Traffic package page retweet method and system based on traffic usage data

Abstract

This application discloses a method and system for retweeting a traffic package page based on traffic usage data. The method comprises: obtaining a traffic package to be retweeted and multiple traffic usage data, wherein the traffic package to be retweeted includes multiple traffic availability items and traffic availability values ​​corresponding to each traffic availability item, and the traffic usage data includes multiple traffic usage items and traffic usage values ​​corresponding to each traffic usage item; filtering the multiple traffic usage data based on the traffic availability values ​​and traffic usage values ​​to obtain multiple filtering results; calculating the degree of match between each filtering result and the traffic package to be retweeted; determining the page retweet frequency of the traffic package to be retweeted for each filtering result based on the matching degree and a preset retweet frequency comparison table, and retweeting the traffic package to be retweeted based on the page retweet frequency. This technical solution can improve the rationality and accuracy of traffic package retweeting.

Description

Technical Field

[0001] The present application belongs to the field of data processing technology, and specifically relates to a method and system for forwarding traffic package pages based on traffic usage data. Background Art

[0002] With the development of the internet, data traffic, a key resource for internet access, is being purchased and used in large quantities. To meet diverse data traffic demands, pushing data package information to terminals through page forwarding has become a key technical means for carrier systems to manage data packages. Page forwarding, through data processing, allows carrier systems to push data package information to terminals for purchase, effectively improving the efficiency of data package screening and purchase.

[0003] In existing technology, operators typically process data from data on data package release times to determine the order in which data packages are released. Based on this order, they then determine the retweet frequency for each data package, retweeting the data packages on a page according to the corresponding retweet frequency. Alternatively, they set different retweet frequencies for different data packages based on experience and demand for data conversion. However, different terminals have different data usage characteristics, and existing technology suffers from issues such as inefficient data package retweet methods and inaccurate retweet results. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a method and system for forwarding traffic package pages based on traffic usage data, which solves the problems of unreasonable forwarding methods and inaccurate forwarding results in the prior art. By determining the matching degree between traffic usage characteristics and traffic availability characteristics of the traffic package to be forwarded, and determining the page forwarding frequency of the traffic package to be forwarded based on the matching degree, the purpose of forwarding traffic packages in combination with traffic usage characteristics can be achieved, thereby improving the rationality and accuracy of traffic package forwarding.

[0005] In a first aspect, an embodiment of the present application provides a method for forwarding a traffic package page based on traffic usage data, the method comprising:

[0006] Obtaining a traffic package to be retweeted and a plurality of traffic usage data, wherein the traffic package to be retweeted includes a plurality of available traffic items and a traffic available value corresponding to each available traffic item, and the traffic usage data includes a plurality of traffic usage items and a traffic usage value corresponding to each traffic usage item;

[0007] Filtering multiple traffic usage data based on traffic available values ​​and traffic usage values ​​to obtain multiple filtering results;

[0008] Calculate the matching degree between each screening result and the traffic package to be retweeted;

[0009] Based on the matching degree and the preset retweet frequency comparison table, the page retweet frequency of the traffic package to be retweeted corresponding to each screening result is determined, and the traffic package to be retweeted is retweeted according to the page retweet frequency.

[0010] Optionally, calculate the matching degree between each screening result and the traffic package to be retweeted, including:

[0011] Performing a first-level classification of the traffic usage items of each screening result based on a plurality of preset traffic thresholds and traffic usage values, and determining a distribution characteristic of the traffic usage items of each screening result based on the first-level classification result;

[0012] performing a second-level classification of traffic availability items based on a plurality of preset traffic thresholds and traffic availability values, and determining traffic availability distribution characteristics of the traffic package to be retweeted based on the second-level classification result;

[0013] The matching degree of each screening result with the traffic package to be retweeted is determined based on the distribution characteristics of traffic usage items and the distribution characteristics of traffic availability items.

[0014] Optionally, the matching degree of each screening result with the traffic package to be retweeted is determined based on the distribution characteristics of the traffic usage item and the distribution characteristics of the traffic availability item, including:

[0015] Determine the traffic usage pattern of each screening result based on the distribution characteristics of traffic usage items, and predict the traffic demand information of each screening result based on the traffic usage pattern;

[0016] The degree of difference between the traffic demand information and the distribution characteristics of the available traffic items is calculated, and the matching degree between each screening result and the traffic package to be retweeted is determined based on the degree of difference.

[0017] Optionally, the difference between the traffic demand information and the distribution characteristics of the available traffic items is calculated, including:

[0018] Mapping the traffic demand information and the distribution characteristics of available traffic items into the same traffic information list, and identifying the intersection and union of the traffic demand information and the distribution characteristics of available traffic items;

[0019] The ratio of the intersection to the union is calculated, and the degree of difference between the flow demand information and the distribution characteristics of the flow available items is determined based on the ratio.

[0020] Optionally, the matching degree of each screening result with the traffic package to be retweeted is determined based on the distribution characteristics of the traffic usage item and the distribution characteristics of the traffic availability item, including:

[0021] Read the traffic usage data and traffic packages to be retweeted of the same level in the traffic usage item distribution characteristics and traffic availability item distribution characteristics;

[0022] Based on the traffic usage data and traffic packages to be retweeted at the same level, calculate the similarity between the distribution characteristics of traffic usage items and the distribution characteristics of traffic availability items at each level;

[0023] The similarity in each level is weightedly calculated with the corresponding level to determine the overall similarity between the distribution characteristics of traffic usage items and the distribution characteristics of traffic available items, and obtain the matching degree of each screening result and the traffic package to be retweeted.

[0024] Optionally, based on the traffic usage data and traffic packages to be retweeted at the same level, the similarity of the traffic usage item distribution characteristics and the traffic availability item distribution characteristics at each level is calculated, including:

[0025] Use the traffic usage items in the traffic usage data of the same level as the horizontal axis and the traffic usage value corresponding to each traffic usage item as the vertical axis to draw the distribution characteristic curve of the traffic usage items of the same level;

[0026] Use the traffic availability items in the traffic packages to be retweeted of the same level as the horizontal axis and the traffic availability value corresponding to each traffic availability item as the vertical axis to draw a distribution characteristic curve of traffic availability items of the same level;

[0027] The distance between the traffic usage item distribution characteristic curve and the traffic availability item distribution characteristic curve in the same level is calculated to obtain the similarity between the traffic usage item distribution characteristic and the traffic availability item distribution characteristic in each level.

[0028] Optionally, after determining the page retweet frequency of the traffic package to be retweeted corresponding to each screening result, the method further includes:

[0029] Obtain the traffic expiration time, remaining traffic data, and traffic effective time of the traffic package to be retweeted for each filtering result;

[0030] Calculate the time interval between the traffic expiration time and the traffic effective time, normalize the remaining traffic data and the time interval, and obtain a normalized result of the remaining traffic data and a normalized result of the time interval;

[0031] A weighted value of the normalized result is calculated based on the preset time weight, the preset flow weight, the flow remaining data normalized result, and the time interval normalized result, and the matching degree is updated based on the weighted value of the normalized result.

[0032] In a second aspect, an embodiment of the present application provides a traffic package page retweet system based on traffic usage data, the system comprising:

[0033] a data acquisition module, configured to acquire a traffic package to be retweeted and a plurality of traffic usage data, wherein the traffic package to be retweeted includes a plurality of available traffic items and a traffic available value corresponding to each available traffic item, and the traffic usage data includes a plurality of traffic usage items and a traffic usage value corresponding to each traffic usage item;

[0034] A data screening module, configured to screen a plurality of traffic usage data based on traffic available values ​​and traffic usage values, and obtain a plurality of screening results;

[0035] A matching degree calculation module is used to calculate the matching degree between each screening result and the traffic package to be retweeted;

[0036] The page retweet module is used to determine the page retweet frequency corresponding to each screening result of the traffic package to be retweeted based on the matching degree and the preset retweet frequency comparison table, and retweet the traffic package to be retweeted according to the page retweet frequency.

[0037] In a third aspect, an embodiment of the present application provides an electronic device comprising a processor, a memory, and a program or instruction stored in the memory and executable on the processor, wherein the program or instruction, when executed by the processor, implements the steps of the method of the first aspect.

[0038] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method of the first aspect are implemented.

[0039] In the fifth aspect, an embodiment of the present application also provides a computer program product, which includes a computer program stored in a computer-readable storage medium. At least one processor of the device reads and executes the computer program from the computer-readable storage medium, so that the device performs the method of the first aspect.

[0040] In an embodiment of the present application, a traffic package to be retweeted and multiple traffic usage data are obtained, wherein the traffic package to be retweeted includes multiple traffic available items and traffic available values ​​corresponding to each traffic available item, and the traffic usage data includes multiple traffic usage items and traffic usage values ​​corresponding to each traffic usage item; the multiple traffic usage data are filtered based on the traffic available values ​​and traffic usage values ​​to obtain multiple filtering results; the matching degree of each filtering result with the traffic package to be retweeted is calculated; based on the matching degree and a preset retweet frequency comparison table, the page retweet frequency corresponding to each filtering result of the traffic package to be retweeted is determined, and the traffic package to be retweeted is retweeted based on the page retweet frequency. The above-mentioned traffic package page retweet method based on traffic usage data solves the problems of unreasonable retweet methods and inaccurate retweet results in the prior art. By determining the matching degree between the traffic usage characteristics and the traffic available characteristics of the traffic package to be retweeted, and determining the page retweet frequency of the traffic package to be retweeted based on the matching degree, the purpose of retweeting the traffic package in combination with the traffic usage characteristics can be achieved, thereby improving the rationality and accuracy of traffic package retweet. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a flow chart of a method for forwarding a traffic package page based on traffic usage data provided by an embodiment of the present application;

[0042] Figure 2 This is a flow chart of calculating the matching degree based on distribution characteristics provided by this application;

[0043] Figure 3 This is a flowchart of calculating matching degree based on traffic usage data provided by this application;

[0044] Figure 4 It is a schematic diagram of the flow characteristic curve provided by this application;

[0045] Figure 5 This is a structural block diagram of a traffic package page retweet system based on traffic usage data provided by an embodiment of the present application;

[0046] Figure 6 This is a structural block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0047] To further clarify the objectives, technical solutions, and advantages of this application, specific embodiments of the present application are described in further detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are intended only to illustrate this application and are not intended to limit the present application. It should also be noted that, for ease of description, the drawings only illustrate portions relevant to this application, not all of them. Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts depict each operation (or step) as a sequential process, many of the operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of each operation can be rearranged. A process may terminate upon completion of its operations, but may also have additional steps not shown in the accompanying drawings. A process may correspond to a method, function, procedure, subroutine, subprogram, and the like.

[0048] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0049] The terms "first," "second," and the like in the specification and claims of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable with appropriate information, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. In addition, the term "and / or" in the specification and claims refers to at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.

[0050] First, the use scenario of this solution can be a scenario where the operator system promotes traffic packages to attract purchases of traffic packages, especially a scenario where traffic package pages are retweeted and promoted at different frequencies based on traffic usage data. By determining the degree of match between traffic usage characteristics and traffic availability characteristics of the traffic package to be retweeted, and determining the retweet frequency of the page of the traffic package to be retweeted based on the match, the purpose of retweeting the traffic package in combination with traffic usage characteristics can be achieved, thereby improving the rationality and accuracy of traffic package retweets. Based on the above usage scenarios, it can be understood that the executor of this solution can be a server used to execute tasks of the communication business processing system or platform.

[0051] Below, in conjunction with the accompanying drawings, a method and system for forwarding traffic package pages based on traffic usage data provided by the embodiment of the present application will be described in detail through specific embodiments and their application scenarios.

[0052] Figure 1 This is a flow chart of a method for forwarding a traffic package page based on traffic usage data provided by an embodiment of the present application. Figure 1 As shown, the specific steps include:

[0053] S101, obtain a traffic package to be forwarded and multiple traffic usage data, the traffic package to be forwarded includes multiple traffic available items and traffic available values ​​corresponding to each traffic available item, and the traffic usage data includes multiple traffic usage items and traffic usage values ​​corresponding to each traffic usage item.

[0054] The traffic package to be forwarded may be traffic package data that the operator system needs to forward and push to the terminal. This may be a newly launched traffic package or a previously launched package that needs to increase exposure or conversion rates. The traffic package to be forwarded includes multiple available traffic items and available traffic values ​​corresponding to each available traffic item. Available traffic items may be traffic services available in the traffic package to be forwarded. Examples include: provincial universal traffic, national universal traffic, and dedicated traffic for specific software applications. The available traffic value corresponding to each available traffic item may be the total available traffic or available traffic parameters for each traffic service provided. Examples include: 20GB provincial universal traffic and unlimited provincial universal traffic. Multiple traffic usage data may include the actual traffic used by each terminal within a preset time period. The traffic usage data includes multiple traffic usage items corresponding to each terminal and the traffic usage value corresponding to each traffic usage item. A traffic usage item may be a traffic service actually used within a preset time period. The traffic usage value corresponding to each traffic usage item may be the traffic value consumed by each terminal for each traffic usage item within the preset time period. For example: A consumed a total of 2G of traffic on application x.

[0055] In one embodiment, a method can be provided to receive product data uploaded by an operator to obtain a traffic package to be retweeted, and to obtain multiple traffic usage data by reading the historical traffic usage records of the traffic package. The traffic package to be retweeted includes multiple available traffic items and the available traffic value corresponding to each available traffic item, and the traffic usage data includes multiple traffic usage items and the traffic usage value corresponding to each traffic usage item.

[0056] S102: Filter multiple traffic usage data based on the traffic available value and the traffic usage value to obtain multiple filtering results.

[0057] The screening result may be traffic usage data in which the traffic usage value is less than or equal to the traffic available value.

[0058] In one embodiment, multiple traffic usage data sets can be filtered by comparing the available traffic value with the traffic usage value, and traffic usage data sets with traffic usage values ​​greater than the available traffic value can be filtered out, thereby obtaining multiple filtering results. Since the traffic package to be retweeted is intended for exposure and conversion rates, when the traffic usage value exceeds the available traffic value provided by the traffic package to be retweeted, the details of the traffic package to be retweeted are likely not to be viewed or purchased, and therefore such traffic usage data can be directly filtered out.

[0059] S103: Calculate the matching degree between each screening result and the traffic package to be retweeted.

[0060] The matching degree between each screening result and the traffic package to be forwarded may be the similarity between each screened traffic usage data and the traffic package to be forwarded.

[0061] In one embodiment, a plurality of traffic availability items can be used as elements, and the traffic availability value corresponding to each traffic availability item can be used as the element value to construct a traffic packet vector of the traffic packet to be retweeted. In addition, a plurality of traffic usage items in the traffic usage data corresponding to each screening result can be used as elements, and the traffic usage value corresponding to each traffic usage item can be used as the element value to construct a traffic usage vector of each screening result. By calculating the Euclidean distance between the traffic packet vector and the traffic usage vector of each screening result, the matching degree of each screening result and the traffic packet to be retweeted can be obtained.

[0062] S104: Based on the matching degree and the preset retweet frequency comparison table, determine the page retweet frequency of the traffic package to be retweeted corresponding to each screening result, and retweet the traffic package to be retweeted according to the page retweet frequency.

[0063] The preset retweet frequency comparison table may be a table pre-set by the operator, mapping matching degrees to preset retweet frequencies based on the retweet requirements of the traffic package to be retweeted. Each preset retweet frequency in the preset retweet frequency comparison table corresponds to a matching degree range. The page retweet frequency may be the number of times the traffic package to be retweeted is retweeted to the terminal corresponding to each filter result within a preset time period.

[0064] In one embodiment, the matching degree range between each screening result and the traffic packet to be retweeted can be identified, and the page retweet frequency corresponding to each screening result can be determined based on the preset retweet frequency corresponding to each matching degree range in a preset retweet frequency comparison table. Based on the matching degree and the preset retweet frequency comparison table, the page retweet frequency for retweeting the traffic packet to be retweeted to the terminal corresponding to each screening result is determined, and the traffic packet to be retweeted is retweeted according to the page retweet frequency.

[0065] In one embodiment, optionally, after determining the page retweet frequency of the traffic packet to be retweeted corresponding to each screening result, the method further includes:

[0066] Obtain the traffic expiration time, remaining traffic data, and traffic effective time of the traffic package to be retweeted for each filtering result;

[0067] Calculate the time interval between the traffic expiration time and the traffic effective time, normalize the remaining traffic data and the time interval, and obtain a normalized result of the remaining traffic data and a normalized result of the time interval;

[0068] A weighted value of the normalized result is calculated based on the preset time weight, the preset flow weight, the flow remaining data normalized result, and the time interval normalized result, and the matching degree is updated based on the weighted value of the normalized result.

[0069] Among them, the traffic expiration time may be the package expiration time of the currently used traffic package corresponding to each filtering result. The traffic remaining data may be the remaining traffic value of the package of the currently used traffic package corresponding to each filtering result before the end of the current month. The traffic effective time may be the earliest available time of the traffic package to be retweeted. Normalization may be an operation that unifies the traffic remaining data and the time interval into the same evaluation standard to eliminate the data dimension. The preset time weight may be a pre-set parameter that represents the degree of influence of the time interval on the matching degree. The preset traffic weight may be a pre-set parameter that represents the degree of influence of the remaining traffic on the matching degree. The preset time weight is inversely proportional to the time interval, that is, the larger the time interval, the smaller the matching degree, and the smaller the preset time weight; the preset traffic weight is inversely proportional to the remaining traffic, that is, the smaller the remaining traffic, the higher the matching degree, and the larger the preset time weight.

[0070] In one embodiment, the traffic expiration time can be obtained by reading the identifier of the currently used traffic package corresponding to each screening result, reading the traffic usage record to obtain the remaining traffic data, and reading the parameter corresponding to the traffic effective time field in the traffic package to be retweeted to obtain the traffic effective time. The time interval between the traffic expiration time and the traffic effective time corresponding to each screening result is calculated, and the remaining traffic data and the time interval are normalized using the maximum-minimum normalization method to obtain a normalized result of the remaining traffic data and a normalized result of the time interval. By normalizing the remaining traffic data and the time interval, the dimensional difference between the remaining traffic data and the time interval can be eliminated. The product of the preset time weight and the normalized result of the time interval and the product of the preset traffic weight and the normalized result of the remaining traffic data are calculated, and the two product values ​​are added together to calculate the weighted value of the normalized result. The weighted value of the normalized result of each screening result can be added to the corresponding matching degree to obtain an updated matching degree result for each screening result.

[0071] This solution calculates the time interval between the traffic expiration time and the traffic effectiveness time after determining the page retweet frequency of the traffic package to be retweeted corresponding to each screening result, calculates the weighted value of the normalized result based on the preset time weight, preset traffic weight, the normalized result of the remaining traffic data and the normalized result of the time interval, and updates the matching degree. This can achieve the purpose of determining the matching degree between the screening result and the traffic package to be retweeted by combining the remaining traffic and the package expiration data, improves the comprehensiveness of the matching degree evaluation results, and is conducive to the subsequent determination of the accuracy of the retweet frequency of the traffic package to be retweeted.

[0072] The technical solution provided by the embodiment of the present application obtains a traffic package to be retweeted and multiple traffic usage data, wherein the traffic package to be retweeted includes multiple traffic available items and traffic available values ​​corresponding to each traffic available item, and the traffic usage data includes multiple traffic usage items and traffic usage values ​​corresponding to each traffic usage item; the multiple traffic usage data are filtered based on the traffic available values ​​and traffic usage values ​​to obtain multiple filtering results; the matching degree of each filtering result with the traffic package to be retweeted is calculated; based on the matching degree and a preset retweet frequency comparison table, the page retweet frequency corresponding to each filtering result of the traffic package to be retweeted is determined, and the traffic package to be retweeted is retweeted based on the page retweet frequency. The above-mentioned traffic package page retweet method based on traffic usage data solves the problems of unreasonable retweet methods and inaccurate retweet results in the prior art. By determining the matching degree between the traffic usage characteristics and the traffic available characteristics of the traffic package to be retweeted, and determining the page retweet frequency of the traffic package to be retweeted based on the matching degree, the purpose of retweeting the traffic package in combination with the traffic usage characteristics can be achieved, thereby improving the rationality and accuracy of traffic package retweet.

[0073] Figure 2 This is a flow chart of calculating the matching degree based on distribution characteristics provided by this application. Figure 2 As shown, the specific steps include:

[0074] S201, performing a first-level classification of traffic usage items of each screening result based on a plurality of preset traffic thresholds and traffic usage values, and determining a distribution characteristic of the traffic usage items of each screening result based on the first-level classification result.

[0075] Among them, the preset traffic threshold can be a pre-set range of traffic values ​​for different traffic levels. The first-level division result can be the result obtained by grouping the traffic usage items in each screening result by level. The different levels in each first-level division result include different traffic usage items in the corresponding screening results. The traffic usage items with higher traffic usage values ​​have higher corresponding levels in the first-level division results. The traffic usage item distribution characteristics can be the distribution characteristics of the levels of the traffic usage items of each screening result. For example: which traffic usage items are distributed at higher levels, and which traffic usage items are distributed at lower levels. According to the traffic usage item distribution characteristics of each screening result, the traffic usage items with higher frequency can be determined.

[0076] In one embodiment, each traffic usage value in each filtering result can be compared with multiple preset traffic thresholds to determine the preset traffic threshold to which each traffic usage value belongs, and the traffic usage items corresponding to the traffic usage value can be divided into the level to which the preset traffic threshold to which the traffic usage value belongs, so as to perform a first-level division on each traffic usage item in each filtering result, and determine the traffic usage item distribution characteristics of each filtering result based on the first-level division result.

[0077] S202 , performing a second-level classification of traffic availability items based on a plurality of preset traffic thresholds and traffic availability values, and determining traffic availability distribution characteristics of the traffic package to be forwarded based on the second-level classification result.

[0078] The second level classification result may be a result of grouping the traffic usage items in each screening result by level. The traffic availability distribution characteristics may be the distribution characteristics of the level of the traffic availability items of the traffic package to be retweeted. Based on the traffic availability item distribution characteristics of the traffic package to be retweeted, the traffic usage item applicable to the traffic package to be retweeted may be determined.

[0079] In one embodiment, each traffic availability value in the traffic package to be forwarded can be compared with multiple preset traffic thresholds to determine the preset traffic threshold to which each traffic availability value belongs, and the traffic availability items corresponding to the traffic availability value can be divided into the level to which the preset traffic threshold to which the traffic usage value belongs, so as to perform a second-level division on each traffic availability item in the traffic package to be forwarded, and determine the distribution characteristics of the traffic availability items of the traffic package to be forwarded based on the second-level division result.

[0080] S203: Determine the matching degree between each screening result and the traffic package to be retweeted based on the traffic usage item distribution characteristics and the traffic availability item distribution characteristics.

[0081] In one embodiment, the difference between the traffic usage value corresponding to the traffic usage item of the traffic usage item distribution characteristics at the same level and the traffic usage value corresponding to the same traffic usage item in the traffic availability item distribution characteristics can be calculated, and the differences can be added to obtain the matching degree of the traffic usage item distribution characteristics and the traffic availability item distribution characteristics at the same level, and the matching degrees of all levels can be added to obtain the matching degree of each screening result and the traffic package to be retweeted.

[0082] In one embodiment, optionally, determining the matching degree of each screening result with the traffic package to be retweeted based on the traffic usage item distribution characteristics and the traffic availability item distribution characteristics includes:

[0083] Determine the traffic usage pattern of each screening result based on the distribution characteristics of traffic usage items, and predict the traffic demand information of each screening result based on the traffic usage pattern;

[0084] The degree of difference between the traffic demand information and the distribution characteristics of the available traffic items is calculated, and the matching degree between each screening result and the traffic package to be retweeted is determined based on the degree of difference.

[0085] The traffic usage pattern can be the usage frequency characteristics of the traffic usage item corresponding to each filtering result. The higher the level of the traffic usage item, the higher the usage frequency. The traffic demand information can be the required traffic usage and the required usage value for each filtering result. The traffic demand information corresponds to the level of the traffic usage item; the higher the level of the traffic usage item, the higher the traffic demand. The degree of difference can be the difference between the traffic demand and the available traffic data provided by the traffic package to be retweeted.

[0086] In one embodiment, the traffic usage pattern of each screening result can be determined based on the distribution characteristics of the traffic usage items, and the usage frequency of each traffic usage item can be determined based on the traffic usage pattern. At the same time, the associated traffic usage items of each traffic usage item and the level of the associated traffic usage items can be identified, and the level of the associated traffic usage items can be used as an influencing factor to predict the traffic demand information of each screening result. For example: if a certain traffic usage item is intra-provincial traffic usage, then its associated traffic usage items are national traffic usage and whether the provincial traffic is speed-limited. When the provincial traffic usage level is the first level, the national traffic usage level is the second level, and the provincial traffic speed-limited usage is the first level, then the provincial traffic usage level, the national traffic usage level, and the provincial traffic speed-limited usage level are averaged, and the average value is rounded up to obtain the final usage demand level of the provincial traffic usage traffic usage item in the traffic demand information. The associated traffic usage items can be compatible or mutually exclusive with each traffic usage item.

[0087] Calculate the difference between traffic demand items and traffic available items of the same level in the traffic demand information and traffic available item distribution characteristics, and add the differences of each level to obtain the degree of difference between the traffic demand information and the traffic available item distribution characteristics. The degree of difference is determined as the matching degree between each screening result and the traffic package to be retweeted.

[0088] This solution determines the traffic usage pattern of each screening result, predicts traffic demand information, and determines the matching degree of each screening result with the traffic package to be retweeted based on the degree of difference between the traffic demand information and the distribution characteristics of available traffic items. This can achieve the purpose of matching degree evaluation in combination with demand prediction results, and further improve the accuracy of matching degree calculation results.

[0089] In one embodiment, optionally, calculating the difference between the traffic demand information and the distribution characteristics of the traffic available items includes:

[0090] Mapping the traffic demand information and the distribution characteristics of available traffic items into the same traffic information list, and identifying the intersection and union of the traffic demand information and the distribution characteristics of available traffic items;

[0091] The ratio of the intersection to the union is calculated, and the degree of difference between the flow demand information and the distribution characteristics of the flow available items is determined based on the ratio.

[0092] The traffic information list may be a list that associates traffic items with corresponding levels. The intersection may be the number of traffic usage items in the traffic demand information that have the same level, traffic item, and traffic value as the traffic availability item distribution characteristics. The union may be the total number of traffic items in the traffic demand information that have the same level as the traffic availability item distribution characteristics.

[0093] In one embodiment, the traffic demand information and the distribution characteristics of the traffic available items can be mapped to the same traffic information list, the intersection and union of the traffic demand information and the distribution characteristics of the traffic available items in the traffic information list can be identified, the ratio of the intersection and union of the traffic items of each level can be calculated, and the ratio of each level can be added to obtain the degree of difference between the traffic demand information and the distribution characteristics of the traffic available items.

[0094] This solution determines the degree of difference between the traffic demand information and the distribution characteristics of the traffic available items by identifying the intersection and union of the traffic demand information and the distribution characteristics of the traffic available items, calculating the ratio of the intersection and the union, and thus simplifying the steps for calculating the degree of difference and improving the efficiency of determining the degree of difference.

[0095] The technical solution provided in the embodiment of the present application determines the traffic usage item distribution characteristics of each filtering result by ranking the traffic usage items of each filtering result, determines the traffic availability distribution characteristics of the traffic package to be retweeted by ranking the traffic availability items, and then determines the matching degree of each filtering result and the traffic package to be retweeted. This can achieve the purpose of calculating the matching degree of the traffic package to be retweeted based on the usage characteristics, which is conducive to improving the rationality of subsequent retweets of the traffic package.

[0096] Figure 3 This is a flow chart of calculating matching degree based on traffic usage data provided by this application. Figure 3 As shown, the specific steps include:

[0097] S301, reading the traffic usage data and the traffic package to be forwarded of the same level in the traffic usage item distribution characteristics and the traffic availability item distribution characteristics.

[0098] In one embodiment, based on the levels corresponding to the traffic usage items and the traffic availability items, the traffic usage data and the traffic packets to be forwarded of the same level in the traffic usage item distribution characteristics and the traffic availability item distribution characteristics can be read.

[0099] S302 , based on the traffic usage data of the same level and the traffic package to be retweeted, calculate the similarity of the traffic usage item distribution characteristics and the traffic availability item distribution characteristics in each level.

[0100] In one embodiment, the average value of the traffic usage value of the traffic usage data in the same level and the average value of the traffic available value of the traffic package to be forwarded can be calculated respectively, and the difference between the average value of the traffic usage value and the average value of the traffic available value can be calculated to obtain the similarity of the traffic usage item distribution characteristics and the traffic available item distribution characteristics in each level.

[0101] In one embodiment, optionally, based on traffic usage data and traffic packets to be retweeted at the same level, calculating the similarity between traffic usage item distribution characteristics and traffic availability item distribution characteristics at each level includes:

[0102] Use the traffic usage items in the traffic usage data of the same level as the horizontal axis and the traffic usage value corresponding to each traffic usage item as the vertical axis to draw the distribution characteristic curve of the traffic usage items of the same level;

[0103] Use the traffic availability items in the traffic packages to be retweeted of the same level as the horizontal axis and the traffic availability value corresponding to each traffic availability item as the vertical axis to draw a distribution characteristic curve of traffic availability items of the same level;

[0104] The distance between the traffic usage item distribution characteristic curve and the traffic availability item distribution characteristic curve in the same level is calculated to obtain the similarity between the traffic usage item distribution characteristic and the traffic availability item distribution characteristic in each level.

[0105] The traffic usage item distribution characteristic curve may be a curve representing traffic usage characteristics obtained by connecting traffic usage values ​​corresponding to traffic usage items of the same level. The traffic availability item distribution characteristic curve may be a curve representing traffic service characteristics that can be provided by the traffic package to be retweeted obtained by connecting traffic availability values ​​corresponding to traffic availability items of the same level.

[0106] Figure 4 It is a schematic diagram of the flow characteristic curve provided by this application.

[0107] like Figure 4 As shown in the figure, the curve connected by the dotted line represents the traffic usage item distribution characteristic curve, the solid line represents the traffic availability item distribution characteristic curve, the white points represent the coordinate points of the traffic usage items, and the black points represent the coordinate points of the traffic availability items. Among them, the traffic usage item distribution characteristic curve includes traffic usage item A, traffic usage item B, traffic usage item C, traffic usage item D, and traffic usage item F, and the traffic availability item distribution characteristic curve includes traffic availability item A, traffic availability item C, traffic availability item D, traffic availability item E, and traffic availability item F. Each traffic usage item and traffic availability item corresponds to the same or different traffic values. In the process of curve drawing, the traffic availability values ​​of traffic items with traffic usage item distribution characteristics but without traffic availability item distribution characteristics are padded with 0, and the usage values ​​of each traffic usage item and the availability values ​​of each traffic availability item are connected respectively to obtain the traffic usage item distribution characteristic curve and the traffic availability item distribution characteristic curve.

[0108] In one embodiment, the traffic usage items in the traffic usage data of the same level can be used as the horizontal axis, and the traffic usage value corresponding to each traffic usage item can be used as the vertical axis. The coordinate points of each traffic usage item can be connected to draw a traffic usage item distribution characteristic curve for each screening result at the same level. The traffic availability items in the traffic packets to be retweeted at the same level can be used as the horizontal axis, and the traffic availability value corresponding to each traffic availability item can be used as the vertical axis. The coordinate points of each traffic availability item can be connected to draw a traffic availability item distribution characteristic curve for the same level. The Euclidean distance between the traffic usage item distribution characteristic curve and the traffic availability item distribution characteristic curve at the same level can be calculated to obtain the similarity between the traffic usage item distribution characteristics and the traffic availability item distribution characteristics at each level.

[0109] This solution draws the traffic usage item distribution characteristic curve and the traffic availability item distribution characteristic curve of the same level, calculates the distance between the curves, and obtains the similarity of the traffic usage item distribution characteristics and the traffic availability item distribution characteristics in each level, which can improve the efficiency of similarity calculation.

[0110] S303: Perform weighted calculation on the similarity in each level and the corresponding level to determine the overall similarity between the distribution characteristics of traffic usage items and the distribution characteristics of traffic availability items, and obtain the matching degree between each screening result and the traffic package to be retweeted.

[0111] In one embodiment, the level is used as a weight, the similarity in each level and the weighted value of the corresponding level are calculated, and the weighted values ​​of each level are added together to obtain the overall similarity between the distribution characteristics of traffic usage items and the distribution characteristics of traffic available items. The overall similarity is used as the matching degree of each screening result and the traffic package to be retweeted.

[0112] The technical solution provided in the embodiment of the present application calculates the similarity between the distribution characteristics of traffic usage items and the distribution characteristics of traffic availability items at each level, performs weighted calculation on the similarity in each level and the corresponding level, determines the overall similarity, and obtains the matching degree between each screening result and the traffic package to be retweeted, thereby improving the efficiency and accuracy of the matching degree calculation.

[0113] Figure 5 This is a structural block diagram of a traffic package page forwarding system based on traffic usage data provided by an embodiment of the present application. Figure 5 As shown, specifically including the following:

[0114] A data acquisition module 501 is configured to acquire a traffic package to be retweeted and a plurality of traffic usage data, wherein the traffic package to be retweeted includes a plurality of available traffic items and a corresponding available traffic value for each available traffic item, and the traffic usage data includes a plurality of traffic usage items and a corresponding traffic usage value for each traffic usage item;

[0115] A data screening module 502 is configured to screen a plurality of traffic usage data based on the traffic available value and the traffic usage value to obtain a plurality of screening results;

[0116] A matching degree calculation module 503 is used to calculate the matching degree between each screening result and the traffic package to be retweeted;

[0117] The page retweet module 504 is used to determine the page retweet frequency corresponding to each screening result of the traffic package to be retweeted based on the matching degree and the preset retweet frequency comparison table, and retweet the traffic package to be retweeted according to the page retweet frequency.

[0118] Optionally, the matching degree calculation module 503 is specifically configured to:

[0119] Performing a first-level classification of the traffic usage items of each screening result based on a plurality of preset traffic thresholds and traffic usage values, and determining a distribution characteristic of the traffic usage items of each screening result based on the first-level classification result;

[0120] performing a second-level classification of traffic availability items based on a plurality of preset traffic thresholds and traffic availability values, and determining traffic availability distribution characteristics of the traffic package to be retweeted based on the second-level classification result;

[0121] The matching degree of each screening result with the traffic package to be retweeted is determined based on the distribution characteristics of traffic usage items and the distribution characteristics of traffic availability items.

[0122] Optionally, the matching degree calculation module 503 is specifically configured to:

[0123] Determine the traffic usage pattern of each screening result based on the distribution characteristics of traffic usage items, and predict the traffic demand information of each screening result based on the traffic usage pattern;

[0124] The degree of difference between the traffic demand information and the distribution characteristics of the available traffic items is calculated, and the matching degree between each screening result and the traffic package to be retweeted is determined based on the degree of difference.

[0125] Optionally, the matching degree calculation module 503 is specifically configured to:

[0126] Mapping the traffic demand information and the distribution characteristics of available traffic items into the same traffic information list, and identifying the intersection and union of the traffic demand information and the distribution characteristics of available traffic items;

[0127] The ratio of the intersection to the union is calculated, and the degree of difference between the flow demand information and the distribution characteristics of the flow available items is determined based on the ratio.

[0128] Optionally, the matching degree calculation module 503 is specifically configured to:

[0129] Read the traffic usage data and traffic packages to be retweeted of the same level in the traffic usage item distribution characteristics and traffic availability item distribution characteristics;

[0130] Based on the traffic usage data and traffic packages to be retweeted at the same level, calculate the similarity between the distribution characteristics of traffic usage items and the distribution characteristics of traffic availability items at each level;

[0131] The similarity in each level is weightedly calculated with the corresponding level to determine the overall similarity between the distribution characteristics of traffic usage items and the distribution characteristics of traffic available items, and obtain the matching degree of each screening result and the traffic package to be retweeted.

[0132] Optionally, the matching degree calculation module 503 is specifically configured to:

[0133] Use the traffic usage items in the traffic usage data of the same level as the horizontal axis and the traffic usage value corresponding to each traffic usage item as the vertical axis to draw the distribution characteristic curve of the traffic usage items of the same level;

[0134] Use the traffic availability items in the traffic packages to be retweeted of the same level as the horizontal axis and the traffic availability value corresponding to each traffic availability item as the vertical axis to draw a distribution characteristic curve of traffic availability items of the same level;

[0135] The distance between the traffic usage item distribution characteristic curve and the traffic availability item distribution characteristic curve in the same level is calculated to obtain the similarity between the traffic usage item distribution characteristic and the traffic availability item distribution characteristic in each level.

[0136] Optionally, the system further includes:

[0137] A data acquisition module is used to obtain the traffic expiration time, traffic remaining data and traffic effective time of the traffic package to be forwarded for each screening result;

[0138] A normalization calculation module is used to calculate the time interval between the flow expiration time and the flow effective time, normalize the flow remaining data and the time interval, and obtain a normalized result of the flow remaining data and a normalized result of the time interval;

[0139] The matching degree updating module is used to calculate the weighted value of the normalized result based on the preset time weight, the preset flow weight, the normalized result of the flow remaining data and the normalized result of the time interval, and update the matching degree based on the weighted value of the normalized result.

[0140] The technical solution provided by the embodiment of the present application includes a data acquisition module for acquiring a traffic package to be retweeted and multiple traffic usage data, wherein the traffic package to be retweeted includes multiple traffic availability items and traffic availability values ​​corresponding to each traffic availability item, and the traffic usage data includes multiple traffic usage items and traffic usage values ​​corresponding to each traffic usage item; a data screening module for screening the multiple traffic usage data based on the traffic availability values ​​and the traffic usage values ​​to obtain multiple screening results; a matching degree calculation module for calculating the matching degree of each screening result with the traffic package to be retweeted; and a page retweet module for determining the page retweet frequency corresponding to each screening result of the traffic package to be retweeted based on the matching degree and a preset retweet frequency comparison table, and retweeting the traffic package to be retweeted according to the page retweet frequency. The above-mentioned traffic package page retweet system based on traffic usage data solves the problems of unreasonable retweet methods and inaccurate retweet results in the existing technology. By determining the matching degree between traffic usage characteristics and traffic availability characteristics of the traffic package to be retweeted, the page retweet frequency of the traffic package to be retweeted is determined according to the matching degree. This can achieve the purpose of retweeting traffic packages in combination with traffic usage characteristics, thereby improving the rationality and accuracy of traffic package retweet.

[0141] In an embodiment of the present application, a traffic package page retweet system based on traffic usage data can be configured as a component, integrated circuit, or chip in a terminal. This can be a mobile electronic device or a non-mobile electronic device. Exemplary mobile electronic devices include mobile phones, tablet computers, laptop computers, PDAs, in-vehicle electronic devices, wearable devices, ultra-mobile personal computers (UMPCs), netbooks, or personal digital assistants (PDAs). Non-mobile electronic devices include servers, network attached storage (NAS), personal computers (PCs), televisions, ATMs, or self-service kiosks, and the present embodiment does not impose specific limitations.

[0142] In an embodiment of the present application, a traffic package page forwarding system based on traffic usage data may be an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0143] The traffic package page retweet system based on traffic usage data provided in the embodiment of the present application can implement each process implemented by each of the above method embodiments. To avoid repetition, it will not be repeated here.

[0144] like Figure 6 As shown, an embodiment of the present application also provides an electronic device 600, including a processor 601, a memory 602, and a program or instruction stored in the memory 602 and executable on the processor 601. When the program or instruction is executed by the processor 601, each process of the above-mentioned embodiment of the method for forwarding a traffic package page based on traffic usage data is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0145] It should be noted that the electronic devices in the embodiments of the present application include the mobile electronic devices and non-mobile electronic devices mentioned above.

[0146] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, each process of the above-mentioned embodiment of the traffic package page forwarding method based on traffic usage data is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0147] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer-readable storage medium, such as a computer read-only memory (ROM), random access memory (RAM), a magnetic disk, or an optical disk.

[0148] The present application also provides a program product comprising program code. When the program product is executed on a computer device, the program code is used to cause the computer device to execute the steps of the method described above in accordance with each exemplary embodiment of the present application. For example, the computer device can execute a method for forwarding a traffic package page based on traffic usage data described in an embodiment of the present application. The program product can be implemented using any combination of one or more readable media.

[0149] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system comprising 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 system. In the absence of more restrictive information, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or system comprising the element. In addition, it should be noted that the scope of the methods and systems in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and each step may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0150] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases, the former is a better embodiment. Based on this understanding, the technical solution of this application, or the part that contributes to the prior art, can be embodied in the form of a computer software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the method described in each embodiment of this application.

[0151] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of this application and the claims, all of which are within the protection of this application.

[0152] The above are only preferred embodiments of the present application and the technical principles employed. The present application is not limited to the specific embodiments described herein, and any obvious changes, readjustments, and substitutions that are possible for a person skilled in the art will not depart from the scope of protection of the present application. Therefore, although the present application has been described in detail through the above embodiments, the present application is not limited to the above embodiments and may include many other equivalent embodiments without departing from the concept of the present application. The scope of the present application is determined by the scope of the claims.

Claims

1. A method for forwarding a traffic package page based on traffic usage data, characterized in that: The method comprises: Obtaining a traffic package to be retweeted and a plurality of traffic usage data, wherein the traffic package to be retweeted includes a plurality of available traffic items and a traffic available value corresponding to each of the available traffic items, and the traffic usage data includes a plurality of traffic usage items and a traffic usage value corresponding to each of the traffic usage items; Filtering the plurality of traffic usage data based on the traffic available value and the traffic usage value to obtain a plurality of filtering results; Calculating the degree of match between each of the screening results and the traffic package to be retweeted, including: performing a first-level classification on the traffic usage items of each of the screening results based on a plurality of preset traffic thresholds and the traffic usage value, and determining a traffic usage item distribution characteristic of each of the screening results based on the first-level classification result; performing a second-level classification on the traffic availability items based on the plurality of preset traffic thresholds and the traffic availability value, and determining a traffic availability item distribution characteristic of the traffic package to be retweeted based on the second-level classification result; and determining the degree of match between each of the screening results and the traffic package to be retweeted based on the traffic usage item distribution characteristic and the traffic availability item distribution characteristic. Based on the matching degree and the preset retweet frequency comparison table, the page retweet frequency of the traffic package to be retweeted corresponding to each screening result is determined, and the traffic package to be retweeted is retweeted according to the page retweet frequency.

2. The method for forwarding a traffic package page based on traffic usage data according to claim 1, characterized in that: The determining, based on the traffic usage item distribution characteristics and the traffic available item distribution characteristics, of a matching degree between each of the screening results and the traffic package to be retweeted includes: Determining a traffic usage pattern of each of the screening results based on the traffic usage item distribution characteristics, and predicting traffic demand information of each of the screening results based on the traffic usage pattern; The degree of difference between the traffic demand information and the distribution characteristics of the traffic available items is calculated, and the matching degree between each of the screening results and the traffic package to be forwarded is determined based on the degree of difference.

3. The method for forwarding a traffic package page based on traffic usage data according to claim 2, characterized in that: The calculating the difference between the traffic demand information and the distribution characteristics of the traffic available items includes: Mapping the traffic demand information and the traffic available item distribution characteristics into the same traffic information list, and identifying the intersection and union of the traffic demand information and the traffic available item distribution characteristics; A ratio of the intersection to the union is calculated, and a degree of difference between the flow demand information and a distribution characteristic of the flow available items is determined based on the ratio.

4. The method for forwarding a traffic package page based on traffic usage data according to claim 1, characterized in that: The determining, based on the traffic usage item distribution characteristics and the traffic available item distribution characteristics, of a matching degree between each of the screening results and the traffic package to be retweeted includes: Reading the traffic usage data and the traffic package to be forwarded of the same level in the traffic usage item distribution characteristics and the traffic availability item distribution characteristics; Based on the traffic usage data of the same level and the traffic package to be retweeted, calculating the similarity between the traffic usage item distribution characteristics and the traffic availability item distribution characteristics in each level; The similarity in each level is weightedly calculated with the corresponding level to determine the overall similarity between the distribution characteristics of the traffic usage items and the distribution characteristics of the traffic availability items, and obtain the matching degree between each of the screening results and the traffic package to be retweeted.

5. The method for forwarding a traffic package page based on traffic usage data according to claim 4, characterized in that: The calculating, based on the traffic usage data of the same level and the traffic package to be retweeted, the similarity between the traffic usage item distribution characteristics and the traffic availability item distribution characteristics at each level includes: Using the traffic usage items in the traffic usage data of the same level as the horizontal axis and the traffic usage value corresponding to each traffic usage item as the vertical axis to draw a distribution characteristic curve of the traffic usage items of the same level; Using the traffic available items in the traffic packages to be retweeted of the same level as the horizontal axis and the traffic available value corresponding to each of the traffic available items as the vertical axis to draw a distribution characteristic curve of the traffic available items of the same level; The distance between the traffic usage item distribution characteristic curve and the traffic availability item distribution characteristic curve in the same level is calculated to obtain the similarity between the traffic usage item distribution characteristic and the traffic availability item distribution characteristic in each level.

6. The method for forwarding a traffic package page based on traffic usage data according to claim 1, characterized in that: After determining the page retweet frequency of the traffic package to be retweeted corresponding to each screening result, the method further includes: Obtaining the traffic expiration time, traffic remaining data, and traffic validity time of the traffic package to be forwarded for each of the screening results; Calculating the time interval between the traffic expiration time and the traffic effectiveness time, normalizing the traffic remaining data and the time interval to obtain a normalized result of the traffic remaining data and a normalized result of the time interval; A weighted value of the normalized result is calculated based on a preset time weight, a preset flow weight, the flow remaining data normalized result, and the time interval normalized result, and the matching degree is updated based on the weighted value of the normalized result.

7. A traffic package page retweet system based on traffic usage data, characterized in that: The system comprises: a data acquisition module, configured to acquire a traffic package to be retweeted and a plurality of traffic usage data, wherein the traffic package to be retweeted includes a plurality of available traffic items and a traffic available value corresponding to each of the available traffic items, and the traffic usage data includes a plurality of traffic usage items and a traffic usage value corresponding to each of the traffic usage items; a data screening module, configured to screen the plurality of traffic usage data based on the traffic available value and the traffic usage value to obtain a plurality of screening results; a matching degree calculation module, configured to calculate a matching degree between each of the screening results and the traffic package to be retweeted, including: performing a first-level classification of the traffic usage items of each of the screening results based on a plurality of preset traffic thresholds and the traffic usage value, and determining a traffic usage item distribution characteristic of each of the screening results based on the first-level classification result; performing a second-level classification of the traffic availability items based on the plurality of preset traffic thresholds and the traffic availability value, and determining a traffic availability item distribution characteristic of the traffic package to be retweeted based on the second-level classification result; and determining a matching degree between each of the screening results and the traffic package to be retweeted based on the traffic usage item distribution characteristic and the traffic availability item distribution characteristic. The page retweet module is used to determine the page retweet frequency corresponding to each screening result of the traffic package to be retweeted based on the matching degree and the preset retweet frequency comparison table, and retweet the traffic package to be retweeted according to the page retweet frequency.

8. An electronic device, characterized in that: It includes a processor, a memory, and a program or instruction stored in the memory and executable on the processor. When the program or instruction is executed by the processor, the steps of a traffic package page forwarding method based on traffic usage data as described in any one of claims 1 to 6 are implemented.

9. A readable storage medium, characterized in that The readable storage medium stores a program or instruction, and when the program or instruction is executed by the processor, the steps of a traffic package page forwarding method based on traffic usage data as described in any one of claims 1 to 6 are implemented.

Images