relates to the technical field of poor quality positioning, and provides an Internet television program source poor quality positioning method and device. The method comprises the following steps: carrying out service dial testing on a program source data stream, and generating a program source potential quality abnormity alarm; carrying out soft probe acquisition on the program source quality data to generate a program source quality excellent rate; performing time sequence correlation on the program source potential quality abnormity alarm and the program source quality excellent rate, and identifying a program source poor quality event; performing simulation dial testing on the program source poor-quality event on the program source data stream to generate a program source poor-quality simulation result; and generating a program source poor quality positioning result based on the program source potential quality abnormity alarm, the program source quality excellent rate and the program source poor quality simulation result. According to the method and the device, the efficiency and the accuracy of poor quality positioning can be effectively improved, serious influence on user experience is avoided, and subsequent countermeasures can be abandoned when it is accurately determined that the user does not perceive poor quality of the program source actually, so that unnecessary resource waste is avoided.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of quality difference positioning, and particularly relates to an Internet television program source quality difference positioning method and device. BACKGROUND

[0002] With the rapid growth of Internet television business users, the demand of the majority of users for high-resolution content resource playing is also rapidly growing. In order to improve the viewing experience of user families, it is necessary to effectively position the quality difference of Internet television program sources, so as to take timely measures to ensure the quality of Internet television program sources.

[0003] The current program source quality difference positioning method is realized by manual re-investigation after receiving user complaints, which results in low efficiency and accuracy of quality difference positioning, and has caused serious impact on user experience. Some methods cannot evaluate the actual perception of users on program source quality difference, and taking measures to deal with program source quality difference in the case that users have not actually perceived the quality difference of program sources will result in unnecessary waste of resources.

[0004] In summary, the current program source quality difference positioning method has low efficiency and accuracy of quality difference positioning, and has caused serious impact on user experience. Some methods will result in unnecessary waste of resources. SUMMARY

[0005] The embodiments of the present application provide an Internet television program source quality difference positioning method and device to solve the technical problem that the current program source quality difference positioning method has low efficiency and accuracy of quality difference positioning, and has caused serious impact on user experience, and some methods will result in unnecessary waste of resources.

[0006] In a first aspect, the embodiments of the present application provide an Internet television program source quality difference positioning method, which comprises: performing service dialing on program source data streams to generate program source potential quality abnormality alarms; performing soft probe collection on program source quality data to generate program source quality good rate; performing time sequence association on the program source potential quality abnormality alarms and the program source quality good rate to identify program source quality difference events; performing simulation dialing on program source data streams on the program source quality difference events to generate program source quality difference simulation results; generating program source quality difference positioning results based on the program source potential quality abnormality alarms, the program source quality good rate and the program source quality difference simulation results.

[0007] In one embodiment, the performing soft probe collection on program source quality data to generate program source quality good rate comprises: slice the program source quality data according to a first time granularity to obtain a plurality of first-granularity slices; For each first-granularity slice in the plurality of first-granularity slices, calculate a ratio of a non-defective user number corresponding to non-defective data to a total user number corresponding to all data, to obtain a program source quality good rate on each first-granularity slice.

[0008] In one embodiment, after obtaining the program source quality good rate on each first-granularity slice, the method comprises: slice the program source quality data according to a second time granularity to obtain a plurality of second-granularity slices; the second time granularity is greater than the first time granularity; For each second-granularity slice in the plurality of second-granularity slices, obtain a plurality of matching first-granularity slices included therein; sum the non-defective user numbers corresponding to each matching first-granularity slice to obtain a total non-defective user number; sum the total user numbers corresponding to each matching first-granularity slice to obtain a total total user number; calculate a ratio of the total non-defective user number to the total total user number to obtain a program source quality good rate on each second-granularity slice.

[0009] In one embodiment, the method of time-series associating the program source potential quality abnormality alarm with the program source quality good rate to identify a program source quality deterioration event comprises: obtain a change trend of the program source quality good rate corresponding to the occurrence time of the program source potential quality abnormality alarm and time periods before and after the occurrence time; identify a program source quality deterioration event based on the change trend.

[0010] In one embodiment, the method of obtaining a change trend of the program source quality good rate corresponding to the occurrence time of the program source potential quality abnormality alarm and time periods before and after the occurrence time comprises: obtain program source quality good rates on target-granularity slices corresponding to the occurrence time, a time period before the occurrence time, and a time period after the occurrence time, to obtain a first quality good rate, a second quality good rate, and a third quality good rate; respectively calculate change rate absolute values between the first quality good rate and the second quality good rate and the third quality good rate to obtain the change trend.

[0011] In one embodiment, the method of identifying a program source quality deterioration event based on the change trend comprises: determine that there is a program source quality difference event in a target time period between the previous time point and the occurrence time point when an absolute value of a change rate between the first quality good rate and the second quality good rate is greater than an absolute value threshold; and / or determine that there is a program source quality difference event in a target time period between the occurrence time point and the next time point when an absolute value of a change rate between the first quality good rate and the third quality good rate is greater than an absolute value threshold.

[0012] In an embodiment, the simulating and testing of the program source data stream for the program source quality difference event generates a program source quality difference simulation result, including: obtaining a target data stream in the target time period from the program source data stream; simulating and testing the target data stream to generate a program source quality difference simulation result.

[0013] In a second aspect, an embodiment of the present application provides an internet television program source quality difference positioning device, including: a testing module, configured to: test a program source data stream for service, and generate a program source potential quality abnormality alarm; a soft probe collection module, configured to: collect soft probe for program source quality data, and generate a program source quality good rate; a centralized application module, configured to: time sequence correlate the program source potential quality abnormality alarm and the program source quality good rate, and identify a program source quality difference event; a testing module, configured to: simulate and test the program source data stream for the program source quality difference event, and generate a program source quality difference simulation result; a centralized application module, configured to: based on the program source potential quality abnormality alarm, the program source quality good rate, and the program source quality difference simulation result, generate a program source quality difference positioning result.

[0014] In a third aspect, an embodiment of the present application provides an electronic device, including a processor and a memory storing a computer program, and the processor implements steps of the internet television program source quality difference positioning method of the first aspect when executing the program.

[0015] In a fourth aspect, an embodiment of the present application provides a computer program product, including a computer program, and the computer program implements steps of the internet television program source quality difference positioning method of the first aspect when executed by a processor.

[0016] In a fifth aspect, an embodiment of the present application provides a non-transitory computer readable storage medium, including a computer program, and the computer program implements steps of the internet television program source quality difference positioning method of the first aspect when executed by a processor.

[0017] The Internet TV program source quality poor location method and apparatus provided in this application perform service testing on the program source data stream, generate potential quality anomaly alarms for the program source, collect program source quality data using soft probes, generate a program source quality excellence rate, correlate the potential quality anomaly alarms with the program source quality excellence rate in a time sequence, identify program source quality poor events, perform simulation testing on the program source data stream for program source quality poor events, obtain program source quality poor simulation results, and generate program source quality poor location results based on the potential quality anomaly alarms, the program source quality excellence rate, and the program source quality poor simulation results. This application identifies potential quality anomalies in program sources through business dialing tests and generates alarms for potential quality anomalies. It also collects program source quality data viewed by users using soft probes and generates a program source quality excellence rate. The alarms for potential quality anomalies are then correlated with this excellence rate in a time sequence. Since the excellence rate can be used to assess users' actual perception of potential quality anomalies (i.e., poor program source quality), a poor program source quality event can be identified when a potential quality anomaly occurs and users actually perceive it. By triggering a simulated dialing test for this event, a post-event review of the program source is simulated, further verifying the user's actual perception of the poor program source quality and generating simulation results. Finally, by integrating and analyzing the alarms for potential quality anomalies, the excellence rate, and the simulation results, a precise location of the poor program source quality can be obtained. In summary, this application, on the one hand, eliminates the need for manual reverse investigation based on user complaints, effectively improving the efficiency and accuracy of poor quality location and avoiding serious impact on user experience. On the other hand, it can assess users' actual perception of poor program source quality through the program source quality excellence rate, and further verify users' actual perception of poor program source quality through simulated dialing. Thus, when it is accurately determined that users have not actually perceived poor program source quality, subsequent countermeasures can be abandoned, thereby avoiding unnecessary waste of resources. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is one of the flowcharts illustrating the method for locating poor quality Internet TV program sources provided in this application embodiment; Figure 2 This is a second schematic flowchart of the Internet TV program source quality poor location method provided in the embodiments of this application; Figure 3 is a service quality index schematic diagram of a program source data stream in a poor-quality program source positioning method provided by an embodiment of the present application; Figure 4 is a third flow schematic diagram of a poor-quality program source positioning method provided by an embodiment of the present application; Figure 5 is a fourth flow schematic diagram of a poor-quality program source positioning method provided by an embodiment of the present application; Figure 6 is an interaction schematic diagram of various modules in a poor-quality program source positioning device provided by an embodiment of the present application; Figure 7 is a structural schematic diagram of an electronic device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0020] To make the objectives, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some embodiments but not all embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the scope of protection of the present application.

[0021] Figure 1 is a first flow schematic diagram of a poor-quality program source positioning method provided by an embodiment of the present application. With reference to Figure 1 , an embodiment of the present application provides a poor-quality program source positioning method, which can include: 101. performing service dialing on a program source data stream to generate a program source potential quality anomaly alarm; 102. performing soft probe collection on program source quality data to generate a program source quality good rate; 103. performing time sequence association on the program source potential quality anomaly alarm and the program source quality good rate to identify a program source poor-quality event; 104. performing simulation dialing on the program source data stream for the program source poor-quality event to generate a program source poor-quality simulation result; 105. generating a program source poor-quality positioning result based on the program source potential quality anomaly alarm, the program source quality good rate and the program source poor-quality simulation result.

[0022] With reference to Figure 2The Internet TV program source provides a program source data stream, which can be a live streaming data, and synchronizes the program source data stream to a content distribution network in real time through a license holder switch. The content distribution network caches the program source data stream for user calling. The user requests and calls the program source data stream from the content distribution network through a set top box. The content distribution network distributes the program source data stream to the set top box. The set top box decodes the program source data stream and outputs it to the user's TV screen for the user to watch. The set top box records the program source quality data of the program source data stream in real time during operation.

[0023] In step 101, the service of the program source data stream flowing through the license holder switch is tested. The service quality indicators of the program source data stream under each program source identifier are focused on, such as video encoding type, audio encoding type, throughput rate, TS (Transport Stream) packet loss rate, CC (Continuity Counter) error, health degree, VMOS (Video Mean Opinion Score) value, screen flashing frequency, screen flashing time, flow interruption time, flow interruption frequency, etc. As shown in FIG. 1, potential quality abnormal events such as "black screen", "static frame" and "screen flashing" are identified, and potential quality abnormal alarms are generated based on the potential quality abnormal events. Figure 3

[0024] In step 102, the program source quality data recorded in the set top box is collected by a soft probe. The program source quality data is analyzed and calculated to generate a program source quality good rate.

[0025] In step 103, the potential quality abnormal alarm can be used as a trigger condition. Based on the program source identifier, the potential quality abnormal alarm and the quality good rate corresponding to each program source are time-series associated. If the large fluctuations of the potential quality abnormal alarm and the quality good rate corresponding to a program source occur in the same period, it can be confirmed that the potential quality abnormality of the program source actually exists and can be actually perceived by the user. Therefore, the potential quality abnormal event of the program source in the same period can be confirmed as a program source quality poor event, and the occurrence period, program source identifier, affected user number and affected duration of the program source quality poor event are output.

[0026] In step 104, the program source data stream in the occurrence period of the program source quality poor event in the content distribution network is simulated and tested to further verify the actual perception of the user to the program source quality poor, i.e. whether the user perceives "black screen", "static frame", "screen flashing" and the like and the degree of perception, and form a program source quality poor simulation result.

[0027] ​In step 105, the potential quality anomaly alarm of the program source, the quality good rate of the program source and the poor quality simulation result of the program source are integrated and analyzed to generate a poor quality positioning result of the program source, to determine whether to take countermeasures, and to guide the execution of the countermeasures when it is determined to take the countermeasures. The countermeasures can include complaint preprocessing, fault handling and cost settlement, etc.

[0028] The internet television program source poor quality positioning method provided by the embodiment can perform service dialing on the program source data stream, generate a program source potential quality anomaly alarm, perform soft probe collection on the program source quality data, generate a program source quality good rate, perform time sequence correlation on the program source potential quality anomaly alarm and the program source quality good rate, identify a program source poor quality event, perform simulation dialing on the program source data stream to obtain a program source poor quality simulation result, and generate a program source poor quality positioning result based on the program source potential quality anomaly alarm, the program source quality good rate and the program source poor quality simulation result. The embodiment can identify a possible program source potential quality anomaly event through service dialing, and generate a program source potential quality anomaly alarm. The program source quality data of user viewing is obtained through soft probe collection, and a program source quality good rate is generated. The program source potential quality anomaly alarm and the program source quality good rate are time sequence correlated. Since the program source quality good rate can be used to evaluate the actual perception of the user to the program source potential quality anomaly, i.e., the program source poor quality, the program source poor quality event can be identified when the program source has a potential quality anomaly and the user actually perceives the anomaly. The simulation dialing for the program source poor quality event is triggered to simulate the after-look at the program source, so as to further verify the actual perception of the user to the program source poor quality, and generate a program source poor quality simulation result. Then, the program source potential quality anomaly alarm, the program source quality good rate and the program source poor quality simulation result can be integrated and analyzed to obtain an accurate program source poor quality positioning result. In summary, on the one hand, the embodiment can effectively improve the efficiency and accuracy of poor quality positioning without manual recheck based on user complaints, and avoid serious impact on user experience. On the other hand, the actual perception of the user to the program source poor quality can be evaluated through the program source quality good rate, and the actual perception of the user to the program source poor quality can be further verified through simulation dialing, so that the subsequent countermeasures can be abandoned when it is accurately determined that the user does not actually perceive the program source poor quality, thereby avoiding unnecessary waste of resources.

[0029] Further, the embodiment can accurately monitor and position the program source quality by integrating the data of service dialing, soft probe collection and simulation dialing, to identify and position the monitoring blind spot of the program source technical level and transmission link without problems but with business quality problems.

[0030] Figure 4Fig. 3 is a flowchart of a third method for positioning poor-quality program sources of an Internet TV according to an embodiment of the present application. Referring to Fig. 3, the method comprises the following steps. Figure 4 In one embodiment, soft-probe collection of program source quality data and generation of a good-quality rate of program sources can comprise: 401. Slice the program source quality data according to a first time granularity to obtain a plurality of first-granularity slices. 402. For each first-granularity slice of the plurality of first-granularity slices, calculate the ratio of the number of non-defective users to the total number of users corresponding to all data, to obtain the good-quality rate of program sources on each first-granularity slice.

[0031] In step 401, the first time granularity can be set according to actual requirements, which is not limited herein. In the present embodiment, the first time granularity can be set to 5 minutes, i.e., each first-granularity slice is a 5-minute slice of program source quality data.

[0032] In step 402, each first-granularity slice includes program source quality data of a plurality of users and a plurality of program sources. The number of users with quality problems in the program source quality data in the first-granularity slice can be counted as the number of defective users, the number of users corresponding to all program source quality data in the first-granularity slice can be counted as the total number of users, the ratio of the number of defective users to the total number of users corresponding to the same program source can be calculated, and 1 minus the ratio can be obtained as the good-quality rate of program sources of each program source on the first-granularity slice. The good-quality rate of program sources of each program source on other first-granularity slices can be obtained in the same way, which is not described herein.

[0033] Further, after obtaining the good-quality rate of program sources of each program source on each first-granularity slice, the method can further comprise: Slice the program source quality data according to a second time granularity to obtain a plurality of second-granularity slices. The second time granularity is greater than the first time granularity. For each second-granularity slice of the plurality of second-granularity slices, obtain a plurality of matching first-granularity slices included therein. Sum the number of non-defective users corresponding to each matching first-granularity slice to obtain the total number of non-defective users. Sum the total number of users corresponding to each matching first-granularity slice to obtain the total number of users. Calculate the ratio of the total number of non-defective users to the total number of users to obtain the good-quality rate of program sources on each second-granularity slice.

[0034] That is, if a time granularity greater than 5 minutes is required, for example, 1 hour, each second granularity slice is a program source quality data slice with a length of 1 hour, and 12 matched first granularity slices are included in each second granularity slice, for example, in the second granularity slice from 18:00 to 19:00 of a day, 12 matched first granularity slices from 18:00:00 to 18:00:05, 18:00:05 to 18:00:10, 18:00:10 to 18:00:15, 18:00:15 to 18:00:20, 18:00:20 to 18:00:25, 18:00:25 to 18:00:30, 18:00:30 to 18:00:35, 18:00:35 to 18:00:40, 18:00:40 to 18:00:45, 18:00:45 to 18:00:50, 18:00:50 to 18:00:55, 18:00:55 to 18:01:00 are included.

[0035] The quality difference user numbers corresponding to the 12 first granularity slices are summed to obtain the total quality difference user number, the total quantity user numbers corresponding to the 12 first granularity slices are summed to obtain the total quantity user number, the ratio of the total quality difference user number to the total quantity user number corresponding to the same program source is calculated, and then 1 is subtracted from the ratio to obtain the program source quality good rate of each program source on the second granularity slice; the program source quality good rates of each program source on other second granularity slices can be obtained in the same way, which will not be described here. Taking the four second granularity slices from 19:00 to 22:00 of the 31st of a year as an example, the program source quality good rate and the total quality difference user number of the program source XXX thereon can be shown in the following table: Table 1 Program source quality good rate and total quality difference user number table

[0036] Among them, the data of 19:00 of the 31st is the data of the second granularity slice from 18:00 of the 31st to 19:00 of the 31st, the data of 20:00 of the 31st is the data of the second granularity slice from 19:00 of the 31st to 20:00 of the 31st, the data of 21:00 of the 31st is the data of the second granularity slice from 20:00 of the 31st to 21:00 of the 31st, and the data of 22:00 of the 31st is the data of the second granularity slice from 21:00 of the 31st to 22:00 of the 31st.

[0037] The embodiment can accurately measure the influence degree of the program source quality difference on the user, and thus accurately obtain the program source quality good rate of each small time granularity slice, by slicing the program source quality data of all network users according to a small time granularity, obtaining a plurality of small time granularity slices, and calculating the ratio of the non-defective user number to the total user number on each small time granularity slice. When a larger time granularity is faced, a plurality of matching first granularity slices included in the corresponding larger time granularity slice can be directly obtained, the non-defective user number and the total user number corresponding to the first granularity slices are summed respectively, and the ratio after the summing is calculated, so that the program source quality good rate of each larger time granularity slice can be conveniently and accurately obtained.

[0038] Figure 5 FIG. 4 is a flowchart of an Internet television program source quality difference positioning method provided by an embodiment of the present application. Referring to FIG. 4, Figure 5 In one embodiment, the program source potential quality anomaly alarm and the program source quality good rate are time-series associated, and the program source quality difference event is identified, which can include: 501. Obtain the change trend of the program source quality good rate corresponding to the occurrence time of the program source potential quality anomaly alarm and the time before and after the occurrence time; 502. Identify the program source quality difference event based on the change trend.

[0039] Step 501 specifically includes: 501a. Obtain the program source quality good rate on the target granularity slice corresponding to the occurrence time, the time before the occurrence time and the time after the occurrence time, to obtain a first quality good rate, a second quality good rate and a third quality good rate; 501b. Calculate the change rate absolute value between the first quality good rate and the second quality good rate and the third quality good rate respectively, to obtain the change trend.

[0040] Referring to Table 1, it is assumed that 20:00 on the 31st is the occurrence time of the program source potential quality anomaly alarm, then 19:00 on the 31st is the time before the occurrence time, and 21:00 on the 31st is the time after the occurrence time.

[0041] In step 501a, the program source potential quality anomaly alarm corresponding to the identifier of the program source XXX is associated with the program source quality good rate corresponding to the identifier of the program source XXX at the occurrence time, the time before the occurrence time and the time after the occurrence time of the program source XXX, wherein the first quality good rate is 99.73%, the second quality good rate is 99.99%, and the third quality good rate is 99.98%.

[0042] In step 501b, the absolute values of the change rates between 99.73% and 99.99% and between 99.73% and 99.98% are calculated, i.e., the absolute value of (99.73%-99.99%) / 99.99% is calculated to be 0.26%, and the absolute value of (99.98%-99.73%) / 99.73% is calculated to be 0.25%.

[0043] In step 502, the following steps are specifically included: When the absolute value of the change rate between the first quality good rate and the second quality good rate is greater than the absolute value threshold, it is determined that there is a program source quality difference event in the target period between the previous time and the occurrence time; and / or when the absolute value of the change rate between the first quality good rate and the third quality good rate is greater than the absolute value threshold, it is determined that there is a program source quality difference event in the target period between the occurrence time and the next time.

[0044] That is, when 0.26% is greater than the absolute value threshold, it can be determined that the fluctuation of the program source quality good rate of the program source XXX in the target period between 19:00 on the 31st and 20:00 on the 31st has a perceptual impact on the user, and it is determined that there is a program source quality difference event of the program source XXX in the target period, triggering the simulation dialing, when 0.26% is not greater than the absolute value threshold, it can be determined that the fluctuation of the program source quality good rate of the program source XXX in the target period between 19:00 on the 31st and 20:00 on the 31st does not have a perceptual impact on the user, and the process is ended; and / or when 0.25% is greater than the absolute value threshold, it can be determined that the fluctuation of the program source quality good rate of the program source XXX in the target period between 20:00 on the 31st and 21:00 on the 31st has a perceptual impact on the user, and it is determined that there is a program source quality difference event of the program source XXX in the target period, triggering the simulation dialing, when 0.25% is not greater than the absolute value threshold, it can be determined that the fluctuation of the program source quality good rate of the program source XXX in the target period between 20:00 on the 31st and 21:00 on the 31st does not have a perceptual impact on the user, and the process is ended.

[0045] The embodiment is based on the time sequence association of the program source potential quality abnormality alarm triggering and the program source quality good rate, calculates the absolute values of the change rates of the program source quality good rate between the occurrence time of the program source potential quality abnormality alarm and the time before and after the occurrence time, and screens out the target period with a large fluctuation of the program source quality good rate, i.e., the target period that has a perceptual impact on the user, by the absolute value threshold, the target period including the occurrence time of the program source potential quality abnormality alarm, so that it can be determined that the program source has a potential quality abnormality and the user actually perceives the abnormality, and then the program source quality difference event in the target period can be accurately determined.

[0046] In one embodiment, the simulation testing of the program source quality degradation event on the program source data stream generates a program source quality degradation simulation result, which can include: The target data stream in the target period is obtained from the program source data stream, and the simulation testing is performed on the target data stream to generate a program source quality degradation simulation result.

[0047] In this embodiment, the program source corresponding to the program source quality degradation event, for example, the program source XXX in Table 1, is intercepted in the target period of the quality degradation event, and the program source data stream is used as a target data stream for simulation testing. The simulation testing simulates the user's viewing of the program source XXX in the target period, further verifies the actual perception of the user to the program source quality degradation of the program source XXX, and helps to improve the accuracy of the subsequent program source quality degradation positioning result.

[0048] The Internet television program source quality degradation positioning device provided by the embodiments of the present application is described below. The Internet television program source quality degradation positioning device described below can be correspondingly referred to the Internet television program source quality degradation positioning method described above.

[0049] The embodiments of the present application provide an Internet television program source quality degradation positioning device, which can include: The testing module is configured to perform service testing on the program source data stream to generate a program source potential quality anomaly alarm. The soft probe collection module is configured to perform soft probe collection on the program source quality data to generate a program source quality good rate. The centralized application module is configured to time sequence correlate the program source potential quality anomaly alarm and the program source quality good rate to identify a program source quality degradation event. The testing module is configured to perform simulation testing of the program source quality degradation event on the program source data stream to generate a program source quality degradation simulation result. The centralized application module is configured to generate a program source quality degradation positioning result based on the program source potential quality anomaly alarm, the program source quality good rate, and the program source quality degradation simulation result.

[0050] The Internet television program source poor quality positioning device provided by the embodiment performs service dialing on the program source data stream, generates a program source potential quality abnormality alarm, performs soft probe collection on the program source quality data, generates a program source quality good rate, performs time sequence association on the program source potential quality abnormality alarm and the program source quality good rate, identifies a program source poor quality event, performs simulation dialing on the program source data stream for the program source poor quality event, obtains a program source poor quality simulation result, and generates a program source poor quality positioning result based on the program source potential quality abnormality alarm, the program source quality good rate, and the program source poor quality simulation result. The embodiment identifies a possible program source potential quality abnormality event through service dialing, generates a program source potential quality abnormality alarm, acquires program source quality data viewed by a user through soft probe collection, and generates a program source quality good rate. The program source quality good rate can be used to evaluate the actual perception of the user to the program source potential quality abnormality, that is, the actual perception of the user to the program source poor quality. Therefore, the program source poor quality event can be identified when the program source has a potential quality abnormality and the user actually perceives the abnormality. Simulation dialing for the program source poor quality event is triggered to simulate the after-look of the program source, thereby further verifying the actual perception of the user to the program source poor quality and generating a program source poor quality simulation result. Further, accurate program source poor quality positioning results can be obtained through integrated analysis of the program source potential quality abnormality alarm, the program source quality good rate, and the program source poor quality simulation result. In summary, the embodiment can improve the efficiency and accuracy of poor quality positioning without manual re-investigation based on user complaints, avoid serious impact on user experience, evaluate the actual perception of the user to the program source poor quality through the program source quality good rate, and further verify the actual perception of the user to the program source poor quality through simulation dialing, thereby abandoning subsequent measures when it is accurately determined that the user does not actually perceive the program source poor quality, and avoiding unnecessary resource waste.

[0051] In one embodiment, the soft probe collection module is specifically configured to: slice the program source quality data according to a first time granularity to obtain a plurality of first granularity slices; for each first granularity slice in the plurality of first granularity slices, calculate a ratio of a number of non-poor quality users corresponding to non-poor quality data to a total number of users corresponding to all data, to obtain a program source quality good rate on each first granularity slice.

[0052] In one embodiment, the soft probe collection module is specifically configured to: slice the program source quality data according to a second time granularity to obtain a plurality of second granularity slices; the second time granularity is greater than the first time granularity; For each second granularity slice in the plurality of second granularity slices, a plurality of matching first granularity slices included therein are obtained; The non-defective user numbers corresponding to each matching first granularity slice are summed up to obtain a total number of non-defective users; The total user numbers corresponding to each matching first granularity slice are summed up to obtain a total number of total users; The ratio of the total number of non-defective users to the total number of total users is calculated to obtain a program source quality good rate on each second granularity slice.

[0053] In one embodiment, the centralized application module is specifically configured to: Obtain the change trend of the program source quality good rate corresponding to the occurrence time of the program source potential quality abnormality alarm and the time before and after the occurrence time; Identify a program source quality defect event based on the change trend.

[0054] In one embodiment, the centralized application module is specifically configured to: Obtain the program source quality good rate on the target granularity slice corresponding to the occurrence time, the time before the occurrence time, and the time after the occurrence time, to obtain a first quality good rate, a second quality good rate, and a third quality good rate; Calculate the absolute value of the change rate between the first quality good rate and the second quality good rate and the third quality good rate, respectively, to obtain the change trend.

[0055] In one embodiment, the centralized application module is specifically configured to: When the absolute value of the change rate between the first quality good rate and the second quality good rate is greater than an absolute value threshold, it is determined that there is a program source quality defect event in a target period between the time before the occurrence time and the occurrence time; and / or When the absolute value of the change rate between the first quality good rate and the third quality good rate is greater than an absolute value threshold, it is determined that there is a program source quality defect event in a target period between the occurrence time and the time after the occurrence time.

[0056] In one embodiment, the dialing test module is specifically configured to: Obtain a target data stream in the target period from the program source data stream; Perform simulation dialing test on the target data stream to generate a program source quality defect simulation result.

[0057] Reference Figure 6 The interaction between each module in the embodiment device can be described as follows: 1. The dialing test module synchronizes the program source data stream of the license plate side switch; 2. The testing module performs service testing on the program source data stream, generates potential quality anomaly alarms for the program source, and pushes them to the centralized application module in real time according to the program source identifier. 3. The content delivery network synchronizes and caches the program source data stream sent by the licensee's switch; 4. Users access program source data streams in the content delivery network through their set-top boxes; 5. The content delivery network distributes the program source data stream to the set-top box, so that the set-top box can decode it and output it to the user's TV screen; 6. The set-top box records the program source quality data of the program source data stream in real time. The soft probe acquisition module performs soft probe acquisition on the program source quality data, generates the program source quality excellence rate, and pushes it to the centralized application module in real time according to the program source identifier. 7. The centralized application module correlates potential quality anomaly alarms of program sources with the program source quality excellence rate in a time sequence to identify poor program source quality events. 8. The centralized application module sends a simulation testing request to the testing module; this request carries information such as the program source identifier and target time period corresponding to the program source quality poor event. 9. The testing module intercepts the program source data stream corresponding to the program source identifier and the target time period within the content delivery network for simulation testing, and generates simulation results of poor program source quality. 10. The test module sends the simulation results of poor program source quality to the centralized application module; 11. The centralized application module performs time-series correlation on the program source potential quality anomaly alarm, the program source quality excellence rate, and the program source poor quality simulation results, and integrates and analyzes them to generate program source poor quality location results.

[0058] Figure 7 This is a schematic diagram of the structure of the electronic device provided in the embodiments of this application, such as... Figure 7 As shown, the electronic device may include: a processor 710, a communication interface 720, a memory 730, and a communication bus 740, wherein the processor 710, the communication interface 720, and the memory 730 communicate with each other via the communication bus 740. The processor 710 can call a computer program stored in the memory 730 to execute the steps of the Internet television program source quality deterioration localization method, such as including: Perform service testing on the program source data stream and generate alarms for potential quality anomalies in the program source. Soft probes are used to collect program source quality data to generate the program source quality excellence rate. The potential quality anomaly alarm of the program source is correlated with the quality excellence rate of the program source in a time sequence to identify poor quality events of the program source. simulate the program source quality difference event on the program source data stream to generate a program source quality difference simulation result; generate a program source quality difference positioning result based on the program source potential quality anomaly alarm, the program source quality good rate, and the program source quality difference simulation result.

[0059] In addition, the logical instructions in the memory 730 described above can be implemented in the form of a software function unit and sold or used as an independent product, and can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0060] On the other hand, the embodiments of the present application also provide a computer program product, which includes a computer program that can be stored on a non-transitory computer readable storage medium, and when the computer program is executed by a processor, the computer can execute the steps of the internet television program source quality difference positioning method provided by the above-mentioned embodiments, for example, including: performing service probing on the program source data stream to generate a program source potential quality anomaly alarm; performing soft probe collection on the program source quality data to generate a program source quality good rate; performing time sequence association on the program source potential quality anomaly alarm and the program source quality good rate to identify a program source quality difference event; simulate the program source quality difference event on the program source data stream to generate a program source quality difference simulation result; generate a program source quality difference positioning result based on the program source potential quality anomaly alarm, the program source quality good rate, and the program source quality difference simulation result.

[0061] On the other hand, the embodiments of the present application also provide a non-transitory computer readable storage medium having a computer program stored thereon, wherein the computer program is used to cause a processor to execute the steps of the internet television program source quality difference positioning method provided by the above-mentioned embodiments, for example, including: performing service probing on the program source data stream to generate a program source potential quality anomaly alarm; The program source quality data is collected by a soft probe to generate a program source quality good rate; The program source potential quality anomaly alarm is time-correlated with the program source quality good rate to identify a program source poor quality event; The program source data stream is simulated to test the program source poor quality event to generate a program source poor quality simulation result; Based on the program source potential quality anomaly alarm, the program source quality good rate and the program source poor quality simulation result, a program source poor quality positioning result is generated.

[0062] The non-transitory computer readable storage medium can be any available medium or data storage device that the processor can access including, but not limited to, a magnetic storage (e.g., floppy disks, hard disks, tape, MO, etc.), optical storage (e.g., CD, DVD, BD, HVD, etc.), and semiconductor storage (e.g., ROM, EPROM, EEPROM, NAND FLASH, SSD, etc.).

[0063] The device embodiments described above are merely illustrative, wherein the units illustrated as separate components can or can not be physically separated, and the components illustrated as units can or can not be physical units, i.e., they can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purposes of the embodiments according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0064] From the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be realized by means of software plus necessary universal hardware platforms, and of course, can also be realized by hardware. Based on such understanding, the above technical solutions can be embodied in the form of software products, which can be stored in a computer readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and include a number of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0065] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for some technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. An Internet television program source quality poor positioning method, characterized in that, The method comprises: performing service probing on a program source data stream to generate a program source potential quality anomaly alarm; performing soft probe collection on program source quality data to generate a program source quality good rate; performing time sequence correlation between the program source potential quality anomaly alarm and the program source quality good rate to identify a program source poor quality event; performing simulation probing on the program source data stream according to the program source poor quality event to generate a program source poor quality simulation result; and generating a program source poor quality positioning result based on the program source potential quality anomaly alarm, the program source quality good rate, and the program source poor quality simulation result.

2. The method of claim 1, wherein the method further comprises: The method of performing soft probe collection on program source quality data to generate a program source quality good rate comprises: ​ slicing the program source quality data according to a first time granularity to obtain a plurality of first-granularity slices; for each first-granularity slice in the plurality of first-granularity slices, calculating a ratio of a number of non-poor-quality users to a total number of users in the first-granularity slice to obtain a program source quality good rate on each first-granularity slice.

3. The method of claim 2, wherein the step of determining the quality of the Internet television program source comprises the steps of: After obtaining the program source quality good rate on each first-granularity slice, the method comprises: ​ slicing the program source quality data according to a second time granularity to obtain a plurality of second-granularity slices; the second time granularity is greater than the first time granularity; for each second-granularity slice in the plurality of second-granularity slices, obtaining a plurality of matching first-granularity slices included in the second-granularity slice; summing up the numbers of non-poor-quality users corresponding to the matching first-granularity slices to obtain a total number of non-poor-quality users; summing up the total numbers of users corresponding to the matching first-granularity slices to obtain a total number of users; calculating a ratio of the total number of non-poor-quality users to the total number of users to obtain a program source quality good rate on each second-granularity slice.

4. The method of claim 1, wherein the method further comprises: The method of performing time sequence correlation between the program source potential quality anomaly alarm and the program source quality good rate to identify a program source poor quality event comprises: ​ obtaining a change trend of the program source quality good rate corresponding to a time point of occurrence of the program source potential quality anomaly alarm and time points before and after the time point of occurrence; based on the change trend, identifying a program source poor quality event.

5. The method for locating poor quality Internet television program sources according to claim 4, characterized in that, The method of obtaining a change trend of the program source quality good rate corresponding to a time point of occurrence of the program source potential quality anomaly alarm and time points before and after the time point of occurrence comprises: obtaining program source quality good rates on target-granularity slices corresponding to the time point of occurrence, a time point before the time point of occurrence, and a time point after the time point of occurrence to obtain a first quality good rate, a second quality good rate, and a third quality good rate; respectively calculating absolute values of change rates between the first quality good rate and the second quality good rate and the third quality good rate to obtain the change trend.

6. The method of claim 5, wherein the step of determining the quality of the Internet television program source comprises the steps of: The method of identifying a program source poor quality event based on the change trend comprises: ​ when an absolute value of a change rate between the first quality good rate and the second quality good rate is greater than an absolute value threshold, determining that there is a program source poor quality event in a target period between the time point before the time point of occurrence and the time point of occurrence; and / or When an absolute value of a change rate between the first quality good rate and the third quality good rate is greater than an absolute value threshold, it is determined that there is a program source quality difference event in a target period between the occurrence time and the later time.

7. The method of claim 6, wherein the step of determining the quality of the Internet television program source comprises the steps of: The simulation detection of the program source quality difference event on the program source data stream generates a program source quality difference simulation result, and the simulation detection includes: ​ Obtaining target data stream in the target period from the program source data stream; The simulation detection of the program source quality difference event on the program source data stream generates a program source quality difference simulation result, and the simulation detection includes:

8. An Internet television program source quality poor positioning device, characterized in that, It includes: The detection module is used for detecting the program source data stream, and generating a program source potential quality abnormality alarm; The soft probe collection module is used for collecting the program source quality data by a soft probe, and generating a program source quality good rate; The centralized application module is used for time sequence correlation between the program source potential quality abnormality alarm and the program source quality good rate, and identifying a program source quality difference event; The detection module is used for simulating the program source quality difference event on the program source data stream, and generating a program source quality difference simulation result; The centralized application module is used for generating a program source quality difference positioning result based on the program source potential quality abnormality alarm, the program source quality good rate and the program source quality difference simulation result.

9. An electronic device comprising a processor and a memory having a computer program stored therein, characterized in that, The processor executes the computer program to realize the steps of the internet television program source quality difference positioning method in any one of claims 1 to 7.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the internet television program source quality difference positioning method in any one of claims 1 to 7.

11. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the steps of the internet television program source quality difference positioning method in any one of claims 1 to 7.

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