Information sorting method, device, equipment and computer storage medium

Abstract

The embodiment of the present application provides an information sorting method, device, electronic device and computer storage medium; the method includes: determining multiple published information to be sorted in a network community; determining the popularity value of each published information according to the sorting parameters of each published information in the multiple published information, wherein the sorting parameters at least include a content quality parameter and a timeliness parameter, and the timeliness parameter represents the length of time between the publishing time of the published information and the current time; the popularity value of the published information is positively correlated with the content quality parameter of the published information, and the popularity value of the published information is negatively correlated with the timeliness parameter of the published information; and sorting each published information in the multiple published information according to its popularity value to obtain a sorting result.

Description

Technical Field

[0001] The present application relates to data sorting technology in financial technology (Fintech), and is related to but not limited to an information sorting method, device, electronic device and computer storage medium. Background Art

[0002] With the development of computer technology, more and more technologies are being applied in the financial field. Traditional finance is gradually transforming into financial technology. However, due to the security and real-time requirements of the financial industry, higher requirements are also placed on technology.

[0003] Currently, in online communities, users can post or discuss a topic; posts in online communities can be sorted based on the number of votes cast by users. However, the current post sorting is based on only one factor, the number of votes cast by users, and the final sorting result is not accurate enough. Summary of the invention

[0004] The embodiments of the present application provide an information sorting method, device, electronic device and computer storage medium, which can solve the problem of inaccurate sorting results in the prior art.

[0005] The technical solution of the embodiment of the present application is implemented as follows:

[0006] The present application provides an information sorting method, the method comprising:

[0007] Determining multiple published information to be sorted in a network community;

[0008] Determine the popularity value of each of the multiple release information according to the sorting parameters of each of the multiple release information, wherein the sorting parameters at least include a content quality parameter and a timeliness parameter, and the timeliness parameter indicates the length of time between the release time of the release information and the current time; the popularity value of the release information is positively correlated with the content quality parameter of the release information, and the popularity value of the release information is negatively correlated with the timeliness parameter of the release information;

[0009] According to the popularity value of each of the multiple pieces of published information, the respective pieces of published information are sorted to obtain a sorting result.

[0010] In some embodiments of the present application, the method further includes:

[0011] Determine a content quality parameter of each published information according to the at least two content quality elements of each published information.

[0012] In some embodiments of the present application, the method further includes:

[0013] Determining priorities of multiple candidate content quality factors for each of the published information;

[0014] Among the multiple candidate content quality factors, candidate content quality factors with priorities greater than a priority threshold are selected as the at least two content quality factors.

[0015] In some embodiments of the present application, determining the priorities of the multiple candidate content quality factors of each published information includes:

[0016] Receiving an instruction for indicating priorities of candidate content quality factors; determining priorities of the plurality of candidate content quality factors according to the instruction;

[0017] Alternatively, the priorities of the multiple candidate content quality factors of each release information are determined according to the type of each release information and the corresponding relationship between the preset type of release information and the priorities of the candidate content quality factors.

[0018] In some embodiments of the present application, the ranking parameter further includes historical reference information of the publisher of each published information, and the historical reference information represents the content quality parameter of the historical published information;

[0019] The popularity value of the published information is positively correlated with the historical reference information of the publisher.

[0020] In some embodiments of the present application, the ranking parameter further includes a moving average, which represents: a ratio of an average amount of information released in a first time period to an average amount of information released in a second time period in the network community; the first time period is a part of the second time period;

[0021] The popularity value of the published information is positively correlated with the moving average of the published information to be sorted.

[0022] In some embodiments of the present application, determining the popularity value of each piece of published information according to the ranking parameter of each piece of published information in the plurality of pieces of published information includes:

[0023] Determine a gravity factor, wherein the gravity factor is the reciprocal of the moving average;

[0024] The popularity value of each published information is determined according to the gravity factor, and the content quality parameter and timeliness parameter of each published information.

[0025] The present application provides an information sorting device, the device comprising:

[0026] A determination module, used for determining a plurality of published information to be sorted in the network community;

[0027] A processing module, configured to determine the popularity value of each of the plurality of published information according to a ranking parameter of each of the plurality of published information, wherein the ranking parameter at least includes a content quality parameter and a timeliness parameter, and the timeliness parameter indicates the length of time between the publishing time of the published information and the current time; the popularity value of the published information is positively correlated with the content quality parameter of the published information, and the popularity value of the published information is negatively correlated with the timeliness parameter of the published information;

[0028] The sorting module is used to sort the individual pieces of published information according to the popularity value of each piece of published information in the multiple pieces of published information to obtain a sorting result.

[0029] In some embodiments of the present application, the processing module is further used to:

[0030] Determine a content quality parameter of each published information according to the at least two content quality elements of each published information.

[0031] In some embodiments of the present application, the processing module is further used to:

[0032] Determining priorities of multiple candidate content quality factors for each of the published information;

[0033] Among the multiple candidate content quality factors, candidate content quality factors with priorities greater than a priority threshold are selected as the at least two content quality factors.

[0034] In some embodiments of the present application, the processing module is used to determine the priorities of the multiple candidate content quality factors of each published information, including:

[0035] Receiving an instruction for indicating priorities of candidate content quality factors; determining priorities of the plurality of candidate content quality factors according to the instruction;

[0036] Alternatively, the priorities of the multiple candidate content quality factors of each release information are determined according to the type of each release information and the corresponding relationship between the preset type of release information and the priorities of the candidate content quality factors.

[0037] In some embodiments of the present application, the ranking parameter further includes historical reference information of the publisher of each published information, and the historical reference information represents the content quality parameter of the historical published information;

[0038] The popularity value of the published information is positively correlated with the historical reference information of the publisher.

[0039] In some embodiments of the present application, the ranking parameter further includes a moving average, which represents: a ratio of an average amount of information released in a first time period to an average amount of information released in a second time period in the network community; the first time period is a part of the second time period;

[0040] The popularity value of the published information is positively correlated with the moving average of the published information to be sorted.

[0041] In some embodiments of the present application, the processing module is used to determine the popularity value of each piece of published information according to the sorting parameter of each piece of published information in the plurality of published information, including:

[0042] Determine a gravity factor, wherein the gravity factor is the reciprocal of the moving average;

[0043] The popularity value of each published information is determined according to the gravity factor, and the content quality parameter and timeliness parameter of each published information.

[0044] An embodiment of the present application provides an electronic device, the electronic device comprising:

[0045] A memory for storing executable instructions;

[0046] The processor is used to implement any one of the above-mentioned information sorting methods when executing the executable instructions stored in the memory.

[0047] An embodiment of the present application provides a computer-readable storage medium storing executable instructions for implementing any of the above-mentioned information sorting methods when executed by a processor.

[0048] In an embodiment of the present application, multiple published information to be sorted in a network community are determined; the popularity value of each published information is determined according to the sorting parameters of each published information in the multiple published information, wherein the sorting parameters at least include a content quality parameter and a timeliness parameter, and the timeliness parameter represents the length of time between the publishing time of the published information and the current time; the popularity value of the published information is positively correlated with the content quality parameter of the published information, and the popularity value of the published information is negatively correlated with the timeliness parameter of the published information; and the published information in the multiple published information is sorted according to the popularity value of each published information to obtain a sorting result.

[0049] It can be seen that in the embodiment of the present application, the content quality parameters and timeliness parameters of the published information can be comprehensively considered to obtain the heat value ranking result of the published information. Compared with the scheme in the prior art that only determines the heat value of the published information by a single factor of the number of votes, the embodiment of the present application can accurately obtain the heat value ranking result of the published information. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 is an optional flow chart of the information sorting method provided in the embodiment of the present application;

[0051] Figure 2 Schematic diagram of article popularity ranking in an embodiment of the present application;

[0052] Figure 3 is a schematic diagram of a curve showing changes in the popularity of published information over time corresponding to different gravity factors in an embodiment of the present application;

[0053] Figure 4 It is a schematic diagram of an optional composition structure of the information sorting device of the embodiment of the present application;

[0054] Figure 5 It is a schematic diagram of an optional composition structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0055] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0056] The embodiments of the present application provide an information sorting method, device, electronic device and computer storage medium. The information sorting method of the embodiments of the present application can be applied to a computer system composed of a terminal and / or a server, and can be operated with many other general or special computing system environments or configurations. Here, the terminal can be a thin client, a thick client, a handheld or laptop device, a microprocessor-based system, a set-top box, a programmable consumer electronic product, a network personal computer, a small computer system, etc., and the server can be a server computer system, a small computer system, a large computer system, and a distributed cloud computing technology environment including any of the above systems, etc.

[0057] Electronic devices such as terminals and servers can be described in the general context of computer system executable instructions (such as program modules) executed by a computer system. In general, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in a distributed cloud computing environment, where tasks are performed by remote processing devices linked through a communication network. In a distributed cloud computing environment, program modules can be located on local or remote computing system storage media including storage devices.

[0058] The following is an exemplary description of the information sorting method in the embodiment of the present application.

[0059] Figure 1 An optional flowchart of the information sorting method provided in the embodiment of the present application, such as Figure 1 As shown, the process may include:

[0060] Step 101: Determine a plurality of published information to be sorted in a network community.

[0061] In the embodiment of the present application, the published information may be a published article or post; and the online community may be a website for publishing articles or posts.

[0062] Step 102: Determine the popularity value of each published information according to the sorting parameters of each published information among the multiple published information, wherein the sorting parameters include at least a content quality parameter and a timeliness parameter, and the timeliness parameter represents the length of time between the publishing time of the published information and the current time; the popularity value of the published information is positively correlated with the content quality parameter of the published information, and the popularity value of the published information is negatively correlated with the timeliness parameter of the published information.

[0063] In the embodiment of the present application, the timeliness parameter is an important reference factor for determining the popularity value of the published information. The longer the time between the release time of the published information and the current time, the lower the popularity value of the published information. The content quality parameter is used to characterize the content quality of the published information. The larger the content quality parameter, the higher the content quality of the invention information.

[0064] Step 103: sorting each of the multiple pieces of published information according to their popularity values ​​to obtain a sorting result.

[0065] In the embodiment of the present application, each published information can be sorted in order from high to low according to the popularity value, so that it is convenient for users to browse the published information with high popularity. Figure 2 , which can intuitively display the popularity ranking of articles in the company's internal forum system.

[0066] In practical applications, steps 101 to 103 can be implemented based on a processor of an electronic device, and the processor can be at least one of an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a CPU, a controller, a microcontroller, and a microprocessor. It can be understood that the electronic device that implements the above-mentioned processor function can also be other, and the embodiments of the present application are not limited thereto.

[0067] It can be seen that in the embodiment of the present application, the content quality parameters and timeliness parameters of the published information can be comprehensively considered to obtain the heat value ranking result of the published information. Compared with the scheme in the prior art that only determines the heat value of the published information by a single factor of the number of votes, the embodiment of the present application can accurately obtain the heat value ranking result of the published information.

[0068] Furthermore, the embodiments of the present application do not require users to vote on the published information and can be applied to scenarios where voting on the published information is not possible, which to a certain extent expands the scope of application of the embodiments of the present application.

[0069] In some embodiments of the present application, the content quality parameter of each published information may be determined according to at least two content quality elements of each published information.

[0070] In one implementation, the at least two content quality factors include at least two of the following: number of views, number of comments, number of favorites, number of likes, a parameter used to characterize whether it is recommended, a parameter used to characterize whether it is pinned, and a parameter used to characterize whether it is public.

[0071] Exemplarily, the value of the parameter used to characterize whether the information is recommended can be 0 or 1. When the value of the parameter used to characterize whether the information is recommended is 0, it means that the published information is not recommended; when the value of the parameter used to characterize whether the information is recommended is 1, it means that the published information has been recommended.

[0072] Exemplarily, the value of the parameter used to characterize whether the information is pinned to the top can be 0 or 1. When the value of the parameter used to characterize whether the information is pinned to the top is 0, it indicates that the published information is not pinned to the top; when the value of the parameter used to characterize whether the information is pinned to the top is 1, it indicates that the published information is pinned to the top.

[0073] Exemplarily, the value of the parameter used to characterize whether the information is public can be 0 or 1. When the value of the parameter used to characterize whether the information is public is 0, it indicates that the information is not public; when the value of the parameter used to characterize whether the information is public is 1, it indicates that the information is public.

[0074] It should be noted that the above-mentioned contents are merely exemplary descriptions of the parameters used to characterize whether a recommendation is obtained, the parameters used to characterize whether a top item is displayed, and the parameters used to characterize whether a item is public, and the embodiments of the present application are not limited thereto.

[0075] In one implementation, after obtaining at least two content quality factors of each published information, a weighted sum of the at least two content quality factors of each published information may be performed to obtain a content quality parameter of each published information.

[0076] Exemplarily, the at least two content quality factors are n content quality factors, n is an integer greater than or equal to 2, and the n content quality factors are represented by x1 to x2, respectively. n The weights of these n content quality factors are w1 to w n , the content quality parameter of the published information can be calculated according to formula (1):

[0077] S=x1w1+...+x n w n (1)

[0078] Wherein, S represents the content quality parameter of the published information.

[0079] Exemplarily, the at least two content quality factors include seven content quality factors, which are: number of views, number of comments, number of collections, number of likes, a parameter used to characterize whether it is recommended, a parameter used to characterize whether it is pinned, and a parameter used to characterize whether it is public, among which the number of views is x1, the number of comments is x2, the number of collections is x3, the number of likes is x4, the parameter used to characterize whether it is recommended is x5, the parameter used to characterize whether it is pinned is x6, and the parameter used to characterize whether it is public is x7.

[0080] Exemplarily, the weights corresponding to x1 to x7 can be described in Table 1.

[0081] Table 1

[0082]

[0083] It should be noted that Table 1 is merely an example of the weights of parameters x1 to x7. In the embodiments of the present application, the weights of parameters x1 to x7 are not limited to the contents of Table 1.

[0084] It can be seen that the embodiment of the present application can more accurately obtain the content quality parameters of the published information based on comprehensive consideration of at least two content quality factors, which is conducive to accurately obtaining the popularity value of the published information.

[0085] In some embodiments of the present application, it is also possible to first determine multiple candidate content quality factors for each published information, and determine the priorities of the multiple candidate content quality factors for each published information; then, among the multiple candidate content quality factors, the candidate content quality factors with a priority greater than the priority threshold are selected as the above-mentioned at least two content quality factors.

[0086] In the embodiment of the present application, the priority threshold can be pre-set according to actual conditions.

[0087] Exemplarily, the seven candidate content quality factors for published information are: number of views, number of comments, number of favorites, number of likes, a parameter for characterizing whether it is recommended, a parameter for characterizing whether it is pinned, and a parameter for characterizing whether it is public; here, the priority value can be used to represent the priority of each candidate content quality factor, and the higher the priority value, the higher the priority of the candidate content quality factor.

[0088] Exemplarily, the priority value of views is 2, the priority value of comments is 3, the priority value of favorites is 5, the priority value of likes is 5, the priority value of the parameter used to characterize whether it is recommended is 6, the priority value of the parameter used to characterize whether it is pinned is 7, the priority value of the parameter used to characterize whether it is public is 5, and the priority threshold is 4. Then, from the above seven candidate content quality factors, the number of favorites, the number of likes, the parameter used to characterize whether it is recommended, the parameter used to characterize whether it is pinned, and the parameter used to characterize whether it is public can be selected as at least two of the above seven content quality factors.

[0089] It can be seen that the embodiments of the present application can determine content quality parameters based on content quality factors with higher priorities, which is conducive to obtaining content quality parameters according to actual needs.

[0090] In some embodiments of the present application, an instruction for indicating the priority of candidate content quality factors may be received; and the priorities of multiple candidate content quality factors may be determined according to the instruction.

[0091] In actual applications, the user may input an instruction indicating the priority of the candidate content quality factors into the electronic device through human-computer interaction, and the above instruction may carry the priority value of each candidate content quality factor.

[0092] It can be seen that the embodiment of the present application can determine the priority of candidate content quality factors according to user needs, and then determine the content quality parameters.

[0093] In some embodiments of the present application, the priorities of multiple candidate content quality elements of each published information may be determined according to the type of each published information and the correspondence between the preset type of published information and the priorities of the candidate content quality elements.

[0094] In practical applications, various published information can be classified according to the fields to which they belong, the number of characters and other attributes to obtain the types of published information; and a correspondence between the types of published information and the priorities of candidate content quality factors can be established in advance for various types of published information.

[0095] It can be seen that the embodiments of the present application can determine the priorities of various candidate content quality factors of the published information according to the type of the published information, that is, the priority value that can match the type of the published information is conducive to accurately determining the priorities of the candidate content quality factors according to the type of the published information, and further conducive to accurately determining the content quality factors.

[0096] In some embodiments of the present application, the above-mentioned sorting parameters also include historical reference information of the publisher of each published information, and the historical reference information represents the content quality parameters of the historical published information; the popularity value of the published information is positively correlated with the historical reference information of the publisher. Exemplarily, the content quality parameters of the historical published information can be determined based on at least two content quality factors of the historical published information, and the at least two content quality factors of the historical published information can include at least two of the following: number of views, number of comments, number of favorites, number of likes, a parameter used to characterize whether it is recommended, a parameter used to characterize whether it is pinned, and a parameter used to characterize whether it is public. In one implementation method, a weighted summation can be performed on the at least two content quality factors of the historical published information to obtain the content quality parameters of the historical published information, that is, to obtain the historical reference information.

[0097] It can be understood that in the case where a publisher publishes information multiple times, the popularity value of the information most recently published by the publisher can be determined based on the content quality parameters of the publisher's historical published information. Therefore, the embodiment of the present application can derive the popularity value of the published information based on the content quality parameters of the publisher's historical published information, and the factors considered when deriving the popularity value of the published information are more comprehensive.

[0098] In some embodiments of the present application, the above-mentioned sorting parameters also include a moving average (MA), which represents: the ratio of the average amount of information released in the first time period to the average amount of information released in the second time period in the online community; the first time period is a part of the second time period; the heat value of the released information is positively correlated with the moving average of the released information to be sorted.

[0099] Exemplarily, the first time period is the time period of the published information to be sorted, and the first time period may be 1 hour, 1 day, 1 week, etc., and the second time period may be 1 day, 1 week, 1 month, etc.

[0100] Exemplarily, the average amount of information released in the first time period may be the average of the number of information released in multiple consecutive first time periods, and the average amount of information released in the second time period may be the average of the number of information released in multiple consecutive second time periods; it can be understood that when the first time period changes, the average amount of information released in the first time period in the online community will also change accordingly; when the second time period changes, the average amount of information released in the second time period in the online community will also change accordingly, and therefore, the moving average may be different for information released in different time periods.

[0101] It can be seen that the embodiment of the present application can derive the popularity value of the released information on the basis of considering the moving average, and the factors considered when deriving the popularity value of the released information are more comprehensive.

[0102] In the embodiment of the present application, according to the sorting parameter of each of the plurality of published information, the implementation method of determining the popularity value of each of the published information may be:

[0103] Determine the gravity factor, which is the reciprocal of the moving average;

[0104] The popularity value of each published information is determined according to the gravity factor, and the content quality parameter and timeliness parameter of each published information.

[0105] Here, the moving average is a positive number less than 1, and the gravity factor is a positive number greater than 1.

[0106] It can be seen that the embodiment of the present application can derive the popularity value of the published information on the basis of considering the gravity factor, and the factors considered when deriving the popularity value of the published information are more comprehensive.

[0107] In some embodiments, the popularity value of the published information can be calculated according to formula (2):

[0108]

[0109] Among them, F represents the popularity value of the published information, t now Indicates the current time, t public represents the release time of the information, and G represents the gravity factor. It can be seen that, referring to formula (2), as time goes by, t now The value of becomes larger, making the value of F smaller.

[0110] In some embodiments, it can be calculated according to formula (3):

[0111]

[0112] Among them, t n is the current time in seconds, t public is the release time of the published information expressed in seconds, (t n -t p ) / 3600 / 24 ​​represents the number of days between the release time of the information and the current time. n -t p ) / 3600 / 24+1 is a number greater than 1, and the gravity factor G is a positive number greater than 1, then the denominator of F in formula (3) is n An increasing function that grows with the growth of .

[0113] In some embodiments, Figure 3 The following is a schematic diagram showing the change of the popularity of published information over time corresponding to different gravity factors G. Figure 3 In the figure, the horizontal axis represents time, and the vertical axis represents the popularity of the published information. Figure 3 The gravity factors corresponding to curves 1, 2, and 3 are 2, 1.8, or 1.5, respectively; Figure 3 In the case where the gravity factor is 1.5, the curve converges more smoothly, which is more in line with the display requirements of the heat value.

[0114] It can be understood that since the moving average reflects the average number of each piece of information released within a period of time in the online community, and the gravity factor is the inverse of the moving average, the higher the average number of each piece of information released within a period of time in the online community, the lower the gravity factor; further, combined with the above-mentioned formula for calculating the heat value of the released information, it can be seen that the lower the gravity factor, the higher the heat value of the released information to be sorted. That is to say, the embodiment of the present application calculates the heat value of the released information to be sorted by combining the gravity factor, so that the calculated heat value of the released information can reflect the average number of each piece of information released within a period of time in the online community. Furthermore, the embodiment of the present application can more accurately derive the heat value of the released information based on a comprehensive consideration of the average number of each piece of information released within a period of time in the online community.

[0115] In the related art, even if the popularity value of published information can be determined based on multiple factors, the popularity value of the published information is only calculated by weighted average of the multiple factors. This scheme for calculating the popularity value of published information does not take into account the average value of the number of published information within a period of time in the online community, but only considers the factors of the published information itself. Therefore, the factors considered when deriving the popularity value of the published information are not comprehensive enough.

[0116] In the embodiment of the present application, instead of simply taking a weighted average of multiple factors to obtain the heat value of the published information, the heat value of the published information to be sorted can be calculated in combination with the gravity factor. Based on the above-mentioned recorded content, it can be seen that the embodiment of the present application can make the calculated heat value of the published information reflect the average value of the quantity of each published information within a period of time in the network community. Therefore, the factors considered when deriving the heat value of the published information are more comprehensive, and it is conducive to more accurately deriving the heat value of the published information.

[0117] Based on the information sorting method proposed in the above embodiment, the embodiment of the present application further proposes an information sorting device; Figure 4 This is a schematic diagram of an optional structure of the information sorting device according to an embodiment of the present application, such as Figure 4 As shown, the information sorting device 400 may include:

[0118] A determination module 401 is used to determine a plurality of published information to be sorted in the network community;

[0119] The processing module 402 is used to determine the popularity value of each of the multiple release information according to the sorting parameters of each of the multiple release information, wherein the sorting parameters at least include a content quality parameter and a timeliness parameter, and the timeliness parameter indicates the length of time between the release time of the release information and the current time; the popularity value of the release information is positively correlated with the content quality parameter of the release information, and the popularity value of the release information is negatively correlated with the timeliness parameter of the release information;

[0120] The sorting module 403 is used to sort the respective pieces of published information according to the popularity value of each piece of published information in the plurality of pieces of published information to obtain a sorting result.

[0121] In some embodiments of the present application, the processing module 402 is further configured to:

[0122] Determine a content quality parameter of each published information according to the at least two content quality elements of each published information.

[0123] In some embodiments of the present application, the processing module 402 is further configured to:

[0124] Determining priorities of multiple candidate content quality factors for each of the published information;

[0125] Among the multiple candidate content quality factors, candidate content quality factors with priorities greater than a priority threshold are selected as the at least two content quality factors.

[0126] In some embodiments of the present application, the processing module 402 is used to determine the priorities of the multiple candidate content quality factors of each published information, including:

[0127] Receiving an instruction for indicating priorities of candidate content quality factors; determining priorities of the plurality of candidate content quality factors according to the instruction;

[0128] Alternatively, the priorities of the multiple candidate content quality factors of each release information are determined according to the type of each release information and the corresponding relationship between the preset type of release information and the priorities of the candidate content quality factors.

[0129] In some embodiments of the present application, the ranking parameter further includes historical reference information of the publisher of each published information, and the historical reference information represents the content quality parameter of the historical published information;

[0130] The popularity value of the published information is positively correlated with the historical reference information of the publisher.

[0131] In some embodiments of the present application, the ranking parameter further includes a moving average, which represents: a ratio of an average amount of information released in a first time period to an average amount of information released in a second time period in the network community; the first time period is a part of the second time period;

[0132] The popularity value of the published information is positively correlated with the moving average of the published information to be sorted.

[0133] In some embodiments of the present application, the processing module 402 is used to determine the popularity value of each of the plurality of published information according to the ranking parameter of each of the plurality of published information, including:

[0134] Determine a gravity factor, wherein the gravity factor is the reciprocal of the moving average;

[0135] The popularity value of each published information is determined according to the gravity factor, and the content quality parameter and timeliness parameter of each published information.

[0136] In practical applications, the determination module 401, the processing module 402 and the sorting module 403 can all be implemented using a processor of an electronic device, and the processor can be at least one of an ASIC, a DSP, a DSPD, a PLD, an FPGA, a CPU, a controller, a microcontroller, and a microprocessor. It can be understood that the electronic device that implements the functions of the processor can also be other, and the embodiment of the present application is not limited thereto.

[0137] It should be noted that the description of the above device embodiment is similar to the description of the above method embodiment, and has similar beneficial effects as the method embodiment. For technical details not disclosed in the device embodiment of the present application, please refer to the description of the method embodiment of the present application for understanding.

[0138] It should be noted that in the embodiment of the present application, if the above-mentioned information sorting method is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium, including a number of instructions to enable a computer device (which can be a terminal, a server, etc.) to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a U disk, a mobile hard disk, a read-only memory (ROM), a magnetic disk or an optical disk. In this way, the embodiment of the present application is not limited to any specific combination of hardware and software.

[0139] Correspondingly, an embodiment of the present application further provides a computer program product, which includes computer executable instructions, and the computer executable instructions are used to implement any information sorting method provided in the embodiment of the present application.

[0140] Correspondingly, an embodiment of the present application further provides a computer storage medium, on which computer executable instructions are stored, and the computer executable instructions are used to implement any one of the information sorting methods provided in the above embodiments.

[0141] The present application also provides an electronic device, Figure 5 A schematic diagram of an optional structure of an electronic device provided in an embodiment of the present application, such as Figure 5 As shown, the electronic device 500 includes:

[0142] Memory 501, used for storing executable instructions;

[0143] The processor 502 is used to implement any one of the above-mentioned information sorting methods when executing the executable instructions stored in the memory 501.

[0144] The processor 502 may be at least one of an ASIC, a DSP, a DSPD, a PLD, a FPGA, a CPU, a controller, a microcontroller, and a microprocessor.

[0145] The above-mentioned computer-readable storage medium / memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a magnetic random access memory (FRAM), a flash memory (Flash Memory), a magnetic surface memory, an optical disk, or a compact disc read-only memory (CD-ROM) and the like; it can also be various terminals including one or any combination of the above-mentioned memories, such as mobile phones, computers, tablet devices, personal digital assistants, etc.

[0146] It should be noted here that the description of the above storage medium and device embodiments is similar to the description of the above method embodiments, and has similar beneficial effects as the method embodiments. For technical details not disclosed in the storage medium and device embodiments of this application, please refer to the description of the method embodiments of this application for understanding.

[0147] It should be understood that the "some embodiments" mentioned throughout the specification means that specific features, structures or characteristics related to the embodiments are included in at least one embodiment of the present application. Therefore, the "in some embodiments" appearing throughout the specification may not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics can be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the size of the sequence number of the above-mentioned processes does not mean the order of execution, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application. The above-mentioned sequence numbers of the embodiments of the present application are only for description and do not represent the advantages and disadvantages of the embodiments.

[0148] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0149] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as: multiple units or components can be combined, or can be integrated into another system, or some features can be ignored or not executed. In addition, the coupling, direct coupling, or communication connection between the components shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0150] The units described above as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units; they may be located in one place or distributed on multiple network units; some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment of the present application.

[0151] In addition, all functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may be a separate unit, or two or more units may be integrated into one unit; the above-mentioned integrated units may be implemented in the form of hardware or in the form of hardware plus software functional units.

[0152] Alternatively, if the above-mentioned integrated unit of the present application is implemented in the form of a software function module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application can essentially or in other words, the part that contributes to the relevant technology can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for the automatic test line of the device to execute all or part of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as mobile storage devices, ROMs, magnetic disks or optical disks.

[0153] The methods disclosed in several method embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments.

[0154] The features disclosed in several method or device embodiments provided in this application can be arbitrarily combined without conflict to obtain new method embodiments or device embodiments.

[0155] The above is only an implementation method of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for sorting information, characterized in that: The method comprises: Determining multiple published information to be sorted in a network community; Performing a weighted summation on at least two content quality factors of each of the multiple release information to obtain a content quality parameter of each of the release information; the at least two content quality factors include at least two of the following: number of views, number of comments, number of favorites, number of likes, a parameter used to characterize whether it is recommended, a parameter used to characterize whether it is pinned, and a parameter used to characterize whether it is public; Determine the heat value of each of the multiple release information according to the sorting parameters of each release information; wherein the sorting parameters include the content quality parameter, the timeliness parameter and the moving average, the timeliness parameter represents the time interval between the release time of the release information and the current time; the moving average represents: the ratio of the average amount of release information in the first time period to the average amount of release information in the second time period in the network community; the first time period is a part of the second time period; the heat value of the release information is positively correlated with the content quality parameter of the release information, and the heat value of the release information is negatively correlated with the timeliness parameter of the release information; the heat value is the ratio of numerator data and denominator data, the numerator data is generated according to the content quality parameter, the denominator data is generated according to the gravity factor and the timeliness parameter, and the gravity factor is the inverse of the moving average; According to the popularity value of each of the multiple pieces of published information, the respective pieces of published information are sorted to obtain a sorting result.

2. The method according to claim 1, characterized in that The method further comprises: Determining priorities of multiple candidate content quality factors for each of the published information; Among the multiple candidate content quality factors, candidate content quality factors with priorities greater than a priority threshold are selected as the at least two content quality factors.

3. The method according to claim 2, characterized in that The determining of the priorities of the multiple candidate content quality factors of each published information includes: Receiving an instruction for indicating priorities of candidate content quality factors; determining priorities of the plurality of candidate content quality factors according to the instruction; Alternatively, the priorities of the multiple candidate content quality factors of each release information are determined according to the type of each release information and the corresponding relationship between the preset type of release information and the priorities of the candidate content quality factors.

4. The method according to claim 1, characterized in that: The ranking parameters also include historical reference information of the publisher of each published information, and the historical reference information represents the content quality parameter of the historical published information; The popularity value of the published information is positively correlated with the historical reference information of the publisher.

5. The method according to claim 1, characterized in that The popularity value of the published information is positively correlated with the moving average of the published information to be sorted.

6. An information sorting device, characterized in that: The device comprises: A determination module, used for determining a plurality of published information to be sorted in the network community; The processing module is used to perform weighted summation on at least two content quality factors of each of the multiple release information to obtain a content quality parameter of each of the release information; the at least two content quality factors include at least two of the following: number of views, number of comments, number of favorites, number of likes, a parameter used to characterize whether it is recommended, a parameter used to characterize whether it is pinned, and a parameter used to characterize whether it is public; according to the sorting parameter of each of the multiple release information, determine the popularity value of each of the release information; wherein the sorting parameter includes the content quality parameter, timeliness parameter and moving average, and the timeliness parameter represents the popularity of the release information. The time interval between the release time and the current time; the moving average represents: the ratio of the average amount of information released in the first time period to the average amount of information released in the second time period in the network community; the first time period is a part of the second time period; the heat value of the released information is positively correlated with the content quality parameter of the released information, and the heat value of the released information is negatively correlated with the timeliness parameter of the released information; the heat value is the ratio of the numerator data and the denominator data, the numerator data is generated according to the content quality parameter, the denominator data is generated according to the gravity factor and the timeliness parameter, and the gravity factor is the reciprocal of the moving average; The sorting module is used to sort the individual pieces of published information according to the popularity value of each piece of published information in the multiple pieces of published information to obtain a sorting result.

7. An electronic device, characterized in that: The electronic device comprises: A memory for storing executable instructions; A processor, configured to implement the information sorting method according to any one of claims 1 to 5 when executing the executable instructions stored in the memory.

8. A computer-readable storage medium, characterized in that: Executable instructions are stored, and when executed by a processor, the information sorting method described in any one of claims 1 to 5 is implemented.

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