Disclosure of Invention
The invention provides a mobile phone flow point giving method and system based on big data analysis, which can calculate and give points through flow threshold management, avoid the problem of excessive or insufficient point giving, and meet the point giving and obtaining requirements of users in different use scenes.
In order to solve the above technical problems, the present invention provides a mobile phone traffic integral giving method based on big data analysis, including:
Acquiring resource use data of a user, wherein the resource use data comprises first resource use data and second resource use data;
According to the first resource use data, performing first integral calculation to obtain a first donation integral;
According to the first resource usage data, performing first flow calculation to obtain a first flow usage value;
When the first flow using value is larger than a first preset flow threshold value, performing second integral calculation to obtain a second donation integral;
according to the second resource use data, second flow calculation is carried out, and a second flow use value is obtained;
And stopping the point giving of the current day when the second flow using value is larger than a second preset flow threshold value, and carrying out point giving according to the first giving point and the second giving point based on preset point giving conditions.
Preferably, the first resource usage data includes pre-threshold traffic consumption, pre-threshold text usage times, pre-threshold video usage times, and pre-threshold picture usage times;
The second resource usage data includes post-threshold traffic consumption, post-threshold text usage times, post-threshold video usage times, and post-threshold picture usage times.
Preferably, the calculating the first score according to the first resource usage data to obtain a first gifting score includes:
The calculation formula of the first integral calculation is as follows:
In the formula,Integrating the first gift; the flow consumption before the threshold value; The number of times of text use before the threshold value; the video frequency is the video frequency before the threshold value; The number of times of using the picture before the threshold value; and integrating the first weight coefficient to respectively correspond to the integrating weights of the flow, the text, the video and the picture.
Preferably, the performing a first flow calculation according to the first resource usage data to obtain a first flow usage value includes:
The calculation formula of the first flow calculation is as follows:
In the formula,A value for a first flow usage; the flow consumption before the threshold value; The number of times of text use before the threshold value; the video frequency is the video frequency before the threshold value; The number of times of using the picture before the threshold value; AndAnd respectively representing flow consumption ratios of flow, text, video and picture for the flow conversion coefficients.
Preferably, when the first flow usage value is greater than a first preset flow threshold, performing a second integration calculation to obtain a second gifting integral, including:
The calculation formula of the second integral calculation is as follows:
In the formula,Integrating for a second gift; the flow consumption after the threshold value is set; The text use times after the threshold value; the video frequency is the video frequency after the threshold value; the number of times of using the picture after the threshold value; AndAnd integrating the second weight coefficient to respectively correspond to the integrating weights of the flow, the text, the video and the picture.
Preferably, the calculating the second flow according to the second resource usage data to obtain a second flow usage value includes:
the second flow calculation formula is:
In the formula,A value for a second flow usage; the flow consumption after the threshold value is set; The text use times after the threshold value; the video frequency is the video frequency after the threshold value; the number of times of using the picture after the threshold value; AndAnd respectively representing flow consumption ratios of flow, text, video and picture for the flow conversion coefficients.
Preferably, the performing the point gifting according to the first gifting point and the second gifting point based on a preset point gifting condition includes:
Giving a first giving integral when the first flow usage value is equal to a first preset flow threshold value;
and when the first flow using value is larger than a first preset flow threshold value, giving a second giving integral based on a set time interval.
In a second aspect, the present invention provides a mobile phone flow integral gifting system based on big data analysis, comprising:
The data acquisition module is used for acquiring the resource use data of the user;
the first integral calculation module is used for carrying out first integral calculation according to the first resource use data to obtain a first donation integral;
the first flow calculation module is used for carrying out first flow calculation according to the first resource use data to obtain a first flow use value;
The second integral calculation module is used for carrying out second integral calculation to obtain a second donation integral when the first flow using value is larger than a first preset flow threshold value;
the second flow calculation module is used for carrying out second flow calculation according to the second resource use data to obtain a second flow use value;
And the integral donation module is used for stopping the integral donation of the current day when the second flow using value is larger than a second preset flow threshold value, and carrying out integral donation according to the first donation integral and the second donation integral based on preset integral donation conditions.
In a third aspect, the present invention further provides an electronic device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, where the processor implements the mobile phone traffic integral gifting method based on big data analysis according to any one of the above when executing the computer program.
In a fourth aspect, the present invention further provides a computer readable storage medium, where the computer readable storage medium includes a stored computer program, and when the computer program runs, controls a device where the computer readable storage medium is located to execute the mobile phone traffic integral gifting method based on big data analysis according to any one of the above.
Compared with the prior art, the mobile phone flow integral giving method and system based on big data analysis have the following beneficial effects that the mobile phone flow integral giving method and system based on big data analysis are provided. The method comprises the steps of obtaining resource use data of a user, wherein the resource use data comprise first resource use data and second resource use data, conducting first integral calculation according to the first resource use data to obtain first donation integral, conducting first flow calculation according to the first resource use data to obtain a first flow use value, conducting second integral calculation when the first flow use value is larger than a first preset flow threshold value to obtain second donation integral, conducting second flow calculation according to the second resource use data to obtain a second flow use value, stopping the daily integral donation when the second flow use value is larger than a second preset flow threshold value, and conducting integral donation according to the first donation integral and the second donation integral based on preset integral donation conditions.
In the method, reasonable integral giving can be realized by acquiring the resource use data of the user and combining the preset flow threshold and the integral calculation rule. When the flow rate of the user reaches a preset threshold value, corresponding integral calculation is carried out, so that the number of the given integral is dynamically adjusted. The method has the beneficial effects that excessive or too little point gifting can be avoided, and point distribution is ensured to be consistent with the actual use condition of the user, so that the point gifting and obtaining requirements of the user under different use scenes are met.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a first embodiment of the present invention provides a mobile phone traffic score giving method based on big data analysis, comprising the following steps:
s11, acquiring resource use data of a user.
And S12, performing first integral calculation according to the first resource use data to obtain a first donation integral.
S13, according to the first resource use data, performing first flow calculation to obtain a first flow use value.
And S14, when the first flow using value is larger than a first preset flow threshold value, performing second integral calculation to obtain a second donation integral.
And S15, performing second flow rate calculation according to the second resource use data to obtain a second flow rate use value.
And S16, stopping the integral donation of the current day when the second flow using value is larger than a second preset flow threshold, and carrying out integral donation according to the first donation integral and the second donation integral based on preset integral donation conditions.
In order to facilitate an understanding of the invention, some preferred embodiments of the invention will be described further below.
In step S11, resource usage data of the user is acquired. Wherein the resource usage data includes first resource usage data and second resource usage data.
Preferably, the first resource usage data includes pre-threshold traffic consumption, pre-threshold text usage times, pre-threshold video usage times, and pre-threshold picture usage times;
The second resource usage data includes post-threshold traffic consumption, post-threshold text usage times, post-threshold video usage times, and post-threshold picture usage times.
Specifically, the first resource usage data mainly refers to usage data before a user reaches a preset flow threshold, and covers flow consumption, text usage times, video usage times and picture usage times. The data reflect the basic use condition of the user and provide basis for the system to calculate the initial integral. The second resource usage data primarily means that after the user exceeds the flow threshold, the system will continue to monitor such data for controlling the upper bound of the credit. Including traffic consumption after exceeding a threshold and frequency of use of various multimedia content.
Specifically, in the first resource usage data, the pre-threshold traffic consumption is a network traffic usage condition before the user reaches a preset traffic threshold. The system will record the user's flow consumption data in order to calculate the base points. The pre-threshold text usage times are times that the user browses or uses text content before the threshold. For example, the system may record the user's text message or article browsing frequency through an application interface or using a log. The number of pre-threshold video uses is specifically the number of times the user views the video before the threshold. The system may count this data by analyzing the number of video accesses or plays. The pre-threshold number of picture uses records the number of times the user views or sends the picture, which data may be obtained from the media access log or image load record of the application. In the invention, the data are used for calculating the basic integral, mainly reflecting the use condition of the user before the flow threshold is reached, and the system carries out the evaluation of the first-stage integral gifting according to the data.
Specifically, in the second resource usage data, the post-threshold traffic consumption refers to that when the user traffic consumption exceeds a preset threshold, the system will record the traffic usage situation thereafter to control the upper limit of the credit giving. The number of text uses after the threshold is that after the user reaches the threshold, the frequency of use of their text content is continually monitored to determine whether to cease giving additional credits. The video frequency after the threshold value is used for recording the frequency of watching the video frequency after the threshold value by a user, so that the integral gifting is avoided to exceed the preset range in a scene with high data consumption. The number of picture uses after the threshold records how often the user views or sends the picture, and such data helps the system reasonably stop the point gifts after the upper gifting limit is reached.
Optionally, the system can monitor the traffic usage of the user in real time through the device or the network operator background, thereby obtaining the resource usage data. In a specific application scenario, data can be obtained by analyzing a log file generated by an application or equipment, and flow information of each data transmission is recorded, so that flow consumption of a user is calculated. The system may monitor the user's browsing, sending or receiving text operations through the application layer's API. For example, when a user reads an article or sends a message, the application invokes the corresponding interface, whereby the system records the number of operations. The system records each video playing or viewing behavior of the user by analyzing the access log related to video playing. The system will record the user's behavior of viewing, downloading or uploading pictures. For example, each time a user loads picture content, the application will generate a corresponding access record.
In step S12, a first point calculation is performed according to the first resource usage data, so as to obtain a first gifted point.
Preferably, the calculating the first score according to the first resource usage data to obtain a first gifting score includes:
The calculation formula of the first integral calculation is as follows:
In the formula,Integrating the first gift; the flow consumption before the threshold value; The number of times of text use before the threshold value; the video frequency is the video frequency before the threshold value; The number of times of using the picture before the threshold value; and integrating the first weight coefficient to respectively correspond to the integrating weights of the flow, the text, the video and the picture.
Specifically, the formula is specifically configured to participate in the point calculation according to each consumption data in the first resource usage data, so as to generate a first gifting point. Each term uses data multiplied by a corresponding weight coefficient and the portions summed to produce a composite integral value. In this way, the system can quantify the usage of the user before the flow threshold, and provide different integration weights for different resource usage.
Optionally, the system will record the flow consumption value in order to calculate the contribution of the flow consumption in the total number of credits. Since traffic consumption is the core indicator used by the user network, this setting weights the highest. The pre-threshold number of text uses records the user's need for lightweight content (e.g., articles or messages). The system may give a weight below the traffic consumption weight value based on its impact on the traffic. And the video content occupies higher flow, so the integral weight of the video use times is higher than the text use weight, so that the influence of the video use on the integral is reflected more accurately. The picture content occupies a traffic volume between text and video. The system may balance the impact of the user using the picture content by assigning a value between the two weights to the item as a picture traffic consumption weight.
It is worth to say that the weight of each used resource can be calculated by analyzing historical data, carrying out statistical analysis based on a large amount of historical data of the user, and calculating the average consumption condition of each type of resource. For example, the frequency of use and contribution to the flow can be analyzed, the machine learning model is optimized, the relation between the resource use and the integral requirement can be analyzed by using the machine learning model (such as regression analysis, cluster analysis and the like), the weights can be automatically adjusted by training the model, business rules and strategies are set manually according to business strategies of a company or a platform, for example, if the platform wants to encourage users to use video resources more, higher weights can be set for the video manually, A/B tests are used for evaluating the influence of different weight combinations on the user behavior, different weight combinations are tested by a plurality of groups of users, and the optimal weight configuration is gradually found by analyzing the user behavior and feedback, the clustering method in big data analysis is used for grouping the resource use data of the users into different use behavior groups (such as users who prefer videos or prefer texts), and specific weights are set for different groups.
In step S13, a first flow rate calculation is performed according to the first resource usage data, and a first flow rate usage value is obtained.
Preferably, the performing a first flow calculation according to the first resource usage data to obtain a first flow usage value includes:
The calculation formula of the first flow calculation is as follows:
In the formula,A value for a first flow usage; the flow consumption before the threshold value; The number of times of text use before the threshold value; the video frequency is the video frequency before the threshold value; The number of times of using the picture before the threshold value; AndAnd respectively representing flow consumption ratios of flow, text, video and picture for the flow conversion coefficients.
It is worth noting that in the present invention, the traffic conversion coefficient is a parameter used to quantify the impact of different types of network resource usage on the traffic consumption. In network traffic management, users may generate multiple types of data interactions, including text messages, pictures, video, etc., that contribute differently to network traffic. The flow conversion coefficient is used to convert these different types of data usage into a unified flow consumption unit (bit or byte) so that comparison and accumulation can be performed.
Specifically, in the calculation process, a flow conversion coefficient is introduced, and this coefficient is used to represent the flow consumption proportion corresponding to different types of resource usage (such as flow, text, video and picture). By means of these coefficients, different types of usage behavior can be converted into a unified flow usage value. It should be noted that, the determination of the flow conversion coefficient is calculated based on the user resource usage data, and the coefficient is set in advance and needs to be directly invoked. Specifically, the traffic conversion coefficient is used to convert different types of resource usage (such as traffic consumption, text usage times, video usage times, picture usage times) into a uniform traffic usage value. The flow conversion coefficient can be determined by analyzing historical resource usage data of a user by utilizing a big data analysis technology to determine the contribution proportion of different resource usage types (such as flow consumption, text, video and picture usage times) to total flow consumption, verifying and adjusting the weight coefficients through the flow usage condition in actual application to ensure that the weight coefficients can accurately reflect the influence of different resource usage on the flow, dynamically adjusting the flow conversion coefficient according to the change of a network usage mode and a new data analysis result, and keeping the accuracy and the effectiveness of an integral gifting system.
In step S14, when the first flow usage value is greater than a first preset flow threshold, a second integral calculation is performed to obtain a second gifting integral.
Preferably, when the first flow usage value is greater than a first preset flow threshold, performing a second integration calculation to obtain a second gifting integral, including:
The calculation formula of the second integral calculation is as follows:
In the formula,Integrating for a second gift; the flow consumption after the threshold value is set; The text use times after the threshold value; the video frequency is the video frequency after the threshold value; the number of times of using the picture after the threshold value; AndAnd integrating the second weight coefficient to respectively correspond to the integrating weights of the flow, the text, the video and the picture.
In particular, the method comprises the steps of,Representing the points obtained by the user according to the use condition of the resources after a certain condition is reached.Representing the flow consumed by the user after exceeding the first flow threshold. This value refers to the portion of the user's traffic usage that exceeds the preset limit.Indicating the number of text uses by the user after exceeding the text use threshold. Also, if the user's text usage exceeds a preset threshold,That is the number of times this exceeds.AndThe same applies to the same.
It is worth noting that the second point calculation quantifies the user's different types of resource usage into points. The quantification method can effectively reflect the contribution degree of the user on the platform and help the platform manager to better know the user behavior. By setting the scoring weights for different resources, the platform can guide the user to use a particular type of resource. For example, it may be desirable for the user to use the video more than the text, and then the scoring weight of the video may be set higher.
Specifically, the score weight can be determined by a platform incentive strategy, for example, if the platform wants to encourage consumption of video content, the weight of video use can be increased so that a user watching the video obtains more scores, data analysis is performed, the use frequency and the user retention rate of different resources are observed through analysis of the use data of the user, the weight is adjusted according to the data analysis result, for example, if the user retention rate of video use is found to be higher, the score weight of the video can be considered to be increased, the user behavior is balanced, the diversity of the user is considered in weight setting, excessive concentration on one resource is avoided, and balanced use of the user among different types of resources can be promoted through weight setting.
In step S15, a second flow rate calculation is performed according to the second resource usage data, and a second flow rate usage value is obtained.
Preferably, the calculating the second flow according to the second resource usage data to obtain a second flow usage value includes:
the second flow calculation formula is:
In the formula,A value for a second flow usage; the flow consumption after the threshold value is set; The text use times after the threshold value; the video frequency is the video frequency after the threshold value; the number of times of using the picture after the threshold value; AndAnd respectively representing flow consumption ratios of flow, text, video and picture for the flow conversion coefficients.
Specifically, the flow rate conversion coefficient used in calculating the second flow rate usage value is the same as the flow rate conversion coefficient used in calculating the first flow rate usage value. The flow conversion coefficient can be determined by data analysis, calculating the corresponding actual flow consumption of each resource use by analyzing the historical use data of the user, obtaining an average value based on the data as the flow conversion coefficient, experiment and A/B test, observing the change of the user behavior and the actual condition of the flow consumption by setting different flow conversion coefficients in different user groups, selecting the optimal coefficient according to the test result, predicting the relation between the different resource use and the flow consumption by using a statistical model or a machine learning model based on the prediction of the model, thereby determining the proper flow conversion coefficient, considering the resource characteristics, and considering that different resources (such as video, text and pictures) have different flow characteristics, such as that the video consumption flow is larger than the text consumption flow, the picture consumption flow is larger than the picture consumption flow, and taking the difference into consideration when determining the conversion coefficient, and reasonably setting.
In step S16, when the second flow usage value is greater than a second preset flow threshold, the present day of the credit donation is stopped, and the credit donation is performed according to the first and second donation credits based on a preset credit donation condition.
In particular, the main purpose of this step is to control traffic consumption, reduce resource abuse and optimize user behavior. In a specific application scenario, if the upper limit is not set, the user may use a large amount of resources (such as video, pictures, etc.) under the incentive of integration, resulting in too fast consumption of resources or additional cost. By setting the second flow threshold, the system can control daily flow consumption within a reasonable range, avoiding excessive use of resources. Preventing malicious swipes of points, some users may use resources frequently in order to get more points, even by programmatically simulating usage behavior. This threshold can effectively prevent such abusive behavior, ensure fairness and rationality of the credit donation, and reduce the risk of the system suffering from "brushing credits" or "flow abuse". The user quality is improved, the limitation of the set flow threshold value can guide the user to reasonably use the resources, and unnecessary behaviors caused by unreasonable integral excitation are avoided. Thus, the use quality of users can be improved, and more efficient and valuable resource utilization is encouraged. The user experience is optimized, through flow use limitation, the platform can reduce network congestion or service delay caused by massive consumption of resources, and the overall user experience is improved. Limiting the upper limit of daily credit gifts also allows the user experience to be more balanced and controllable.
Preferably, the performing the point gifting according to the first gifting point and the second gifting point based on a preset point gifting condition includes:
Giving a first giving integral when the first flow usage value is equal to a first preset flow threshold value;
and when the first flow using value is larger than a first preset flow threshold value, giving a second giving integral based on a set time interval.
Specifically, this gifting mechanism means that a bonus point can be obtained when the traffic usage of the user reaches a certain criterion (a first preset traffic threshold). This encourages users to use resources to meet this criterion, but not to encourage them to consume too much. The gifting of the first gifting score is relatively simple, and does not involve a time interval based on whether the user's traffic usage meets a threshold. When the user flow exceeds the threshold value, the platform can avoid the rapid consumption of resources caused by one-time point donation through setting the point rewards of the time interval, and simultaneously can also encourage the user to continuously use the resources. Such integration rules apply to scenarios where the platform wishes the user to continue active use after reaching a threshold. It can also help control system load and avoid excitation imbalance due to one-time awarding excessive integration. In general, in the present invention, the credit giving rule includes two phases. And in the first stage, when the user reaches a threshold value, the first donation point is rewarded immediately, so that the user is ensured to reach the basic use standard preset by the platform, and the rewards can be obtained. And a second stage, wherein after the user exceeds the threshold value, the second donation points are continuously rewarded at set time intervals, the user is encouraged to keep active above the basic use standard, and the frequency and the magnitude of the donation points are controlled.
It should be noted that the determination of the set time interval affects the pace of the credit gifts and the user activity, which may be determined by analyzing the user activity time and determining the optimal time interval by analyzing the user activity in different time periods. For example, if the average activity time of the user is 2 hours, then the time interval may be set to 30 minutes to 1 hour to ensure that the credit covers a majority of the user's activity period. Product goals and user experience, if frequent user interaction is desired in a short period of time, the time interval may be shortened, such as rewarding points every 15 or 30 minutes. Conversely, if longer use by the user is desired, a longer time interval, such as 1 hour or more, may be set. Too short a time interval may cause frequent reminders of the points to disturb the user, and too long a time interval may reduce the interest of the user in obtaining the points, thus requiring balancing according to the specific user experience goals of the product. System load and cost control, in high concurrency situations, can extend the time interval to avoid excessive system pressure. For example, when a user accesses a peak period (e.g., 8 to 10 pm), the time interval is extended to relieve the load. Adaptive time intervals, for high active users, the system may shorten the time interval to increase the viscosity, and for low active users, may lengthen the time interval to maintain long-term use.
The working process of the invention is described below by taking a more common scene as an example, and the working process is as follows:
When a user uses a mobile phone in daily life, various activities such as browsing web pages, sending text messages, watching videos, viewing pictures, etc. are performed. The system monitors and records the resource use data of the user in real time through the data acquisition module, wherein the resource use data comprises flow consumption, text use times, video use times and picture use times.
When the user uses the traffic, the system classifies traffic consumption (first resource usage data) before the threshold according to a preset threshold. The system uses a first integral calculation module to calculate a first donation integral of the user according to the first resource use data and a preset integral first weight coefficient. Meanwhile, the first flow calculating module calculates a first flow using value of the user according to the first resource using data and the flow conversion coefficient.
If the user's first flow usage value exceeds a preset first flow threshold, the system will enter a second phase. The system begins recording the traffic consumption (second resource usage data) after the threshold and calculates a second gifting score for the user based on the second resource usage data and the score second weight coefficient using a second score calculation module. Meanwhile, the second flow calculating module calculates a second flow using value of the user according to the second resource using data and the flow conversion coefficient.
If the user's second flow usage value exceeds a second preset flow threshold, the system will cease the bonus points donation on the current day via the bonus points donation module. If the second flow usage value of the user does not exceed the second preset flow threshold, the system performs integral donation according to the first donation integral and the second donation integral of the user based on the preset integral donation condition through the integral donation module.
When the flow threshold is met or exceeded, the user gets a corresponding point prize, which encourages the user to continue to use the service and possibly redeem the prize in the point mall. The system ensures that the integral distribution accords with the actual use condition of the user by reasonably setting the flow conversion coefficient and the integral weight coefficient, and avoids the problem that the integral is given too much or too little.
The invention provides a mobile phone flow rate integration giving method based on big data analysis, which comprises the steps of obtaining resource usage data of a user, wherein the resource usage data comprise first resource usage data and second resource usage data, performing first integration calculation according to the first resource usage data to obtain first giving points, performing first flow rate calculation according to the first resource usage data to obtain first flow rate usage values, performing second integration calculation when the first flow rate usage values are larger than a first preset flow rate threshold value to obtain second giving points, performing second flow rate calculation according to the second resource usage data to obtain second flow rate usage values, stopping giving points on the same day when the second flow rate usage values are larger than a second preset flow rate threshold value, and performing point giving according to the first giving points and the second giving points based on preset giving conditions.
In the method, reasonable integral giving can be realized by acquiring the resource use data of the user and combining the preset flow threshold and the integral calculation rule. When the flow rate of the user reaches a preset threshold value, corresponding integral calculation is carried out, so that the number of the given integral is dynamically adjusted. The method has the beneficial effects that excessive or too little point gifts can be avoided, and point distribution is ensured to be consistent with the actual use condition of the user.
Referring to fig. 2, a second embodiment of the present invention provides a mobile phone traffic score gifting system based on big data analysis, including:
The data acquisition module is used for acquiring the resource use data of the user;
the first integral calculation module is used for carrying out first integral calculation according to the first resource use data to obtain a first donation integral;
the first flow calculation module is used for carrying out first flow calculation according to the first resource use data to obtain a first flow use value;
The second integral calculation module is used for carrying out second integral calculation to obtain a second donation integral when the first flow using value is larger than a first preset flow threshold value;
the second flow calculation module is used for carrying out second flow calculation according to the second resource use data to obtain a second flow use value;
And the integral donation module is used for stopping the integral donation of the current day when the second flow using value is larger than a second preset flow threshold value, and carrying out integral donation according to the first donation integral and the second donation integral based on preset integral donation conditions.
In an alternative embodiment, the first integral calculation module is specifically configured to:
and performing first integral calculation, wherein the calculation formula of the first integral calculation is as follows:
In the formula,Integrating the first gift; the flow consumption before the threshold value; The number of times of text use before the threshold value; the video frequency is the video frequency before the threshold value; The number of times of using the picture before the threshold value; and integrating the first weight coefficient to respectively correspond to the integrating weights of the flow, the text, the video and the picture.
In an alternative embodiment, the first flow calculation module is specifically configured to:
Performing first flow calculation, wherein the calculation formula of the first flow calculation is as follows:
In the formula,A value for a first flow usage; the flow consumption before the threshold value; The number of times of text use before the threshold value; the video frequency is the video frequency before the threshold value; The number of times of using the picture before the threshold value; AndAnd respectively representing flow consumption ratios of flow, text, video and picture for the flow conversion coefficients.
In an alternative embodiment, the second integral calculation module is specifically configured to:
And performing second integral calculation, wherein the calculation formula of the second integral calculation is as follows:
In the formula,Integrating for a second gift; the flow consumption after the threshold value is set; The text use times after the threshold value; the video frequency is the video frequency after the threshold value; the number of times of using the picture after the threshold value; AndAnd integrating the second weight coefficient to respectively correspond to the integrating weights of the flow, the text, the video and the picture.
In an alternative embodiment, the second flow calculation module is specifically configured to:
a second flow rate calculation is performed and, the second flow calculation formula is:
In the formula,A value for a second flow usage; the flow consumption after the threshold value is set; The text use times after the threshold value; the video frequency is the video frequency after the threshold value; the number of times of using the picture after the threshold value; AndAnd respectively representing flow consumption ratios of flow, text, video and picture for the flow conversion coefficients.
In an alternative embodiment, the point gifting module is specifically configured to:
Giving a first giving integral when the first flow usage value is equal to a first preset flow threshold value;
and when the first flow using value is larger than a first preset flow threshold value, giving a second giving integral based on a set time interval.
It should be noted that, the mobile phone flow integral gifting system based on big data analysis provided by the embodiment of the present invention is used for executing all flow steps of the mobile phone flow integral gifting method based on big data analysis in the above embodiment, and the working principles and beneficial effects of the two correspond one to one, so that the description is omitted.
The embodiment of the invention also provides electronic equipment. The electronic device comprises a processor, a memory, and a computer program stored in the memory and executable on the processor, such as a mobile phone traffic credit giving method program based on big data analysis. The processor executes the computer program to implement the steps in the embodiments of the mobile phone traffic integral gifting method based on big data analysis, for example, step S11 shown in fig. 1. Or the processor, when executing the computer program, performs the functions of the modules/units of the device embodiments described above, such as the credit giving module.
The computer program may be divided into one or more modules/units, which are stored in the memory and executed by the processor to accomplish the present invention, for example. The one or more modules/units may be a series of computer program instruction segments capable of performing the specified functions, which instruction segments are used for describing the execution of the computer program in the electronic device.
The electronic equipment can be a desktop computer, a notebook computer, a palm computer, an intelligent tablet and other computing equipment. The electronic device may include, but is not limited to, a processor, a memory. It will be appreciated by those skilled in the art that the above components are merely examples of electronic devices and are not limiting of electronic devices, and may include more or fewer components than those described above, or may combine certain components, or different components, e.g., the electronic devices may also include input-output devices, network access devices, buses, etc.
The Processor may be a central processing unit (Central Processing Unit, CPU), other general purpose Processor, digital signal Processor (DIGITAL SIGNAL Processor, DSP), application SPECIFIC INTEGRATED Circuit (ASIC), off-the-shelf Programmable gate array (Field-Programmable GATE ARRAY, FPGA) or other Programmable logic device, discrete gate or transistor logic device, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like that is a control center of the electronic device, connecting various parts of the overall electronic device using various interfaces and lines.
The memory may be used to store the computer program and/or modules, and the processor may implement various functions of the electronic device by running or executing the computer program and/or modules stored in the memory and invoking data stored in the memory. The memory may mainly include a storage program area which may store an operating system, an application program required for at least one function (such as a sound playing function, an image playing function, etc.), etc., and a storage data area which may store data created according to the use of the cellular phone (such as audio data, a phonebook, etc.), etc. In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, memory, plug-in hard disk, smart memory card (SMART MEDIA CARD, SMC), secure Digital (SD) card, flash memory card (FLASH CARD), at least one disk storage device, flash memory device, or other volatile solid-state storage device.
Wherein the integrated modules/units of the electronic device may be stored in a computer readable storage medium if implemented in the form of software functional units and sold or used as stand alone products. Based on such understanding, the present invention may implement all or part of the flow of the method of the above embodiment, or may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, and when the computer program is executed by a processor, the computer program may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include any entity or device capable of carrying the computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the computer readable medium contains content that can be appropriately scaled according to the requirements of jurisdictions in which such content is subject to legislation and patent practice, such as in certain jurisdictions in which such content is subject to legislation and patent practice, the computer readable medium does not include electrical carrier signals and telecommunication signals.
It should be noted that the above-described apparatus embodiments are merely illustrative, and the units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. In addition, in the drawings of the embodiment of the device provided by the invention, the connection relation between the modules represents that the modules have communication connection, and can be specifically implemented as one or more communication buses or signal lines. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
The foregoing embodiments have been provided for the purpose of illustrating the general principles of the present invention, and are not to be construed as limiting the scope of the invention. It should be noted that any modifications, equivalent substitutions, improvements, etc. made by those skilled in the art without departing from the spirit and principles of the present invention are intended to be included in the scope of the present invention.