Preheating point position determination method, device and equipment

Abstract

This application relates to the field of intelligent analysis technology, and discloses a method, apparatus, and device for determining pre-hotspot positions, including: determining the playback frequency and first-screen playback time corresponding to each playback point based on historical playback behavior data; selecting candidate pre-hotspot positions from the playback points based on the playback frequency and first-screen playback time; determining the popularity corresponding to each candidate pre-hotspot position based on a popularity parameter; and selecting pre-hotspot positions from the candidate pre-hotspot positions based on their popularity. Because it can quickly determine frequently accessed candidate pre-hotspot positions with long first-screen playback times based on historical playback behavior data analysis, and further select based on the popularity of each candidate pre-hotspot position according to relevant settings, it ensures that reasonable candidate pre-hotspot positions can be selected as pre-hotspot positions, thus achieving automated selection of pre-hotspot positions and reducing the human burden.

Description

Technical Field

[0001] This application relates to the field of intelligent analysis technology, and in particular to a method, apparatus and equipment for determining pre-hot spot locations. Background Technology

[0002] In multi-level network scenarios, if a user wants to view video data of a certain location, the user needs to initiate an image acquisition request. After receiving the image acquisition request, the platform will retrieve the video data through multiple service media network nodes. The transmission of the video data will then go through multiple service media network nodes to reach the platform, and then the platform will send it to the user's device. The overall streaming time is long, which affects the user's viewing experience, especially the first screen loading speed, and there is also the problem of inconsistent playback experience for high-frequency and high-quality locations.

[0003] To address this issue, the relevant technology involves setting up pre-hotspot positions based on human experience and pre-fetching the video data for these positions. This means that the platform retrieves video data from the playback point in advance through the service media network nodes and caches it. This ensures that when a user initiates an image retrieval request, the platform can use the cached data from the pre-fetching process to provide the image first, thereby improving the first-screen loading speed of the pre-hotspot positions and reducing the first-screen loading time.

[0004] However, manually setting preheating hotspots is labor-intensive and inefficient. Furthermore, the actual number of preheating hotspots required can change as users' habits evolve, making it impossible to adjust manually in a timely manner. In addition, manual setting can easily result in too many or too few preheating hotspots, which does not meet the actual preheating needs. Summary of the Invention

[0005] The main purpose of this application is to provide a method, apparatus and equipment for determining preheating hot spots, which aims to solve the technical problems of high cost, low efficiency and inflexible adjustment of preheating hot spots in related technologies, resulting in poor actual results.

[0006] To achieve the above objectives, this application proposes a method for determining pre-hot spot locations, the method comprising:

[0007] Based on historical playback behavior data, determine the playback frequency and first screen playback time corresponding to each playback point. The first screen playback time is the interval between the moment when the user requests to retrieve the image and the moment when the image corresponding to the playback point is first displayed on the user's device. The playback point is a device or apparatus that performs image acquisition at a preset point.

[0008] Candidate pre-hot spots are selected from the playback points based on the playback frequency and the first screen playback time.

[0009] Based on the heat parameters, determine the heat corresponding to each candidate preheating hot spot;

[0010] Pre-hot spots are selected from the candidate pre-hot spots based on their popularity.

[0011] In one possible implementation of this application, the popularity parameter includes playback frequency and first screen playback time;

[0012] The process of determining the popularity of each candidate pre-hot spot based on popularity parameters includes:

[0013] The playback frequency score for each candidate hotspot is determined based on the playback frequency corresponding to the candidate hotspot position, and the first screen playback time score for each candidate hotspot position is determined based on the first screen playback time corresponding to the candidate hotspot position.

[0014] Based on the playback frequency score and the first screen time score, a popularity score is generated for each candidate pre-hot spot. The popularity score is used to characterize the popularity of the candidate pre-hot spot.

[0015] In one possible implementation of this application, the step of determining the playback frequency score corresponding to each candidate hotspot position based on the playback frequency corresponding to the candidate hotspot position, and determining the first-screen playback time score corresponding to each candidate hotspot position based on the first-screen playback time corresponding to the candidate hotspot position, includes:

[0016] The difference between the playback frequency and the frequency threshold of each candidate hotspot is calculated to determine the frequency threshold difference corresponding to each candidate hotspot.

[0017] Determine the target difference range to which the frequency threshold difference of each candidate hotspot bit belongs;

[0018] Determine the target time interval to which the first-screen playback time belongs for each candidate pre-hotspot position;

[0019] Find the interval score corresponding to the target time interval to obtain the first screen time score corresponding to each candidate pre-hot spot, and find the interval score corresponding to the target difference interval to obtain the playback frequency score corresponding to each candidate pre-hot spot.

[0020] In one possible implementation of this application, the popularity parameters include playback frequency, first screen playback time, and preheating boost ratio;

[0021] The process of determining the popularity of each candidate pre-hot spot based on popularity parameters includes:

[0022] Estimate the time required to preheat the first screen for each candidate preheating hotspot;

[0023] The preheating boost ratio corresponding to each candidate preheating hot spot is determined based on the preheating time of the first screen and the playback time of the first screen.

[0024] The popularity of each candidate preheating hotspot is determined based on the preheating boost ratio, the playback frequency, and the first screen time.

[0025] In one possible implementation of this application, the popularity parameters include playback frequency, first-screen playback time, and historical preheating tags;

[0026] The process of determining the popularity of each candidate pre-hot spot based on popularity parameters includes:

[0027] Based on historical preheating records, the historical preheating tags corresponding to each candidate preheating hot spot are determined. The historical preheating tags are used to indicate whether the candidate preheating hot spot was previously selected as a preheating hot spot.

[0028] The popularity of each candidate preheating spot is determined based on the historical preheating tags, the playback frequency, and the first screen time.

[0029] In one possible implementation of this application, determining the popularity of each candidate pre-hot spot based on the popularity parameter includes:

[0030] Determine the importance of each candidate hotspot;

[0031] Determine the correction coefficient corresponding to the importance of the pre-hot spot;

[0032] Determine the heat parameter score for each candidate hot spot, and correct each heat parameter score based on the correction coefficient;

[0033] Based on the corrected scores of each of the aforementioned heat parameters, the heat corresponding to each candidate preheating hot spot is determined.

[0034] In one possible implementation of this application, determining the importance of each candidate pre-hotspot bit includes:

[0035] Obtain the location, setting time, and associated services of each candidate hotspot location;

[0036] The importance level of a location is determined based on its position.

[0037] The importance level of a time is determined based on the location settings.

[0038] Obtain the business importance level corresponding to the business associated with the location;

[0039] The importance level of each candidate hotspot is determined based on the location importance level, the time importance level, and the business importance level. The importance level is used to characterize the importance of the hotspot.

[0040] In one possible implementation of this application, selecting a pre-hotspot position from the candidate pre-hotspot positions based on the popularity score result includes:

[0041] The preheating resource requirement for a single point is estimated based on the preheating resource requirements corresponding to each candidate preheating hot spot. The preheating resource requirement for a single point is the bandwidth resource required to prefetch traffic for a single preheating hot spot.

[0042] The preheating bandwidth resources are determined based on the platform's total resources and the preheating allocation ratio.

[0043] The total number of preheating hotspots is determined based on the preheating bandwidth resources and the single-point preheating resource requirements.

[0044] Pre-hotspot positions are selected from the candidate pre-hotspot positions based on the total number of pre-hotspot positions and the popularity of each candidate pre-hotspot position.

[0045] Furthermore, to achieve the above objectives, this application also proposes a preheating spot location determination device, the device comprising:

[0046] The determination module is used to determine the playback frequency and first screen playback time corresponding to each playback point based on historical playback behavior data. The first screen playback time is the interval between the moment when the user requests to retrieve the image and the moment when the image corresponding to the playback point is first displayed on the user's device. The playback point is a device or apparatus that performs image acquisition at a preset point.

[0047] The filtering module is used to select candidate pre-hot spots from the playback points based on the playback frequency and the first screen playback time;

[0048] The popularity module is used to determine the popularity of each candidate pre-hot spot based on popularity parameters;

[0049] The selection module is used to select a pre-hot spot from the candidate pre-hot spot positions based on the popularity of each candidate pre-hot spot position.

[0050] In addition, to achieve the above objectives, this application also proposes a pre-hot spot determination device, the device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the pre-hot spot determination method as described above.

[0051] In addition, to achieve the above objectives, this application also proposes a storage medium, which is a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the steps of the pre-hot spot determination method as described above.

[0052] In addition, to achieve the above objectives, this application also proposes a computer program product comprising a computer program that, when executed by a processor, implements the steps of the pre-hot spot determination method as described in any of the preceding claims.

[0053] One or more technical solutions proposed in this application have at least the following technical effects:

[0054] By analyzing historical playback behavior data, it can quickly identify candidate hotspots that are frequently accessed and have a long initial playback time. Combined with relevant settings, it can further select based on the popularity of each candidate hotspot, ensuring that candidate hotspots are selected reasonably. This achieves automated selection of hotspots and reduces the burden of manpower. Attached Figure Description

[0055] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0056] To more clearly illustrate the technical solutions in the embodiments of 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, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0057] Figure 1 This is a flowchart illustrating an embodiment of the method for determining pre-hot spots in this application.

[0058] Figure 2 This is a flowchart illustrating Embodiment 2 of the method for determining pre-hot spots in this application.

[0059] Figure 3 This is a flowchart illustrating Embodiment 3 of the method for determining pre-hot spots in this application;

[0060] Figure 4 This is a schematic diagram of the overall process for determining pre-hot spot positions according to an embodiment of this application;

[0061] Figure 5 This is a schematic diagram of the module structure of the pre-hot spot determination device according to an embodiment of this application;

[0062] Figure 6 This is a schematic diagram of the device structure of the hardware operating environment involved in the pre-hot spot determination method in the embodiments of this application.

[0063] The purpose, features, and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0064] It should be understood that the specific embodiments described herein are merely illustrative of the technical solutions of this application and are not intended to limit this application.

[0065] To better understand the technical solution of this application, a detailed description will be provided below in conjunction with the accompanying drawings and specific implementation methods.

[0066] Based on this, embodiments of this application provide a method for determining pre-hotspot positions, referring to... Figure 1 , Figure 1 This is a flowchart illustrating the first embodiment of the pre-hot spot determination method of this application.

[0067] In this embodiment, the preheating hotspot determination method includes steps S10 to S40:

[0068] Step S10: Determine the playback frequency and first screen playback time corresponding to each playback point based on historical playback behavior data.

[0069] It should be noted that the executing entity in this embodiment can be a video playback platform that manages multiple playback points, or a pre-hotspot determination device set in the video playback platform, or a pre-hotspot determination device that is independent of the video playback platform but can manage and control the video playback platform. The pre-hotspot determination device can be a personal computer, a server or other electronic device, or other devices that can achieve the same or similar functions. This embodiment does not limit this. In this embodiment and the following embodiments, the pre-hotspot determination device is used as an example to describe the pre-hotspot determination method of this application.

[0070] It should be noted that the first screen playback time can be the interval between the moment the user requests to retrieve the image and the moment the image corresponding to the playback point is first displayed on the user's device. The playback point can be a device or apparatus that captures images at a preset point, such as a camera or other similar device.

[0071] In practical use, historical playback behavior data can be analyzed and processed to count the number of times each playback point is played and the first screen playback duration of each playback. Then, the playback frequency of the playback point is obtained by dividing the playback duration by the counted duration. The average, maximum, minimum or median of the first screen playback duration of multiple playbacks is used as the first screen playback time of the playback point.

[0072] Among them, historical playback behavior data can be user playback behavior data collected previously. For example, user playback behavior data can be "the user requested to schedule the image at playback point B during time period A, with a total playback duration of 10 seconds and a first screen loading time of 1 second".

[0073] Of course, this is only an illustrative example for ease of understanding, and does not specifically limit the format of user playback behavior data. Depending on actual needs, user playback behavior data can be recorded in a more concise format, such as "Time: A, add: B, Atime: 10, ft_time: 1". This embodiment does not impose any restrictions on this.

[0074] Step S20: Select candidate pre-hot spots from the playback points based on the playback frequency and the first screen playback time.

[0075] It's important to note that a higher playback frequency indicates more times the video at that playback point is played by users. If loading is slow, playback points with high playback frequency will have a greater impact than those with low playback frequency. Similarly, a longer initial screen loading time indicates a slower initial screen loading speed at that playback point, resulting in a greater impact. The selection of pre-playing hotspots is precisely to mitigate this impact. Therefore, points with high playback frequency and longer initial screen loading times can be selected as candidate pre-playing hotspots.

[0076] In practical implementation, the administrators of the preheating hotspot location determination device can pre-set preheating filtering rules. Then, based on the playback frequency and the first screen playback time, candidate preheating hotspot locations are selected from the playback locations through the preheating filtering rules. For example, if the preheating filtering rule is set to a playback frequency greater than a preset frequency threshold or a first screen playback time greater than a preset duration threshold, then the playback location is selected as a candidate preheating hotspot location; or, if the preheating filtering rule is set to a playback frequency greater than a preset frequency threshold and a first screen playback time greater than a preset duration threshold, then the playback location is selected as a candidate preheating hotspot location.

[0077] Step S30: Determine the popularity of each candidate pre-hot spot based on the popularity parameter;

[0078] Step S40: Select a pre-hot spot from the candidate pre-hot spots based on the popularity of each candidate pre-hot spot.

[0079] It should be noted that the heat parameters can be the parameters used when calculating heat, and the specific heat parameters used can be set in advance by the personnel in charge of the preheating point location equipment.

[0080] In practical use, prefetching video streams from pre-hotspot positions consumes bandwidth resources on the video platform. Furthermore, video stream processing and caching further deplete the platform's memory and computing resources. The number of pre-hotspot positions determines the number of playback points required for prefetching. Setting too many pre-hotspot positions can consume a significant amount of the video platform's resources. Since prefetching is typically continuous, this can lead to a sustained and prolonged consumption of bandwidth, memory, and computing resources, potentially preventing the platform from responding promptly to other normal media fetching requests and directly impacting its service. Quality and user experience are paramount. Therefore, after identifying candidate pre-heating spots, further selection is needed. Under the premise that the video platform is not affected, the most important parts to be pre-heated should be selected as pre-heating spots. The popularity of a playback point is used to characterize the impact on the platform when the playback is slow. Therefore, we can first determine the popularity of each candidate pre-heating spot based on the popularity parameter. Then, we can select pre-heating spots from the candidate pre-heating spots according to their popularity, so as to ensure that when the number of available pre-heating spots is limited, the candidate pre-heating spots with higher popularity are selected first.

[0081] In one possible implementation of this embodiment, to avoid the pre-hotspot bit setting consuming too many resources, step S40 shown in this embodiment may include:

[0082] The preheating resource requirement for a single point is estimated based on the preheating resource requirements corresponding to each candidate preheating hot spot. The preheating resource requirement for a single point is the bandwidth resource required to prefetch traffic for a single preheating hot spot.

[0083] The preheating bandwidth resources are determined based on the platform's total resources and the preheating allocation ratio.

[0084] The total number of preheating hotspots is determined based on the preheating bandwidth resources and the single-point preheating resource requirements.

[0085] Pre-hotspot positions are selected from the candidate pre-hotspot positions based on the total number of pre-hotspot positions and the popularity of each candidate pre-hotspot position.

[0086] It should be noted that the single-point preheating resource requirement refers to the bandwidth resources required to prefetch traffic from a single preheating hotspot.

[0087] It is understandable that if candidate hotspot positions with scores greater than the threshold are selected as hotspot positions, the number of such candidate hotspot positions may be uncertain, which may lead to the selection of too many playback points as hotspot positions. In order to determine the number of selectable hotspot positions, it is necessary to first determine the bandwidth resources required for each hotspot position to warm up. Therefore, the preheating resource requirements of a single point can be estimated based on the preheating resource requirements corresponding to each candidate hotspot position.

[0088] In practical applications, the maximum, minimum, average, or median preheating resource requirements corresponding to each candidate preheating hot spot can be calculated, and the calculated results can be used as the single-point preheating resource requirements.

[0089] The specific requirements for the values ​​to be used can be determined according to actual needs. For example, if it is strictly forbidden for the bandwidth resources occupied by the preheating hotspot to exceed the preset resources, the calculated maximum value can be used as the single-point preheating resource requirement; if it is allowed for the bandwidth resources occupied by the preheating hotspot to exceed the preset resources, and the amount of excess resources allowed is large, the calculated minimum value can be used as the single-point preheating resource requirement; if it is desired that the bandwidth resources occupied by the preheating hotspot be close to the preset resources, the calculated average or median value can be used as the single-point preheating resource requirement.

[0090] It should be noted that the total platform resources can be the total amount of available bandwidth resources on the video platform, and the preheating allocation ratio can be the proportion of bandwidth resources allocated to preheating hotspots. Multiplying the total platform resources by the preheating allocation ratio will determine the preheating bandwidth resources.

[0091] In practical use, the total number of preheating hotspots can be obtained by dividing the preheating bandwidth resources by the single-point preheating resource requirements. Since the divisor may not be an integer, the divisor can be rounded up or down, and the rounded value can be used as the total number of preheating hotspots.

[0092] In practical use, after determining the total number of pre-hotspot positions N, the candidate pre-hotspot positions can be sorted from high to low based on their popularity. The top N candidate pre-hotspot positions in the sorting results are then selected as pre-hotspot positions to strictly control the number of pre-hotspot positions, avoid the pre-fetching of pre-hotspot positions from consuming too many resources, and at the same time ensure that playback points with higher popularity are selected as pre-hotspot positions.

[0093] This embodiment provides a method for determining pre-hotspot positions. By analyzing historical playback behavior data, it can quickly identify candidate pre-hotspot positions that are frequently accessed and have a long first-screen playback time. Combined with relevant settings, it can further select candidates based on their popularity, ensuring that candidate pre-hotspot positions can be reasonably selected as pre-hotspot positions. This achieves automated selection of pre-hotspot positions and reduces the burden of manpower.

[0094] Based on the first embodiment of this application, in the second embodiment of this application, the same or similar content as the first embodiment described above can be referred to the above description, and will not be repeated hereafter.

[0095] In this embodiment, the popularity parameter may include playback frequency and first screen playback time;

[0096] Based on this, please refer to Figure 2 Step S30 may include steps S301 to S302:

[0097] Step S301: Determine the playback frequency score corresponding to each candidate hotspot position based on the playback frequency corresponding to the candidate hotspot position, and determine the first screen playback time score corresponding to each candidate hotspot position based on the first screen playback time corresponding to the candidate hotspot position.

[0098] It should be noted that the playback frequency score is a quantitative score of the popularity of the candidate pre-hotspot position calculated from the perspective of playback frequency. Similarly, the first screen playback time score is a quantitative score of the popularity of the candidate pre-hotspot position calculated from the perspective of first screen playback time.

[0099] In one possible implementation of this embodiment, to ensure the reasonableness of the popularity rating results, step S301 of this embodiment may include steps S3011 to S3014:

[0100] Step S3011: Calculate the difference between the playback frequency of each candidate hotspot and the frequency threshold to determine the frequency threshold difference corresponding to each candidate hotspot.

[0101] It should be noted that the frequency threshold can be the average or median of the frequency at which each playback point is accessed, used to characterize the frequency at which a playback point with moderate popularity is accessed.

[0102] The difference between the playback frequency of a candidate hotspot and the frequency threshold, i.e. the frequency threshold difference corresponding to the candidate hotspot, can be used to characterize the difference between the candidate hotspot and a playback point with average popularity in terms of playback frequency.

[0103] Step S3012: Determine the target difference range to which the frequency threshold difference of each candidate hot spot bit belongs.

[0104] In practical use, the administrators of the pre-hot spot location determination equipment can pre-set multiple numerical ranges for the frequency threshold difference. After obtaining the frequency threshold difference of each candidate pre-hot spot location, they can determine the numerical range to which the frequency threshold difference belongs and use that numerical range as the target difference range.

[0105] For example: Suppose that the preset numerical range has multiple ranges such as 1-10, 11-100, 100-1000, 1000-10000, and above 10000. If the frequency threshold difference of candidate hot spot A is 500, then the 100-1000 range is the target difference range corresponding to candidate hot spot A.

[0106] Step S3013: Determine the target time interval to which the first screen playback time corresponding to each candidate pre-hot spot belongs.

[0107] It should be noted that the administrators of the pre-hotspot location determination device can pre-set multiple numerical ranges for the first screen playback time. After obtaining the first screen playback time corresponding to the candidate pre-hotspot location, they can compare the first screen playback time corresponding to the candidate pre-hotspot location with each numerical range to determine the numerical range to which the first screen playback time corresponding to the candidate pre-hotspot location belongs, and use this numerical range as the target playback time range.

[0108] Of course, when determining the target time interval to which the first screen playback time corresponding to the candidate pre-hot spot belongs, the difference between the first screen playback time corresponding to the candidate pre-hot spot and the time threshold (the time threshold can also be the first screen playback time of a playback point with moderate popularity, and the time threshold can also be determined by the average or median) can be calculated first, and then the target time interval corresponding to the difference can be determined. This embodiment does not impose any restrictions on this.

[0109] Step S3014: Find the interval score corresponding to the target time interval, obtain the first screen time score corresponding to each candidate pre-hot spot, and find the interval score corresponding to the target difference interval, obtain the playback frequency score corresponding to each candidate pre-hot spot.

[0110] It should be noted that the administrators of the preheating hotspot location determination equipment can set corresponding interval scores for each numerical interval. The later the numerical interval, that is, the larger the starting value and / or ending value of the interval, the larger the corresponding interval score.

[0111] In practical use, the interval score of the target time interval corresponding to the candidate hotspot position can be used as the first screen time score corresponding to the candidate hotspot position, thereby obtaining the first screen time score corresponding to each candidate hotspot position; similarly, the interval score of the target difference interval corresponding to the candidate hotspot position can be used as the playback frequency score corresponding to the candidate hotspot position, thereby obtaining the playback frequency score corresponding to each candidate hotspot position.

[0112] Step S302: Generate a popularity score result for each candidate pre-hot spot based on the playback frequency score and the first screen time consumption score. The popularity score result is used to characterize the popularity of the candidate pre-hot spot.

[0113] It should be noted that, in order to make reasonable selections, each candidate hotspot needs to be scored to generate a popularity score result for each candidate hotspot.

[0114] The popularity score is used to characterize the popularity of candidate pre-hot spots. The popularity of candidate pre-hot spots refers to the impact of long loading times on the video platform. It can be regarded as the degree of need for pre-fetching the stream at this point. The higher the popularity, the more necessary it is to pre-fetch the stream at this playback point to improve the first screen loading speed. Conversely, the lower the popularity, the less necessary it is to pre-fetch the stream at this playback point.

[0115] In practical use, in order to comprehensively evaluate the scores of each candidate hotspot position in terms of playback frequency and first screen playback time, the playback frequency score and first screen playback time score corresponding to the candidate hotspot position can be added together, and the sum obtained can be used as the popularity score result corresponding to the candidate hotspot position.

[0116] Of course, other methods can also be used for calculation, such as weighted summation of the playback frequency score and the first screen time score corresponding to the candidate pre-hotspot position, and using the result as the popularity score for the candidate pre-hotspot position. The weighting coefficients for the weighted summation can be preset by the administrator of the device determining the pre-hotspot position. Alternatively, a multiplication method can be used, for example, multiplying the playback frequency score and the first screen time score as the popularity score for the candidate pre-hotspot position.

[0117] In practical use, the popularity score is used to characterize the popularity of candidate hot spots. Therefore, hot spots can be selected from the candidate hot spots based on the popularity score. To facilitate the selection, the popularity score can be represented in the form of a score. For example, the higher the score, the higher the popularity of the candidate hot spot; the lower the score, the lower the popularity of the candidate hot spot.

[0118] Based on this, when actually selecting pre-hotspot positions, a corresponding score threshold can be set for the popularity score results, and the candidate pre-hotspot positions with scores greater than the score threshold in the corresponding popularity score results can be selected as pre-hotspot positions.

[0119] In one possible implementation of this embodiment, the popularity score result can also be generated by combining the preheating effect (such as the preheating improvement ratio, or the preheating improvement magnitude) to ensure that the popularity score result is more reasonable. In this case, the popularity parameters may include playback frequency, first screen playback time and preheating improvement ratio.

[0120] Step S30 in this embodiment may include:

[0121] Estimate the time required to preheat the first screen for each candidate preheating hotspot;

[0122] The preheating boost ratio corresponding to each candidate preheating hot spot is determined based on the preheating time of the first screen and the playback time of the first screen.

[0123] The popularity of each candidate preheating hotspot is determined based on the preheating boost ratio, the playback frequency, and the first screen time.

[0124] It should be noted that the preheating first screen time refers to the first screen playback time of the candidate preheating spot after preheating. The preheating improvement ratio refers to the reduction ratio of the first screen playback time before and after preheating.

[0125] In practical use, the preheating time of the first screen corresponding to the candidate hotspot can be estimated by pre-setting algorithms or intelligent models based on the device information and network status of the candidate hotspot.

[0126] Of course, you can also record the time taken by the video platform to call the video data of the candidate hotspot positions, and estimate the time taken for the first screen of the candidate hotspot positions to warm up based on the average time taken.

[0127] In practical applications, the difference between the time taken to warm up the first screen and the time taken to play the first screen can be calculated, and the ratio of this difference to the time taken to play the first screen can be used as the preheating boost ratio corresponding to the candidate preheating hotspot.

[0128] In practical use, after determining the preheating enhancement ratio, the preheating enhancement ratio can be combined with the playback frequency and the first screen playback time to serve as preheating parameters, thereby calculating the popularity of each candidate preheating hot spot. For example, the ratio range in which the preheating enhancement ratio is located can be determined, and the score value corresponding to the ratio range can be used as the enhancement ratio score corresponding to the candidate preheating hot spot. Alternatively, the preheating enhancement ratio can be multiplied by a preset constant, and the product obtained can be used as the enhancement ratio score corresponding to the candidate preheating hot spot.

[0129] After determining the boost ratio score, the playback frequency score can be determined based on the playback frequency, and the first screen playback time score can be determined based on the first screen playback time. Then, by combining the boost ratio score, playback frequency score, and first screen playback time score, the popularity score result corresponding to each candidate pre-hot spot position is constructed, and the popularity score result represents the popularity corresponding to each candidate pre-hot spot position.

[0130] The methods for determining the playback frequency score based on playback frequency and the first screen playback time score based on first screen playback time are consistent with the above implementation. The calculation method for combining the improvement ratio score, playback frequency score, and first screen playback time score can also be summation or weighted summation, which is similar to the method for constructing the popularity score results corresponding to each candidate pre-hot spot based on the playback frequency score and the first screen playback time score. It will not be elaborated here.

[0131] In one possible implementation of this embodiment, the popularity score result can also be generated by combining whether there has been a preheating before, so as to ensure that the popularity score result is more reasonable. In this case, the preheating parameters may include playback frequency, first screen playback time and historical preheating tags.

[0132] Step S30 in this embodiment may include:

[0133] Determine the historical preheating tags corresponding to each candidate preheating hotspot based on historical preheating records;

[0134] The popularity of each candidate preheating spot is determined based on the historical preheating tags, the playback frequency, and the first screen time.

[0135] It should be noted that historical preheating records can be records of previously selected preheating hotspot positions. The historical preheating tag is used to indicate whether the candidate preheating hotspot position was previously selected as a preheating hotspot position.

[0136] In practical use, historical preheating records can be used to determine whether candidate preheating hotspots have been selected as preheating hotspots, thereby setting corresponding historical preheating labels.

[0137] In practical use, a preheating record score can be constructed based on historical preheating tags, a playback frequency score can be determined based on playback frequency, and a first screen playback time score can be determined based on first screen playback time. Then, by combining the preheating record score, playback frequency score, and first screen playback time score, a popularity score result corresponding to each candidate preheating hot spot can be constructed, and the popularity score result can be used to represent the popularity of each candidate preheating hot spot.

[0138] The methods for determining the playback frequency score based on playback frequency and the first screen playback time score based on first screen playback time are consistent with the above implementation. The calculation method for combining the preheating record score, playback frequency score, and first screen playback time score can also be summation or weighted summation, which is similar to the method for constructing the popularity score results corresponding to each candidate preheating hot spot based on the playback frequency score and the first screen playback time score. It will not be elaborated here.

[0139] The implementation method of building a pre-heating record score based on historical pre-heating tags can be adjusted according to actual needs, for example:

[0140] If the actual requirement is to prioritize candidates that were not selected as pre-heating hotspots, then if the historical pre-heating tag indicates that the candidate pre-heating hotspot was not selected as a pre-heating hotspot, the pre-heating record score can be set to a higher level, such as 1. Conversely, if the historical pre-heating tag indicates that the candidate pre-heating hotspot was selected as a pre-heating hotspot, the pre-heating record score can be set to a lower level, such as 0.

[0141] If the actual demand is that the candidate hotspot position is selected first, then if the historical preheating tag indicates that the candidate hotspot position was not selected as a hotspot position, the preheating record score can be set to a lower value, such as 0. Conversely, if the historical preheating tag indicates that the candidate hotspot position was selected as a hotspot position, the preheating record score can be set to a higher value, such as 1.

[0142] In one possible implementation of this embodiment, in order to ensure that the selection of pre-playback hotspots can be based on a comprehensive consideration of the importance of each playback point, step S30 of this embodiment may include:

[0143] Determine the importance of each candidate hotspot;

[0144] Determine the correction coefficient corresponding to the importance of the pre-hot spot;

[0145] Determine the heat parameter score for each candidate hot spot, and correct each heat parameter score based on the correction coefficient;

[0146] Based on the corrected scores of each of the aforementioned heat parameters, the heat corresponding to each candidate preheating hot spot is determined.

[0147] It should be noted that the importance of the playback point refers to the degree of importance of the playback point. The correction coefficient can be a positive number. The higher the importance of the playback point, the larger its corresponding correction coefficient. Conversely, the lower the importance of the playback point, the smaller its corresponding correction coefficient.

[0148] In practical use, the heat parameter score of each candidate hot spot can be calculated first based on the heat parameter. Then, the heat parameter score is multiplied by the correction coefficient, and the product is used as the heat score result. The heat score result represents the heat corresponding to each candidate hot spot.

[0149] The method for determining the popularity parameter score is the same as the method described above for generating the popularity score results for each candidate pre-hot spot based on the playback frequency score and the first screen time score, and will not be repeated here.

[0150] Understandably, when generating the popularity score, various factors such as playback frequency and first-screen playback time are taken into account to ensure the rationality of the popularity score results, thereby ensuring that the pre-hot spot positions can be selected reasonably.

[0151] In one possible implementation of this embodiment, in order to ensure that the importance of each candidate hotspot can be reasonably determined, the step of determining the importance of each candidate hotspot may include:

[0152] Obtain the location, setting time, and associated services of each candidate hotspot location;

[0153] The importance level of a location is determined based on its position.

[0154] The importance level of a time is determined based on the location settings.

[0155] Obtain the business importance level corresponding to the business associated with the location;

[0156] The importance level identifier corresponding to each candidate hotspot position is determined based on the location importance level, the time importance level, and the business importance level. The importance level is used to characterize the importance of the hotspot position.

[0157] It should be noted that the location of the point can be the location where the image of the candidate pre-hot spot is collected, the time of setting the point can be the time when the candidate pre-hot spot is set, and the associated service of the point can be the service associated with the candidate pre-hot spot, such as intelligent recognition, intelligent detection, etc.

[0158] In practical use, the location of a point can be detected to determine whether the area is a specific important area, such as an intersection. If it is a specific important area, the importance level of that important area can be used as the importance level of the location; if it is not a specific important area, the importance level of the location can be set to the default value.

[0159] When determining the importance level of a playback point, the difference between the point's initial setting time and the current time can be calculated. Then, the importance level can be generated based on this difference. For example, if, according to actual needs, the earlier the playback point is set, the higher its importance level, then the larger the difference, the higher the importance level; the smaller the difference, the lower the importance level. Conversely, if, according to actual needs, the later the playback point is set, the higher its importance level, then the smaller the difference, the higher the importance level; the larger the difference, the lower the importance level.

[0160] In practical applications, the importance level of the business associated with the location corresponding to the candidate pre-hot spot can be used as the importance level of the business corresponding to the candidate pre-hot spot.

[0161] In a specific implementation, the maximum, minimum, or average value among the location importance level, time importance level, and business importance level can be used as the importance level corresponding to the candidate hotspot position. The importance level is used to characterize the importance of the hotspot position.

[0162] It should be noted that the above methods for determining the popularity score results (i.e., the methods for determining the popularity of candidate pre-heating spots) can be combined in any way to construct new methods for generating popularity score results. For example, popularity score results corresponding to each candidate pre-heating spot can be generated based on the improvement ratio score, pre-heating record score, playback frequency score, and first screen time score. If necessary, a correction coefficient can be added to the improvement ratio score, pre-heating record score, playback frequency score, and first screen time score to generate popularity score results corresponding to each candidate pre-heating spot.

[0163] This embodiment provides a method for determining pre-hotspot positions. Since various different methods can be used to generate popularity scores, it ensures that the generated popularity scores can correctly represent the popularity of each candidate pre-hotspot position, thus ensuring that pre-hotspot positions can be selected reasonably.

[0164] Based on the first embodiment of this application, in the third embodiment of this application, the content that is the same as or similar to that in the first embodiment described above can be referred to the above description, and will not be repeated hereafter. Based on this, please refer to... Figure 3 Step S10 may include steps S101 to S105:

[0165] Step S101: Obtain the statistical analysis duration, data filtering conditions, and preheating filtering rules.

[0166] It should be noted that the statistical analysis duration, data filtering conditions, and preheating filtering rules can all be preset by the administrators of the preheating hotspot locations. The statistical analysis duration is used to specify the collection time span of the historical data to be analyzed, for example, setting the statistical analysis duration to 2 days or 1 day. The data filtering conditions are used to filter the data that needs to be statistically analyzed from the historical playback behavior data. The data filtering conditions can be set according to one or more of the following: location identifier, user identifier, behavior category, etc.

[0167] Step S102: Determine the statistical time period based on the current time and the statistical analysis duration.

[0168] Step S103: Locate the historical playback behavior data corresponding to the collection time within the statistical period and generate a behavior dataset.

[0169] It should be noted that since video platforms may serve a large number of users, the historical playback behavior data is actually massive. Directly performing full analysis would take an extremely long time and require extremely high computing resources, making this method impractical. Furthermore, the popularity of each playback point may change significantly over time, and historical data that is too far removed from the current moment is not very reliable. Therefore, it is possible to analyze only a portion of the data. Based on this, the administrators of the pre-hotspot location determination devices can set the corresponding statistical analysis duration.

[0170] In practical use, the collection time period for the historical playback behavior data to be extracted can be assembled based on the current time and the duration of statistical analysis.

[0171] For example: Suppose the current time is 09-18 9:00, and the statistical analysis period is 1 day, then the statistical period is from 09-17 9:00 to 09-18 9:00.

[0172] Understandably, after obtaining the statistical period, one can find the historical playback behavior data that falls within the statistical period at the corresponding collection time. Then, the found data can be aggregated into a set to obtain the behavior dataset.

[0173] Step S104: Filter the behavior dataset according to the data filtering conditions to generate a filtered behavior dataset.

[0174] It should be noted that when collecting users' historical behavior data, some data may be irrelevant to the pre-hotspot positions. For example, this could include users performing configuration updates or playing locally cached historical videos. Additionally, some playback points may have been set to be unsuitable as pre-hotspot positions, or some users may have been marked as not to be included in statistical analysis (e.g., test users are used for testing purposes and do not represent the actual user's operating habits, so they can be excluded from statistical analysis). To avoid analyzing such invalid data, the administrators of the pre-hotspot position determination devices can pre-set data filtering conditions. After obtaining the behavior dataset, they can filter the behavior dataset according to the data filtering conditions, removing such invalid data from the collection, and using the processed behavior dataset as the filtered behavior dataset.

[0175] Step S105: Determine the playback frequency and first screen playback time corresponding to each playback point based on the historical playback behavior data in the filtered behavior dataset.

[0176] Understandably, after filtering, the filtered behavior dataset contains historical playback behavior data related to the selection of pre-hot spots. Therefore, the historical playback behavior data in the filtered behavior dataset can be analyzed and processed to determine the playback frequency and first screen playback time corresponding to each playback point.

[0177] In one possible implementation of this embodiment, the update of the pre-hotspot bit can be performed automatically to ensure that the pre-hotspot bit can be updated periodically. In this case, step S101 of this embodiment may include:

[0178] When the triggering conditions for the preheating update task are detected to be met, the task information corresponding to the preheating update task is obtained.

[0179] Extract the statistical analysis duration, data filtering conditions, and preheating filtering rules from the task information.

[0180] It should be noted that if the triggering conditions for the preheating update task are met, it means that the preheating hotspot needs to be updated. In order to ensure that the preheating hotspot can be correctly filtered, the task information corresponding to the preheating update task can be obtained, and the statistical analysis duration, data filtering conditions and preheating filtering rules can be extracted from the task information.

[0181] The task information can be pre-set by the administrators of the preheating hotspot location determination equipment. In addition to information such as statistical analysis duration, data filtering conditions, and preheating filtering rules, the task information can also include more information, such as task name and task identifier. If necessary, the threshold required to determine the preheating hotspot location can also be included in the task information. For example, the task information can also include the N value when selecting the preheating hotspot location.

[0182] In practical use, the administrators of the preheating hotspot location determination equipment can set up multiple preheating update tasks according to actual needs. The task information of each preheating update task can be the same or different. This embodiment does not impose any restrictions on this.

[0183] In one possible implementation of this embodiment, the trigger condition for detecting a preheating update task can be determined to be met if at least one of the following conditions is met:

[0184] The system always meets the time matching rules in the triggering conditions;

[0185] The task information for the pre-launch update task has been updated;

[0186] The task execution command corresponding to the preheating update task has been detected.

[0187] It should be noted that the preheating update task can be a periodically executed scheduled task. The time matching rule can be preset by the administrator of the preheating hotspot location. The time matching rule can be set based on a time expression. For example, if the time matching rule is set to "0 0 2**?*", it means that the time matching rule is met at 2:00 AM every day.

[0188] To ensure that administrators can quickly update the preheating hotspots after updating the determination conditions, the triggering conditions for the preheating update task can be determined when the task information of the preheating update task is updated. For example, if the statistical analysis duration, data filtering conditions and / or preheating filtering rules in the task information of the preheating update task are updated, it can be determined that the triggering conditions for the preheating update task are met.

[0189] Of course, the preheating update task can also be manually triggered by the administrator, or it can be triggered by a chain after other tasks are executed. After manual triggering or being triggered by a chain after other tasks are executed, the preheating hotspot determination device will generate or receive a task execution instruction. Therefore, when the task execution instruction corresponding to the preheating update task is detected, it can be determined that the triggering condition of the preheating update task has been met.

[0190] To facilitate understanding, we will now combine... Figure 3 This explanation is provided, but it does not limit the scope of this solution. Figure 3 This is a schematic diagram illustrating the overall process of determining the pre-hot spot in this embodiment.

[0191] like Figure 4 As shown, the pre-hot spot determination device can include the following core functions during the pre-hot spot determination process:

[0192] Intelligent analysis function: Automatically collects and analyzes user playback behavior data to identify high-frequency playback points that take a long time to play the first screen.

[0193] Dynamic resource allocation function: Administrators can allocate network bandwidth resources required for intelligent preheating based on factors such as network conditions, server load, and user behavior.

[0194] Preheating execution function: Based on the results of intelligent analysis, the preheating task is automatically executed, a preheating hot spot is selected, and the stream is pre-fetched for the preheating hot spot to ensure that the first screen loading speed can be improved for high-frequency playback points with slow first screen loading, so that they can open instantly.

[0195] Real-time adjustment mechanism: Create scheduled tasks to analyze and identify the most needed preheating hotspots based on the latest streaming behavior data from the platform, so as to continuously and dynamically update the intelligent preheating points and improve the streaming playback experience of users on the platform under the condition of limited intelligent preheating network resources.

[0196] The specific execution process is as follows:

[0197] After deployment, the pre-heating hotspot determination device reviews previous (e.g., the previous day's) streaming media playback data (i.e., historical playback behavior data) based on statistical analysis duration and data filtering conditions, and stores this data properly. Then, it analyzes the stored streaming media playback data to determine the playback frequency and first-screen playback time for each playback point. Based on filtering criteria (i.e., pre-heating filtering rules, such as filtering by playback frequency and first-screen playback loading time), it selects playback node positions with pre-heating needs (i.e., candidate pre-heating hotspots). Then, using relevant algorithms or models, it calculates a popularity score for each candidate pre-heating hotspot (this popularity score comprehensively considers factors such as the importance of the playback point and access frequency). Finally, considering the current available network resource ratio (e.g., the set N value), it intelligently selects the points most in need of pre-heating as pre-heating hotspots.

[0198] The above-mentioned pre-hotspot execution process is executed through a scheduled task configuration. Based on the scheduled task configuration, it will periodically and automatically update historical playback behavior data and automatically update the pre-hotspot positions to ensure that it always focuses on the most popular playback points and makes the most popular playback points the pre-hotspot positions.

[0199] In addition, if the administrator adjusts the network resource allocation ratio or modifies the spot selection rules, i.e., modifies the information related to the scheduled task, these new settings will be saved immediately and a scheduled task will be executed. Based on the modified rules, the most suitable preheating spots will be reselected to achieve timely dynamic updates, ensuring the timeliness and accuracy of the preheating task. At the same time, according to the set time period, new preheating update tasks will be automatically reallocated and prepared for execution.

[0200] This embodiment provides a method for determining pre-hotspot positions. Because historical playback behavior data can be filtered at multiple levels according to relevant configurations, it ensures that the filtered data is relevant to the selection of pre-hotspot positions and is analyzed, avoiding the analysis and influence of invalid data, thus ensuring the effectiveness and accuracy of the method for determining pre-hotspot positions.

[0201] It should be noted that the above examples are only for understanding this application and do not constitute a limitation on the method for determining the hot spot of this application. Any simple modifications based on this technical concept are within the protection scope of this application.

[0202] This application also provides a preheating point location determination device, please refer to... Figure 5 The preheating point determination device includes:

[0203] The determination module 10 is used to determine the playback frequency and first screen playback time corresponding to each playback point based on historical playback behavior data. The first screen playback time is the interval between the moment when the user requests to retrieve the image and the moment when the image corresponding to the playback point is first displayed on the user's device. The playback point is a device or apparatus that performs image acquisition at a preset point.

[0204] The filtering module 20 is used to select candidate pre-hot spots from the playback points based on the playback frequency and the first screen playback time;

[0205] The popularity module 30 is used to determine the popularity of each candidate pre-hot spot based on the popularity parameters.

[0206] The selection module 40 is used to select a pre-hot spot from the candidate pre-hot spot based on the popularity of each candidate pre-hot spot.

[0207] The preheating hotspot determination device provided in this application, employing the preheating hotspot determination method in the above embodiments, addresses the technical problems of related technologies that rely on manual setting of preheating hotspots, resulting in high costs, low efficiency, and inflexible adjustments, leading to unsatisfactory actual results. Compared to the prior art, the beneficial effects of the preheating hotspot determination device provided in this application are the same as those of the preheating hotspot determination method provided in the above embodiments, and other technical features in the preheating hotspot determination device are the same as those disclosed in the methods of the above embodiments, and will not be repeated here.

[0208] This application provides a pre-hot spot determination device, which includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the pre-hot spot determination method in the above embodiment 1.

[0209] The following is for reference. Figure 6 The diagram illustrates a structural schematic of a pre-hotspot location determination device suitable for implementing embodiments of this application. The pre-hotspot location determination device in embodiments of this application may include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Portable Application Description), PMPs (Portable Media Players), in-vehicle terminals (e.g., in-vehicle navigation terminals), and fixed terminals such as digital TVs and desktop computers. Figure 6 The pre-hot spot determination device shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of this application.

[0210] like Figure 6 As shown, the hot spot determination device may include a processing unit 1001 (e.g., a central processing unit, a graphics processing unit, etc.) that can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 1002 or a program loaded from a storage device 1003 into a random access memory (RAM) 1004. The RAM 1004 also stores various programs and data required for the operation of the hot spot determination device. The processing unit 1001, ROM 1002, and RAM 1004 are interconnected via a bus 1005. An input / output (I / O) interface 1006 is also connected to the bus. Typically, the following systems can be connected to the I / O interface 1006: input devices 1007 including, for example, touchscreens, touchpads, keyboards, mice, image sensors, microphones, accelerometers, gyroscopes, etc.; output devices 1008 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 1003 including, for example, magnetic tapes, hard disks, etc.; and communication devices 1009. Communication device 1009 allows the pre-hotspot location determination device to communicate wirelessly or wiredly with other devices to exchange data. Although pre-hotspot location determination devices with various systems are shown in the figures, it should be understood that implementation or possession of all the systems shown is not required. More or fewer systems may be implemented alternatively.

[0211] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication device, or installed from storage device 1003, or installed from ROM 1002. When the computer program is executed by processing device 1001, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0212] The pre-hot spot determination device provided in this application, employing the pre-hot spot determination method in the above embodiments, can solve the technical problems of related technologies that rely on manual setting of pre-hot spots, resulting in high costs, low efficiency, and inflexible adjustments, leading to poor actual results. Compared with the prior art, the beneficial effects of the pre-hot spot determination device provided in this application are the same as those of the pre-hot spot determination method provided in the above embodiments, and other technical features of this pre-hot spot determination device are the same as those disclosed in the previous embodiment method, and will not be repeated here.

[0213] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0214] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0215] This application provides a computer-readable storage medium having computer-readable program instructions (i.e., a computer program) stored thereon, the computer-readable program instructions being used to execute the pre-hot spot determination method in the above embodiments.

[0216] The computer-readable storage medium provided in this application may be, for example, a USB flash drive, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared systems or devices, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to: electrical connections having one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, system, or device. The program code contained on the computer-readable storage medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination thereof.

[0217] The aforementioned computer-readable storage medium may be included in the pre-hot spot determination device; or it may exist independently and not assembled into the pre-hot spot determination device.

[0218] The aforementioned computer-readable storage medium carries one or more programs. When these programs are executed by the preheating hotspot determination device, the preheating hotspot determination device: determines the playback frequency and first-screen playback time corresponding to each playback point based on historical playback behavior data. The first-screen playback time is the interval between the moment the user requests to retrieve the image and the moment the image corresponding to the playback point is first displayed on the user's device. The playback point is a device or apparatus that performs image acquisition at a preset point. Based on the playback frequency and the first-screen playback time, it selects candidate preheating hotspots from the playback points using preheating filtering rules. It scores each candidate preheating hotspot to generate a popularity score result corresponding to each candidate preheating hotspot, the popularity score result being used to characterize the popularity level of the candidate preheating hotspot. Based on the popularity score result, it selects a preheating hotspot from the candidate preheating hotspots.

[0219] Computer program code for performing the operations of this application can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a Local Area Network (LAN) or a Wide Area Network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0220] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0221] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself.

[0222] The readable storage medium provided in this application is a computer-readable storage medium that stores computer-readable program instructions (i.e., a computer program) for executing the above-described pre-hot spot determination method. This solves the technical problems of related technologies that rely on manual setting of pre-hot spots, resulting in high costs, low efficiency, and inflexible adjustments, leading to poor actual results. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in this application are the same as those of the pre-hot spot determination method provided in the above embodiments, and will not be repeated here.

[0223] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the pre-hot spot determination method described above.

[0224] The computer program product provided in this application can solve the technical problems of related technologies that rely on manual setting of pre-hot spots, which is costly, inefficient, and lacks flexibility, resulting in poor actual performance. Compared with the prior art, the beneficial effects of the computer program product provided in this application are the same as those of the pre-hot spot determination method provided in the above embodiments, and will not be repeated here.

[0225] The above description is only a part of the embodiments of this application and does not limit the patent scope of this application. All equivalent structural transformations made under the technical concept of this application and using the contents of the specification and drawings of this application, or direct / indirect applications in other related technical fields, are included in the patent protection scope of this application.

Claims

1. A method for determining pre-hot spot locations, characterized in that, The method includes: Based on historical playback behavior data, determine the playback frequency and first screen playback time corresponding to each playback point. The first screen playback time is the interval between the time when the user requests to retrieve the image and the time when the image corresponding to the playback point is first displayed on the user's device. The playback point is a device or apparatus that performs image acquisition at a preset point. Candidate pre-hot spots are selected from the playback points based on the playback frequency and the first screen playback time. Based on the popularity parameter, the popularity corresponding to each candidate pre-hot spot is determined. The popularity is used to characterize the degree of impact on the platform when the playback of the candidate pre-hot spot is slow. Pre-hot spots are selected from the candidate pre-hot spots based on their popularity.

2. The preheat point location determination method of claim 1, wherein, The popularity parameters include playback frequency and first screen playback time; The process of determining the popularity of each candidate pre-hot spot based on popularity parameters includes: The playback frequency score for each candidate hotspot is determined based on the playback frequency corresponding to the candidate hotspot position, and the first screen playback time score for each candidate hotspot position is determined based on the first screen playback time corresponding to the candidate hotspot position. Based on the playback frequency score and the first screen time score, a popularity score is generated for each candidate pre-hot spot. The popularity score is used to characterize the popularity of the candidate pre-hot spot.

3. The preheat point location determination method of claim 2, wherein, The step of determining the playback frequency score for each candidate pre-hotspot position based on the playback frequency corresponding to the candidate pre-hotspot position, and determining the first-screen playback time score for each candidate pre-hotspot position based on the first-screen playback time corresponding to the candidate pre-hotspot position, includes: The difference between the playback frequency and the frequency threshold of each candidate hotspot is calculated to determine the frequency threshold difference corresponding to each candidate hotspot. Determine the target difference range to which the frequency threshold difference of each candidate hotspot bit belongs; Determine the target time interval to which the first-screen playback time belongs for each candidate pre-hotspot position; Find the interval score corresponding to the target time interval to obtain the first screen time score corresponding to each candidate pre-hot spot, and find the interval score corresponding to the target difference interval to obtain the playback frequency score corresponding to each candidate pre-hot spot.

4. The pre-heat spot location determination method of claim 1, wherein, The popularity parameters include playback frequency, first screen playback time, and preheating boost ratio; The process of determining the popularity of each candidate pre-hot spot based on popularity parameters includes: Estimate the time required to preheat the first screen for each candidate preheating hotspot; The preheating boost ratio corresponding to each candidate preheating hot spot is determined based on the preheating time of the first screen and the playback time of the first screen. The popularity of each candidate preheating hotspot is determined based on the preheating boost ratio, the playback frequency, and the first screen playback time.

5. The pre-heat spot location determination method of claim 1, wherein, The popularity parameters include playback frequency, first screen playback time, and historical preheating tags; The process of determining the popularity of each candidate pre-hot spot based on popularity parameters includes: Based on historical preheating records, the historical preheating tags corresponding to each candidate preheating hot spot are determined. The historical preheating tags are used to indicate whether the candidate preheating hot spot was previously selected as a preheating hot spot. The popularity of each candidate preheating spot is determined based on the historical preheating tags, the playback frequency, and the first screen playback time.

6. The method for determining pre-hot spot locations as described in claim 1, characterized in that, The process of determining the popularity of each candidate pre-hot spot based on popularity parameters includes: Determine the importance of each candidate hotspot; Determine the correction coefficient corresponding to the importance of the pre-hot spot; Determine the heat parameter score for each candidate hot spot, and correct each heat parameter score based on the correction coefficient; Based on the corrected scores of each of the aforementioned heat parameters, the heat corresponding to each candidate preheating hot spot is determined.

7. The method for determining pre-hot spot locations as described in claim 6, characterized in that, The determination of the importance of each candidate hotspot includes: Obtain the location, setting time, and associated services of each candidate hotspot location; The importance level of a location is determined based on its position. The importance level of a time is determined based on the location settings. Obtain the business importance level corresponding to the business associated with the location; The importance level of each candidate hotspot is determined based on the location importance level, the time importance level, and the business importance level. The importance level is used to characterize the importance of the hotspot.

8. The method for determining preheating hotspot locations as described in any one of claims 1 to 7, characterized in that, The process of selecting pre-hotspot positions from the candidate pre-hotspot positions based on their popularity includes: The preheating resource requirement for a single point is estimated based on the preheating resource requirement corresponding to each candidate preheating hot spot. The single point preheating resource requirement is the bandwidth resource required to prefetch a single preheating hot spot. The preheating bandwidth resources are determined based on the platform's total resources and the preheating allocation ratio. The total number of preheating hotspots is determined based on the preheating bandwidth resources and the single-point preheating resource requirements. Pre-hotspot positions are selected from the candidate pre-hotspot positions based on the total number of pre-hotspot positions and the popularity of each candidate pre-hotspot position.

9. A preheating point determination device, characterized in that, The device includes: The determination module is used to determine the playback frequency and first screen playback time corresponding to each playback point based on historical playback behavior data. The first screen playback time is the interval between the time when the user requests to retrieve the image and the time when the image corresponding to the playback point is first displayed on the user's device. The playback point is a device or apparatus that performs image acquisition at a preset point. The filtering module is used to select candidate pre-hot spots from the playback points based on the playback frequency and the first screen playback time; The popularity module is used to determine the popularity of each candidate hot spot based on the popularity parameter. The popularity is used to characterize the degree of impact on the platform when the playback of the candidate hot spot is slow. The selection module is used to select a pre-hot spot from the candidate pre-hot spot positions based on the popularity of each candidate pre-hot spot position.

10. A preheating spot location determination device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the pre-hot spot determination method as described in any one of claims 1 to 8.

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