CN106815241B

CN106815241B - Information processing method and terminal

Info

Publication number: CN106815241B
Application number: CN201510859739.2A
Authority: CN
Inventors: 傅颖然
Original assignee: Tencent Technology Beijing Co Ltd
Current assignee: Tencent Technology Beijing Co Ltd
Priority date: 2015-11-30
Filing date: 2015-11-30
Publication date: 2020-10-30
Anticipated expiration: 2035-11-30
Also published as: CN106815241A

Abstract

The invention discloses an information processing method and a terminal, wherein the information processing method comprises the following steps: acquiring user information release data, and classifying the user information release data to obtain first information; acquiring a first configuration coefficient, and acquiring second information according to the first configuration coefficient and the first information; the first configuration coefficient is used for representing target weight of user information release in different dimensions; determining a user grading strategy based on the second information, and performing strategy rationality simulation processing according to the determined user grading strategy to obtain third information; and carrying out user grade division according to at least one of the first information, the second information and the third information.

Description

Information processing method and terminal

Technical Field

The present invention relates to the field of communications technologies, and in particular, to an information processing method and a terminal.

Background

In daily application of the internet, in addition to responding to the playing of the information requested by the user, there is a need to issue specific information, such as issuing specific information (e.g., advertisement) before the information requested by the user is played, during the playing of the information requested by the user, or after the playing of the information requested by the user is finished; in order to realize maximum utilization of information distribution resources, the best method is to grade users who distribute information, and then adopt different information distribution strategies for users of different grades.

At present, the user is graded usually by analyzing a large amount of user-related data through manpower, various data of different users are continuously compared, the efficiency is low, the calculation error amount is high, and the grading period is long.

In summary, providing an information processing scheme to efficiently implement user ranking has become an urgent technical problem to be solved.

Disclosure of Invention

In view of this, embodiments of the present invention are intended to provide an information processing method and a terminal, which can efficiently implement user level classification.

The technical scheme of the embodiment of the invention is realized as follows:

the embodiment of the invention provides an information processing method, which comprises the following steps:

acquiring user information release data, and classifying the user information release data to obtain first information;

acquiring a first configuration coefficient, and acquiring second information according to the first configuration coefficient and the first information; the first configuration coefficient is used for representing target weight of user information release in different dimensions;

determining a user grading strategy based on the second information, and performing strategy rationality simulation processing according to the determined user grading strategy to obtain third information;

and carrying out user grade division according to at least one of the first information, the second information and the third information.

In the foregoing solution, the acquiring the user information distribution data includes:

the method comprises the steps of obtaining at least one user information release statement in a first state, and extracting user information release data in the user information release statement.

In the above scheme, the method further comprises:

and when determining that different versions exist in the user information release application table with the same number in the first state, updating the user information release application table to be the latest version.

In the foregoing solution, the first configuration coefficient includes: the method comprises the following steps of (1) weighting a frame coefficient target, a multi-screen coefficient target, a north coefficient target and a yield deviation coefficient target;

the obtaining second information according to the first configuration coefficient and the first information includes:

determining a frame coefficient, a multi-screen coefficient, a north coefficient and a profit deviation coefficient of user information release, and obtaining second information according to the frame coefficient, the multi-screen coefficient, the north coefficient, the profit deviation coefficient and corresponding target weights; the second information is used for representing a profit coefficient of user information distribution.

In the foregoing solution, the determining a user ranking policy based on the second information includes:

sorting the information issuing income coefficients of different users based on the second information, and determining the grade of the user for carrying out simulation operation according to the obtained income coefficient sequence and a preset first condition;

or acquiring a user grade division reference factor, determining guide coefficients according to the reference factor and the second information, sequencing the guide coefficients of different users, and determining the grade of the user for carrying out simulation operation according to the obtained guide coefficient sequence and a preset second condition.

In the foregoing solution, the performing policy rationality simulation processing according to the determined user rating policy to obtain third information includes:

and obtaining a second configuration coefficient for carrying out strategy rationality simulation, and calculating Key Performance Indicators (KPIs) of the user according to the second configuration coefficient, the determined user grade division strategy and the user information release data to obtain KPI expected values corresponding to the current grade of the user.

An embodiment of the present invention further provides a terminal, where the terminal includes: the system comprises a first acquisition module, a second acquisition module, a processing module and a grading module; wherein the content of the first and second substances,

the first obtaining module is used for obtaining user information release data and classifying the user information release data to obtain first information;

the second obtaining module is used for obtaining a first configuration coefficient and obtaining second information according to the first configuration coefficient and the first information; the first configuration coefficient is used for representing target weight of user information release in different dimensions;

the processing module is used for determining a user grade division strategy based on the second information and carrying out strategy rationality simulation processing according to the determined user grade division strategy to obtain third information;

and the grade division module is used for carrying out user grade division according to at least one of the first information, the second information and the third information.

In the above scheme, the first obtaining module is specifically configured to obtain at least one user information release statement in a first state, and extract user information release data in the user information release statement.

In the foregoing solution, the terminal further includes an updating module, configured to update the user information distribution application table to be a latest version when it is determined that different versions exist in the user information distribution application table with the same number currently in the first state.

the second obtaining module is specifically configured to determine a frame coefficient, a multi-screen coefficient, a north coefficient and a profit deviation coefficient of user information release, and obtain second information according to the frame coefficient, the multi-screen coefficient, the north coefficient, the profit deviation coefficient and corresponding target weights; the second information is used for representing a profit coefficient of user information distribution.

In the above scheme, the processing module is specifically configured to sort the information distribution revenue coefficients of different users based on the second information, and determine the level of the user for performing the simulation operation according to the obtained revenue coefficient sequence and a preset first condition;

In the above scheme, the processing module is specifically configured to obtain a second configuration coefficient for performing policy rationality simulation, and perform calculation on a user key performance indicator KPI according to the second configuration coefficient, the determined user rating division policy, and user information release data to obtain a KPI expected value corresponding to the current rating of the user.

By adopting the embodiment of the invention, user information release data are obtained, and the user information release data are classified to obtain first information; acquiring a first configuration coefficient, and acquiring second information according to the first configuration coefficient and the first information; the first configuration coefficient is used for representing target weight of user information release in different dimensions; determining a user grading strategy based on the second information, and performing strategy rationality simulation processing according to the determined user grading strategy to obtain third information; and carrying out user grade division according to at least one of the first information, the second information and the third information. Therefore, massive user release data can be automatically and quickly processed, at least one type of information for user grading is obtained, grading is further performed on the user, the user grading efficiency is greatly improved, and human resources are saved.

Drawings

FIG. 1 is a diagram of hardware entities performing information interaction in an embodiment of the present invention;

FIG. 2 is a schematic flow chart of an information processing method according to an embodiment of the present invention;

FIG. 3 is a flowchart illustrating a second information processing method according to an embodiment of the present invention;

FIG. 4 is a flow chart of a third information processing method according to an embodiment of the present invention;

FIG. 5 is a flowchart illustrating a fourth information processing method according to an embodiment of the present invention;

FIG. 6 is a flow chart of a fifth information processing method according to an embodiment of the present invention;

fig. 7 is a schematic structural diagram of a terminal according to an embodiment of the present invention;

fig. 8 is a schematic structural diagram of a second terminal according to an embodiment of the present invention.

Detailed Description

The following describes the embodiments in further detail with reference to the accompanying drawings.

Fig. 1 is a schematic diagram of hardware entities of each party performing information interaction in the embodiment of the present invention, in fig. 1, three types of hardware entities, that is, a server 11, a terminal 21, and terminals 31 to 33, are included, the terminal 21 may be a mobile phone terminal, and the terminals 31 to 33 may include types of a desktop, a PC, an all-in-one machine, and the like. The terminals 21 and 31-33 can exchange information with the server 11 through the network.

Based on the above architecture diagram of each hardware entity in fig. 1, the embodiment of the present invention mainly includes: the method comprises the steps that a terminal (such as a terminal 21 and terminals 31-33) obtains user information release data through communication with a server (such as a server 11), and classification processing is carried out on the user information release data to obtain first information; acquiring a first configuration coefficient, and acquiring second information according to the first configuration coefficient and the first information; the first configuration coefficient is used for representing target weight of user information release in different dimensions; determining a user grading strategy based on the second information, and performing strategy rationality simulation processing according to the determined user grading strategy to obtain third information; and carrying out user grade division according to at least one of the first information, the second information and the third information.

The terminal described herein may be any of the terminals 21, 31-33 described above in fig. 1 and is not limited to the description herein; the server may be an electronic device formed by a cluster system, and integrated into one or a plurality of unit functions to implement the unit functions, and both the client and the server at least include a database for storing data and a processor for data processing, or include a storage medium arranged in the server or a storage medium arranged independently.

As for the processor for data Processing, when executing Processing, the processor can be implemented by a microprocessor, a Central Processing Unit (CPU), a Digital Signal Processor (DSP), or a Programmable logic Array (FPGA); for the storage medium, the storage medium contains operation instructions, which may be computer executable codes, and the operation instructions implement the steps in the flow of the information processing method according to the above-described embodiment of the present invention.

Fig. 8 shows an example of the above-described terminal as the hardware entity S81. The terminal comprises a processor 81, a storage medium 82 and at least one external communication interface 83; the processor 81, the storage medium 82 and the external communication interface 83 are all connected by a bus 84.

Based on the structure of fig. 1 described above, the following embodiments of the present invention are proposed.

Method embodiment one

Fig. 2 is a schematic flow chart of an information processing method according to an embodiment of the present invention, and as shown in fig. 2, the information processing method according to the embodiment of the present invention includes:

step 201: the method comprises the steps of obtaining user information release data, and carrying out classification processing on the user information release data to obtain first information.

Based on the embodiment of the present invention, in practical application, the acquiring of the user information distribution data includes:

acquiring at least one user information release statement in a first state, and extracting user information release data in the user information release statement;

here, the user information issue statement table may be understood as an information table that a user applies for becoming a high-quality user, such as a platinum user; the user information issuing reporting table comprises: basic information of a user and an information issuing strategy of the user; the user basic information includes a user name, a user abbreviation, and the like, for example: the user name is xx food international trade limited;

in an embodiment, the information issuing policy of the user may include at least one of an information issuing annual frame amount, an information issuing targeted unit price, an information issuing targeted platform, information issuing targeted content, information issuing amount ratios of different platforms, information issuing amount ratios of different regions, and the like;

the information release year frame amount refers to the amount of money for information release released in each quarter, and the total amount of the year frame is the amount of money for information release released in one year; the information release directional amount refers to the amount of money for information release released in different areas (such as Beijing, Tianjin and the like); the information publishing orientation platform comprises: the system comprises a mobile terminal, an ipad terminal, an iphone terminal, an IOS terminal, an android terminal, a PC terminal, a multi-screen joint casting and the like; the information distribution targeted content can be movies, art, TV shows, entertainment and the like; the region may be a city.

Based on the embodiment of the invention, in practical application, each user information release statement form has a unique number for users to search, modify and the like; the user information release statement table may include a plurality of states: draft status, commit status, etc.; the user information release reporting form in the draft state can modify all information at will, if the user information release reporting form in the submission state is modified, a new version of the user information release reporting form can be generated, and meanwhile, an old version of the application form can be retained, namely, the user information release reporting form with the same number can have a plurality of versions;

correspondingly, the method further comprises the following steps:

when different versions of a user information release application table with the same number in a first state are determined, updating the user information release application table to be the latest version; here, the first state may be a commit state.

Based on the embodiment of the present invention, in practical application, the first information includes: the information issuing year frame amount, the information issuing oriented content, the information issuing amount of a preset platform and the like; the first information can be used as reference information for user grading;

the information release amount of the preset platform is obtained by classifying the user information release data, and the method comprises the following steps:

determining the information distribution amount of each platform in a user information distribution statement according to the information distribution directional amount, the information distribution directional platform, the information distribution amount ratios of different platforms and the information distribution amount ratios of different regions in the user information distribution data, and then classifying the information distribution amount of each platform to obtain the information distribution amount of a preset platform;

here, the preset platform includes: the system comprises a PC end, a mobile end, an iphone end, an ipad end, an aphone end and an apad end;

for each platform:

platform information distribution amount is platform release amount/sigma (area price is area information distribution amount ratio);

after the information release amount of each platform in the user information release statement is obtained by applying the above formula, classifying the information release amount of each platform to obtain the information release amount of a preset platform:

the PC end put volume is the PC end put volume (original) + multi-screen joint casting and multi-screen joint casting PC exposure ratio;

the input amount of the mobile terminal is equal to the input amount of the mobile terminal (original), multi-screen joint projection and multi-screen joint projection mobile exposure ratio;

the input amount of the iPad end is equal to the input amount of the iPad end (original) + the input amount of the mobile end ×, the input amount of the iPad end + the input amount of the pad end (original) × (the ratio of iPad exposure/(the ratio of iPad exposure + the ratio of iPad exposure)) + the input amount of the IOS end (original) ((the ratio of iPad exposure/(the ratio of iPad exposure + the ratio of iPhone exposure)));

the method comprises the following steps that (1) the amount of an aPad end is equal to the amount of an aPad end (original) + the amount of a moving end (aPad exposure proportion + aPad exposure proportion)) + the amount of an android end (original) (aPad exposure proportion/(aPad exposure proportion + aPad exposure proportion));

the method for calculating the input amount of the iphone end and the input amount of the aphone end is similar; wherein a plurality of exposure ratios referred to in the above formula are set in advance, and the respective exposure ratios are 100% in sum.

Based on the embodiment of the invention, in practical application, the method further comprises the following steps: recording the first information to a user grade division strategy table;

correspondingly, the user information release data in the user information release statement table can be obtained by associating the user level division policy table with at least one user information release statement table in the first state; when the user information issuing application table is in a submitting state, namely after being submitted by a user, the user information issuing application table enters a public pool so as to be associated with the user grading strategy table;

correspondingly, before the obtaining of the user information release data, the method further includes: creating the user grading strategy table; when the user level division strategy table is established, the user information release reporting table in the submission state is associated to the user level division strategy table, and when the user information release reporting table in the submission state has more than one version, the associated user information release reporting table is updated to be the latest version;

here, the user ranking policy table is created and set with a validity period and a validity period, that is, when the user ranking policy table starts to be valid and when the user ranking policy table starts to be invalid, and the validity period usually ends to the end of the year, that is, 12 months and 31 days of the year.

In one embodiment, the user ranking policy table has more than one state, including: draft state, alternative state, waiting for examination and approval and the like; when the user level division policy table is in a draft state, if the associated user information release statement table is updated, the associated user information release statement table can be updated to be the latest version, however, when the user level division policy table is in a non-draft state (an alternative state/to-be-examined and approved, etc.), the updating of any associated user information release statement table does not affect the user level division policy table.

Based on the embodiment of the invention, in practical application, the user grading policy table has a function of a sand table, so that modification on information release requirements and bids of users is facilitated, the modification is stored, and the negotiation by two parties who propose a declaration and a customization policy is facilitated.

Step 202: and acquiring a first configuration coefficient, and acquiring second information according to the first configuration coefficient and the first information.

Here, the first configuration coefficient is preset and is used for representing target weights of user information release in different dimensions; the method comprises the following steps: a frame coefficient index weight N1, a profit deviation coefficient index weight N2, a multi-screen coefficient index weight N3, and a north coefficient index weight N4;

determining a frame coefficient, a multi-screen coefficient, a north coefficient and a profit deviation coefficient of user information release, and obtaining second information according to the frame coefficient, the multi-screen coefficient, the north coefficient, the profit deviation coefficient and corresponding target weights; the second information is used for representing a profit coefficient of user information release;

the yield coefficient issued by the user information is frame coefficient target weight N1 frame coefficient + multi-screen coefficient target weight N3 multi-screen coefficient + north coefficient target weight N4 north coefficient + yield deviation coefficient target weight N2 yield deviation coefficient;

wherein, the frame coefficient is min (1.2, max (-0.8, A1/B1-1)); wherein, A1 is the annual box amount of the user, B1 is the average value of the annual box amounts of all the users; here, the all users are users in all reporting tables.

The yield deviation factor is min (2, max (-2,1-a 2/B2)); wherein, A2 is the profit deviation ratio of the user, B2 is the average value of the profit deviation ratios of all users;

the income deviation proportion of the user is the income deviation amount/the information issuing total amount;

the income deviation amount is sigma-divided city (user city price-internal control price) and user city information distribution amount;

user city information distribution amount (total amount of information distribution/∑ city) (user city price/user city information distribution amount ratio)

Internal control price (platform standard price) (1+ internal control price ratio);

here, the user city price is an information distribution targeting unit price of the user; the standard price of the platform and the internal control pricing proportion are preset, such as: the PC end standard price of the core city is 30 yuan/PCM, the mobile end standard price of the key city is 14 yuan/CPM, and when the orientation condition is frequency, the internal control pricing proportion of the frequency of 1 is 30%; each time the information is released, the exposure (imp) is displayed, and one thousand exposures are a CPM.

The multi-screen coefficient is A3/B3-1; wherein, A3 is the (mobile + multi-screen) amount proportion of the user, and B3 is the average value of the (mobile + multi-screen) amount proportions of all users;

wherein, the proportion (mobile + multi-screen) is 1-PC end amount/total amount of all platforms.

North coefficient ═ min (1, max (-1, 1-a 4/B4)); wherein, A4 is the north stock demand of the user, B4 is the average value of the north stock demand of all users; in Beijing and Shanghai, Beijing.

Based on the embodiment of the present invention, in practical application, the revenue coefficient issued by the user information may be used as reference information for ranking the user, such as: the income coefficients of all users are sorted in the descending order, the first 15 sorted users can be divided into platinum users according to the requirement of the number of platinum users, the next 30 users are alternative platinum users, and the rest are common users.

Based on the embodiment of the invention, in practical application, the method further comprises: and recording the second information to a user grading strategy table.

Step 203: and determining a user grade division strategy based on the second information, and performing strategy reasonableness simulation processing according to the determined user grade division strategy to obtain third information.

Based on the embodiment of the present invention, in practical application, the determining the user ranking policy based on the second information includes:

or acquiring a user grade division reference factor, determining guide coefficients according to the reference factor and the second information, sequencing the guide coefficients of different users, and determining the grade of the user for carrying out simulation operation according to the obtained guide coefficient sequence and a preset second condition;

here, the preset first condition may be a profit coefficient threshold or a number of users in a class;

the income coefficient threshold value corresponds to the grade of a user performing simulation operation and can be set according to actual requirements; such as: the income coefficient threshold value corresponding to the first-level user for carrying out simulation operation is 0.8, and the income coefficient threshold value corresponding to the second-level user for carrying out simulation operation is 0.6; thus, it can be determined that users with profit coefficient greater than or equal to 0.8 are primary users (platinum users), users with profit coefficient greater than or equal to 0.6 and less than 0.8 are secondary users (alternative platinum users), and the rest are common users;

the number of the level users corresponds to the level of the user performing the simulation operation, and can be set according to actual needs; such as: the number of the first-level users for carrying out simulation operation is 15, the number of the second-level users is 30, the first 15 users for setting income coefficient sequencing are the first-level users, the second 30 users are the second-level users, and the rest are common users;

in practical application, the user level division reference factor may be a reference factor for representing the importance degree of the user, which is set according to historical data issued by user information; for example: if the information release amount of a certain user is first in the last three years, the user grade division reference factor of the certain user can be set to be higher, if the user grade division reference factor is more than 1.5 and less than 2, and if the certain user is a common user in the last three years, the user grade division reference factor of the certain user can be set to be lower, if the user grade division reference factor is more than 0.6 and less than 0.8;

the guidance coefficient is a revenue coefficient issued by the user information and is a user grade division reference factor;

the second condition may be a guide coefficient threshold or a number of ranked users;

the guidance coefficient threshold value corresponds to the grade of a user performing simulation operation and can be set according to actual requirements; such as: the guidance coefficient threshold value corresponding to the first-level user for carrying out the simulation operation is 0.8, and the guidance coefficient threshold value corresponding to the second-level user for carrying out the simulation operation is 0.6; thus, the users with the guidance coefficient more than or equal to 0.8 can be determined as the primary users, the users with the guidance coefficient more than or equal to 0.6 and less than 0.8 can be determined as the secondary users, and the rest are the common users;

in one embodiment, the guidance coefficient may be used as reference information for user rating;

based on the embodiment of the invention, in practical application, the method further comprises: and recording the guide coefficient to a user grading strategy table.

Based on the embodiment of the present invention, in practical applications, the performing policy rationality simulation processing according to the determined user rating classification policy to obtain third information includes:

acquiring a second configuration coefficient for performing strategy rationality simulation, and calculating Key Performance Indicators (KPIs) of the user according to the second configuration coefficient, the determined user grade division strategy and user information release data to obtain KPI expected values corresponding to the current grade of the user;

here, the second configuration coefficient is preset, and includes: annual income KPI, quarterly income KPI, inventory KPI, selling rate upper limit, alternative platinum quota proportion, etc.;

the KPI comprises: the north resource of the PC end, the north resource of the mobile end and the resource of the ipad end;

the method for carrying out strategy rationality simulation processing on the north resource of the PC terminal, the north resource of the mobile terminal and the ipad terminal according to the determined user grade division strategy comprises the following steps:

respectively carrying out analog calculation according to the determined user grading strategies to obtain the total income, the total inventory, the platinum user income, the platinum user inventory, the alternative platinum user income, the alternative platinum user inventory, the common user income and the common user inventory of the north resource of the PC terminal, the north resource of the mobile terminal and the resource of the ipad terminal;

total revenue-annual revenue KPI- Σ (single quarterly out-of-policy revenue); wherein the content of the first and second substances,

the single quarter policy-specific revenue min { quarter revenue KPI, quarter executed revenue }; wherein the content of the first and second substances,

the executed revenue for the quarter: since the effective date of the user ranking policy table is not necessarily 01-01, assuming that the effective date is 04-15, the executed revenue of the first quarter is the revenue of 01-01 to 03-31, and the executed revenue of the second quarter is the revenue of 04-01 to 04-14; wherein the content of the first and second substances,

daily execution revenue: assuming today is 01-15, the exact execution revenue per day of 01-01 to 01-14 can be obtained, while the execution revenue per day of 01-15 to 04-14 is the average of the previous execution revenue;

total inventory: equal to the stock KPI, estimating the stock during policy execution;

total platinum user revenue ═ Σ (single platinum user revenue); wherein the content of the first and second substances,

the income of the single platinum user is the annual release amount-sigma of the application form issued by the platinum user information (the amount outside the application form in a single quarter); wherein the content of the first and second substances,

the annual sum of money put in the information issuing application form is the sum of money put in the user information issuing application form for information issuing in one year;

the sum outside the application form of the single quarter is max (the release sum of the single quarter in the application form and the executed income of the user in the quarter);

total platinum user stock ═ Σ (single platinum user stock); wherein the content of the first and second substances,

the single platinum user stock is the single platinum user income/sigma city (user city price is the ratio of user city delivery demand);

the platinum user information issuing price is equal to platinum user income/platinum user stock;

total income ═ Σ of alternative platinum users (single alternative platinum user income); wherein the content of the first and second substances,

the income of the single alternative platinum user is the annual sum-sigma (sum outside the application form in a single quarter) of the annual sum of the application form issued by the information of the alternative platinum user; wherein the content of the first and second substances,

the sum outside the application form of the single quarter is max (the sum of the release of the single quarter in the application form is proportional to the alternative platinum quota, and the income of the user executed in the quarter);

total stock of alternative platinum users ═ Σ (single alternative platinum user stock); wherein the content of the first and second substances,

the single alternative platinum user stock is the single alternative platinum user income/sigma city (user city price is the ratio of the user city throwing demand amount);

the alternative platinum user information issuing price is alternative platinum user income/alternative platinum user stock;

the total income of the common users is the total income-the total income of the platinum users-the total income of the alternative platinum users;

the general user total stock is the total stock with the selling rate upper limit, the platinum user total stock and the alternative platinum user total stock;

the general user information distribution price is general user income/general user stock.

In practical application, the total income, total stock, platinum user income, platinum user stock, alternative platinum user income, alternative platinum user stock, common user income and common user stock of the north-bound resources of the PC terminal, the north-bound resources of the mobile terminal and the resources of the ipad terminal can be used as a reference for user grading.

Step 204: and carrying out user grade division according to at least one of the first information, the second information and the third information.

Here, the user rating may be performed only according to the first information, such as the total amount of the user information distribution year frame, or may be performed only according to the second information, that is, the income coefficient of the user, or may be performed only according to the third information, such as the total income of the north resource of the PC terminal, the total stock, the platinum user income, the platinum user stock, the alternative platinum user income, the alternative platinum user stock, the general user income, and the simulation calculation result of the general user stock; user ranking may also be performed in combination with at least one of the first information, the second information, and the third information, such as user ranking based on a sum of the result of the first information ranking multiplied by a first factor, such as 40%, and the result of the second information ranking multiplied by a second factor, such as 60%.

Method embodiment two

Fig. 3 is a schematic flow chart of an information processing method according to an embodiment of the present invention, and as shown in fig. 3, the information processing method according to the embodiment of the present invention includes:

step 301: the method comprises the steps of obtaining user information release data, and carrying out classification processing on the user information release data to obtain first information.

Based on the embodiment of the invention, in practical application, the user information publishing data can be user advertisement related data;

the acquiring of the user information release data includes:

in an embodiment, the information distribution policy of the user may include at least one of an information distribution annual amount, an information distribution targeted unit price, an information distribution targeted platform, information distribution targeted content, an information distribution amount ratio of different platforms, an information distribution amount ratio of different regions, and the like.

correspondingly, the method further comprises the following steps:

for each platform:

Step 302: and acquiring a first configuration coefficient, and acquiring second information according to the first configuration coefficient and the first information.

Step 303: and carrying out user grade division according to the second information.

Based on the embodiment of the present invention, in practical application, the performing user rating according to the second information includes:

sorting the users based on the second information, and grading the users according to a sorting result and a preset first condition; wherein the first condition is a revenue coefficient threshold or a number of users in a class;

the income coefficient threshold comprises at least one and corresponds to the user grade respectively; such as: the income coefficient threshold corresponding to the first-level user is 0.8, namely the user with the income coefficient reaching 0.8 is the first-level user;

the number of users in the levels is the number of users corresponding to each level, such as 10 primary users, 15 secondary users, and the like.

For example: and sequencing the profit coefficients issued by each user information according to the descending order, and determining the users with the profit coefficients reaching 0.8 as primary users, the users with the profit coefficients reaching 0.6 as secondary users and the rest as common users according to the sequencing result and the profit coefficient threshold.

Method embodiment three

Fig. 4 is a schematic flow chart of an information processing method according to an embodiment of the present invention, and as shown in fig. 4, the information processing method according to the embodiment of the present invention includes:

step 401: the method comprises the steps of obtaining user information release data, and carrying out classification processing on the user information release data to obtain first information.

the acquiring of the user information release data includes:

correspondingly, the method further comprises the following steps:

for each platform:

Step 402: and acquiring a first configuration coefficient, and acquiring second information according to the first configuration coefficient and the first information.

Step 403: and acquiring a user grade division reference factor, and determining a guidance coefficient according to the reference factor and the second information.

Here, the user ranking reference factor may be a reference factor for representing the importance of the user, which is set according to the historical data of user information distribution; for example: if the information release amount of a certain user is first in the last three years, the user grade division reference factor of the certain user can be set to be higher, if the user grade division reference factor is more than 1.5 and less than 2, and if the certain user is a common user in the last three years, the user grade division reference factor of the certain user can be set to be lower, if the user grade division reference factor is more than 0.6 and less than 0.8;

and the guiding coefficient is a revenue coefficient issued by the user information and is a user grade division reference factor.

Step 404: and carrying out user grading based on the guide coefficient.

Based on the embodiment of the present invention, in practical application, the user ranking based on the guidance coefficient includes:

sorting the users based on the guide coefficients, and grading the users according to a sorting result and a preset second condition;

the preset second condition is a guidance coefficient threshold or a level user number;

the guidance coefficient threshold comprises at least one, and the guidance coefficient threshold corresponds to user grades respectively; such as: the guidance coefficient threshold corresponding to the first-level user is 0.8, namely the user with the guidance coefficient reaching 0.8 is the first-level user;

for example: and sequencing the guidance coefficients issued by each user information according to the descending order, determining the user with the guidance coefficient reaching 0.8 as a primary user, determining the user with the guidance coefficient reaching 0.6 as a secondary user and determining the rest as common users according to the sequencing result and the guidance coefficient threshold.

Method example four

Fig. 5 is a schematic flow chart of an information processing method according to an embodiment of the present invention, and as shown in fig. 5, the information processing method according to the embodiment of the present invention includes:

step 501: the method comprises the steps of obtaining user information release data, and carrying out classification processing on the user information release data to obtain first information.

Based on the embodiment of the invention, in practical application, each user information release statement form has a unique number for users to search, modify and the like; the user information release statement comprises a plurality of states: draft status, commit status, etc.; the user information release reporting form in the draft state can modify all information at will, if the user information release reporting form in the submission state is modified, a new version of the user information release reporting form can be generated, and meanwhile, an old version of the application form can be retained, namely, the user information release reporting form with the same number can have a plurality of versions;

correspondingly, the method further comprises the following steps:

for each platform:

Step 502: and acquiring a first configuration coefficient, and acquiring second information according to the first configuration coefficient and the first information.

Step 503: and determining a user grade division strategy based on the second information, and performing strategy reasonableness simulation processing according to the determined user grade division strategy to obtain third information.

the number of the level users corresponds to the level of the user performing the simulation operation, and can be set according to actual needs; such as: the number of the primary users performing the simulation operation is 15, the number of the secondary users is 30, the first 15 users setting the income coefficient sorting are the primary users, the second 30 users are the secondary users, and the rest are the common users.

Step 504: and carrying out user grade division according to the third information.

Here, since the third information includes various KPIs corresponding to the north-up resource of the PC, the north-up resource of the mobile terminal, and the ipad resource, at least one KPI corresponding to at least one of the north-up resource of the PC, the north-up resource of the mobile terminal, and the ipad resource may be selected when the user is classified according to the third information; for example: selecting the total income corresponding to the north resource of the PC terminal, namely carrying out user grade division according to the total income corresponding to the north resource of the PC terminal corresponding to each user obtained by the strategy rationality simulation processing, and specifically setting a corresponding total income grade threshold value, i.e., the total income corresponding to each user level, for example, the total income threshold corresponding to the first-level user is W ten thousand yuan, it is determined that the division result of the primary users whose total income reaches W ten thousand yuan after the simulation process is performed is reasonable, the user is still a primary user, the division result of the primary user with the total income not reaching W ten thousand yuan after the simulation processing is obviously unreasonable, the user is set as a secondary user, and correspondingly, if the division result of the secondary user with the simulation processing is unreasonable, namely the expected KPI value is not reached, the secondary user is set as a common user.

Method example five

Fig. 6 is a schematic flow chart of an information processing method according to an embodiment of the present invention, and as shown in fig. 6, the information processing method according to the embodiment of the present invention includes:

step 600: a user ranking policy table is created.

Here, the user ranking policy table is used for associating the user information release statement table submitted to the public pool, and recording and displaying user information release related data and user ranking related data; the user information issuing statement table can be understood as an information table of a user who applies for becoming a high-quality user, such as a platinum user; the user information release statement is shown as the following table;

field(s)	Remarks for note
		Statement form ID	xxxx
Name of statement	XXX (Only)
		Statement state	Draft (draft)
Number of statement form	S20140112001 (unique)
		Statement form version	V1
Basic information of user	User nameUser industry information, etc
		Others	。。。

Watch 1

The user level division policy table comprises a name, a number, an ID, a version number and a state, and is also provided with a validity period and a validity period when being created, namely when the user level division policy table starts to take effect and when the user level division policy table starts to fail, wherein the normal validity period is up to the end of the year, namely 12 months and 31 days of the year; the user rating policy table is shown as the following table:

field(s)

Remarks for note

Policy Table ID	xxxx
		Policy table name	XXX (Only)
Policy Table numbering	Z20150112001 (unique)
		Policy table states	Alternative state
Policy table version	ZF2015001
		Policy table effective date	2015-03-01 to 2015-12-31
Frame factor	Weight (%)
		Coefficient of profit deviation	Weight (%)
Coefficient of multi-screen	Weight (%)
		Coefficient of north	Weight (%)
PC end exposure ratio	Weight (%)
		Exposure duty ratio of mobile terminal	Weight (%)
Others	。。。

Watch two

Based on the embodiment of the invention, in practical application, the user grade division policy table also has a sand table function, so that modification on information release requirements and bids of users is facilitated, the modification is stored, and the negotiation by two parties who propose a declaration and a customization policy is facilitated; the sand table function of the user ranking policy table described herein may be implemented by associating a sand table policy table as shown below:

watch III

Step 601: and acquiring user information release data, classifying the user information release data to obtain first information, and recording the first information to the user level division policy table.

Here, the acquiring the user information distribution data includes:

associating the user level division policy table and at least one user information release statement table in a first state, and extracting user information release data in the user information release statement table;

the user information issuing reporting table comprises: basic information of a user and an information issuing strategy of the user; the user basic information includes a user name, a user abbreviation, and the like, for example: the user name is xx food international trade limited;

in an embodiment, the information issuing policy of the user may include at least one of an information issuing annual frame amount, an information issuing targeted unit price, an information issuing targeted platform, information issuing targeted content, information issuing amount ratios of different platforms, information issuing amount ratios of different regions, and the like; the information release strategy of the user can be related to the user information release statement table in the form of a table, and the information release statement table is shown in the following table;

watch four

correspondingly, the method further comprises the following steps:

wherein, here, the preset platform includes: the system comprises a PC end, a mobile end, an iphone end, an ipad end, an aphone end and an apad end;

for each platform:

In an embodiment, when the user information distribution application table is in a submission state, that is, after being submitted by a user, the user information distribution application table enters a public pool so as to be associated with the user ranking policy table.

Step 602: and acquiring a first configuration coefficient, acquiring second information according to the first configuration coefficient and the first information, and recording the second information to the user grade division policy table.

Step 603: acquiring a user grade division reference factor, determining guide coefficients according to the reference factor and the second information, sequencing the guide coefficients of different users, and determining the grade of the user for carrying out simulation operation according to the obtained guide coefficient sequence and a preset second condition.

the preset second condition is a guide coefficient threshold value or a grade user number;

Step 604: and performing strategy rationality simulation processing according to the determined grade of the user to obtain third information, and recording the third information to the user grade division strategy table.

Based on the embodiment of the invention, in practical application, the steps specifically include:

acquiring a second configuration coefficient for performing strategy rationality simulation, and performing KPI calculation according to the second configuration coefficient, the determined user level and user information release data to obtain a KPI expected value corresponding to the current user level;

here, the second configuration coefficient is preset, and includes: annual income KPI, quarterly income KPI, inventory KPI, selling rate upper limit, alternative platinum quota proportion, etc.; the second configuration coefficient for performing the policy rationality simulation may be represented by a policy table KPI sub-table:

watch five

Step 605: and carrying out user grade division according to the first information, the second information and the third information in the user grade division policy table.

In one embodiment, the method specifically includes:

ranking the users according to the first information, the second information and the third information respectively, weighting the ranking of the users according to the weighting coefficients of the first information, the second information and the third information respectively to obtain final user ranking, and finally performing user ranking according to the number of preset ranking users;

for example: the ranking of users a1, a2, a3 and a4 … obtained according to the total amount of the user information release year boxes is 1, 2, 3 and 4 … respectively, the ranking of users a1, a2, a3 and a4 … obtained according to the income coefficients of the users is 2, 3, 1 and 4 … respectively, the ranking of users a1, a2, a3 and a4 … obtained according to the total income of resources in the north of the PC end of the users is 3, 2, 4 and 1 … respectively, and then weighting processing is carried out: (1, 2, 3, 4 …) × M1+ (2, 3, 1, 4 …) × M2+ (2, 3, 1, 4 …) × M3 obtains ranking values possibly corresponding to users a1, a2, a3, a4 … and possibly corresponding to 1.7, 1.3, 4.3, 3.2 …, namely corresponding user ranks a2, a1, a4, a3 …, and finally carries out user rank division according to the preset number of rank users, wherein if the number of primary users is 10 and the number of secondary users is 15, the first 10 ranked users such as a2, a1, a4, a3 are primary users, the second 15 ranked users are secondary users, and the rest users are common users; wherein, the M1, the M2 and the M3 are weighting coefficients corresponding to the first information, the second information and the third information, respectively; the number of the users in the grade can be set according to actual needs.

Terminal embodiment

Fig. 7 is a schematic structural diagram of the terminal according to the present invention; as shown in fig. 7, the composition structure of the terminal of the present invention includes: a first acquisition module 71, a second acquisition module 72, a processing module 73 and a grading module 74; wherein the content of the first and second substances,

the first obtaining module 71 is configured to obtain user information distribution data, and perform classification processing on the user information distribution data to obtain first information;

the second obtaining module 72 is configured to obtain a first configuration coefficient, and obtain second information according to the first configuration coefficient and the first information; the first configuration coefficient is used for representing target weight of user information release in different dimensions;

the processing module 73 is configured to determine a user rating policy based on the second information, and perform policy rationality simulation processing according to the determined user rating policy to obtain third information;

the ranking module 74 is configured to perform user ranking according to at least one of the first information, the second information, and the third information.

Based on the embodiment of the present invention, in an actual application process, the first obtaining module 71 is specifically configured to obtain at least one user information release statement in a first state, and extract user information release data in the user information release statement;

Based on the embodiment of the present invention, in the practical application process, the terminal further includes an updating module 45, configured to update the user information distribution application table to be the latest version when it is determined that different versions exist in the user information distribution application table with the same number currently in the first state; here, the first state may be a commit state.

here, the preset platform includes: the system comprises a PC end, a mobile end, an iphone end, an ipad end, an apad end and an apad end.

In an embodiment, the first obtaining module 71 is further configured to record the first information to a user ranking policy table;

correspondingly, the terminal further includes a creating module 76, configured to create the user ranking policy table;

the user grading strategy table has a function of a sand table, so that modification on information release requirements and bids of users is facilitated, the modification is stored, and consultation by two parties who propose a declaration and a customization policy is facilitated.

Based on the embodiment of the present invention, in an actual application process, the first configuration coefficient includes: the method comprises the following steps of (1) weighting a frame coefficient target, a multi-screen coefficient target, a north coefficient target and a yield deviation coefficient target;

the second obtaining module 72 is specifically configured to determine a frame coefficient, a multi-screen coefficient, a north coefficient, and a profit deviation coefficient of user information distribution, and obtain second information according to the frame coefficient, the multi-screen coefficient, the north coefficient, the profit deviation coefficient, and a corresponding target weight; the second information is used for representing a profit coefficient of user information distribution.

In an embodiment, the second obtaining module 72 is further configured to record the second information to a user ranking policy table.

Based on the embodiment of the present invention, in an actual application process, the processing module 43 is specifically configured to sort the information distribution revenue coefficients of different users based on the second information, and determine the level of the user for performing the simulation operation according to the obtained revenue coefficient sequence and a preset first condition;

the income coefficient threshold value corresponds to the grade of a user performing simulation operation and can be set according to actual requirements;

the number of the level users corresponds to the level of the user performing the simulation operation, and can be set according to actual needs;

in practical application, the user level division reference factor may be a reference factor for representing the importance degree of the user, which is set according to historical data issued by user information;

the guidance coefficient threshold corresponds to the grade of the user performing the simulation operation, and can be set according to actual needs.

Based on the embodiment of the present invention, in an actual application process, the processing module 73 is specifically configured to obtain a second configuration coefficient for performing policy rationality simulation, and perform KPI calculation on a user key performance indicator according to the second configuration coefficient, a determined user rating division policy, and user information release data, so as to obtain a KPI expected value corresponding to a current rating of a user;

the KPI comprises: the north resource of the PC terminal, the north resource of the mobile terminal and the resource of the ipad terminal.

Here, it should be noted that: the above description related to the terminal is similar to the above description of the method, and the description of the beneficial effects of the same method is omitted for brevity. For technical details that are not disclosed in the terminal embodiments of the present invention, refer to the description of the method embodiments of the present invention.

In the embodiment of the present invention, the first obtaining module 71, the second obtaining module 72, the processing module 73, the grading module 74, the updating module 75, and the creating module 76 may be implemented by a Central Processing Unit (CPU), a Digital Signal Processor (DSP), a Field Programmable Gate Array (FPGA), or an integrated Circuit (ASIC) in a terminal or a server.

In the several embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described device embodiments are merely illustrative, for example, the division of the modules is only one logical functional division, and there may be other division ways in actual implementation, such as: multiple modules or components may be combined, or may be integrated into another system, or some features may be omitted, or not implemented. In addition, the coupling, direct coupling or communication connection between the components shown or discussed may be through some interfaces, and the indirect coupling or communication connection between the devices or units may be electrical, mechanical or other forms.

The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical modules, that is, may be located in one place, or may be distributed on a plurality of network modules; some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of the embodiment.

In addition, all the functional modules in the embodiments of the present invention may be integrated into one processing module, or each module may be separately used as one unit, or two or more modules may be integrated into one module; the integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional module.

Those of ordinary skill in the art will understand that: all or part of the steps for implementing the method embodiments may be implemented by hardware related to program instructions, and the program may be stored in a computer readable storage medium, and when executed, the program performs the steps including the method embodiments; and the aforementioned storage medium includes: a mobile storage device, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

Alternatively, the integrated unit of the present invention may be stored in a computer-readable storage medium if it is implemented in the form of a software functional module and sold or used as a separate product. Based on such understanding, the technical solutions of the embodiments of the present invention may be essentially implemented or a part contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the methods described in the embodiments of the present invention. And the aforementioned storage medium includes: a removable storage device, a ROM, a RAM, a magnetic or optical disk, or various other media that can store program code.

The above description is only for the specific embodiments of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention, and all the changes or substitutions should be covered within the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the appended claims.

Claims

1. An information processing method, characterized in that the method comprises:

creating a user level division strategy table; the user grading strategy table is used for grading advertisement delivery users;

associating at least one user advertising information release reporting table in a submitted state to the user level division policy table;

acquiring user advertisement information release data from a server, wherein the user advertisement information release data comprises advertisement information release directional money, an advertisement information release directional platform, advertisement information release quantity ratios of different advertisement information release directional platforms and advertisement information release quantity ratios of different regions;

determining the advertisement information release amount of each advertisement information release targeting platform in the user advertisement information release statement list according to the user advertisement information release data;

presetting a plurality of exposure ratios corresponding to a plurality of advertisement information publishing orientation platforms, wherein the sum of the exposure ratios is 1;

calculating the advertisement information release amount of each preset advertisement information release platform according to the plurality of exposure ratios and the advertisement information release amount of each advertisement information release directional platform to serve as first information;

recording the first information to the user level division policy table;

acquiring a first configuration coefficient, and acquiring second information according to the first configuration coefficient and the first information; the first configuration coefficient is used for representing the target weight of the user advertisement information release in different dimensions;

recording the second information to the user level division policy table;

determining user grades for carrying out simulation operation based on the second information, acquiring a second configuration coefficient for carrying out strategy rationality simulation, carrying out strategy rationality simulation processing according to the second configuration coefficient, the determined user grades and the user advertisement information release data, and calculating to obtain a Key Performance Indicator (KPI) expected value corresponding to each user grade as third information; recording third information to the user level division policy table;

ranking the advertisement delivery users according to the first information, the second information and the third information in the user grade division policy table respectively;

respectively carrying out weighting on the rank ranks of the advertisement putting users according to the weighting coefficients of the first information, the second information and the third information to obtain the final user rank ranks;

and based on the final user grade ranking, carrying out grade division on the advertisement delivery users according to the preset grade user number, and determining whether the user grade used in the simulation processing is reasonable or not according to the grade division result.

2. The method of claim 1, further comprising:

and when determining that different versions exist in the user advertisement information release application table with the same number in the current submission state, updating the user advertisement information release application table to be the latest version.

3. The method of claim 1, wherein the first configuration factor comprises: the method comprises the following steps of (1) weighting a frame coefficient target, a multi-screen coefficient target, a north coefficient target and a yield deviation coefficient target;

determining a frame coefficient, a multi-screen coefficient, a north coefficient and a profit deviation coefficient of advertisement information release of a user, and obtaining the second information according to the frame coefficient, the multi-screen coefficient, the north coefficient, the profit deviation coefficient and corresponding target weight; the second information is used for representing the income coefficient of the user advertisement information release.

4. The method of claim 3, wherein determining the user level for performing the simulation operation based on the second information comprises:

ranking the advertising information release income coefficients of different users based on the second information, and determining the user level for carrying out simulation operation according to the obtained income coefficient sequence and a preset first condition;

or acquiring a user grade division reference factor, determining guide coefficients according to the reference factor and the second information, sequencing the guide coefficients of different users, and determining the user grade for carrying out simulation operation according to the obtained guide coefficient sequence and a preset second condition.

5. An information processing terminal characterized by comprising: the system comprises a creating module, a first obtaining module, a second obtaining module, a processing module and a grading module; wherein the content of the first and second substances,

the creating module is used for creating a user level division policy table; the user grading strategy table is used for grading advertisement delivery users; associating at least one user advertising information release statement table in a first state to the user level division policy table;

the first acquisition module is used for acquiring user advertisement information release data from a server, wherein the user advertisement information release data comprises advertisement information release directional money, advertisement information release directional platforms, advertisement information release quantity ratios of different advertisement information release directional platforms and advertisement information release quantity ratios of different regions; determining the advertisement information release amount of each advertisement information release targeting platform in the user advertisement information release statement list according to the user advertisement information release data; presetting a plurality of exposure ratios corresponding to a plurality of advertisement information publishing orientation platforms, wherein the sum of the exposure ratios is 1; calculating the advertisement information release amount of each preset advertisement information release platform according to the plurality of exposure ratios and the advertisement information release amount of each advertisement information release directional platform to serve as first information; recording the first information to the user level division policy table;

the second obtaining module is used for obtaining a first configuration coefficient and obtaining second information according to the first configuration coefficient and the first information; recording the second information to the user level division policy table; the first configuration coefficient is used for representing the target weight of the user advertisement information release in different dimensions;

the processing module is used for determining user grades for carrying out simulation operation based on the second information, acquiring a second configuration coefficient for carrying out strategy rationality simulation, carrying out strategy rationality simulation processing according to the second configuration coefficient, the determined user grades and the user advertisement information release data, and calculating to obtain a key performance indicator KPI expected value corresponding to each user grade as third information; recording third information to the user level division policy table;

the ranking module is used for ranking the advertisement delivery users according to the first information, the second information and the third information in the user ranking policy table respectively; respectively carrying out weighting on the rank ranks of the advertisement putting users according to the weighting coefficients of the first information, the second information and the third information to obtain the final user rank ranks; and based on the final user grade ranking, carrying out grade division on the advertisement delivery users according to the preset grade user number, and determining whether the user grade used in the simulation processing is reasonable or not according to the grade division result.

6. The terminal of claim 5, further comprising an updating module, configured to update the user advertisement information distribution application table to a latest version when it is determined that different versions exist in the user advertisement information distribution application table with the same number currently in the submission state.

7. The terminal of claim 5, wherein the first configuration factor comprises: the method comprises the following steps of (1) weighting a frame coefficient target, a multi-screen coefficient target, a north coefficient target and a yield deviation coefficient target;

the second obtaining module is specifically configured to determine a frame coefficient, a multi-screen coefficient, a north coefficient and a profit deviation coefficient of advertisement information release of a user, and obtain the second information according to the frame coefficient, the multi-screen coefficient, the north coefficient, the profit deviation coefficient and corresponding target weights; the second information is used for representing the income coefficient of the user advertisement information release.

8. The terminal according to claim 7, wherein the processing module is specifically configured to rank advertisement information distribution revenue coefficients of different users based on the second information, and determine a rank of a user for performing the simulation operation according to the obtained revenue coefficient sequence and a preset first condition;

9. A computer-readable storage medium storing executable instructions for causing a processor to implement the information processing method of any one of claims 1 to 4 when executed.

10. An information processing system, the system comprising: a server and a terminal;

the server is used for sending user advertisement information release data comprising advertisement information release directional money, advertisement information release directional platforms, advertisement information release amount ratios of different advertisement information release directional platforms and advertisement information release amount ratios of different regions;

the terminal is used for creating a user grade division policy table; the user grading strategy table is used for grading advertisement delivery users; associating at least one user advertising information release reporting table in a submitted state to the user level division policy table;

acquiring the user information publishing data from the server;

according to the user advertisement information release data, determining the advertisement information release amount of each advertisement information release targeting platform in the user advertisement information release statement;

presetting a plurality of exposure ratios corresponding to a plurality of advertisement information publishing orientation platforms, wherein the sum of the exposure ratios is 1; calculating the advertisement information release amount of each preset advertisement information release platform according to the plurality of exposure ratios and the advertisement information release amount of each advertisement information release directional platform to serve as first information; recording the first information to the user level division policy table;

acquiring a first configuration coefficient, and acquiring second information according to the first configuration coefficient and the first information; recording the second information to the user level division policy table;

the first configuration coefficient is used for representing the target weight of the user advertisement information release in different dimensions; determining user grades for carrying out simulation operation based on the second information, acquiring a second configuration coefficient for carrying out strategy rationality simulation, carrying out strategy rationality simulation processing according to the second configuration coefficient, the determined user grades and the user advertisement information release data, and calculating to obtain a Key Performance Indicator (KPI) expected value corresponding to each user grade as third information; recording third information to the user level division policy table;

ranking the advertisement delivery users according to the first information, the second information and the third information in the user grade division policy table respectively; respectively carrying out weighting on the rank ranks of the advertisement putting users according to the weighting coefficients of the first information, the second information and the third information to obtain the final user rank ranks; and based on the final user grade ranking, carrying out grade division on the advertisement delivery users according to the preset grade user number, and determining whether the user grade used in the simulation processing is reasonable or not according to the grade division result.