Resource information configuration method and device, equipment, storage medium and program product

Abstract

Embodiments of the present disclosure provide a resource information configuration method and device, equipment, a storage medium and a program product. The method comprises: obtaining first play amount information and first video interaction information corresponding to each of a plurality of first videos played within a first preset time period; for each first video, determining whether the first video meets a preset scoring condition according to the first play amount information and / or the first video interaction information of the first video; if the first video meets the preset scoring condition, calculating a first score of the first video by using a video value model, and configuring resource information of the first video according to the first score of the first video. The method monitors the play data and interaction changes of the video in real time, dynamically adjusts the value score of the video, avoids the "pseudo-high heat" phenomenon in video recommendation, improves the accuracy of video recommendation, and optimizes the configuration efficiency of resource information.

Description

Technical Field

[0001] This disclosure relates to the field of Internet technology, and in particular to a method, apparatus, device, storage medium, and program product for configuring resource information. Background Technology

[0002] With the rapid development of video applications, accurately assessing video value has become a core issue for improving user experience and optimizing resource allocation. A video's "value score" integrates key indicators such as viewing time, user interaction (e.g., likes, comments, shares), and content characteristics to measure its popularity and potential. This scoring mechanism not only helps video applications prioritize high-value content but also dynamically adjusts its priority in the recommendation stream based on video performance, thereby maximizing resource utilization efficiency.

[0003] However, when the volume of videos becomes too large, to ensure the stability of the server system, it is not feasible to evaluate the value of all videos; instead, a subset of videos must be evaluated. At this point, determining which videos to select and when to trigger the video value model for evaluation becomes a pressing issue. Summary of the Invention

[0004] This disclosure provides a method, apparatus, device, storage medium, and program product for configuring resource information, which can improve the accuracy of video recommendations and optimize the efficiency of resource information configuration.

[0005] Obtain the first play count information and first video interaction information corresponding to each of the multiple first videos played within a first preset time period;

[0006] For each first video, determine whether the first video meets the preset scoring conditions based on the first video's first play count information and / or first video's first video interaction information;

[0007] If the first video meets the preset scoring conditions, then the first score of the first video is calculated using the video value model, and the resource information of the first video is configured based on the first score of the first video.

[0008] Secondly, embodiments of this disclosure provide a resource information configuration device, including:

[0009] The acquisition unit is used to acquire the first playback count information and the first video interaction information corresponding to each of the multiple first videos played within a first preset time period;

[0010] The determining unit is used to determine, for each first video, whether the first video meets the preset scoring conditions based on the first video's first play count information and / or first video's first video interaction information.

[0011] The configuration unit is configured to, if the first video meets the preset scoring conditions, calculate the first score of the first video through the video value model, and configure the resource information of the first video based on the first score of the first video.

[0012] Thirdly, embodiments of this disclosure provide an electronic device, including: a processor and a memory;

[0013] The memory stores computer-executed instructions;

[0014] The processor executes computer execution instructions stored in the memory, causing the at least one processor to perform the resource information configuration method described in the first aspect and various possible designs of the first aspect.

[0015] Fourthly, embodiments of this disclosure provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the resource information configuration method described in the first aspect and various possible designs of the first aspect.

[0016] Fifthly, embodiments of this disclosure provide a computer program product, including a computer program that, when executed by a processor, implements the resource information configuration method described in the first aspect and various possible designs of the first aspect.

[0017] This embodiment provides a method, apparatus, device, storage medium, and program product for configuring resource information. The method includes: acquiring first playback volume information and first video interaction information corresponding to each of multiple first videos played within a first preset duration. For each first video, based on the first playback volume information and / or the first video interaction information, it is determined whether the first video meets preset scoring conditions. If the first video meets the preset scoring conditions, a first score is calculated using a video value model, and resource information for the first video is configured based on the first score. In this technical solution, by dynamically adjusting the video's value score through real-time monitoring of video playback data and interaction changes, the "pseudo-high popularity" phenomenon in video recommendations is avoided, improving the accuracy of video application recommendations and optimizing resource allocation efficiency. Thus, the calculation frequency should be increased in the early stages of video release to capture trends in popularity; the frequency can be appropriately reduced after entering a stable period to save computing resources. Therefore, the dynamic calculation strategy can accurately reflect the actual value of the video, improve resource allocation efficiency, optimize user experience, and ensure the timeliness and accuracy of recommended content. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of this disclosure 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 disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 Flowchart of the resource information configuration method provided in the embodiments of this disclosure Figure 1 ;

[0020] Figure 2 A schematic diagram of a resource information configuration method provided in this embodiment of the disclosure. Figure 1 ;

[0021] Figure 3 Flowchart of the resource information configuration method provided in the embodiments of this disclosure Figure 2 ;

[0022] Figure 4 Flowchart of the resource information configuration method provided in the embodiments of this disclosure Figure 3 ;

[0023] Figure 5 A schematic diagram of the structure of the information display device provided in the embodiments of this disclosure;

[0024] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0026] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in one or more embodiments of this specification are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of related data must comply with relevant laws, regulations and standards, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0027] With the rapid development of video applications, accurately assessing video value has become a core issue for improving user experience and optimizing resource allocation. A video's "value score" integrates key indicators such as viewing time, user interaction (e.g., likes, comments, shares), and content characteristics to measure its popularity and potential. This scoring mechanism not only helps video applications prioritize high-value content but also dynamically adjusts its priority in the recommendation stream based on video performance, thereby maximizing resource utilization efficiency.

[0028] However, when the volume of videos becomes too large, to ensure the stability of the server system, it is not feasible to evaluate the value of all videos; instead, a subset of videos must be evaluated. At this point, determining which videos to select and when to trigger the video value model for evaluation becomes a pressing issue.

[0029] To address the technical problems in the existing technology, the inventor's technical concept is as follows:

[0030] First, the accuracy of selecting trending videos and calculating their value has a profound impact on video value assessment. Trending videos often gain a large number of interactions and views in a short period, and their value score may surge due to trending events, topic effects, or dissemination on social networks. However, this short-term popularity is not necessarily sustainable. Judging a video's long-term performance solely based on its high value score at a single moment can easily lead to bias. Therefore, video applications should prioritize recommending such content when its popularity reaches its peak. This can maximize user engagement and content exposure in the short term, but failure to adjust the value assessment of these videos in a timely manner may result in wasted resources, causing potentially valuable videos that should be promoted to be overlooked.

[0031] Secondly, the timing of the calculation is equally crucial, as results from different time points reflect different stages in a video's lifecycle. If video value calculations are limited to fixed time points, dynamic changes may be overlooked. Current technology obtains the total number of views for each video and determines the timing for calculating its score based on this total. However, a video might initially gain high attention due to a trending event, but as the event's popularity fades, views and interactions decrease. If the video application fails to update its value score in time, it may miss the signal of declining popularity, resulting in a "pseudo-high popularity" phenomenon. This means that due to the rapid decline in popularity, the video's actual value is not adjusted in time, causing it to occupy an excessively high priority position in the recommendation stream, affecting the display opportunities of other videos. Therefore, determining the timing of video score calculation based solely on total views has low accuracy.

[0032] In summary, the purpose of this invention is to propose a method for scoring the value of trending videos and replaying pseudo-trending videos. By monitoring video playback data and interaction changes in real time, the value score of the video is dynamically adjusted to avoid the "pseudo-trending" phenomenon in video recommendations, improve the accuracy of video application recommendations, and optimize resource allocation efficiency.

[0033] Accordingly, the specific steps may include: First, obtaining the first play count information and first video interaction information corresponding to each of the multiple first videos played within a first preset duration. Then, for each first video, determining whether the first video meets the preset scoring conditions based on the first play count information and / or the first video interaction information. Finally, if the first video meets the preset scoring conditions, calculating the first score of the first video using a video value model, and configuring the resource information of the first video based on the first score.

[0034] This technical solution dynamically adjusts the video's value score by monitoring real-time video playback data and interaction changes. This avoids the phenomenon of "pseudo-high popularity" in video recommendations, improves the accuracy of video application recommendations, and optimizes resource allocation efficiency. Therefore, the calculation frequency should be increased in the early stages of video release to capture trends in popularity; once the period of stability is reached, the frequency can be appropriately reduced to conserve computing resources. Thus, the dynamic calculation strategy accurately reflects the actual value of a video, improves resource allocation efficiency, optimizes user experience, and ensures the timeliness and accuracy of recommended content.

[0035] The following describes the specific implementation process of the resource information configuration method and device involved in the embodiments of this disclosure. Some examples are merely illustrative and not intended to limit the scope. The execution subject of the resource information configuration method involved in the embodiments of this disclosure is an electronic device, which may be a terminal, server, etc.

[0036] Figure 1 Flowchart of the resource information configuration method provided in the embodiments of this disclosure Figure 1 ,like Figure 1 As shown, the configuration method for this resource information may include:

[0037] S101. Obtain the first play count information and first video interaction information corresponding to each of the multiple first videos played within the first preset duration.

[0038] In this embodiment of the disclosure, the value of the first preset duration is not specifically limited and can be set and modified as needed. Optionally, the first preset duration is 1 hour, for example, a video played from 12:00 to 13:00.

[0039] Optionally, the first play count information includes the first play increase of the first video within a first preset duration; the first video interaction information includes the first interaction count, which includes the number of likes, comments, and shares of the first video within the first preset duration;

[0040] Specifically, the increase in the first video's first play count is positively correlated with the first video's popularity value. The first number of interactions with the first video is also positively correlated with the first video's popularity value.

[0041] In some embodiments, such as Figure 2 As shown, video playback logs reported by multiple clients are obtained. These logs include multiple video identifiers, and corresponding playback and interaction information for each identifier. Playback information includes the number of plays and playback duration. Interaction information includes the number of likes, comments, and shares. In this scenario, based on the video playback logs reported by multiple clients, the first play count and first video interaction information for each of the multiple first videos played within a first preset duration can be determined using a popularity counting service.

[0042] For example, multiple clients include client 1, client 2, and client 3.

[0043] The videos played by client 1 between 12:00 and 13:00 include: "Video 1, 2 views, 1 like, 0 comments, and 1 share", "Video 2, 2 views, 1 like, 0 comments, and 1 share", and "Video 3, 2 views, 1 like, 0 comments, and 1 share".

[0044] The videos played by client 2 between 12:00 and 13:00 include: "Video 1, 2 views, 1 like, 0 comments, and 1 share", "Video 3, 2 views, 1 like, 0 comments, and 1 share", and "Video 4, 2 views, 1 like, 0 comments, and 1 share".

[0045] The videos played by client 3 between 12:00 and 13:00 include: "Video 2, 2 views, 1 like, 0 comments, and 1 share", "Video 5, 2 views, 1 like, 0 comments, and 1 share", and "Video 6, 2 views, 1 like, 0 comments, and 1 share".

[0046] In this case, based on the video playback logs reported by multiple clients, the first playback count information and first video interaction information corresponding to each of the multiple first videos played within the first preset duration can be determined as follows:

[0047] Video 1, 4 views, 2 likes, 0 comments, and 2 shares. The corresponding first view increase is 4, and the first interaction is 4.

[0048] Video 2, views 4, likes 2, comments 0, shares 2. The corresponding first view increase is 4, and the first interaction is 4.

[0049] Video 3, views 4, likes 2, comments 0, shares 2. The corresponding first view increase is 4, and the first interaction is 4.

[0050] Video 4, 2 views, 1 like, 0 comments, and 1 share. The corresponding first view increase is 2, and the first interaction is 2.

[0051] Video 5, 2 views, 1 like, 0 comments, and 1 share. The corresponding first view increase is 2, and the first interaction is 2.

[0052] Video 6, 2 views, 1 like, 0 comments, and 1 share. The corresponding first view increase is 2, and the first interaction is 2.

[0053] S102. For each first video, determine whether the first video meets the preset scoring conditions based on the first video's first play count information and / or first video's first video interaction information.

[0054] In some embodiments, the first play count information includes a first play increase; the first video interaction information includes a first interaction count, which includes the number of likes, comments, and shares of the first video within a first preset duration; the preset rating conditions include: the first play increase reaching a preset threshold and / or the first interaction count reaching a preset number;

[0055] Accordingly, based on the first video's first play count information and / or the first video's first interaction information, it is determined whether the first video meets the preset scoring conditions, including: if the first video's first play count reaches a preset threshold and / or the first video's first interaction count reaches a preset number, then the first video is determined to meet the preset scoring conditions; if the first video's first play count does not reach the preset threshold and the first video's first interaction count does not reach the preset number, then the first video is determined not to meet the preset scoring conditions.

[0056] In this embodiment, the values ​​of the preset number of times and the preset threshold are not specifically limited, and can be modified and set as needed. For example, the preset number of times is 1000 times, and the preset threshold is 1000.

[0057] It should be noted that the initial view count and the initial interaction count of a first video are positively correlated with its popularity. Therefore, a first video's popularity is considered high when its initial view count reaches a preset threshold and / or its initial interaction count reaches a preset threshold. High-profile videos, often gaining significant interaction and viewership in a short period, may experience a surge in their value score due to trending events, topic effects, or social media dissemination. Calculating the video value of a first video at this point offers the highest cost-effectiveness.

[0058] In this embodiment of the disclosure, the playback logs of a video can be aggregated over a period of time to track changes in video views. If a video's views increase to a certain threshold within a set time period, it can be considered to have very high popularity, at which point calculating the video's value is most cost-effective. In other words, determining the timing of video value calculation based on video popularity improves the accuracy of the calculation, thereby enhancing the precision of recommended videos and optimizing resource allocation efficiency.

[0059] S103. If the first video meets the preset scoring conditions, the first score of the first video is calculated through the video value model, and the resource information of the first video is configured according to the first score of the first video.

[0060] In this embodiment of the disclosure, the video value model can be any model for calculating video value. Optionally, the video value model can be a neural network model. For example, data such as video views, viewing duration, and interaction volume can be input into the neural network model, which outputs a value score for the video.

[0061] Optionally, such as Figure 2 As shown, if the first video meets the preset scoring criteria, it is added to the video popularity event queue. Then, the first score of the first video in the event queue is calculated sequentially using the video value model.

[0062] In some embodiments, the resource information includes at least one of the following: video transcoding resources, video push priority, and video advertising resources. The video transcoding resources include multiple video transcoding formats, such as high-definition transcoding formats, standard-definition transcoding formats, and smooth transcoding formats.

[0063] Optionally, the higher the first score of the first video, the more resource information can be configured. The resource information of the first video can be configured according to the score range in which the first score falls. For example, the score range includes [0-40), [40-80), and [80-100].

[0064] For example, the first video has a score of 90, falling within the score range of [80-100]. In this case, the resource information corresponding to the first video is as follows: the video's transcoding resources include high-definition transcoding format, standard-definition transcoding format, and smooth transcoding format. The video's push priority is the highest priority. The video's advertising resources are also the highest priority resources.

[0065] For example, the first video has a score of 70, which falls within the score range of [40-80). In this case, the resource information corresponding to the first video is as follows: the video's transcoding resources include standard definition transcoding format and smooth transcoding format. The video's push priority is the second push priority. The video's advertising resources are second priority resources.

[0066] For example, the first video has a score of 20, which falls within the score range of [0-40]. In this case, the resource information corresponding to the first video is as follows: the video's transcoding resources include standard definition transcoding format and smooth transcoding format. The video's push priority is the third priority. The video's advertising resources are also third priority resources.

[0067] The following specific embodiment 1 illustrates the method for configuring resource information in the application.

[0068] Example 1: Given resource and cost constraints, it's impractical to assign value scores to all videos. By using a server-side popularity counting service, we can aggregate client playback logs to obtain the change in video playback volume over a certain period, and then select a batch of highly popular videos for value scoring. The specific steps are as follows:

[0069] Step 1: Set the aggregation time period T0: Let the length of the time period T0 be t_aggr, and let V be the set of videos that have been played within this time period. aggr .

[0070] Step 2: Let P(t, v) represent the video playback event that occurs at time t, and count the cumulative number of video plays C within the time period T0. v (T0) is:

[0071]

[0072] Step 3: Set the high-viewership video playback threshold: The high-viewership video playback threshold is: vv thresh .

[0073] Step 4: Perform high-frequency video detection: Count the cumulative number of views exceeding vv within the T0 time period. thresh All video collections V hot .

[0074] V hot ={v|v∈Vaggr ∩C v (T0)>vv thresh}

[0075] Step 5, High-Temperature Video Value Scoring: For the aggregated high-temporary video set V... hot The videos in the video are scored using a video value model.

[0076] This disclosure provides a method for configuring resource information, including: acquiring first play count information and first video interaction information corresponding to each of multiple first videos played within a first preset duration. For each first video, based on the first play count information and / or the first video interaction information, it is determined whether the first video meets preset scoring conditions. If the first video meets the preset scoring conditions, a first score is calculated using a video value model, and resource information for the first video is configured based on the first score. In this technical solution, by dynamically adjusting the video's value score through real-time monitoring of video playback data and interaction changes, the "pseudo-high popularity" phenomenon in video recommendations is avoided, improving the accuracy of video application recommendations and optimizing resource allocation efficiency. Thus, the calculation frequency should be increased in the early stages of video release to capture trends in popularity; the frequency can be appropriately reduced after entering a stable period to save computing resources. Therefore, the dynamic calculation strategy can accurately reflect the actual value of the video, improve resource allocation efficiency, optimize user experience, and ensure the timeliness and accuracy of recommended content.

[0077] Videos may initially gain high attention due to trending events, but as the event's popularity fades, views and interactions decrease. If the platform fails to update the value score in a timely manner, it may miss the signal of declining popularity, resulting in a "pseudo-high popularity" phenomenon. This means that due to the rapid decline in popularity, the video's actual value has not been adjusted in time, causing it to occupy an excessively high priority position in the recommendation feed and affecting the display opportunities of other videos.

[0078] In some embodiments, such as Figure 2 As shown, for target videos that have already been scored and configured with resource information, their play counts, viewing durations, and interaction volumes can be monitored through a pseudo-high-profile video detection service. If the interaction data (such as likes, comments, and shares) of these videos shows a significant decrease over a period of time, the video is added to the "pseudo-high-profile video replay queue." Then, the video value model recalculates the value score of the target videos in the pseudo-high-profile video replay queue. The advantage of this approach is that it avoids re-triggers video value assessment for all videos, saving system resources.

[0079] Optionally, such as Figure 3 As shown, the method may include:

[0080] S301. Obtain the second play count information and second video interaction information corresponding to each of the target videos with multiple configured resource information within a second preset time period.

[0081] In this embodiment of the disclosure, the value of the second preset duration is not specifically limited and can be set and modified as needed. Optionally, the second preset duration is 1 hour, for example, a video played from 13:00 to 14:00.

[0082] Optionally, the second play count information includes the second play increase of the target video within the second preset duration; the second video interaction information includes the second interaction count, which includes the number of likes, comments, and shares of the target video within the second preset duration.

[0083] In some embodiments, second play count information and second video interaction information corresponding to each of multiple target videos with configured resource information can be periodically acquired within a second preset duration. Accordingly, this step may include: acquiring the system's remaining resource information; determining the re-scoring cycle of the target videos based on the first score and / or remaining resource information of the target videos with configured resource information; and periodically acquiring the second play count information and second video interaction information corresponding to each target video within a second preset duration according to the re-scoring cycle.

[0084] Optionally, for videos with extremely high value, the iteration frequency of video value scores can be accelerated by shortening the re-scoring cycle time window, thus preventing the occurrence of falsely high-profile videos. When system resources are strained, the re-scoring cycle time window can be extended to reduce the iteration frequency of video value scores and prolong their validity period. Correspondingly, the higher the initial score, the shorter the re-scoring cycle. The less remaining resource information, the longer the re-scoring cycle.

[0085] For example, a dynamic time window can be set (e.g., 3 hours, 1 day, or 3 days), and the time window configuration can be dynamically adjusted according to business needs. For videos with extremely high value scores in the score range [80-100], the re-scoring cycle can be set to 3 hours. However, when the system's remaining resources are low (e.g., CPU resources are less than 10%), the re-scoring cycle can be adjusted to 1 day.

[0086] S302. For each target video, determine whether the target video meets the re-scoring criteria based on the second play count information and / or the second video interaction information of the target video.

[0087] Optionally, the increase in the second number of views for a target video is positively correlated with its popularity score. The number of second interactions for a target video is also positively correlated with its popularity score. In this case, videos with decreased popularity scores can be selected for re-evaluation.

[0088] Accordingly, based on the second view count information and / or the second video interaction information of the target video, it is determined whether the target video meets the re-scoring criteria, including:

[0089] If the second play count of the target video does not reach the preset threshold and the second interaction count of the target video does not reach the preset number of times, then the target video is determined to meet the re-scoring conditions.

[0090] If the second play count of the target video reaches a preset threshold and / or the second interaction count of the target video reaches a preset number, then the target video is determined not to meet the re-scoring conditions.

[0091] S303. If the target video meets the re-scoring conditions, the second score of the target video is calculated through the video value model, and the resource information of the target video is configured according to the first and second scores of the target video.

[0092] In this embodiment of the disclosure, if the difference between the first score and the second score is large, the popularity value of the target video will decrease significantly, and in this case, the resource information of the target video needs to be reconfigured.

[0093] Optionally, the resource information of the target video is configured based on the first score and the second score of the target video, including: determining the ratio of the first score to the second score; if the ratio is greater than a preset ratio, the resource information of the target video is reconfigured based on the second score; if the ratio is less than the preset ratio, the resource information of the target video is not reconfigured.

[0094] It should be noted that, to further conserve resources in video value assessment, the replay volume of pseudo-high-profile videos can be controlled through a threshold. That is, when there are a large number of target videos with configured resource information, videos with higher value can be selected for re-evaluation. Optionally, a threshold for re-triggering video value calculation can be preset. Only for videos whose current value exceeds the system's replay threshold will step S301 be executed to obtain the second playback volume information and second video interaction information corresponding to each video within a second preset duration.

[0095] In other embodiments, the video's value score is dynamically adjusted based on changes in popularity throughout the video's lifecycle to prevent videos with high initial popularity from still occupying too many recommendation resources after their popularity declines.

[0096] Optionally, such as Figure 2 As shown, when the popularity of a video rapidly declines, the business needs to adjust the video's value score in a timely manner. At this time, the offline data warehouse of the value model can be used to analyze pseudo-high-popularity videos.

[0097] Optionally, such as Figure 4As shown, a method for reconfiguring the resource information of a target video may include:

[0098] S401. Obtain a first video set consisting of multiple target videos whose first score is greater than a preset score among multiple first videos played within a first preset duration, and obtain a second video set consisting of multiple target videos whose second score is greater than a preset score among multiple second videos played within a second preset duration.

[0099] S402. For each target video in the first video set, if the target video does not belong to the second video set, then the target video is determined to meet the re-scoring condition.

[0100] S403. Calculate the second score of the target video using the video value model, and configure the resource information of the target video based on the first and second scores of the target video.

[0101] For example, such as Figure 2 As shown, the first preset duration is the comparison time period T1; the second preset duration is the verification time period T2.

[0102] The logic for detecting pseudo-high-temperature videos after a certain moment is as follows:

[0103] Step 1: Set the comparison time period T1: Let the length of time period T1 be t_slot, and let V be the length of all videos scored by the model within this time period. slot .

[0104] Step 2: Set the validation time period T2: Let the length of time period T2 be t_duration, and let V be the length of all videos scored by the model within this time period. duration .

[0105] Step 3: Calculate the latest score for any video within the verification period:

[0106] S v (T2)=S v (t latest ),t latest =argmax{t|S v (t) exists, and t∈T2}

[0107] Step 4: Set the high video value score threshold to: S thresh .

[0108] Step 5: Perform video pseudo-heat detection: Examine the time interval T1 = (t, t + t_slot) and its subsequent time interval T2 = (t + t_slot, t + t_slot + t_duration), and define the pseudo-heat video set V. replay for:

[0109] V replay ={v|v∈V slot ∩S v (T1)>S thresh and,

[0110] Step 6, Pseudo-high-heat video replay: Replay the aggregated pseudo-high-heat video set V replay The videos in the video are scored using a video value model.

[0111] In this embodiment of the disclosure, by scoring the value of high-profile videos and replaying pseudo-high-profile videos, the service can efficiently identify video content with real potential value under limited resources, optimize the platform's resource allocation and content recommendation strategy, achieve efficient and accurate video value monitoring and adjustment, and provide users with more accurate content recommendations and a richer viewing experience.

[0112] Figure 5 This is a schematic diagram of the structure of the resource information configuration device provided in the embodiments of this disclosure, as shown below. Figure 5 As shown, the resource information configuration device includes:

[0113] The acquisition unit 501 is used to acquire the first playback count information and the first video interaction information corresponding to each of the multiple first videos played within a first preset time period;

[0114] The determining unit 502 is used to determine, for each first video, whether the first video meets the preset scoring conditions based on the first play count information and / or the first video interaction information of the first video.

[0115] The configuration unit 503 is configured to calculate the first score of the first video through the video value model if the first video meets the preset scoring conditions, and configure the resource information of the first video according to the first score of the first video.

[0116] According to one or more embodiments of this disclosure, the first playback volume information includes a first playback growth rate; the first video interaction information includes a first interaction count, which includes the number of likes, comments, and shares of the first video within a first preset duration; the preset rating conditions include: the first playback growth rate reaching a preset threshold and / or the first interaction count reaching a preset number; accordingly, the determining unit 502 determines whether the first video meets the preset rating conditions based on the first playback volume information and / or the first video interaction information of the first video, specifically including: if the first playback growth rate of the first video reaches the preset threshold and / or the first interaction count of the first video reaches the preset number, then the first video is determined to meet the preset rating conditions; if the first playback growth rate of the first video does not reach the preset threshold and the first interaction count of the first video does not reach the preset number, then the first video does not meet the preset rating conditions.

[0117] According to one or more embodiments of this disclosure, the apparatus further includes: a reconfiguration unit, configured to acquire second play count information and second video interaction information corresponding to each of a plurality of target videos with configured resource information within a second preset duration; for each target video, determine whether the target video meets the re-scoring conditions based on the second play count information and / or the second video interaction information of the target video; if the target video meets the re-scoring conditions, calculate the second score of the target video through a video value model, and configure the resource information of the target video based on the first score and the second score of the target video.

[0118] According to one or more embodiments of this disclosure, the second playback volume information includes a second playback increase; the second video interaction information includes a second interaction count; the reconfiguration unit determines whether the target video meets the re-scoring conditions based on the second playback volume information and / or the second video interaction information of the target video, specifically including: if the second playback increase of the target video does not reach the preset threshold and the second interaction count of the target video does not reach the preset count, then the target video is determined to meet the re-scoring conditions; if the second playback increase of the target video reaches the preset threshold and / or the second interaction count of the target video reaches the preset count, then the target video does not meet the re-scoring conditions.

[0119] According to one or more embodiments of this disclosure, the reconfiguration unit is further configured to obtain the remaining resource information of the system; determine the re-scoring cycle of the target video based on the first score of the target video with configured resource information and / or the remaining resource information; and periodically obtain the second playback volume information and second video interaction information corresponding to each of the target videos within a second preset duration according to the re-scoring cycle.

[0120] According to one or more embodiments of this disclosure, the reconfiguration unit is further configured to obtain a first video set consisting of multiple target videos whose first scores are greater than preset scores among multiple first videos played within a first preset duration, and to obtain a second video set consisting of multiple target videos whose second scores are greater than the preset scores among multiple second videos played within a second preset duration; for each target video in the first video set, if the target video does not belong to the second video set, then the target video is determined to meet the re-scoring conditions; the second score of the target video is calculated through a video value model, and the resource information of the target video is configured according to the first score and the second score of the target video.

[0121] According to one or more embodiments of this disclosure, the reconfiguration unit configures the resource information of the target video based on a first score and a second score of the target video, specifically including: determining the ratio of the first score to the second score; if the ratio is greater than a preset ratio, then reconfiguring the resource information of the target video based on the second score; if the ratio is less than the preset ratio, then not reconfiguring the resource information of the target video.

[0122] According to one or more embodiments of this disclosure, the resource information includes at least one of the following: video transcoding resources, video push priority, and video advertising resources.

[0123] refer to Figure 6 The diagram illustrates a structural schematic of an electronic device 600 suitable for implementing embodiments of the present disclosure. The electronic device 600 can be a terminal device or a server. The terminal device can include, but is not limited to, mobile terminals such as mobile phones, laptops, digital broadcast receivers, personal digital assistants (PDAs), tablet computers, portable media players (PMPs), and in-vehicle terminals (e.g., in-vehicle navigation terminals), as well as fixed terminals such as digital TVs and desktop computers. Figure 6 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments disclosed herein.

[0124] like Figure 6 As shown, electronic device 600 may include a processing unit (e.g., a central processing unit, a graphics processing unit, etc.) 601, which can perform various appropriate actions and processes according to a program stored in read-only memory (ROM) 602 or a program loaded from storage device 608 into random access memory (RAM) 603. RAM 603 also stores various programs and data required for the operation of electronic device 600. The processing unit 601, ROM 602, and RAM 603 are interconnected via bus 604. Input / output (I / O) interface 605 is also connected to bus 604.

[0125] Typically, the following devices can be connected to I / O interface 605: input devices 606 including, for example, touchscreens, touchpads, keyboards, mice, cameras, microphones, accelerometers, gyroscopes, etc.; output devices 607 including, for example, liquid crystal displays (LCDs), speakers, vibrators, etc.; storage devices 608 including, for example, magnetic tapes, hard disks, etc.; and communication devices 609. Communication device 609 allows electronic device 600 to communicate wirelessly or wiredly with other devices to exchange data. Although Figure 6 An electronic device 600 with various devices is shown; however, it should be understood that it is not required to implement or possess all of the devices shown. More or fewer devices may be implemented or possessed alternatively.

[0126] In particular, according to embodiments of this disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this disclosure 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 609, or installed from a storage device 608, or installed from a ROM 602. When the computer program is executed by the processing device 601, it performs the functions defined in the methods of embodiments of this disclosure.

[0127] It should be noted that the computer-readable medium described in this disclosure can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this disclosure, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in connection with an instruction execution system, apparatus, or device. In this disclosure, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium can be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wires, optical fibers, RF (radio frequency), etc., or any suitable combination thereof.

[0128] The aforementioned computer-readable medium may be included in the aforementioned electronic device; or it may exist independently and not assembled into the electronic device.

[0129] The aforementioned computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the methods shown in the above embodiments.

[0130] Computer program code for performing the operations of this disclosure 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).

[0131] 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 disclosure. 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.

[0132] The units described in the embodiments of this disclosure can be implemented in software or in hardware. The name of a unit does not necessarily limit the unit itself; for example, the first acquisition unit can also be described as "a unit that acquires at least two Internet Protocol addresses".

[0133] The functions described above in this document can be performed, at least in part, by one or more hardware logic components. For example, exemplary types of hardware logic components that can be used, without limitation, include: Field Programmable Gate Arrays (FPGAs), Application-Specific Integrated Circuits (ASICs), Application Standard Products (ASSPs), System-on-Chip (SoCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0134] In a first aspect, according to one or more embodiments of this disclosure, a method for configuring resource information is provided, comprising:

[0135] Obtain the first play count information and first video interaction information corresponding to each of the multiple first videos played within a first preset time period;

[0136] For each first video, determine whether the first video meets the preset scoring conditions based on the first video's first play count information and / or first video's first video interaction information;

[0137] If the first video meets the preset scoring conditions, then the first score of the first video is calculated using the video value model, and the resource information of the first video is configured based on the first score of the first video.

[0138] According to one or more embodiments of this disclosure, the first playback volume information includes a first playback growth rate; the first video interaction information includes a first interaction count, which includes the number of likes, comments, and shares of the first video within a first preset duration; the preset rating conditions include: the first playback growth rate reaching a preset threshold and / or the first interaction count reaching a preset number; correspondingly, determining whether the first video meets the preset rating conditions based on the first playback volume information and / or the first video interaction information includes: if the first playback growth rate of the first video reaches the preset threshold and / or the first interaction count of the first video reaches the preset number, then the first video is determined to meet the preset rating conditions; if the first playback growth rate of the first video does not reach the preset threshold and the first interaction count of the first video does not reach the preset number, then the first video does not meet the preset rating conditions.

[0139] According to one or more embodiments of this disclosure, the method further includes: acquiring second play count information and second video interaction information corresponding to each of a plurality of target videos with configured resource information within a second preset duration; for each target video, determining whether the target video meets the re-scoring conditions based on the second play count information and / or the second video interaction information of the target video; if the target video meets the re-scoring conditions, calculating the second score of the target video through a video value model, and configuring the resource information of the target video based on the first score and the second score of the target video.

[0140] According to one or more embodiments of this disclosure, the second playback volume information includes a second playback increase; the second video interaction information includes a second interaction count; determining whether the target video meets the re-rating conditions based on the second playback volume information and / or the second video interaction information includes: if the second playback increase of the target video does not reach the preset threshold and the second interaction count of the target video does not reach the preset count, then the target video is determined to meet the re-rating conditions; if the second playback increase of the target video reaches the preset threshold and / or the second interaction count of the target video reaches the preset count, then the target video does not meet the re-rating conditions.

[0141] According to one or more embodiments of this disclosure, the method further includes: obtaining resource remaining information of the system; determining a re-scoring cycle for the target video based on a first score of the target video with configured resource information and / or the resource remaining information; and periodically obtaining second play count information and second video interaction information corresponding to each of the target videos within a second preset duration according to the re-scoring cycle.

[0142] According to one or more embodiments of this disclosure, the method further includes: obtaining a first video set consisting of multiple target videos whose first score is greater than a preset score among multiple first videos played within a first preset duration; and obtaining a second video set consisting of multiple target videos whose second score is greater than the preset score among multiple second videos played within a second preset duration; for each target video in the first video set, if the target video does not belong to the second video set, then determining that the target video meets the re-scoring condition; calculating the second score of the target video through a video value model, and configuring the resource information of the target video according to the first score and the second score of the target video.

[0143] According to one or more embodiments of this disclosure, configuring the resource information of the target video based on a first score and a second score includes: determining a ratio of the first score to the second score; if the ratio is greater than a preset ratio, reconfiguring the resource information of the target video based on the second score; if the ratio is less than the preset ratio, not reconfiguring the resource information of the target video.

[0144] According to one or more embodiments of this disclosure, the resource information includes at least one of the following: video transcoding resources, video push priority, and video advertising resources.

[0145] Secondly, according to one or more embodiments of this disclosure, a resource information configuration apparatus is provided, comprising:

[0146] The acquisition unit is used to acquire the first playback count information and the first video interaction information corresponding to each of the multiple first videos played within a first preset time period;

[0147] The determining unit is used to determine, for each first video, whether the first video meets the preset scoring conditions based on the first video's first play count information and / or first video's first video interaction information.

[0148] The configuration unit is configured to, if the first video meets the preset scoring conditions, calculate the first score of the first video through the video value model, and configure the resource information of the first video based on the first score of the first video.

[0149] According to one or more embodiments of this disclosure, the first playback volume information includes a first playback growth rate; the first video interaction information includes a first interaction count, which includes the number of likes, comments, and shares of the first video within a first preset duration; the preset rating conditions include: the first playback growth rate reaching a preset threshold and / or the first interaction count reaching a preset number; accordingly, the determining unit 502 determines whether the first video meets the preset rating conditions based on the first playback volume information and / or the first video interaction information of the first video, specifically including: if the first playback growth rate of the first video reaches the preset threshold and / or the first interaction count of the first video reaches the preset number, then the first video is determined to meet the preset rating conditions; if the first playback growth rate of the first video does not reach the preset threshold and the first interaction count of the first video does not reach the preset number, then the first video does not meet the preset rating conditions.

[0150] According to one or more embodiments of this disclosure, the apparatus further includes: a reconfiguration unit, configured to acquire second play count information and second video interaction information corresponding to each of a plurality of target videos with configured resource information within a second preset duration; for each target video, determine whether the target video meets the re-scoring conditions based on the second play count information and / or the second video interaction information of the target video; if the target video meets the re-scoring conditions, calculate the second score of the target video through a video value model, and configure the resource information of the target video based on the first score and the second score of the target video.

[0151] According to one or more embodiments of this disclosure, the second playback volume information includes a second playback increase; the second video interaction information includes a second interaction count; the reconfiguration unit determines whether the target video meets the re-scoring conditions based on the second playback volume information and / or the second video interaction information of the target video, specifically including: if the second playback increase of the target video does not reach the preset threshold and the second interaction count of the target video does not reach the preset count, then the target video is determined to meet the re-scoring conditions; if the second playback increase of the target video reaches the preset threshold and / or the second interaction count of the target video reaches the preset count, then the target video does not meet the re-scoring conditions.

[0152] According to one or more embodiments of this disclosure, the reconfiguration unit is further configured to obtain the remaining resource information of the system; determine the re-scoring cycle of the target video based on the first score of the target video with configured resource information and / or the remaining resource information; and periodically obtain the second playback volume information and second video interaction information corresponding to each of the target videos within a second preset duration according to the re-scoring cycle.

[0153] According to one or more embodiments of this disclosure, the reconfiguration unit is further configured to obtain a first video set consisting of multiple target videos whose first scores are greater than preset scores among multiple first videos played within a first preset duration, and to obtain a second video set consisting of multiple target videos whose second scores are greater than the preset scores among multiple second videos played within a second preset duration; for each target video in the first video set, if the target video does not belong to the second video set, then the target video is determined to meet the re-scoring conditions; the second score of the target video is calculated through a video value model, and the resource information of the target video is configured according to the first score and the second score of the target video.

[0154] According to one or more embodiments of this disclosure, the reconfiguration unit configures the resource information of the target video based on a first score and a second score of the target video, specifically including: determining the ratio of the first score to the second score; if the ratio is greater than a preset ratio, then reconfiguring the resource information of the target video based on the second score; if the ratio is less than the preset ratio, then not reconfiguring the resource information of the target video.

[0155] According to one or more embodiments of this disclosure, the resource information includes at least one of the following: video transcoding resources, video push priority, and video advertising resources.

[0156] Thirdly, according to one or more embodiments of the present disclosure, an electronic device is provided, comprising: at least one processor and a memory;

[0157] The memory stores computer-executed instructions;

[0158] The at least one processor executes computer execution instructions stored in the memory, causing the at least one processor to perform the resource information configuration method described in the first aspect and various possible designs of the first aspect.

[0159] Fourthly, according to one or more embodiments of the present disclosure, a computer-readable storage medium is provided, wherein computer-executable instructions are stored therein, and when a processor executes the computer-executable instructions, the resource information configuration method described in the first aspect and various possible designs of the first aspect is implemented.

[0160] Fifthly, according to one or more embodiments of the present disclosure, a computer program product is provided, including a computer program that, when executed by a processor, implements the resource information configuration method described in the first aspect and various possible designs of the first aspect.

[0161] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the above-described concept. For example, technical solutions formed by substituting the above features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

[0162] Furthermore, while the operations are described in a specific order, this should not be construed as requiring these operations to be performed in the specific order shown or in a sequential order. In certain environments, multitasking and parallel processing may be advantageous. Similarly, while several specific implementation details are included in the above discussion, these should not be construed as limiting the scope of this disclosure. Certain features described in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments.

[0163] Although the subject matter has been described using language specific to structural features and / or methodological logic, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. Rather, the specific features and actions described above are merely illustrative examples of implementing the claims.

Claims

1. A method for configuring resource information, characterized in that, include: Obtain the first play count information and first video interaction information corresponding to each of the multiple first videos played within a first preset time period; For each first video, determine whether the first video meets the preset scoring conditions based on the first video's first play count information and / or first video's first video interaction information; If the first video meets the preset scoring conditions, then the first score of the first video is calculated using the video value model, and the resource information of the first video is configured based on the first score of the first video.

2. The method according to claim 1, characterized in that, The first play count information includes the first play increase; the first video interaction information includes the first interaction count, which includes the number of likes, comments, and shares of the first video within a first preset duration; The preset scoring conditions include: the first playback growth reaches a preset threshold and / or the first interaction reaches a preset number of times; Accordingly, determining whether the first video meets the preset scoring conditions based on the first video's first play count information and / or first video interaction information includes: If the first playback growth of the first video reaches a preset threshold and / or the first interaction count of the first video reaches a preset number, then the first video is determined to meet the preset scoring conditions. If the first playback growth of the first video does not reach the preset threshold and the first interaction count of the first video does not reach the preset count, then it is determined that the first video does not meet the preset scoring conditions.

3. The method according to claim 1, characterized in that, The method further includes: Acquire the second play count information and second video interaction information corresponding to each of the target videos with multiple configured resource information within a second preset duration; For each target video, based on the second play count information and / or the second video interaction information of the target video, determine whether the target video meets the re-scoring conditions; If the target video meets the re-scoring conditions, then the second score of the target video is calculated using the video value model, and the resource information of the target video is configured based on the first and second scores of the target video.

4. The method according to claim 3, characterized in that, The second play count information includes the second play increase; the second video interaction information includes the second number of interactions; The step of determining whether the target video meets the re-rating criteria based on the second play count information and / or the second video interaction information of the target video includes: If the second playback growth of the target video does not reach the preset threshold and the second interaction count of the target video does not reach the preset count, then the target video is determined to meet the re-scoring conditions. If the second playback increase of the target video reaches the preset threshold and / or the second interaction count of the target video reaches the preset number, then the target video is determined not to meet the re-scoring conditions.

5. The method according to claim 3, characterized in that, The method further includes: Obtain information on remaining system resources; The re-scoring cycle of the target video is determined based on the first score of the target video with configured resource information and / or the remaining resource information. According to the re-scoring cycle, the second play count information and second video interaction information corresponding to each of the target videos within a second preset duration are periodically obtained.

6. The method according to claim 1, characterized in that, The method further includes: Obtain a first video set consisting of multiple target videos whose first score is greater than a preset score from multiple first videos played within a first preset duration; and obtain a second video set consisting of multiple target videos whose second score is greater than the preset score from multiple second videos played within a second preset duration. For each target video in the first video set, if the target video does not belong to the second video set, then the target video is determined to meet the re-scoring conditions; The second score of the target video is calculated using a video value model, and the resource information of the target video is configured based on the first and second scores.

7. The method according to claim 3 or 6, characterized in that, The step of configuring the resource information of the target video based on the first score and the second score of the target video includes: Determine the ratio of the first score to the second score; If the ratio is greater than a preset ratio, the resource information of the target video is reconfigured according to the second score; if the ratio is less than the preset ratio, the resource information of the target video is not reconfigured.

8. The method according to any one of claims 1 to 6, characterized in that, The resource information includes at least one of the following: video transcoding resources, video push priority, and video advertising resources.

9. A resource information configuration device, characterized in that, The device includes: The acquisition unit is used to acquire the first playback count information and the first video interaction information corresponding to each of the multiple first videos played within a first preset time period; The determining unit is used to determine, for each first video, whether the first video meets the preset scoring conditions based on the first video's first play count information and / or first video's first video interaction information. The configuration unit is configured to, if the first video meets the preset scoring conditions, calculate the first score of the first video through the video value model, and configure the resource information of the first video based on the first score of the first video.

10. An electronic device, characterized in that, include: Processor and memory; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the resource information configuration method as described in any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, implement the resource information configuration method as described in any one of claims 1 to 8.

12. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the resource information configuration method as described in any one of claims 1 to 8.

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