Community post heat ranking updating method and device, equipment and storage medium

Abstract

The application relates to the technical field of data analysis, in particular to a community post heat ranking updating method and device, equipment and a storage medium, wherein the method comprises the following steps: in the case that a target community is in a heat ranking mode, acquiring a heat updating frequency of the target community in a current period, calculating a heat score corresponding to each post in the target community according to historical user operation data of the target community, ranking each post based on the heat score to obtain a heat ranking result, and updating the heat ranking result in the current period according to the heat updating frequency. According to the application, the heat ranking updating frequency corresponding to different period sequences of the community can be matched, and the heat ranking result in the current period can be calculated. The ranking result is updated according to the heat period updating frequency, so that the efficient operation of the heat calculation is realized under the premise of saving the platform computing power, the use experience of the user is guaranteed, and the cost consumption of the heat calculation is reduced.

Description

Technical Field

[0001] This application relates to the field of data analysis technology, and in particular to a method, apparatus, device and storage medium for updating the popularity ranking of community posts. Background Technology

[0002] With the rapid development of social media and other online communities, the amount of content produced on the internet has increased accordingly. The amount of content posted by users is huge and the information is complex. It is necessary to extract trending information from a large amount of data so that high-quality content can reach users more easily.

[0003] In related technologies, social software needs to use custom popularity metrics to calculate the different popularity levels of posts in the community. For example, existing technologies typically use Spark or Flink for real-time computation of large amounts of data, and then make hot topic recommendations to users based on the computational popularity results.

[0004] However, in related technologies, the massive amount of data in community posts leads to a decrease in the timeliness of post hotspot calculation. Furthermore, the hotspot algorithm has a long development cycle and is difficult to iterate. Real-time calculation has high requirements for hardware performance, which increases the cost of hotspot calculation. It is difficult to achieve a balance between operational stability and timeliness in actual business, which affects the user experience and urgently needs to be addressed. Summary of the Invention

[0005] This application provides a method, apparatus, device, and storage medium for updating the popularity ranking of community posts, in order to solve the problems in related technologies, such as the large amount of data in community posts, which leads to a decrease in the timeliness of post hotspot calculation, the long development cycle and difficulty in iteration of hotspot algorithms, the high requirements for hardware performance in real-time calculation, which increases the cost of hotspot calculation, makes it difficult to achieve a balance between operational stability and timeliness in actual business, and affects the user experience.

[0006] The first aspect of this application provides a method for updating the popularity ranking of community posts, comprising the following steps: when the target community is in popularity ranking mode, obtaining the period sequence of the target community in the current period; based on the period sequence, matching the popularity update frequency corresponding to the current period in a preset period arrangement table; calculating the popularity score corresponding to each post in the target community based on historical user operation data in the target community, ranking each post based on the popularity score to obtain a popularity ranking result, and updating the popularity ranking result in the current period according to the popularity update frequency.

[0007] Optionally, in one embodiment of this application, the step of calculating the popularity score corresponding to each post in the target community based on the historical user operation data in the target community includes: based on the historical user operation data, confirming all popularity-related operations of the user on each post; and calculating the popularity score of each post using all popularity-related operations respectively.

[0008] Optionally, in one embodiment of this application, the step of calculating the popularity score of each post using all the popularity-related operations includes: obtaining the actual category of each popularity-related operation among all the popularity-related operations corresponding to the current post; determining the weight coefficient corresponding to each popularity-related operation based on the actual category, so as to calculate the popularity score of the current post using the weight coefficient and each popularity-related operation.

[0009] Optionally, in one embodiment of this application, before matching the current period's corresponding popularity update frequency in a preset period arrangement table based on the period sequence, the method further includes: obtaining the target community's historical popularity operation frequency during the previous first preset update period; and generating a preset period arrangement table for the target community in the next first preset update period based on the historical popularity operation frequency.

[0010] Optionally, in one embodiment of this application, generating a preset periodic arrangement table of the target community in the next first preset update period based on the historical popularity operation frequency includes: calculating the periodic frequency corresponding to each third preset update period in the second preset update period according to the historical popularity operation frequency; generating the preset periodic arrangement table according to the sequence of all second preset update periods and all third preset update periods and the periodic frequency, wherein the first preset update period is longer than the second preset update period, and the second preset update period is longer than the third preset update period.

[0011] A second aspect of this application provides a community post popularity ranking update device, comprising: an acquisition module, configured to acquire a period sequence of the target community in the current period when the target community is in popularity ranking mode; a matching module, configured to match the popularity update frequency corresponding to the current period in a preset period arrangement table based on the period sequence; and an update module, configured to calculate the popularity score corresponding to each post in the target community based on historical user operation data in the target community, rank each post based on the popularity score to obtain a popularity ranking result, and update the popularity ranking result in the current period according to the popularity update frequency.

[0012] Optionally, in one embodiment of this application, the update module includes: a confirmation unit, configured to confirm all popularity-related operations performed by a user on each post based on the historical user operation data; and a calculation unit, configured to calculate the popularity score of each post using all the popularity-related operations.

[0013] Optionally, in one embodiment of this application, the calculation unit is specifically used to: obtain the actual category of each heat-related operation among all heat-related operations corresponding to the current post; determine the weight coefficient corresponding to each heat-related operation based on the actual category, so as to calculate the heat score of the current post using the weight coefficient and each heat-related operation.

[0014] Optionally, in one embodiment of this application, the apparatus further includes: an acquisition module, configured to acquire the historical heat operation frequency of the target community in the previous first preset update period before matching the heat update frequency corresponding to the current period in the preset period arrangement table based on the period sequence; and a generation module, configured to generate a preset period arrangement table of the target community in the next first preset update period based on the historical heat operation frequency.

[0015] Optionally, in one embodiment of this application, the generation module includes: a calculation unit, configured to calculate the periodic frequency corresponding to each third preset update period in the second preset update period based on the historical popularity operation frequency; and a generation unit, configured to generate the preset periodic arrangement table based on the sequence of all second preset update periods and all third preset update periods and the periodic frequency, wherein the first preset update period is longer than the second preset update period, and the second preset update period is longer than the third preset update period.

[0016] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the community post popularity ranking update method as described in the above embodiments.

[0017] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for updating the popularity ranking of community posts.

[0018] A fifth aspect of this application provides a computer program that, when executed, implements the above-described method for updating the popularity ranking of community posts.

[0019] This application's embodiments can match the corresponding popularity ranking update frequency according to different period sequences of the community, calculate the hot topic ranking results for the current period, and update the ranking results according to the update frequency of hot topic periods. This achieves efficient operation of hot topic calculation while saving platform computing power, ensuring user experience and reducing the cost of hot topic calculation. Therefore, it solves the problems in related technologies, such as the large amount of data in community posts leading to decreased timeliness of post hot topic calculation, long development cycles and difficult iterations of hot topic algorithms, high hardware requirements for real-time calculation increasing the cost of hot topic calculation, and difficulty in achieving a balance between operational stability and timeliness in actual business, thus affecting user experience.

[0020] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0021] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0022] Figure 1 This is a flowchart illustrating a method for updating the popularity ranking of community posts according to an embodiment of this application;

[0023] Figure 2 This is a schematic diagram illustrating the operating principle of updating the popularity ranking of community posts according to one embodiment of this application.

[0024] Figure 3 This is a schematic diagram of the structure of a community post popularity ranking update device according to an embodiment of this application;

[0025] Figure 4 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application. Detailed Implementation

[0026] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0027] The following description, with reference to the accompanying drawings, outlines a method, apparatus, device, and storage medium for updating the popularity ranking of community posts according to embodiments of this application. Addressing the issues raised in the background section regarding the massive data volume of community posts, which leads to a decrease in the timeliness of post hotspot calculation, long development cycles and iteration difficulties in hotspot algorithms, and high hardware requirements for real-time calculation, the present application provides a method for updating the popularity ranking of community posts. This method matches the corresponding popularity ranking update frequency based on different period sequences of the community, calculates the hotspot ranking result for the current period, and updates the ranking result according to the hotspot time period update frequency. This achieves efficient hotspot calculation while saving platform computing power, ensuring a better user experience and reducing the cost of hotspot calculation. Therefore, this method solves the problems in the related technologies, such as the massive data volume of community posts leading to a decrease in the timeliness of post hotspot calculation, long development cycles and iteration difficulties in hotspot algorithms, high hardware requirements for real-time calculation, increased costs of hotspot calculation, difficulty in maintaining a balance between operational stability and timeliness in actual business operations, and negative impacts on user experience.

[0028] Specifically, Figure 1 This is a flowchart illustrating a method for updating the popularity ranking of community posts, as provided in an embodiment of this application.

[0029] like Figure 1 As shown, the method for updating the popularity ranking of posts in this community includes the following steps:

[0030] In step S101, when the target community is in the popularity ranking mode, the periodic sequence of the target community in the current period is obtained.

[0031] It is understood that, in the embodiments of this application, the popularity ranking mode can be a mode that calculates the popularity of each post in the target community and ranks them by popularity score. The current period of the target community can be obtained by obtaining the current time node of the target community, locating the period position according to the time node, and obtaining the period sequence of the current period.

[0032] In step S102, based on the periodic sequence, the heat update frequency corresponding to the current period is matched in the preset periodic arrangement table.

[0033] It should be noted that the preset periodic arrangement table can be set by those skilled in the art according to the actual situation, and no specific limitation is made here.

[0034] It is understood that, in the embodiments of this application, the preset periodic arrangement table may contain a plan for the popularity update frequency of each period within a certain time period. The periodic sequence can locate the specific position or identity code of the current period in the preset periodic arrangement table in order to match the popularity update frequency corresponding to the current period.

[0035] Optionally, in one embodiment of this application, before matching the current period's corresponding popularity update frequency in the preset period arrangement table based on the period sequence, the method further includes: obtaining the historical popularity operation frequency of the target community in the previous first preset update period; and generating a preset period arrangement table of the target community in the next first preset update period based on the historical popularity operation frequency.

[0036] It should be noted that the first preset update period can be set by those skilled in the art according to the actual situation, and no specific limitation is made here.

[0037] In actual execution, the first preset update period can correspond to the entire duration covered by a preset periodic schedule. All heat operation records of the target community in the previous first preset update period can be extracted from the database or log file. The extracted data is analyzed to calculate the heat operation frequency under each sub-period in the previous first preset update period, that is, the number of heat updates in each sub-period. Based on the historical heat operation frequency, the heat update frequency arrangement for different periods in the next first preset update period can be determined.

[0038] Optionally, in one embodiment of this application, generating a preset periodic arrangement table of the target community in the next first preset update period based on the historical popularity operation frequency includes: calculating the periodic frequency corresponding to each third preset update period in the second preset update period according to the historical popularity operation frequency; generating a preset periodic arrangement table according to the sequence and periodic frequency of all second preset update periods and all third preset update periods, wherein the first preset update period is longer than the second preset update period, and the second preset update period is longer than the third preset update period.

[0039] It should be noted that the second and third preset update periods can be set by those skilled in the art according to the actual situation, and no specific limitations are made here.

[0040] In actual implementation, the first preset update period can correspond to the entire duration covered by a preset periodic schedule, such as one week or ten days; the second preset update period can be a sub-period divided under the preset periodic schedule, such as one day or 30 hours. After each second preset update period in the first preset update period ends, the stored data for popularity operations can be reset to save system resources; the third preset update period can be a sub-period divided under the preset periodic schedule, such as one hour or three hours. The popularity calculation for each third preset update period in the second preset update period uses all the popularity operation data accumulated within the second preset update period. For example, the calculation of the update cycle duration within a third preset update period can be based on the following formula:

[0041]

[0042] Specifically, a preset periodicity table can be constructed based on the sequence and periodic frequency of all second and third preset update periods. This table will include the periodic frequency of each third preset update period within each second preset update period, along with the corresponding date and time. This generated preset periodicity table can be applied to the community popularity update strategy, dynamically adjusting it based on real-time community activities and user feedback to optimize the effectiveness of popularity updates.

[0043] In step S103, the popularity score corresponding to each post in the target community is calculated based on the historical user operation data in the target community. Each post is ranked based on the popularity score to obtain the popularity ranking result. The popularity ranking result is updated in the current period according to the popularity update frequency.

[0044] It is understood that, in the embodiments of this application, historical user operation data may include all user operation data during the second preset update period, including behaviors related to post popularity such as browsing, liking, commenting, and sharing. The user operation data is cleaned and processed to ensure data quality and consistency, and then the popularity score of each post is calculated and sorted.

[0045] Among these methods, users can choose a suitable sorting algorithm (such as quicksort, heapsort, etc.) or use the sorting function of the database to sort posts according to their popularity score, generate a popularity ranking list, and display the popularity ranking results to users through the community platform in the form of leaderboards, hot post recommendations, etc.

[0046] Furthermore, the update frequency of the popularity ranking can be determined based on the community's activity level and operational strategies. Scheduled tasks or event-driven mechanisms can be set to increase the update frequency under occasional events. Then, stream processing technology can be used to calculate and update the popularity ranking in real time, collect user operation data and feedback, thereby continuously optimizing the popularity model and ranking algorithm and improving the user experience.

[0047] Optionally, in one embodiment of this application, calculating the popularity score corresponding to each post in the target community based on historical user operation data in the target community includes: confirming all popularity-related operations of the user on each post based on historical user operation data; and calculating the popularity score of each post using all popularity-related operations.

[0048] In practice, user activity related to popularity can be identified from historical user operation data, such as browsing, liking, commenting, and sharing posts. The popularity score of each post can be calculated using all popularity-related operations, and outliers can be filtered out to ensure that the score is within a reasonable range. By quantifying the impact of user operations on post popularity, users can be encouraged to participate more actively in community interaction, thereby promoting the improvement of community content quality.

[0049] Optionally, in one embodiment of this application, the popularity score of each post is calculated using all popularity-related operations, including: obtaining the actual category of each popularity-related operation among all popularity-related operations corresponding to the current post; determining the weight coefficient corresponding to each popularity-related operation based on the actual category, so as to calculate the popularity score of the current post using the weight coefficient and each popularity-related operation.

[0050] In practice, user actions can be categorized into different types, such as browsing, interaction (likes, comments), and dissemination (sharing). Different types of popularity-related actions are assigned corresponding weights to reflect the degree of contribution of the actions to the popularity of the post. The popularity score of each post can be calculated based on the weights and user action data, using a preset popularity score formula. Furthermore, the weights and calculation formulas can be dynamically adjusted according to community development and changes in user behavior.

[0051] The following detailed description of the working content of the embodiments of this application is based on a specific example. Figure 2 The diagram shown illustrates the operating principle of updating the popularity ranking of community posts according to an embodiment of this application.

[0052] Specifically, it can obtain user actions that trigger posts (likes, comments, replies, favorites, and other actions that may affect popularity), store the unique business ID of the post in a Redis Set data structure for deduplication (or other similar deduplication techniques), and record the cumulative number of operations during the current hour.

[0053] Set up a scheduled task 1 for popularity calculation. Following the timer configured in MySQL, use a Lua script to atomically retrieve and clear data from a Redis Set, query the unique IDs of posts within the retrieved time period, and iterate through the post data (popularity-related data). Calculate the popularity score for each post according to a custom algorithm. Store the calculated popularity score for each post in Elasticsearch (or a data source such as MySQL). For multi-dimensional popularity algorithms, different score fields can be set. The system queries the post list data in Elasticsearch and sorts it according to the popularity score (or a comprehensive sort of multiple scores).

[0054] When requesting data in an app or other platform, the system queries the post list data in Elasticsearch and sorts it according to popularity score (or a comprehensive sort of multiple scores). A scheduled task 2 is set at 0:00 every day to retrieve the number of operations in the current 24-hour period from Redis and save it to MySQL. Based on the data saved in the previous 7 days, the cycle time of the hourly period is calculated (except for manually mandated cycles). For example, the frequency can be appropriately reduced in periods with more operations and increased in periods with fewer operations.

[0055] The community post popularity ranking update method proposed in this application can match the corresponding popularity ranking update frequency according to different period sequences of the community, calculate the hot topic ranking result in the current period, and update the ranking result according to the update frequency of the hot topic period. This achieves efficient operation of hot topic calculation while saving platform computing power, ensuring user experience and reducing the cost of hot topic calculation. Therefore, it solves the problems in related technologies, such as the large amount of community post data leading to decreased timeliness of post hot topic calculation, long development cycle and difficulty in iteration of hot topic algorithms, high hardware requirements for real-time calculation increasing the cost of hot topic calculation, and difficulty in achieving a balance between operational stability and timeliness in actual business, thus affecting user experience.

[0056] Next, the community post popularity ranking update device according to the embodiments of this application is described with reference to the accompanying drawings.

[0057] Figure 3 This is a schematic diagram of the structure of the community post popularity ranking update device according to an embodiment of this application.

[0058] like Figure 3 As shown, the community post popularity ranking update device 10 includes: an acquisition module 100, a matching module 200, and an update module 300.

[0059] The acquisition module 100 is used to acquire the periodic sequence of the target community in the current period when the target community is in the popularity ranking mode.

[0060] The matching module 200 is used to match the current period's heat update frequency in a preset period arrangement table based on the periodic sequence.

[0061] The update module 300 is used to calculate the popularity score corresponding to each post in the target community based on the historical user operation data in the target community, rank each post based on the popularity score, obtain the popularity ranking result, and update the popularity ranking result in the current period according to the popularity update frequency.

[0062] Optionally, in one embodiment of this application, the update module 300 includes:

[0063] The confirmation unit is used to confirm all popularity-related actions of a user on each post based on historical user operation data.

[0064] The calculation unit is used to calculate the popularity score of each post separately using all popularity-related operations.

[0065] Optionally, in one embodiment of this application, the calculation unit is specifically used to: obtain the actual category of each heat-related operation among all heat-related operations corresponding to the current post; determine the weight coefficient corresponding to each heat-related operation based on the actual category, so as to calculate the heat score of the current post using the weight coefficient and each heat-related operation.

[0066] Optionally, in one embodiment of this application, the device 10 further includes:

[0067] The acquisition module is used to acquire the historical popularity operation frequency of the target community in the previous first preset update period before matching the popularity update frequency corresponding to the current period in the preset period arrangement table based on the period sequence.

[0068] The generation module is used to generate a preset periodic arrangement table of the target community for the next first preset update period based on the historical popularity operation frequency.

[0069] Optionally, in one embodiment of this application, the generation module includes:

[0070] The calculation unit is used to calculate the periodic frequency corresponding to each third preset update period in the second preset update period based on the historical heat operation frequency.

[0071] The generation unit is used to generate a preset periodic arrangement table based on the sequence and periodic frequency of all second preset update time periods and all third preset update time periods, wherein the first preset update time period is longer than the second preset update time period, and the second preset update time period is longer than the third preset update time period.

[0072] It should be noted that the foregoing explanation of the method embodiment for updating the popularity ranking of community posts also applies to the community post popularity ranking update device of this embodiment, and will not be repeated here.

[0073] The community post popularity ranking update device proposed in this application can match the corresponding popularity ranking update frequency according to different period sequences of the community, calculate the hot topic ranking result in the current period, and update the ranking result according to the update frequency of the hot topic period. This achieves efficient operation of hot topic calculation while saving platform computing power, ensuring user experience and reducing the cost of hot topic calculation. Therefore, it solves the problems in related technologies, such as the large amount of community post data leading to decreased timeliness of post hot topic calculation, long development cycle and difficulty in iteration of hot topic algorithms, high requirements for hardware performance in real-time calculation, increased cost of hot topic calculation, difficulty in achieving a balance between operational stability and timeliness in actual business, and impact on user experience.

[0074] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include:

[0075] The memory 401, the processor 402, and the computer program stored on the memory 401 and capable of running on the processor 402.

[0076] When the processor 402 executes the program, it implements the community post popularity ranking update method provided in the above embodiments.

[0077] Furthermore, electronic devices also include:

[0078] Communication interface 403 is used for communication between memory 401 and processor 402.

[0079] The memory 401 is used to store computer programs that can run on the processor 402.

[0080] The memory 401 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0081] If the memory 401, processor 402, and communication interface 403 are implemented independently, then the communication interface 403, memory 401, and processor 402 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized into address buses, data buses, control buses, etc. For ease of representation, Figure 4 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0082] Optionally, in a specific implementation, if the memory 401, processor 402, and communication interface 403 are integrated on a single chip, then the memory 401, processor 402, and communication interface 403 can communicate with each other through an internal interface.

[0083] Processor 402 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0084] This embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method for updating the popularity ranking of community posts.

[0085] This embodiment also provides a computer program that, when executed, implements the above-described method for updating the popularity ranking of community posts.

[0086] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0087] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0088] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0089] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0090] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0091] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0092] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0093] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for updating the popularity ranking of community posts, characterized in that, The method comprises the following steps: In the case that the target community is in a hotness ranking mode, a period sequence of the target community in a current period is obtained; Based on the period sequence, a hotness update frequency corresponding to the current period is matched in a preset period arrangement table; According to historical user operation data of the target community, a hotness score corresponding to each post in the target community is calculated, the each post is ranked based on the hotness score, a hotness ranking result is obtained, and the hotness ranking result is updated in the current period according to the hotness update frequency; Before the step of matching the hotness update frequency corresponding to the current period in the preset period arrangement table based on the period sequence, the method further comprises the following steps: A historical hotness operation frequency of the target community in a previous first preset update period is obtained; A preset period arrangement table of the target community in a next first preset update period is generated based on the historical hotness operation frequency; The step of generating the preset period arrangement table of the target community in the next first preset update period based on the historical hotness operation frequency comprises the following steps: According to the historical hotness operation frequency, a period frequency corresponding to each third preset update period in a second preset update period is calculated; The preset period arrangement table is generated according to the sequence of all second preset update periods and all third preset update periods and the period frequency, wherein the first preset update period is greater than the second preset update period, and the second preset update period is greater than the third preset update period.

2. The method of claim 1, wherein, The step of calculating the hotness score corresponding to each post in the target community according to the historical user operation data of the target community comprises the following steps: Based on the historical user operation data, all hotness related operations of a user on the each post are confirmed; The hotness score of the each post is calculated respectively by using the all hotness related operations.

3. The method of claim 2, wherein, The step of calculating the hotness score of the each post respectively by using the all hotness related operations comprises the following steps: An actual category of each hotness related operation in the all hotness related operations corresponding to a current post is obtained; Based on the actual category, a weight coefficient corresponding to the each hotness related operation is confirmed, so as to calculate the hotness score of the current post by using the weight coefficient and the each hotness related operation.

4. A device for updating the popularity ranking of community posts, characterized in that, The method comprises the following steps: An obtaining module is configured to obtain a period sequence of a target community in a current period in the case that the target community is in a hotness ranking mode; A matching module is configured to match a hotness update frequency corresponding to the current period in a preset period arrangement table based on the period sequence; An updating module is configured to calculate a hotness score corresponding to each post in the target community according to historical user operation data of the target community, rank the each post based on the hotness score, obtain a hotness ranking result, and update the hotness ranking result in the current period according to the hotness update frequency. The apparatus further comprises an acquisition module configured to acquire a historical hotness operation frequency of the target community in a last first preset update period based on the periodic sequence before matching a hotness update frequency corresponding to the current period in a preset periodic arrangement table; and a generation module configured to generate a preset periodic arrangement table of the target community in a next first preset update period based on the historical hotness operation frequency. The generation module comprises a calculation unit configured to calculate a period frequency corresponding to each third preset update period in a second preset update period according to the historical hotness operation frequency; and a generation unit configured to generate the preset periodic arrangement table according to a sequence of all second preset update periods and all third preset update periods and the period frequency, wherein the first preset update period is greater than the second preset update period, and the second preset update period is greater than the third preset update period.

5. The apparatus of claim 4, wherein, The update module comprises: a confirmation unit configured to confirm all hotness related operations of a user on each post based on the historical user operation data; a calculation unit configured to calculate a hotness score of each post by using the all hotness related operations.

6. The apparatus of claim 5, wherein, The calculation unit is specifically configured to: acquire an actual category of each hotness related operation in the all hotness related operations corresponding to a current post; confirm a weight coefficient corresponding to each hotness related operation based on the actual category, so as to calculate the hotness score of the current post by using the weight coefficient and each hotness related operation.

7. An electronic device, comprising: comprise: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the hotness ranking update method of the community post according to any one of claims 1-3.

8. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the hotness ranking update method of the community post according to any one of claims 1-3.

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