Data processing method and device and storage medium

Abstract

The invention relates to a data processing method and device and a storage medium, and the data processing method comprises the steps: obtaining first multimedia data and time information corresponding to the first multimedia data, the first multimedia data belongs to preset multimedia data, and the preset multimedia data is multimedia data played by a user; according to the time information corresponding to the first multimedia data, cutting the first multimedia data to obtain second multimedia data, the second multimedia data comprising a plurality of data slices, and the time interval between each two adjacent data slices being a preset time interval; and determining playing information according to the second multimedia data, the playing information being used for representing the playing condition of the preset multimedia data. According to the data processing method and device and the storage medium, the data processing difficulty can be effectively reduced, and then efficient and accurate analysis processing of the data is achieved.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular, to a data processing method, device, and storage medium. Background Art

[0002] With the development of computer technology, multimedia data processing technology has also developed. For example, in the field of teaching, video interaction can be used to broadcast or record teaching. During the video interaction process, a large amount of video data is involved. By analyzing and calculating this video data, the teaching situation can be evaluated. Summary of the Invention

[0003] The purpose of the present disclosure is to provide a data processing method, device and storage medium, which can effectively reduce the difficulty of data processing and thus achieve efficient and accurate analysis and processing of data.

[0004] In order to achieve the above-mentioned purpose, in a first aspect, the present disclosure provides a data processing method, including: obtaining first multimedia data and time information corresponding to the first multimedia data, the first multimedia data belonging to preset multimedia data, and the preset multimedia data being multimedia data played by a user; according to the time information corresponding to the first multimedia data, cutting the first multimedia data to obtain second multimedia data, the second multimedia data including multiple data slices, and the time intervals between each adjacent data slice are preset time intervals; determining playback information based on the second multimedia data, the playback information being used to characterize the playback status of the preset multimedia data.

[0005] Optionally, the data processing method is applied to the server, and obtaining the first multimedia data and the time information corresponding to the first multimedia data includes: receiving the original multimedia data sent by the client, the original multimedia data being the multimedia data collected by the client based on the user's playback behavior during the user's playback of the preset multimedia data; determining the first multimedia data and the time information corresponding to the first multimedia data based on the original multimedia data.

[0006] Optionally, the original multimedia data is compressed data, and determining the time information corresponding to the first multimedia data and the first multimedia data based on the original multimedia data includes: decompressing the original multimedia data to obtain decompressed original multimedia data; and determining the time information corresponding to the first multimedia data and the first multimedia data based on the decompressed original multimedia data.

[0007] Optionally, determining the playback information based on the second multimedia data includes: performing array conversion on the multiple data slices to obtain a target array, where different array elements in the target array correspond to different data slices; and determining the playback information based on the target array.

[0008] Optionally, determining the playback information based on the target array includes: deduplicating repeated array elements in the target array to obtain a deduplicated target array; and determining the playback information based on data slices corresponding to array elements in the deduplicated target array.

[0009] Optionally, determining the playback information based on the target array includes: determining the repeated array elements in the target array; determining the degree of repetition based on the number of the repeated array elements and the total number of array elements in the target array; and determining the playback information used to characterize the repeated playback situation based on the repetition degree and the repeated array elements.

[0010] Optionally, the first multimedia data includes multiple sub-multimedia data, each of which corresponds to different user playback behaviors. The multiple data slices include data slices corresponding to the multiple sub-multimedia data respectively. The array conversion of the multiple data slices to obtain a target array includes: performing array conversion on the data slices corresponding to the multiple sub-multimedia data respectively to obtain multiple arrays; and determining the target array based on the multiple arrays.

[0011] In a second aspect, the present disclosure provides a data processing device, including: an acquisition module, configured to acquire first multimedia data and time information corresponding to the first multimedia data, the first multimedia data belonging to preset multimedia data, and the preset multimedia data being multimedia data played by a user; a processing module, configured to: cut the first multimedia data according to the time information corresponding to the first multimedia data to obtain second multimedia data, the second multimedia data including multiple data slices, and the time intervals between adjacent data slices are preset time intervals; determine playback information based on the second multimedia data, the playback information being used to characterize the playback status of the preset multimedia data.

[0012] In a third aspect, the present disclosure provides a non-temporary computer-readable storage medium having a computer program stored thereon, which implements the data processing method described in the first aspect when executed by a processor.

[0013] In a fourth aspect, the present disclosure provides a data processing device, comprising: a memory on which a computer program is stored; and a processor for executing the computer program in the memory to implement the data processing method described in the first aspect.

[0014] The above technical solution performs data segmentation based on first multimedia data within multimedia data played by a user, generating second multimedia data comprising multiple data slices, wherein the time interval between adjacent data slices is a preset time interval. Furthermore, the second multimedia data is used to determine playback information representing the playback status of the preset multimedia data. The segmentation of the multimedia data achieves fine-grained data segmentation and unified data structure, effectively reducing data processing difficulty and enabling efficient and accurate analysis and processing of multimedia data.

[0015] Other features and advantages of the present disclosure will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings are used to provide a further understanding of the present disclosure and constitute a part of the specification. Together with the following detailed description, they are used to explain the present disclosure but do not constitute a limitation of the present disclosure. In the accompanying drawings: Figure 1 It is a block diagram of a data processing system according to an exemplary embodiment.

[0017] Figure 2 The figure is a flow chart showing a data processing method according to an exemplary embodiment.

[0018] Figure 3 The figure is a schematic diagram of data conversion according to an exemplary embodiment.

[0019] Figure 4 It is a block diagram of a data processing device according to an exemplary embodiment.

[0020] Figure 5 It is a block diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0021] The following describes the specific embodiments of the present disclosure in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to illustrate and explain the present disclosure and are not intended to limit the present disclosure.

[0022] It should be noted that all actions of acquiring signals, information or data in the present disclosure are carried out in compliance with the corresponding data protection laws and policies of the country where they are located and with the authorization given by the owner of the corresponding device.

[0023] With the development of computer technology, multimedia data processing technology has also developed. Multimedia data, such as video data, audio data, and image data, can also be regarded as a kind of streaming data, which can be played as an information stream on the corresponding streaming platform.

[0024] For these multimedia data, there are corresponding data analysis and processing requirements in different application scenarios. For example, in a teaching scenario, video interaction can be used to broadcast or record teaching. The live or recorded video data can be considered a type of multimedia data. During the video interaction process, a large amount of video data is involved. By analyzing and calculating this video data, the teaching situation can be evaluated. Of course, in addition to video data, it can also be in the form of audio data, which is not limited here.

[0025] Currently, there's no effective method for detailed granularity calculations when processing this type of multimedia data. We can only roughly calculate basic completion rates, or calculate completion rates by a few nodes. We can't achieve minute-by-minute statistics or calculate them by free time intervals. In other words, we can only use crude data calculations or data analysis methods to achieve relatively simple data statistics, such as the completion rate of instructional videos.

[0026] Based on this, the embodiment of the present disclosure provides a technical solution in which multimedia data is cut and processed to achieve fine-grained splitting of multimedia data and unification of data structure, effectively reducing the difficulty of data processing. Thus, efficient and accurate analysis and processing of multimedia data can be achieved, and more effective information can be obtained through analysis and calculation.

[0027] Figure 1 1 is a block diagram of a data processing system 100 according to an exemplary embodiment. The data processing system 100 includes a client 101 and a server 102 , wherein the client 101 and the server 102 can be connected through network communication.

[0028] It is understood that the client 101 may include one or more clients 101, and the server 102 may include one or more servers 102, and is not limited to Figure 1 Quantity shown.

[0029] In the data processing system 100, the client 101 can serve as a data processing front-end, which can also serve as a human-computer interaction terminal to implement human-computer interaction based on multimedia data. The server 102 can serve as a data processing back-end, which can also serve as a data processing terminal to implement data processing, including analysis, calculation, and storage.

[0030] Taking a teaching scenario as an example, client 101 can obtain teaching videos from server 102, and users can play the teaching videos through client 101 for learning. Furthermore, while client 101 is playing the teaching videos, it can also collect video data based on the user's playback behavior and send the collected video data to server 102. Server 102 then performs data calculations and analysis based on the data sent by client 101 to determine relevant information that represents the user's teaching situation.

[0031] It is understood that the above teaching scenarios may include not only teaching videos but also multimedia data such as teaching audio. In addition, in addition to teaching scenarios, other scenarios involving data analysis requirements may also be used, which are not limited in the embodiments of the present disclosure.

[0032] Figure 2 is a flow chart showing a data processing method according to an exemplary embodiment. The data processing method can be applied to Figure 1 The server 102 of the data processing system 100 shown in FIG. Figure 2 As shown, the data processing method includes the following steps: Step S21 : obtaining first multimedia data and time information corresponding to the first multimedia data, where the first multimedia data is preset multimedia data, and the preset multimedia data is multimedia data played by a user.

[0033] Step S22: Slice the first multimedia data according to the time information corresponding to the first multimedia data to obtain second multimedia data. The second multimedia data includes a plurality of data slices, and the time interval between each adjacent data slice is a preset time interval.

[0034] Step S23: determining playback information according to the second multimedia data, where the playback information is used to represent the playback status of the preset multimedia data.

[0035] In some embodiments, the preset multimedia data may be video data, audio data, or picture data.

[0036] In some embodiments, the preset multimedia data may be played on the client 101 based on the user's interactive behavior.

[0037] In some embodiments, the first multimedia data is part of the preset multimedia data and may be part of the preset multimedia data. For example, if the preset multimedia data is a video segment with a total duration of 10 minutes, the first multimedia data may be the video data corresponding to minutes 0 to 5. Therefore, the first multimedia data also includes time information, which may indicate the relationship between the first multimedia data and the preset multimedia data.

[0038] In some embodiments, a user plays preset multimedia data on client 101. However, this playback behavior may occur in various situations. For example, for a 10-minute video, the user may watch the entire 10 minutes at once; or the user may watch 5 minutes first and then rewind to 2 minutes to continue watching. Therefore, the playback behavior may result in the video progress being dragged from 5 minutes to 2 minutes. Therefore, different first multimedia data may be generated based on different playback behaviors.

[0039] Since the user's playing behavior occurs on the client 101 and the data analysis and calculation is implemented by the server 102, the client 101 can collect data based on the user's playing behavior to determine the first multimedia data.

[0040] Therefore, as an optional implementation, step S21 includes: receiving original multimedia data sent by the client 101, the original multimedia data being multimedia data collected by the client 101 based on the user's playback behavior during the user's playback of preset multimedia data; and determining the first multimedia data and the time information corresponding to the first multimedia data based on the original multimedia data.

[0041] Regarding the collection of multimedia data based on user playback behavior, for example, if a user watches a video from 0 minutes to 5 minutes, then rewinds to 2 minutes to continue watching, this will result in a playback behavior that drags the video progress from 5 minutes to 2 minutes. Accordingly, the 5-minute node is considered the playback behavior change node. Therefore, video data from 0 to 5 minutes can be collected, as well as data from 2 minutes to subsequent time nodes. The subsequent time node may be the time node of the next playback behavior change, or it may be the final time node of the video data, that is, the user continues watching from 2 minutes to the end of the video.

[0042] Therefore, the original multimedia data may be multimedia data collected once or multiple times during a preset multimedia data playback process. Furthermore, the first multimedia data and the time information corresponding to the first multimedia data may be determined based on the original multimedia data.

[0043] It is understood that since the amount of multimedia data may be relatively large, in order to ensure data transmission stability between the client 101 and the video terminal, the client 101 may compress the transmitted data. Therefore, in some embodiments, the original multimedia data is compressed data. Accordingly, determining the first multimedia data and the time information corresponding to the first multimedia data based on the original multimedia data includes: decompressing the original multimedia data to obtain the decompressed original multimedia data; and determining the first multimedia data and the time information corresponding to the first multimedia data based on the decompressed original multimedia data.

[0044] In some embodiments, the original multimedia data can be in the form of a string, which includes a string representing time information and a string representing data content. By decompressing the original multimedia data, the first multimedia data and the time information corresponding to the first multimedia data can be obtained. Correspondingly, the first multimedia data and the time information corresponding to the first multimedia data can also be in the form of a string.

[0045] In some embodiments, a user may generate multiple playback behaviors. Accordingly, the first multimedia data may include multiple sub-multimedia data, each of which corresponds to a different user playback behavior.

[0046] It can be understood that the above multimedia data may also include name information, for example: video1.

[0047] For example, assume the compressed original multimedia data is represented as [1-3]g, [2-4]g, and [3-5]g. After decompression, the three first multimedia data pieces are obtained: 1, 2, 3; 2, 3, 4; and 3, 4, 5. 1, 2, 3 can represent video data from 1 minute to 3 minutes; 2, 3, 4 can represent video data from 2 minutes to 4 minutes; and 3, 4, 5 can represent video data from 3 minutes to 5 minutes. Accordingly, the user's playback behavior may be: play from 1 minute to 3 minutes; then rewind to 2 minutes, then from 2 minutes to 4 minutes; then rewind to 3 minutes, and then from 3 minutes to 5 minutes. As can be seen, the three video data pieces correspond to three different playback behaviors.

[0048] In teaching scenarios, taking into account the need for detailed statistics on users' consumption or repeated consumption of educational videos, it is necessary to collect a large amount of user consumption data for accurate analysis and statistics. Due to the huge amount of data, the reporting needs to be compressed, but the compressed data cannot be calculated and must be as close to the calculation characteristics as possible.

[0049] In addition, since the data structure reported by the client 101 is not uniform, storage is inconvenient and not suitable for related calculations of the database.

[0050] Therefore, in the embodiment of the present disclosure, a distributed and small-fragment approach is adopted, which can split and stage the calculation features, while also taking into account the characteristics of partial calculation stability (without affecting the final result), thereby improving the data calculation speed.

[0051] Thus, in step S22, the first multimedia data is segmented according to the time information corresponding to the first multimedia data to obtain second multimedia data. The second multimedia data includes multiple data slices, and the time intervals between adjacent data slices are all preset time intervals, so that the data format is unified.

[0052] In some embodiments, the preset time interval can be configured according to the estimated data granularity of the server 102. For example, if the video data is processed at the minute level, the preset time interval can be 1 minute; if the video data is processed at the second level, the preset time interval can be 1 second.

[0053] In some embodiments, since the first multimedia data has corresponding time information, after being cut, the obtained data slices also have corresponding time information, so the order of the multiple data slices may not be restricted.

[0054] In some embodiments, the multiple data slices may be data within a continuous time interval or data within a discontinuous time interval.

[0055] In some embodiments, based on the first multimedia data being multiple components of multimedia data, the obtained multiple data slices may also include data slices corresponding to the multiple components of multimedia data.

[0056] For example, assume that the compressed original multimedia data is represented as [1-3]g, [2-4]g, and [3-5]g. After decompression, the first multimedia data is obtained as follows: 1, 2, 3; 2, 3, 4; and 3, 4, 5. Therefore, after the first multimedia data is split, the three data slices 1, 2, and 3 are obtained; after the second multimedia data is split, the three data slices 2, 3, and 4 are obtained; and after the third multimedia data is split, the three data slices 3, 4, and 5 are obtained.

[0057] It should be noted that the above 1 to 5 are abbreviations of string data. In actual application scenarios, 1 to 5 are all data in string format.

[0058] Based on these multiple, phased and distributed data slices, various data computation operations can be conveniently performed. Therefore, in step S23, data analysis is performed based on the second multimedia data to determine playback information. This playback information can characterize the playback status of the preset multimedia data. In an educational setting, this information can characterize the consumption of the teaching video. Different playback information can be determined in different application scenarios.

[0059] In some embodiments, in order to facilitate data calculation and analysis, data in string form may be converted into array form.

[0060] Therefore, as an optional implementation, step S23 includes: performing array conversion on multiple data slices to obtain a target array, where different array elements in the target array correspond to different data slices; and determining playback information according to the target array.

[0061] In some embodiments, different data elements correspond to different data slices. It can be understood that the array elements in the target array are only used to represent the corresponding data slices, rather than the data of the data slices themselves. Accordingly, the data of the data slices themselves still exist, but data analysis and calculation do not need to be performed. Instead, they are converted into calculations on array elements to achieve data analysis and calculations.

[0062] In some embodiments, the target array and the playback information may be stored in a preset format, such as jsonb format, to facilitate subsequent query at any time.

[0063] In some embodiments, the playback information may be understood as data features extracted from the data, which may reflect the status of the data.

[0064] In some embodiments, when the first multimedia data includes multiple components of multimedia data, the multiple components of multimedia data correspond to different user playback behaviors, and the multiple data slices include data slices corresponding to the multiple components of multimedia data, performing array conversion on the multiple data slices to obtain a target array may include: performing array conversion on the data slices corresponding to the multiple components of multimedia data to obtain multiple arrays; and determining the target array based on the multiple arrays.

[0065] In this embodiment, multiple arrays may be integrated, and the integrated array may be used as the target array.

[0066] In some embodiments, array elements may be integrated while performing array conversion on multiple data slices.

[0067] In some embodiments, array elements in multiple arrays may not be sorted, but are sorted when the target array is obtained by integration.

[0068] In some embodiments, if the data processing requirement is deduplication, then when determining the target array, duplicate elements therein may also be deduplicated, so that the final target array does not contain duplicate array elements.

[0069] Figure 3 FIG. 1 is a schematic diagram of data conversion according to an exemplary embodiment. Figure 3As shown in the figure, in the initial stage, multimedia data is presented as compressed data, including [1-3]g, [2-4]g, and [3-5]g. After decompression, three data sets are obtained: 1, 2, 3; 2, 3, 4; and 3, 4, 5. The data is in string format. After data segmentation and array conversion, three arrays are obtained: [1, 2, 3], [2, 3, 4], and [3, 4, 5]. By deduplicating these three arrays and merging them, the target array [1, 2, 3, 4, 5] is obtained. This target array directly reflects the playback information: the user watched (played) a total of 5 minutes of video.

[0070] Moreover, based on the three arrays [1,2,3], [2,3,4] and [3,4,5], a variety of flexible array calculation methods can also be used. For example, split calculation, first calculate the array [1,2,3] and the array [2,3,4], and then calculate them together with the array [3,4,5]. The result remains unchanged, reflecting the exchange rate and associativity, etc. It is not only suitable for large amounts of data, but also for distributed computing (for example, it can be distributed to different devices for calculation) or staged calculation analysis.

[0071] In some embodiments, determining playback information based on the target array may include: deduplicating repeated array elements in the target array to obtain a deduplicated target array; and determining playback information based on data slices corresponding to array elements in the deduplicated target array.

[0072] In this embodiment, the playback information may be the playback progress of preset multimedia data. The playback progress may be determined by deduplication processing based on the data cutting granularity and the number of corresponding data slices.

[0073] In some embodiments, if deduplication is not performed, the playback duration can be determined by counting the number of array elements in the target array.

[0074] In some embodiments, the playback information is determined based on the target array, including: determining the repeated array elements in the target array; determining the degree of repetition based on the number of repeated array elements and the total number of array elements in the target array; and determining the playback information used to characterize the repeated playback situation based on the degree of repetition and the repeated array elements.

[0075] In this embodiment, the proportion of repeated array elements in the target array can be directly calculated to determine the degree of repetition. For example, if there are 10 array elements in total, of which 2 are repeated elements, the degree of repetition is 20%.

[0076] In some embodiments, the number of repeated data elements refers to the array elements for which the same array element exists.

[0077] In some embodiments, identification information and repetition degree of the data slice corresponding to the repeated array elements may be used to generate playback information, and the playback information may represent the repeated playback situation.

[0078] In some embodiments, the data sent by the client 101 may also include the duration of the user's multimedia data playback, for example, 2 hours or 1 hour, etc. Based on the duration, the ratio of the playback duration to the duration may be determined to analyze the user's playback rate.

[0079] In some embodiments, based on the target array, it is also possible to analyze which multimedia data has not been played. For example, if the preset multimedia data includes 1-10 minutes of video data, but the target data only corresponds to 1-5 minutes of video data slices, then the 6-10 minutes of video data is the video data that has not been played and viewed by the user.

[0080] It can be understood that the playback information may include one or more of the above-mentioned information, and the playback information may be stored or fed back to the corresponding client 101 .

[0081] In the disclosed embodiment, built-in user-defined functions can be used to dynamically analyze data structures and implement query statistics. That is, the above-mentioned playback information determination process can be implemented by custom functions based on the data structure after segmentation to implement data calculation, analysis, and query.

[0082] In the disclosed embodiments, multimedia data is segmented and stored as strings in a corresponding format. An algorithm is then used to concatenate the data and merge the stored strings, without sorting (strings cannot be sorted). The merged data is then converted into an array. Set operations, such as sorting or deduplication, are then performed on the array as needed. Furthermore, the order of merging and sorting the data can be flexibly adjusted.

[0083] In the embodiment of the present disclosure, the above-mentioned data processing process can be executed in stages. For example, during the playback of preset multimedia data, the above-mentioned data processing process is executed multiple times. Each execution of the data processing process can correspond to different data or the same data.

[0084] Furthermore, dynamic data statistics can be achieved at a low cost. Furthermore, the amount of data computation required at each stage is relatively small, and the results of multiple stages can be aggregated. For example, data from 3-4 consecutive hours can be split into 30-minute batches for split calculation. Furthermore, data calculations can be repeated or delayed. Calculation parameters for some data can be modified based on business needs; calculations can be delayed for a period of time; or calculations can be performed only on a portion of the data.

[0085] As can be seen, the technical solution of the disclosed embodiments effectively reduces the difficulty of data processing by segmenting multimedia data, achieving fine-grained data segmentation and unified data structure, thereby enabling efficient and accurate analysis and processing of multimedia data. Furthermore, the flexibility of data processing is enhanced, making it applicable to various multimedia data processing scenarios.

[0086] Figure 4 is a block diagram of a data processing device 400 according to an exemplary embodiment. Figure 4 As shown, the data processing device 400 includes: The acquisition module 401 is configured to: acquire first multimedia data and time information corresponding to the first multimedia data, where the first multimedia data belongs to preset multimedia data, and the preset multimedia data is multimedia data played by a user.

[0087] The processing module 402 is configured to: cut the first multimedia data according to the time information corresponding to the first multimedia data to obtain second multimedia data, where the second multimedia data includes multiple data slices, and the time intervals between each adjacent data slice are preset time intervals; determine playback information based on the second multimedia data, where the playback information is used to characterize the playback status of the preset multimedia data.

[0088] Optionally, the acquisition module 401 is further configured to: receive original multimedia data sent by the client, where the original multimedia data is multimedia data collected by the client based on the user's playback behavior during the user's playback of the preset multimedia data; and determine the first multimedia data and the time information corresponding to the first multimedia data based on the original multimedia data.

[0089] Optionally, the processing module 402 is further configured to: decompress the original multimedia data to obtain decompressed original multimedia data; and determine the first multimedia data and the time information corresponding to the first multimedia data based on the decompressed original multimedia data.

[0090] Optionally, the processing module 402 is further configured to: perform array conversion on the multiple data slices to obtain a target array, where different array elements in the target array correspond to different data slices; and determine playback information according to the target array.

[0091] Optionally, the processing module 402 is further configured to: deduplicate repeated array elements in the target array to obtain a deduplicated target array; and determine playback information based on data slices corresponding to array elements in the deduplicated target array.

[0092] Optionally, the processing module 402 is further configured to: determine the repeated array elements in the target array; determine the degree of repetition based on the number of the repeated array elements and the total number of array elements in the target array; and determine playback information used to characterize the repeated playback situation based on the degree of repetition and the repeated array elements.

[0093] Optionally, the first multimedia data includes multiple sub-multimedia data, each of which corresponds to different user playback behaviors. The multiple data slices include data slices corresponding to the multiple sub-multimedia data. The processing module 402 is further configured to: perform array conversion on the data slices corresponding to the multiple sub-multimedia data to obtain multiple arrays; and determine the target array based on the multiple arrays.

[0094] Regarding the apparatus in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0095] Figure 5 1 is a block diagram of an electronic device 500 according to an exemplary embodiment. For example, the electronic device 500 may be provided as a server. Figure 5 The electronic device 500 includes a processor 522, which may be one or more, and a memory 532 for storing a computer program executable by the processor 522. The computer program stored in the memory 532 may include one or more modules, each corresponding to a set of instructions. In addition, the processor 522 may be configured to execute the computer program to perform the above-mentioned data processing method.

[0096] In addition, the electronic device 500 may further include a power supply component 526 and a communication component 550. The power supply component 526 may be configured to perform power management of the electronic device 500, and the communication component 550 may be configured to implement communication, such as wired or wireless communication, of the electronic device 500. In addition, the electronic device 500 may further include an input / output (I / O) interface 558. The electronic device 500 may operate based on an operating system stored in the memory 532.

[0097] In another exemplary embodiment, a computer-readable storage medium including program instructions is further provided. When the program instructions are executed by a processor, the steps of the above-described data processing method are implemented. For example, the non-transitory computer-readable storage medium may be the memory 532 including the program instructions. The program instructions may be executed by the processor 522 of the electronic device 500 to implement the above-described data processing method.

[0098] In another exemplary embodiment, a computer program product is further provided. The computer program product includes a computer program executable by a programmable device, and has a code portion for executing the above-mentioned data processing method when executed by the programmable device.

[0099] The preferred embodiments of the present disclosure are described in detail above in conjunction with the accompanying drawings. However, the present disclosure is not limited to the specific details of the above embodiments. Within the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all fall within the scope of protection of the present disclosure.

[0100] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any appropriate manner without contradiction. In order to avoid unnecessary repetition, the present disclosure will not further describe various possible combinations.

[0101] In addition, the various embodiments of the present disclosure may be arbitrarily combined, and as long as they do not violate the concept of the present disclosure, they should also be regarded as the contents disclosed by the present disclosure.

Claims

1. A data processing method, characterized in that: include: acquiring first multimedia data and time information corresponding to the first multimedia data, where the first multimedia data belongs to preset multimedia data, and the preset multimedia data is multimedia data played by a user; Slicing the first multimedia data according to the time information corresponding to the first multimedia data to obtain second multimedia data, where the second multimedia data includes a plurality of data slices, and the time intervals between adjacent data slices are preset time intervals; Playback information is determined according to the second multimedia data, where the playback information is used to represent a playback status of the preset multimedia data.

2. The data processing method according to claim 1, wherein: The data processing method is applied to a server, and obtaining the first multimedia data and the time information corresponding to the first multimedia data includes: Receiving original multimedia data sent by a client, wherein the original multimedia data is multimedia data collected by the client according to the user's playing behavior during the user playing the preset multimedia data; The first multimedia data and time information corresponding to the first multimedia data are determined according to the original multimedia data.

3. The data processing method according to claim 2, characterized in that: The original multimedia data is compressed data, and determining the first multimedia data and the time information corresponding to the first multimedia data according to the original multimedia data includes: Decompressing the original multimedia data to obtain decompressed original multimedia data; The first multimedia data and time information corresponding to the first multimedia data are determined according to the decompressed original multimedia data.

4. The data processing method according to claim 1, wherein: The determining the playback information according to the second multimedia data includes: Performing array conversion on the multiple data slices to obtain a target array, where different array elements in the target array correspond to different data slices; The playback information is determined according to the target array.

5. The data processing method according to claim 4, characterized in that: The determining of the playback information according to the target array includes: Deduplication is performed on duplicate array elements in the target array to obtain a deduplicated target array; Playback information is determined based on data slices corresponding to array elements in the target array after deduplication.

6. The data processing method according to claim 4, characterized in that: The determining of the playback information according to the target array includes: determining repeated array elements in the target array; Determining a degree of repetition based on the number of repeated array elements and the total number of array elements in the target array; Playback information for characterizing a repeated playback situation is determined according to the repetition degree and the repetition array element.

7. The data processing method according to any one of claims 4 to 6, characterized in that: The first multimedia data includes multiple sub-multimedia data, each of which corresponds to a different user playback behavior. The multiple data slices include data slices corresponding to each of the multiple multimedia data. The array conversion of the multiple data slices to obtain a target array includes: Performing array conversion on the data slices corresponding to the plurality of sub-multimedia data respectively to obtain a plurality of arrays; The target array is determined based on the multiple arrays.

8. A data processing device, characterized in that: include: an acquisition module configured to acquire first multimedia data and time information corresponding to the first multimedia data, wherein the first multimedia data belongs to preset multimedia data, and the preset multimedia data is multimedia data played by a user; a processing module configured to: segment the first multimedia data according to time information corresponding to the first multimedia data to obtain second multimedia data, where the second multimedia data includes a plurality of data slices, and the time intervals between adjacent data slices are preset time intervals; Playback information is determined according to the second multimedia data, where the playback information is used to represent a playback status of the preset multimedia data.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the data processing method according to any one of claims 1 to 7 is implemented.

10. A data processing device, characterized in that: include: a memory having a computer program stored thereon; A processor, configured to execute the computer program in the memory to implement the data processing method according to any one of claims 1 to 7.

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