CN113055875B - VoLTE user account opening method and device and computing equipment - Google Patents
VoLTE user account opening method and device and computing equipment Download PDFInfo
- Publication number
- CN113055875B CN113055875B CN201911375365.1A CN201911375365A CN113055875B CN 113055875 B CN113055875 B CN 113055875B CN 201911375365 A CN201911375365 A CN 201911375365A CN 113055875 B CN113055875 B CN 113055875B
- Authority
- CN
- China
- Prior art keywords
- user
- account
- account opening
- preset
- opening
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W8/00—Network data management
- H04W8/18—Processing of user or subscriber data, e.g. subscribed services, user preferences or user profiles; Transfer of user or subscriber data
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W8/00—Network data management
- H04W8/18—Processing of user or subscriber data, e.g. subscribed services, user preferences or user profiles; Transfer of user or subscriber data
- H04W8/183—Processing at user equipment or user record carrier
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W8/00—Network data management
- H04W8/18—Processing of user or subscriber data, e.g. subscribed services, user preferences or user profiles; Transfer of user or subscriber data
- H04W8/20—Transfer of user or subscriber data
- H04W8/205—Transfer to or from user equipment or user record carrier
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D30/00—Reducing energy consumption in communication networks
- Y02D30/70—Reducing energy consumption in communication networks in wireless communication networks
Landscapes
- Engineering & Computer Science (AREA)
- Databases & Information Systems (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
Abstract
The embodiment of the invention relates to the technical field of communication, and discloses a VoLTE user account opening method, a VoLTE user account opening device and computing equipment. Wherein the method comprises the following steps: acquiring account opening data of a preset user; according to the account opening data, determining a user which does not open an account in the preset users; acquiring static information of the user without opening an account; inputting the static information into a preset decision model, and obtaining a decision result output by the preset decision model; according to the decision result, determining the non-account opening user with account opening conditions from the non-account opening users; acquiring dynamic information of the user without the account opening with account opening conditions; inputting the dynamic information into a preset account opening probability model, and obtaining account opening probability output by the preset account opening probability model; and according to the account opening probability, opening the account of the user which does not have the account opening condition. Through the mode, the embodiment of the invention can improve the success rate of account opening.
Description
Technical Field
The embodiment of the invention relates to the technical field of wireless communication, in particular to a VoLTE user account opening method, a VoLTE user account opening device and computing equipment.
Background
With the development of 5G networks and the popularization of large-flow packages, the mobile network structure is more and more complex, the problem of insufficient frequency resources is remarkable, and meanwhile, a plurality of network problems such as high network energy consumption, high operation cost, user perception and sliding down are brought, so that the migration of Voice users to Voice over Long-Term Evolution (VoLTE) has become a necessary choice for network development. Currently, voLTE user account opening is mainly performed by: screening non-account opening users, and carrying out batch embedding; the users are reminded to open accounts independently by expanding the service of the new card users through market propaganda, business halls and the like.
The existing VoLTE user account opening method has the problem of low account opening success rate.
Disclosure of Invention
In view of the above problems, the embodiments of the present invention provide a method, an apparatus, and a computing device for opening an account for a VoLTE user, which can improve the success rate of opening an account.
According to an aspect of the embodiment of the present invention, there is provided a VoLTE user account opening method, including: acquiring account opening data of a preset user; according to the account opening data, determining a user which does not open an account in the preset users; acquiring static information of the user without opening an account; inputting the static information into a preset decision model, and obtaining a decision result output by the preset decision model; according to the decision result, determining the non-account opening user with account opening conditions from the non-account opening users; acquiring dynamic information of the user without the account opening with account opening conditions; inputting the dynamic information into a preset account opening probability model, and obtaining account opening probability output by the preset account opening probability model; and according to the account opening probability, opening the account of the user which does not have the account opening condition.
In an optional manner, the determining, according to the account opening data, the non-account opening user among the preset users specifically includes: inquiring whether account opening label data exist in the account opening data of the user in the preset users; if the account opening tag data exist, determining that the user is an account opening user; and if the account opening tag data does not exist, determining that the user is the user who does not open the account.
In an alternative, the static information includes a user card status; the acquiring the static information of the user without the account opening specifically includes: acquiring service operation support data of the user without opening an account; if the preset card support field in the service operation support data is configured to be 1, determining that the user card state is a user card support state; and if the preset card support field in the service operation support data is configured to be 0, determining that the user card state is a user card unsupported state.
In an alternative manner, the static information further includes a terminal status; the step of obtaining the static information of the user who does not open the account specifically further includes: acquiring terminal type information of the user without opening an account; determining the terminal state according to the terminal type information and the corresponding relation between the preset terminal type and the terminal state; the terminal state comprises a terminal supporting state and a terminal non-supporting state.
In an alternative, the dynamic information includes soft switch status; then, acquiring the dynamic information of the non-account opening user with the account opening condition specifically includes: acquiring signaling data of the user without the account opening with the account opening condition; if a preset soft switch field exists in the signaling data, determining that the soft switch state is an off state; and if the preset soft switch field does not exist in the signaling data, determining that the soft switch state is an on state.
In an alternative, the method further comprises: acquiring sample dynamic information of a sample user and a corresponding sample account opening result; inputting the sample dynamic information into a preset cyclic neural network model, and obtaining a sample account opening probability output by the preset cyclic neural network model; training the preset cyclic neural network model according to the sample account opening result and the sample account opening probability; and determining the trained preset cyclic neural network model as the preset account opening probability model.
In an optional manner, the opening of the account for the non-opening user with the opening condition according to the opening probability further includes: determining the priority order of the unoccupied users with the account opening conditions according to the account opening probability and a preset priority principle; the preset priority principle comprises that the higher the account opening probability is, the higher the priority is; and opening accounts of the unoccupied users with the account opening conditions according to the priority order.
According to another aspect of the embodiment of the present invention, there is provided a VoLTE user account opening device, including: the account opening data acquisition module is used for acquiring account opening data of a preset user; the first determining module is used for determining a user which does not open an account in the preset users according to the account opening data; the static information acquisition module is used for acquiring the static information of the user who does not open an account; the decision module is used for inputting the static information into a preset decision model and obtaining a decision result output by the preset decision model; the second determining module is used for determining the non-account opening user with account opening conditions from the non-account opening users according to the decision result; the dynamic information acquisition module is used for acquiring the dynamic information of the user without the account opening with the account opening condition; the probability acquisition module is used for inputting the dynamic information into a preset account opening probability model and acquiring account opening probability output by the preset account opening probability model; and the account opening module is used for opening accounts of the non-account opening users with account opening conditions according to the account opening probability.
According to yet another aspect of an embodiment of the present invention, there is provided a computing device including: the device comprises a processor, a memory and a communication interface, wherein the processor, the memory and the communication interface are communicated with each other; the memory is configured to store at least one executable instruction that causes the processor to perform the operations of the VoLTE user account opening method as described above.
According to another aspect of embodiments of the present invention, there is provided a computer-readable storage medium having stored therein at least one executable instruction for causing a processor to perform the VoLTE user account opening method as described above.
According to the embodiment of the invention, the user who does not open the account is determined in the preset users according to the data of the opening the account, the static information of the user who does not open the account is obtained, the static information is input into the preset decision model, the decision result output by the preset decision model is obtained, the user who does not open the account with the condition of opening the account is determined in the user who does not open the account according to the decision result, the dynamic information of the user who does not open the account is obtained, the dynamic information is input into the preset probability model of opening the account, the probability of opening the account output by the preset probability model is obtained, the user who does not open the account with the condition of opening the account is obtained according to the probability of opening the account, the user who does not open the account with the condition of opening the account can be effectively identified, and the user is opened the account according to the probability of opening the user who does not open the account with the condition of opening the account, so that the success rate of opening the account is improved.
The foregoing description is only an overview of the technical solutions of the embodiments of the present invention, and may be implemented according to the content of the specification, so that the technical means of the embodiments of the present invention can be more clearly understood, and the following specific embodiments of the present invention are given for clarity and understanding.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to designate like parts throughout the figures. In the drawings:
fig. 1 is a schematic flow chart of a VoLTE user account opening method according to an embodiment of the present invention;
fig. 2 is a schematic flow chart of a VoLTE user account opening method according to another embodiment of the present invention;
FIG. 3 shows a training flow diagram of a preset recurrent neural network model;
FIG. 4 shows a schematic diagram of correspondence between usage months and replacement probabilities;
fig. 5 is a schematic flow chart of a VoLTE user account opening method according to another embodiment;
FIG. 6 shows a schematic diagram of a preset decision model;
fig. 7 is a schematic structural diagram of a VoLTE user account opening device according to an embodiment of the present invention;
FIG. 8 illustrates a schematic diagram of a computing device provided by an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.
Currently, voLTE user account opening is mainly performed by: screening non-account opening users, and carrying out batch embedding; the users are reminded to open accounts independently by expanding the service of the new card users through market propaganda, business halls and the like. However, the batch pre-embedding mode cannot identify the type of the terminal user, opens accounts for a large number of users of which the terminal hardware does not support VoLTE, and the open accounts are not registered to cause voice channel roundabout, so that the user experience is poor, and double pressure is brought to a core network; the mode work load of market propaganda is big, needs to throw in a large amount of propaganda cost to the result of opening accounts can't monitor, and the success rate of opening accounts is low.
Based on the above, the embodiment of the invention provides a VoLTE user account opening method, a VoLTE user account opening device and a computing device, which can effectively identify the user without account opening under account opening conditions, thereby improving the success rate of account opening.
In particular, embodiments of the present invention are further described below with reference to the accompanying drawings.
It should be understood, however, that the following examples provided herein may be combined with one another to form new embodiments, so long as they do not conflict.
Fig. 1 shows a flowchart of a VoLTE user account opening method according to an embodiment of the present invention. The method is applied to a computing device. As shown in fig. 1, the method includes:
The preset users refer to a plurality of users which need to be identified as non-account opening users with account opening conditions. For example, the user of a certain number segment may be set as a preset user, or the number of a certain home location may be set as a preset user.
The account opening data is signaling data for reflecting the account opening state. The account opening data may be obtained from a home subscriber server (Home Subscriber Server, HSS).
And 120, determining the user without opening the account among the preset users according to the data of opening the account.
The non-account opening user refers to a user who does not make an account opening, and the user except the user who makes an account can be the non-account opening user in the preset user by determining the user who makes an account in the preset user.
Specifically, step 120 includes:
step 121, inquiring whether account opening label data exists in account opening data of users in preset users;
step 122, if the account opening tag data exists, determining that the user is an account opening user;
and step 123, if the account opening label data does not exist, determining that the user is the user who does not open the account.
Wherein, the label data of opening accounts is "Type: vol euser ", when there is" Type: when VOLTEUSER' indicates that the user is in the account opening state, the user is the user who has opened the account.
And 130, acquiring static information of the user who does not open the account.
Static information refers to information of some elements which are not easy or frequently changed. The static information may include a user card status and a terminal status. The static information of the user who does not open an account is acquired, which specifically includes:
step 131, acquiring service operation support data of a user who does not open an account;
step 132, if the preset card support field in the service operation support data is configured to be 1, determining that the user card state is the user card support state;
step 133, if the preset card support field in the service operation support data is configured to be 0, determining that the user card state is the user card unsupported state;
step 134, obtaining terminal type information of the user who does not open an account;
and 135, determining the terminal state according to the terminal type information and the corresponding relation between the preset terminal type and the terminal state.
The service operation support data refers to data acquired from a service operation support system (BOSS). The preset card support field is 'terminal_write_volte', when 'terminal_write_volte' is configured to be 1, the card is indicated to support the VoLte function, the user card state is determined to be the user card support state, when 'terminal_write_volte' is configured to be 0, the card is indicated to not support the VoLte function, and the user card state is determined to be the user card non-support state. For example, as shown in table 1 below, the acquired service operation support data indicates that the subscriber card status of the subscriber having the international mobile identity of "290210 xxxxxxxxxx 8", "290210 xxxxxxxxxx 5", "290210xxxxxxx 6" is a subscriber card support status, and the subscriber card status of the subscriber having the international mobile identity of "290210xxxxxxxxx4" is a subscriber card non-support status.
TABLE 1
| City | Region(s) | International mobile identification code | Terminal_whether_VoLte | |
| Xi ' an | Not at the | 290210xxxxxxxxx8 | 1 | |
| Xi ' an | Not at the | 290210xxxxxxxxx5 | 1 | |
| Xi ' an | Not at the center | 290210xxxxxxxxx4 | 0 | |
| Xi ' an | Not at the | 290210xxxxxxxxx6 | 1 |
The terminal type information may include information such as a brand, a model, a support network system, etc. of the terminal, and the terminal type information has a preset corresponding relationship with a terminal state. The terminal type information can be acquired by collecting and processing equipment information provided by a manufacturer to establish a terminal library. The terminal states include a terminal support state and a terminal non-support state. The determining the terminal state according to the terminal type information and the corresponding relation between the preset terminal type and the terminal state may be: if the supported network system of the terminal type information comprises TD-LTE or FDD-LTE, determining the terminal state as a terminal supporting state; if the supported network system of the terminal type information does not comprise TD-LTE or FDD-LTE, determining that the terminal state is a terminal non-supported state. For example, as shown in table 2 below, the terminal type information indicates that the terminal status of the user with the terminal brand of millet and the terminal model of 2014216 is the terminal support status, the terminal status of the user with the terminal brand of eastern you and the terminal model of US2 is the terminal non-support status.
TABLE 2
| Terminal brand | Terminal model | Supporting network system |
| Millet | 2014216 | GSM/TD-SCDMA/TD-LTE |
| Glory | BKL-AL20 | GSM/CDMA1X/WCDMA/EVDO/TD-LTE/FDD-LTE |
| Apple tree | A1864 | GSM/CDMA1X/WCDMA/EVDO/TD-LTE/FDD-LTE |
| Qidongyou Si (Qidong you Si) | US2 | GSM |
And 140, inputting the static information into a preset decision model to obtain a decision result output by the preset decision model.
The preset decision model is used for clearing users without account opening conditions. The predetermined decision model may be a decision tree. The decision conditions of the decision tree can be preset according to actual conditions, when the decision conditions are met, a '1' is output, when the decision conditions are not met, a '0' is output, and the decision results of the decision conditions are multiplied, so that the decision result of a preset decision model is output. For example, assuming that the static information includes a user card state and a terminal state, a first decision condition of the preset decision model is whether the user card state is a user card support state, a second decision condition is whether the terminal state is a terminal support state, if the user card state of the user a is a user card support state and the terminal state is a terminal non-support state, the terminal state of the user a is input into the preset decision model, and the output decision result of the preset decision model is "0".
And 150, determining the non-account opening user with account opening conditions from the non-account opening users according to the decision result.
When the decision result is 0, determining that the user does not have an account opening condition; when the decision result is 1, determining that the user has the account opening condition, removing the user which does not have the account opening condition from the user which does not have the account opening condition, and determining the user which does not have the account opening condition.
The dynamic information includes a soft switching state, and the soft switching state refers to a VoLTE switching state on the terminal. Since the VoLTE switch on the terminal can be set on or off by the user, the VoLTE switch state is defined as dynamic information.
Specifically, the method for acquiring the dynamic information of the user without the account opening with the account opening condition specifically comprises the following steps:
step 161, obtaining signaling data of a user without an account having an account opening condition;
step 162, if a preset soft switch field exists in the signaling data, determining that the soft switch state is an off state;
step 163, if the preset soft switch field does not exist in the signaling data, determining that the soft switch state is an on state.
The signaling data refers to signaling data capable of identifying the state of the soft switch. The signaling data may be obtained from a signaling platform. The preset soft switch field refers to a field in preset signaling data for judging the state of the soft switch.
After the terminal is started in the LTE coverage area, the terminal can be jointly attached to the LTE network and the 2G network. In the CSFB UE joint attachment process, the UE and the LTE core network MME inform each other of the voice service support capability. As a CSFB terminal, its "Voice domain preference and UE's usage setting IE" in the Attach Request message will report its voice service support capability, and four different voice service support capabilities are specified in the protocol, namely: 1. CS Voice only (only supporting CS fallback and short message through SGs interface); 2. IMS PS Voice only (IMS VoLTE only); 3. CS voice preferred, IMS PS Voice as secondary (CS fallback is supported preferentially and short messages are sent through SGs interface, IMS VoLTE second); 4. IMS PS voice preferred, CS Voice as secondary (IMS VoLTE, CS fallback and short message second over SGs interface is supported preferentially). The preset soft switch field may be set to "CS Voice only" IMS PS Voice preferred ", where the soft switch state is determined to be an off state when" CS Voice only "or" IMS PS Voice preferred "exists in the signaling data, and the soft switch state is determined to be an on state when" CS Voice only "or" IMS PS Voice preferred "does not exist in the signaling data.
Wherein the dynamic information may further include one or more of payment information, shutdown status, sub-card status, consumption level information, etc., and may be acquired from the service operation support system. The payment information may include payment information of the current month (for example, already paid or owed) and payment information of the historical month; the shutdown state means that the terminal has been shutdown; the auxiliary card state refers to that in some terminals with main cards and auxiliary cards, the number is in the auxiliary card state; the consumption level refers to a consumption level divided according to a preset amount.
The preset account opening probability model is a model capable of outputting account opening probability according to dynamic information. The preset account opening probability model can be trained by a preset cyclic neural network (Recurrent Neural Network, RNN) model.
Wherein, some elements in the dynamic information may be changed easily or frequently, and after the elements which are changed easily or frequently pass through a preset account opening probability model, the output account opening probability is higher.
And 180, opening an account for the user without opening the account according to the probability of opening the account.
Wherein, according to the probability of opening an account, the user who does not open an account and has the condition of opening an account is opened, further comprising:
step 181, determining the priority order of the unoccupied users with the account opening conditions according to the account opening probability and a preset priority principle; the preset priority principle comprises that the higher the account opening probability is, the higher the priority is;
step 182, according to the priority order, the user without the account is opened under the account opening condition.
Wherein, according to the priority order, the user who does not have the account opening condition can be: the priority order ranks first, and then the account is opened in the current month; ranking the second in the priority order, and opening an account in the second month; the second of the priority ranks, then the account is opened in the third month, and so on.
According to the embodiment of the invention, the user who does not open the account is determined in the preset users according to the data of the opening the account, the static information of the user who does not open the account is obtained, the static information is input into the preset decision model, the decision result output by the preset decision model is obtained, the user who does not open the account with the condition of opening the account is determined in the user who does not open the account according to the decision result, the dynamic information of the user who does not open the account is obtained, the dynamic information is input into the preset probability model of opening the account, the probability of opening the account output by the preset probability model is obtained, the user who does not open the account with the condition of opening the account is obtained according to the probability of opening the account, the user who does not open the account with the condition of opening the account can be effectively identified, and the user is opened the account according to the probability of opening the user who does not open the account with the condition of opening the account, so that the success rate of opening the account is improved.
In some embodiments, as shown in fig. 2, the method further comprises:
and 194, determining the trained preset cyclic neural network model as a preset account opening probability model.
The sample user is a preset user for model training. The sample dynamic information is dynamic information in the historical time of the sample user, and the sample dynamic information has a corresponding sample account opening result. For example, the sample dynamic information is historical payment information, the historical payment information of the sample user A comprises 1 month 30 month and 2 months 28 months and 3 months 29 months and 4 months 30 days without payment records, the sample user A comprises 5 months and 2 months with a result of 5 months and 15 days with a success of account opening.
The preset cyclic neural network model performs dynamic weight calculation based on an RNN cyclic intelligent algorithm, and the RNN cyclic intelligent algorithm can be used for fitting a function and training based on big data. The preset cyclic neural network model has a memory function, and the output of the cyclic neural network model not only depends on the current input, but also depends on the current memory, so that the problem of front-back association between the inputs can be solved. The preset recurrent neural network model may be composed of an input layer, a hidden layer and an output layer.
After the sample dynamic information is input into a preset cyclic neural network model, the sample account opening probability output by the preset cyclic neural network model is obtained, then the sample account opening result corresponding to the sample dynamic information is compared with the sample account opening probability, and the threshold value in the preset cyclic neural network model is adjusted, so that training of the preset cyclic neural network model is performed. The training process of the preset cyclic neural network model may be as shown in fig. 3, after the dynamic information input in the sample dynamic information is calibrated by the historical dynamic information in the sample dynamic information, each module may transmit the information to the next module, perform user weight calculation based on the RNN cyclic intelligent algorithm, perform multiple assignment and multiplication, and output the dynamic weight W, thereby calculating the account opening probability according to the dynamic weight.
In some implementations, the method can further include: acquiring a modification period of static information; updating the static information of the non-account opening user according to the changing period of the static information, inputting the updated static information into a preset decision model, and determining the non-account opening user with account opening conditions in the non-account opening user again according to the decision result output by the preset decision model.
Because the user may change the card or change the terminal, some users without account opening conditions may have account opening conditions because of changing the card or changing the mobile phone, so static information needs to be updated at preset time intervals to realize coverage of the user. The modification period of the static information may include: a period of change of the user card state and a period of change of the terminal state. The modification period of the static information can be freely set according to statistical data or empirical values. For example, when a terminal brand is a mobile phone with a terminal price of 3000 yuan, as shown in fig. 4, the change of the replacement probability is large from month 1 to month 21, the change of the replacement probability is 71.69% at month 21, and the change of the replacement probability is small after month 21, the change period of the terminal state of the terminal of the brand is set to 21 months, and the static information is updated at 21 months.
Fig. 5 shows a flowchart of a VoLTE user account opening method according to another embodiment of the present invention. The method is applied to a computing device. As shown in fig. 5, the method includes:
Step 201 and step 202 are the same as the implementation of step 110 and step 120 in the above embodiments, and are not repeated here.
The real-name state is divided into a real-name state and an unamplified state, and the black-and-white list state is divided into a black list state and a non-black list state. Static information such as real name status, black and white list status and the like can be obtained from the service operation support system.
In some other embodiments, the static information may further include: whether it is a government enterprise customer, whether it is an industry application card, whether it is an initial password set, whether it is a competitor contract machine, whether it is to change attribution, etc. The decision conditions in the preset decision model can be set according to different static information.
And 204, inputting the real name state, the black-and-white list state, the user card state and the terminal state into a preset decision model to obtain a decision result output by the preset decision model.
For example, as shown in fig. 6, the decision condition of the preset decision model may be that whether the first decision condition is a real name, if the input real name state is a real name state, then entering a second decision condition, and if the input real name state is an unamplified state, then rejecting the user; if the second decision condition is a blacklist, entering a third decision condition when the input blacklist state is a non-blacklist state, and eliminating the user when the input blacklist state is a blacklist state; the third decision condition is whether the user card is supported or not, if the input user card state is the user card supporting state, a fourth decision condition is entered, and if the input user card state is the user card non-supporting state, a '0' is output, namely the user is rejected; and if the fourth decision condition is that the terminal is supported or not, if the input terminal state is a terminal supporting state, the user has an account opening condition, and if the input terminal state is a terminal non-supporting state, the user performs rejection.
And step 208, determining the priority order of the unoccupied users with the account opening conditions according to the account opening probability and a preset priority principle.
According to the embodiment of the invention, the account opening data of the preset user are acquired, static information such as the real name state, the black-and-white list state, the user card state and the terminal state of the user without account opening is determined in the preset user according to the account opening data, the static information is input into the preset decision model, the decision result output by the preset decision model is acquired, the user without account opening with account opening conditions is determined in the user without account opening according to the decision result, the dynamic information such as the soft switch state, the payment information, the shutdown state, the auxiliary card state and the consumption grade information of the user without account opening with account opening conditions is acquired, the dynamic information is input into the preset account opening probability model, the account opening probability output by the preset account opening probability model is acquired, the priority order of the user without account opening with account opening conditions is determined according to the account opening probability and the preset priority principle, the user without account opening with account opening conditions is carried out according to the priority order, the user without account opening with account opening conditions can be effectively identified, and the user without account opening with account opening conditions is carried out according to the account opening probability of the user without account opening conditions with account opening conditions, so that the success rate of opening is improved.
Fig. 7 shows a schematic structural diagram of a VoLTE user account opening device according to an embodiment of the present invention. As shown in fig. 7, the apparatus 300 includes: an account opening data acquisition module 310, a first determination module 320, a static information acquisition module 330, a decision module 340, a second determination module 350, a dynamic information acquisition module 360, a probability acquisition module 370, and an account opening module 380.
The account opening data acquisition module 310 is configured to acquire account opening data of a preset user; the first determining module 320 is configured to determine, according to the account opening data, a user that does not have an account opening from the preset users; the static information obtaining module 330 is configured to obtain static information of the user who does not open an account; the decision module 340 is configured to input the static information into a preset decision model, and obtain a decision result output by the preset decision model; the second determining module 350 is configured to determine, according to the decision result, a non-account user having an account opening condition from the non-account users; the dynamic information acquisition module 360 is configured to acquire dynamic information of the user who does not have an account opening condition; the probability acquisition module 370 is configured to input the dynamic information into a preset account opening probability model, and acquire an account opening probability output by the preset account opening probability model; the account opening module 380 is configured to open an account for the non-account user having the account opening condition according to the account opening probability.
In an alternative manner, the first determining module 320 is specifically configured to: inquiring whether account opening label data exist in the account opening data of the user in the preset users; if the account opening tag data exist, determining that the user is an account opening user; and if the account opening tag data does not exist, determining that the user is the user who does not open the account.
In an alternative, the static information includes a user card status; the static information acquisition module 330 is specifically configured to: acquiring service operation support data of the user without opening an account; if the preset card support field in the service operation support data is configured to be 1, determining that the user card state is a user card support state; and if the preset card support field in the service operation support data is configured to be 0, determining that the user card state is a user card unsupported state.
In an alternative manner, the static information further includes a terminal status; the static information acquisition module 330 is specifically further configured to: acquiring terminal type information of the user without opening an account; determining the terminal state according to the terminal type information and the corresponding relation between the preset terminal type and the terminal state; the terminal state comprises a terminal supporting state and a terminal non-supporting state.
In an alternative, the dynamic information includes soft switch status; the dynamic information acquisition module 360 is specifically configured to: acquiring signaling data of the user without the account opening with the account opening condition; if a preset soft switch field exists in the signaling data, determining that the soft switch state is an off state; and if the preset soft switch field does not exist in the signaling data, determining that the soft switch state is an on state.
In an alternative, the apparatus 300 further comprises: and a model training module. The model training module is specifically used for: acquiring sample dynamic information of a sample user and a corresponding sample account opening result; inputting the sample dynamic information into a preset cyclic neural network model, and obtaining a sample account opening probability output by the preset cyclic neural network model; training the preset cyclic neural network model according to the sample account opening result and the sample account opening probability; and determining the trained preset cyclic neural network model as the preset account opening probability model.
In an alternative manner, the account opening module 380 is specifically configured to: determining the priority order of the unoccupied users with the account opening conditions according to the account opening probability and a preset priority principle; the preset priority principle comprises that the higher the account opening probability is, the higher the priority is; and opening accounts of the unoccupied users with the account opening conditions according to the priority order.
It should be noted that, the device for opening an account of a VoLTE user provided by the embodiment of the present invention is a device capable of executing the above-mentioned method for opening an account of a VoLTE user, and all embodiments of the above-mentioned method for opening an account of a VoLTE user are applicable to the device, and can achieve the same or similar beneficial effects.
According to the embodiment of the invention, the user who does not open the account is determined in the preset users according to the data of the opening the account, the static information of the user who does not open the account is obtained, the static information is input into the preset decision model, the decision result output by the preset decision model is obtained, the user who does not open the account with the condition of opening the account is determined in the user who does not open the account according to the decision result, the dynamic information of the user who does not open the account is obtained, the dynamic information is input into the preset probability model of opening the account, the probability of opening the account output by the preset probability model is obtained, the user who does not open the account with the condition of opening the account is obtained according to the probability of opening the account, the user who does not open the account with the condition of opening the account can be effectively identified, and the user is opened the account according to the probability of opening the user who does not open the account with the condition of opening the account, so that the success rate of opening the account is improved.
The embodiment of the invention provides a computer readable storage medium, wherein at least one executable instruction is stored in the storage medium, and the executable instruction enables a processor to execute the VoLTE user account opening method in any method embodiment.
According to the embodiment of the invention, the user who does not open the account is determined in the preset users according to the data of the opening the account, the static information of the user who does not open the account is obtained, the static information is input into the preset decision model, the decision result output by the preset decision model is obtained, the user who does not open the account with the condition of opening the account is determined in the user who does not open the account according to the decision result, the dynamic information of the user who does not open the account is obtained, the dynamic information is input into the preset probability model of opening the account, the probability of opening the account output by the preset probability model is obtained, the user who does not open the account with the condition of opening the account is obtained according to the probability of opening the account, the user who does not open the account with the condition of opening the account can be effectively identified, and the user is opened the account according to the probability of opening the user who does not open the account with the condition of opening the account, so that the success rate of opening the account is improved.
Embodiments of the present invention provide a computer program product comprising a computer program stored on a computer storage medium, the computer program comprising program instructions which, when executed by a computer, cause the computer to perform the VoLTE user account opening method in any of the method embodiments described above.
According to the embodiment of the invention, the user who does not open the account is determined in the preset users according to the data of the opening the account, the static information of the user who does not open the account is obtained, the static information is input into the preset decision model, the decision result output by the preset decision model is obtained, the user who does not open the account with the condition of opening the account is determined in the user who does not open the account according to the decision result, the dynamic information of the user who does not open the account is obtained, the dynamic information is input into the preset probability model of opening the account, the probability of opening the account output by the preset probability model is obtained, the user who does not open the account with the condition of opening the account is obtained according to the probability of opening the account, the user who does not open the account with the condition of opening the account can be effectively identified, and the user is opened the account according to the probability of opening the user who does not open the account with the condition of opening the account, so that the success rate of opening the account is improved.
FIG. 8 illustrates a schematic diagram of a computing device according to an embodiment of the present invention, and the embodiment of the present invention is not limited to a specific implementation of the computing device.
As shown in fig. 8, the computing device may include: a processor 402, a communication interface (Communications Interface) 404, a memory 406, and a communication bus 408.
Wherein: processor 402, communication interface 404, and memory 406 communicate with each other via communication bus 408. A communication interface 404 for communicating with network elements of other devices, such as clients or other servers. The processor 402 is configured to execute the program 410, and specifically may execute the VoLTE user account opening method in any of the foregoing method embodiments.
In particular, program 410 may include program code including computer-operating instructions.
The processor 402 may be a central processing unit CPU, or a specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement embodiments of the present invention. The one or more processors included by the computing device may be the same type of processor, such as one or more CPUs; but may also be different types of processors such as one or more CPUs and one or more ASICs.
Memory 406 for storing programs 410. Memory 406 may comprise high-speed RAM memory or may also include non-volatile memory (non-volatile memory), such as at least one disk memory.
According to the embodiment of the invention, the user who does not open the account is determined in the preset users according to the data of the opening the account, the static information of the user who does not open the account is obtained, the static information is input into the preset decision model, the decision result output by the preset decision model is obtained, the user who does not open the account with the condition of opening the account is determined in the user who does not open the account according to the decision result, the dynamic information of the user who does not open the account is obtained, the dynamic information is input into the preset probability model of opening the account, the probability of opening the account output by the preset probability model is obtained, the user who does not open the account with the condition of opening the account is obtained according to the probability of opening the account, the user who does not open the account with the condition of opening the account can be effectively identified, and the user is opened the account according to the probability of opening the user who does not open the account with the condition of opening the account, so that the success rate of opening the account is improved.
The algorithms or displays presented herein are not inherently related to any particular computer, virtual system, or other apparatus. Various general-purpose systems may also be used with the teachings herein. The required structure for a construction of such a system is apparent from the description above. In addition, embodiments of the present invention are not directed to any particular programming language. It will be appreciated that the teachings of the present invention described herein may be implemented in a variety of programming languages, and the above description of specific languages is provided for disclosure of enablement and best mode of the present invention.
In the description provided herein, numerous specific details are set forth. However, it is understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the above description of exemplary embodiments of the invention, various features of the embodiments of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be construed as reflecting the intention that: i.e., the claimed invention requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the apparatus of the embodiments may be adaptively changed and disposed in one or more apparatuses different from the embodiments. The modules or units or components of the embodiments may be combined into one module or unit or component and, furthermore, they may be divided into a plurality of sub-modules or sub-units or sub-components. Any combination of all features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or units of any method or apparatus so disclosed, may be used in combination, except insofar as at least some of such features and/or processes or units are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings), may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments herein include some features but not others included in other embodiments, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the following claims, any of the claimed embodiments can be used in any combination.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The use of the words first, second, third, etc. do not denote any order. These words may be interpreted as names. The steps in the above embodiments should not be construed as limiting the order of execution unless specifically stated.
Claims (8)
1. A VoLTE user account opening method, the method comprising:
acquiring account opening data of a preset user;
According to the account opening data, determining a user which does not open an account in the preset users;
acquiring static information of the user without opening an account; wherein the static information includes a user card status; the obtaining the static information of the user without the account opening comprises the following steps:
acquiring service operation support data of the user without opening an account;
if the preset card support field in the service operation support data is configured to be 1, determining that the user card state is a user card support state;
if the preset card support field in the service operation support data is configured to be 0, determining that the user card state is a user card unsupported state;
the static information also comprises a terminal state;
the obtaining the static information of the user without opening an account further includes:
acquiring terminal type information of the user without opening an account;
determining the terminal state according to the supported network system of the terminal type information and the corresponding relation between the preset terminal type and the terminal state; the terminal state comprises a terminal supporting state and a terminal non-supporting state;
inputting the static information into a preset decision model, and obtaining a decision result output by the preset decision model;
According to the decision result, determining the non-account opening user with account opening conditions from the non-account opening users;
acquiring dynamic information of the user without the account opening with account opening conditions; the dynamic information comprises a sub card state and consumption grade information;
inputting the dynamic information into a preset account opening probability model, and obtaining account opening probability output by the preset account opening probability model;
and according to the account opening probability, opening the account of the user which does not have the account opening condition.
2. The method according to claim 1, wherein the determining, according to the account opening data, a non-account opening user among the preset users specifically includes:
inquiring whether account opening label data exist in the account opening data of the user in the preset users;
if the account opening tag data exist, determining that the user is an account opening user;
and if the account opening tag data does not exist, determining that the user is the user who does not open the account.
3. The method of claim 1, wherein the dynamic information comprises soft switching states;
then, acquiring the dynamic information of the non-account opening user with the account opening condition specifically includes:
Acquiring signaling data of the user without the account opening with the account opening condition;
if a preset soft switch field exists in the signaling data, determining that the soft switch state is an off state;
and if the preset soft switch field does not exist in the signaling data, determining that the soft switch state is an on state.
4. The method according to claim 1, wherein the method further comprises:
acquiring sample dynamic information of a sample user and a corresponding sample account opening result;
inputting the sample dynamic information into a preset cyclic neural network model, and obtaining a sample account opening probability output by the preset cyclic neural network model;
training the preset cyclic neural network model according to the sample account opening result and the sample account opening probability;
and determining the trained preset cyclic neural network model as the preset account opening probability model.
5. The method according to any one of claims 1-4, wherein the opening the account for the non-open user with the open condition according to the open probability, further comprises:
determining the priority order of the unoccupied users with the account opening conditions according to the account opening probability and a preset priority principle; the preset priority principle comprises that the higher the account opening probability is, the higher the priority is;
And opening accounts of the unoccupied users with the account opening conditions according to the priority order.
6. A VoLTE user account opening device, the device comprising:
the account opening data acquisition module is used for acquiring account opening data of a preset user;
the first determining module is used for determining a user which does not open an account in the preset users according to the account opening data;
the static information acquisition module is used for acquiring the static information of the user who does not open an account; wherein the static information includes a user card status; the obtaining the static information of the user without the account opening comprises the following steps:
acquiring service operation support data of the user without opening an account;
if the preset card support field in the service operation support data is configured to be 1, determining that the user card state is a user card support state;
if the preset card support field in the service operation support data is configured to be 0, determining that the user card state is a user card unsupported state;
the static information also comprises a terminal state;
the obtaining the static information of the user without opening an account further includes:
acquiring terminal type information of the user without opening an account;
determining the terminal state according to the supported network system of the terminal type information and the corresponding relation between the preset terminal type and the terminal state; the terminal state comprises a terminal supporting state and a terminal non-supporting state;
The decision module is used for inputting the static information into a preset decision model and obtaining a decision result output by the preset decision model;
the second determining module is used for determining the non-account opening user with account opening conditions from the non-account opening users according to the decision result;
the dynamic information acquisition module is used for acquiring the dynamic information of the user without the account opening with the account opening condition; the dynamic information comprises a sub card state and consumption grade information;
the probability acquisition module is used for inputting the dynamic information into a preset account opening probability model and acquiring account opening probability output by the preset account opening probability model;
and the account opening module is used for opening accounts of the non-account opening users with account opening conditions according to the account opening probability.
7. A computing device, comprising: the device comprises a processor, a memory and a communication interface, wherein the processor, the memory and the communication interface are communicated with each other;
the memory is configured to store at least one executable instruction that causes the processor to perform the operation of the VoLTE subscriber provisioning method according to any of claims 1-5.
8. A computer readable storage medium having stored therein at least one executable instruction for causing a processor to perform the VoLTE user account opening method of any one of claims 1-5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911375365.1A CN113055875B (en) | 2019-12-27 | 2019-12-27 | VoLTE user account opening method and device and computing equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911375365.1A CN113055875B (en) | 2019-12-27 | 2019-12-27 | VoLTE user account opening method and device and computing equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113055875A CN113055875A (en) | 2021-06-29 |
| CN113055875B true CN113055875B (en) | 2023-04-28 |
Family
ID=76506156
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911375365.1A Active CN113055875B (en) | 2019-12-27 | 2019-12-27 | VoLTE user account opening method and device and computing equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113055875B (en) |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108243057B (en) * | 2016-12-27 | 2021-08-13 | ***通信集团浙江有限公司 | VoLTE conversion rate analysis method and system |
| WO2019178816A1 (en) * | 2018-03-22 | 2019-09-26 | 华为技术有限公司 | Method and device for setting supplementary service |
-
2019
- 2019-12-27 CN CN201911375365.1A patent/CN113055875B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN113055875A (en) | 2021-06-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107889069B (en) | Short message gateway selection method, device, server and readable storage medium | |
| CN105719104B (en) | Intelligent approval method and device | |
| CN107679718A (en) | List distribution method, equipment and computer-readable recording medium | |
| CN103077718A (en) | Speech processing method, system and terminal | |
| US10178240B2 (en) | Multi-card resource management method, device and multi-card terminal | |
| CN104702782A (en) | Short message management method and mobile terminal thereof | |
| CN103037000B (en) | Publish-subscribe system and notification message processing method thereof | |
| CN109195217A (en) | The processing method and processing device of LTE network refusal behavior | |
| CN109982293A (en) | Flow product method for pushing, system, electronic equipment and storage medium | |
| WO2016070616A1 (en) | Intelligent terminal and method for managing multi-card data traffic | |
| US12028481B2 (en) | Spam telephone call reducer | |
| CN113055875B (en) | VoLTE user account opening method and device and computing equipment | |
| US11316981B2 (en) | Stack queuing customer care routing with vertical metrics | |
| US9521676B2 (en) | Intelligent routing of packet session data in a multi-SIM user equipment | |
| WO2018010273A1 (en) | Method and device for processing concurrent data services | |
| US20160323210A1 (en) | Instant text message conductor | |
| CN111132035A (en) | Scheduling management method and device in cluster system | |
| CN113873495B (en) | Network access method and device of eSIM card | |
| CN111163237B (en) | Call service flow control method and related device | |
| CN109995949B (en) | Number changing service processing method and device | |
| CN112422746A (en) | Push message processing method and device, storage medium and electronic device | |
| US20140364157A1 (en) | Method And System For Providing A Set Of Target Recipients For A Message | |
| WO2023213288A1 (en) | Model acquisition method and communication device | |
| CN110688490A (en) | Method and device for configuring knowledge graph | |
| CN113038402B (en) | Roaming network search configuration method, device, storage medium and mobile terminal |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |