CN112989201A - Message pushing blocking method and device, storage medium and electronic equipment - Google Patents
Message pushing blocking method and device, storage medium and electronic equipment Download PDFInfo
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Abstract
The embodiment of the application discloses a message pushing blocking method and device, a storage medium and electronic equipment. The method comprises the following steps: determining target characteristics of a push object according to the push object of the message push request; wherein the target features comprise base features and behavior features; taking the target characteristics as input, and training the target characteristics by using a pre-trained message blocking model to obtain an output result; and if the output result meets the preset threshold constraint condition, carrying out message pushing blocking. According to the technical scheme, the message information meeting the threshold constraint condition can be pushed and blocked by utilizing the pre-trained message blocking model, so that the target user of message pushing is more accurate, and the user is prevented from being disturbed.
Description
Technical Field
The embodiment of the application relates to the technical field of internet, in particular to a message pushing blocking method, a message pushing blocking device, a storage medium and electronic equipment.
Background
In modern life, the internet is inseparable from people's life. Various messages can be pushed to the user through the internet.
At present, the push service mainly adopts the means of self-defining push tasks by operators, self-defining timing tasks by a service system and the like, user delineation is carried out according to a target user search strategy customized by the service, and the system pushes the delineated users one by one in a uniform time.
Currently, the push system does not consider whether the user is interested in the current push message and whether the push time is disturbing to the user.
Disclosure of Invention
The embodiment of the application provides a message pushing blocking method and device, a storage medium and electronic equipment, and the message information meeting the threshold constraint condition is pushed and blocked by using a pre-trained message blocking model, so that the target user of message pushing is more accurate, and the user is prevented from being disturbed.
In a first aspect, an embodiment of the present application provides a message push blocking method, where the method includes:
determining target characteristics of a push object according to the push object of the message push request; wherein the target features comprise base features and behavior features;
taking the target characteristics as input, and training the target characteristics by using a pre-trained message blocking model to obtain an output result;
and if the output result meets the preset threshold constraint condition, carrying out message pushing blocking.
In a second aspect, an embodiment of the present application provides a message push blocking apparatus, where the apparatus includes:
the target characteristic determining module is used for determining the target characteristics of the push object according to the push object of the message push request; wherein the target features comprise base features and behavior features;
an output result obtaining module, configured to train the target feature by using a pre-trained message blocking model with the target feature as an input to obtain an output result;
and the message pushing blocking module is used for carrying out message pushing blocking if the output result meets the constraint condition of a preset threshold value.
In a third aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements a message push blocking method according to an embodiment of the present application.
In a fourth aspect, an embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the message push blocking method according to the embodiment of the present application when executing the computer program.
According to the technical scheme provided by the embodiment of the application, the target characteristics of the push object are determined according to the push object of the message push request; wherein the target features comprise basic features and behavior features; taking the target characteristics as input, and training the target characteristics by using a pre-trained message blocking model to obtain an output result; and if the output result meets the preset threshold constraint condition, carrying out message pushing blocking. According to the technical scheme, the message information meeting the threshold constraint condition can be pushed and blocked by utilizing the pre-trained message blocking model, so that the target user of message pushing is more accurate, and the user is prevented from being disturbed.
Drawings
Fig. 1 is a flowchart of a message push blocking method according to an embodiment of the present application;
fig. 2 is a schematic diagram of a message push blocking process provided in the second embodiment of the present application;
fig. 3 is a schematic structural diagram of a message push blocking device according to a third embodiment of the present application;
fig. 4 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present application.
Detailed Description
The present application will be described in further detail with reference to the following drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the application and are not limiting of the application. It should be further noted that, for the convenience of description, only some of the structures related to the present application are shown in the drawings, not all of the structures.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the steps as a sequential process, many of the steps can be performed in parallel, concurrently or simultaneously. In addition, the order of the steps may be rearranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
Example one
Fig. 1 is a flowchart of a message push blocking method provided in an embodiment of the present application, where this embodiment is applicable to a case of performing push blocking processing on message push, and the method may be executed by a message push blocking device provided in an embodiment of the present application, where the device may be implemented by software and/or hardware, and may be integrated in a device such as an intelligent terminal for message blocking.
As shown in fig. 1, the message push blocking method includes:
s110, determining target characteristics of a push object according to the push object of the message push request; wherein the target features include base features and behavior features.
Wherein the target feature may refer to data generated based on the push object. For example, the target feature may push a feature, an information feature, and an active time feature, among others. The push characteristics can include push content or push time and the like; the information characteristics may include gender or age, etc.; the active time feature may include a view resume time or a refresh resume time, etc.
In this embodiment, the push object may refer to a target user performing message pushing, and may determine the push object according to information such as an ID or an identifier of the push object, and read a history message push log of the push object to obtain a target feature.
In this technical solution, optionally, determining a target characteristic of a push object according to the push object of the message push request includes:
determining a pushing object ID according to the message pushing request;
and calling the target characteristics of the push object from a user resource database and a push result database according to the ID of the push object.
In this embodiment, the message push request includes a push object, and the history message of the push object is fetched from the user resource database and the push result database of the history message push log of the push object according to the push object ID, and is used as the target feature.
By obtaining the target characteristics of the push object, the pushed message information can be predicted based on the target characteristics, so that the target user of message push is more accurate, and the user is prevented from being disturbed.
In this technical solution, optionally, the basic features include a push feature, an information feature, and a resume feature;
wherein the push characteristics comprise at least one of a terminal system type, a push time, and a push content;
the information characteristic comprises at least one of gender, age, educational background and wedding status;
the resume features include at least one of resume integrity, job hunting status, job hunting industry, expected salary, and job hunting type.
In this embodiment, the terminal system type may refer to a system type of a terminal used by the push object, and may be an android or an IOS; the push time may refer to the time for pushing the message information; the push content may refer to specific content of the message information that needs to be pushed and is set according to the service requirement.
The resume completion degree can be expressed by percentage, the resume is completely filled, and the resume completion degree is one hundred percent; job hunting states may include lost work, on duty, and pending work; the job hunting types may include full time, part time, and practice.
By determining the basic characteristics, the message information meeting the threshold constraint condition can be pushed and blocked by utilizing a pre-trained message blocking model, so that the target user of message pushing is more accurate, and the user is prevented from being disturbed.
In the technical scheme, optionally, the behavior characteristics include an active time characteristic, a delivery characteristic, a communication characteristic, a search position characteristic and a login characteristic;
wherein the active time characteristics comprise at least one of resume modification time, resume viewing time, resume refreshing time, resume delivery time and IM communication time;
the delivery characteristics comprise delivery resume times in a preset time period;
the communication characteristics comprise communication initiating times within a preset time period;
the search position characteristics comprise the number of search position times in a preset time period;
the login characteristics include login times within a preset time period.
In the scheme, the active time characteristic may refer to last resume modification time, resume viewing time, resume refreshing time, resume delivery time and IM communication time, or may refer to multiple resume modification time, resume viewing time, resume refreshing time, resume delivery time and IM communication time.
The preset time period can be set according to the service requirement. Preferably, the preset time period may refer to 1, 2, 3, 4, 5, 6, 7, 15, 30 days, or the like.
In this embodiment, the search position feature may be both active search and passive search.
By determining the behavior characteristics, the message information meeting the threshold constraint condition can be pushed and blocked by utilizing a pre-trained message blocking model, so that the target user of message pushing is more accurate, and the user is prevented from being disturbed.
And S120, taking the target characteristics as input, and training the target characteristics by using a pre-trained message blocking model to obtain an output result.
In this scheme, the output result may refer to a result of predicting the target feature by the message blocking model. Preferably, the output result may refer to a user click rate.
In this technical solution, optionally, the training process of the message blocking model includes:
acquiring historical message push logs of a preset number of users, and determining data to be processed according to the historical message push logs;
preprocessing the data to be processed to obtain training sample data;
inputting the training sample data into an initial model, and training the initial model according to a pushing result label of the training sample data to obtain a message blocking model.
The historical message push logs of the users with the preset number can be set according to the training requirements of the initial test model. Preferably, the history message push logs of the preset number of users are history message push logs of a million number of users within 30 days.
In this embodiment, the training sample data may refer to data to be processed represented in a numerical form. The method comprises the steps of reading a historical message push log to obtain data to be processed, preprocessing the data to be processed, and converting the data to be processed in a text form into training sample data in a numerical value form. When data to be processed is preprocessed, part of the data needs to be subjected to one-hot coding, namely, the push characteristic needs to be subjected to one-hot coding. One-hot encoding uses an N-bit status register to encode N states, each state having its own independent register bit and only one of which is active at any one time.
In this scheme, the push result tag may be a tag in a numerical form. I.e. the training sample data is represented in numerical form. For example, the information characteristics of the push object of the training sample data include male and female, and male may be represented by 0 and female may be represented by 1.
In this embodiment, the initial model may be a model such as LR (Logistic Regression), xgboost (extreme Gradient boosting), GBDT + FM, or tensoflow. LR is a classification model in machine learning, and the objective of classifying data into two classes is achieved by solving parameters by gradient descent. The XGboost is an optimized distributed gradient enhancement library and is mainly used for solving the problem of supervised learning. GBDT (Gradient Boosting Decision Tree) is an iterative Decision Tree algorithm using pre-pruning, which consists of a plurality of Decision trees, and the conclusions of all the trees are accumulated to be the final answer. The model is a relatively common Machine learning algorithm, and includes multiple layers of networks, where one layer of network is the FM. TensorFlow is a symbolic mathematical system based on data flow programming, and is widely applied to programming realization of various machine learning algorithms. Preferably, the initial model may be XGBoost.
Specifically, the data to be processed is obtained by reading a preset number of historical message push logs, the data to be processed is converted into training sample data which can be identified by an initial model, the training sample data is divided into a training set and a test set to be trained in the initial model, coarse-grained parameter optimization is performed by adopting grid search parameters, and a message blocking model is obtained. And the grid searching parameters are used for selecting the optimal hyper-parameters of the model.
The initial model is trained in advance to obtain the message blocking model, and the message information meeting the threshold constraint condition can be pushed and blocked based on the message blocking model, so that the target user of message pushing is more accurate, and the user is prevented from being disturbed.
And S130, if the output result meets the preset threshold constraint condition, carrying out message pushing blocking.
It can be understood that if the output result does not meet the preset threshold constraint condition, the output result meets the requirement of the target user, and at this time, the message information can be directly pushed to the push object; if the output result meets the preset threshold constraint condition, the output result does not meet the requirement of the pushing object, namely the pushing message may not meet the interest of the pushing object or the pushing time causes disturbance to the pushing object, and at the moment, pushing blocking processing is performed on the message information.
According to the technical scheme provided by the embodiment of the application, the target characteristics of the push object are determined according to the push object of the message push request; wherein the target features comprise basic features and behavior features; taking the target characteristics as input, and training the target characteristics by using a pre-trained message blocking model to obtain an output result; and if the output result meets the preset threshold constraint condition, carrying out message pushing blocking. By executing the technical scheme, the message information meeting the threshold constraint condition can be pushed and blocked by utilizing the pre-trained message blocking model, so that the target user of message pushing is more accurate, and the user is prevented from being disturbed.
Example two
Fig. 2 is a schematic diagram of a message push blocking process provided in the second embodiment of the present application, and the second embodiment is further optimized based on the first embodiment. The concrete optimization is as follows: after the message push blocking, the method further comprises: storing the message information, the output result and the blocking result of the push message to a push log; wherein the message information of the push message is determined according to the message push request. The details which are not described in detail in this embodiment are shown in the first embodiment. As shown in fig. 2, the method comprises the steps of:
s210, determining target characteristics of a push object according to the push object of the message push request; wherein the target features include base features and behavior features.
S220, the target features are used as input, and a pre-trained message blocking model is used for training the target features to obtain an output result.
And S230, if the output result meets the preset threshold constraint condition, carrying out message pushing blocking.
S240, storing the message information, the output result and the blocking result of the push message to a push log; wherein the message information of the push message is determined according to the message push request.
In this embodiment, the blocking result may refer to a result of blocking message information pushing, and may include blocking and non-blocking. When the output result meets the preset threshold constraint condition, the blocking result is to carry out blocking; and when the output result does not meet the preset threshold constraint condition, the blocking result is that blocking is not performed.
In this technical solution, optionally, after saving the message information, the output result, and the blocking result of the push message to the push log, the method further includes:
if the preset message blocking model optimization period is reached, optimizing a message blocking model according to the push log;
alternatively, the first and second electrodes may be,
if the number of the push logs reaches the preset message blocking model optimization number, optimizing a message blocking model according to the push logs;
alternatively, the first and second electrodes may be,
if the push log comprises a preset message blocking model optimization factor, optimizing a message blocking model according to the push log; and the message blocking model optimization factor comprises the blocking result of blocking.
In this embodiment, the message blocking model may perform performance optimization periodically according to an optimization period, and specifically, the optimization may be to adjust parameters of the message blocking model comprehensively according to the message information, the output result, and the blocking result recorded in the push log, so that the prediction result of the message blocking model is more accurate. The message pushing model can be optimized by monitoring the number of the pushed logs and when the number of the pushed logs reaches the preset message blocking model optimization number.
In the scheme, if the push log is detected to include the preset message blocking model optimization factor, the message blocking model can be optimized according to the push log.
By continuously optimizing the message blocking model, the accuracy of the message blocking model in message information pushing blocking can be improved, and ineffective pushing is reduced.
According to the technical scheme provided by the embodiment of the application, the target characteristics of the push object are determined according to the push object of the message push request; wherein the target features comprise basic features and behavior features; taking the target characteristics as input, and training the target characteristics by using a pre-trained message blocking model to obtain an output result; and if the output result meets the preset threshold constraint condition, carrying out message pushing blocking. And storing the message information, the output result and the blocking result of the push message to a push log. By executing the technical scheme, the message pushing meeting the threshold constraint condition can be pushed and blocked by utilizing the pre-trained message blocking model, so that the target user of the message pushing is more accurate, and the user is prevented from being disturbed. Meanwhile, the accuracy rate of the message blocking model for message information pushing blocking can be improved, and invalid pushing is reduced.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a message push blocking apparatus according to a third embodiment of the present application, and as shown in fig. 3, the message push blocking apparatus includes:
a target characteristic determining module 310, configured to determine a target characteristic of a push object according to the push object of the message push request; wherein the target features comprise base features and behavior features;
an output result obtaining module 320, configured to take the target feature as an input, train the target feature by using a pre-trained message blocking model, and obtain an output result;
and the message pushing blocking module 330 is configured to block message pushing if the output result meets a preset threshold constraint condition.
In this technical solution, optionally, the output result obtaining module 320 includes:
the device comprises a to-be-processed data determining unit, a processing unit and a processing unit, wherein the to-be-processed data determining unit is used for acquiring historical message push logs of a preset number of users and determining to-be-processed data according to the historical message push logs;
a training sample data obtaining unit, configured to pre-process the data to be processed to obtain training sample data;
and the message blocking model obtaining unit is used for inputting the training sample data into an initial model, and training the initial model according to a pushing result label of the training sample data to obtain a message blocking model.
In this embodiment, optionally, the target characteristic determining module 310 includes:
a push object ID determination unit, configured to determine a push object ID according to the message push request;
and the target characteristic calling unit is used for calling the target characteristics of the push object from a user resource database and a push result database according to the ID of the push object.
In this technical solution, optionally, the apparatus further includes:
the push message storage module is used for storing the message information, the output result and the blocking result of the push message to a push log; wherein the message information of the push message is determined according to the message push request.
In this technical solution, optionally, the apparatus further includes:
the message blocking model optimizing module is used for optimizing the message blocking model according to the push log if a preset message blocking model optimizing period is reached;
alternatively, the first and second electrodes may be,
if the number of the push logs reaches the preset message blocking model optimization number, optimizing a message blocking model according to the push logs;
alternatively, the first and second electrodes may be,
if the push log comprises a preset message blocking model optimization factor, optimizing a message blocking model according to the push log; and the message blocking model optimization factor comprises the blocking result of blocking.
In this technical solution, optionally, the basic features include a push feature, an information feature, and a resume feature;
wherein the push characteristics comprise at least one of a terminal system type, a push time, and a push content;
the information characteristic comprises at least one of gender, age, educational background and wedding status;
the resume features include at least one of resume integrity, job hunting status, job hunting industry, expected salary, and job hunting type.
In the technical scheme, optionally, the behavior characteristics include an active time characteristic, a delivery characteristic, a communication characteristic, a search position characteristic and a login characteristic;
wherein the active time characteristics comprise at least one of resume modification time, resume viewing time, resume refreshing time, resume delivery time and IM communication time;
the delivery characteristics comprise delivery resume times in a preset time period;
the communication characteristics comprise communication initiating times within a preset time period;
the search position characteristics comprise the number of search position times in a preset time period;
the login characteristics include login times within a preset time period.
The product can execute the method provided by the embodiment of the application, and has the corresponding functional modules and beneficial effects of the execution method.
Example four
Embodiments of the present application also provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform a message push blocking method, the method including:
determining target characteristics of a push object according to the push object of the message push request; wherein the target features comprise base features and behavior features;
taking the target characteristics as input, and training the target characteristics by using a pre-trained message blocking model to obtain an output result;
and if the output result meets the preset threshold constraint condition, carrying out message pushing blocking.
Storage medium-any of various types of memory devices or storage devices. The term "storage medium" is intended to include: mounting media such as CD-ROM, floppy disk, or tape devices; computer system memory or random access memory such as DRAM, DDR RAM, SRAM, EDO RAM, Lanbas (Rambus) RAM, etc.; non-volatile memory such as flash memory, magnetic media (e.g., hard disk or optical storage); registers or other similar types of memory elements, etc. The storage medium may also include other types of memory or combinations thereof. In addition, the storage medium may be located in the computer system in which the program is executed, or may be located in a different second computer system connected to the computer system through a network (such as the internet). The second computer system may provide the program instructions to the computer for execution. The term "storage medium" may include two or more storage media that may reside in different locations, such as in different computer systems that are connected by a network. The storage medium may store program instructions (e.g., embodied as a computer program) that are executable by one or more processors.
Of course, the storage medium provided in this embodiment of the present application contains computer-executable instructions, and the computer-executable instructions are not limited to the message push blocking operation described above, and may also perform related operations in the message push blocking method provided in any embodiment of the present application.
EXAMPLE five
The embodiment of the application provides electronic equipment, and the message pushing blocking device provided by the embodiment of the application can be integrated in the electronic equipment. Fig. 4 is a schematic structural diagram of an electronic device according to a fifth embodiment of the present application. As shown in fig. 4, the present embodiment provides an electronic device 400, which includes: one or more processors 420; the storage device 410 is configured to store one or more programs, and when the one or more programs are executed by the one or more processors 420, the one or more processors 420 implement the message push blocking method provided in the embodiment of the present application, the method includes:
determining target characteristics of a push object according to the push object of the message push request; wherein the target features comprise base features and behavior features;
taking the target characteristics as input, and training the target characteristics by using a pre-trained message blocking model to obtain an output result;
and if the output result meets the preset threshold constraint condition, carrying out message pushing blocking.
Of course, those skilled in the art can understand that the processor 420 also implements the technical solution of the message push blocking method provided in any embodiment of the present application.
The electronic device 400 shown in fig. 4 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 4, the electronic device 400 includes a processor 420, a storage device 410, an input device 430, and an output device 440; the number of the processors 420 in the electronic device may be one or more, and one processor 420 is taken as an example in fig. 4; the processor 420, the storage device 410, the input device 430, and the output device 440 in the electronic apparatus may be connected by a bus or other means, and are exemplified by a bus 450 in fig. 4.
The storage device 410 is a computer-readable storage medium, and can be used to store software programs, computer-executable programs, and module units, such as program instructions corresponding to the message push blocking method in the embodiment of the present application.
The storage device 410 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the storage 410 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, storage 410 may further include memory located remotely from processor 420, which may be connected via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input means 430 may be used to receive input numbers, character information, or voice information, and to generate key signal inputs related to user settings and function control of the electronic device. The output device 440 may include a display screen, speakers, or other electronic equipment.
The electronic equipment provided by the embodiment of the application can achieve the purposes of pushing and blocking the message pushing meeting the threshold constraint condition by utilizing the pre-trained message blocking model, so that the target user of the message pushing is more accurate, and the user is prevented from being disturbed.
The message push blocking device, the storage medium and the electronic device provided in the above embodiments may execute the message push blocking method provided in any embodiment of the present application, and have corresponding functional modules and beneficial effects for executing the method. Technical details that are not described in detail in the above embodiments may be referred to a message push blocking method provided in any embodiments of the present application.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present application and the technical principles employed. It will be understood by those skilled in the art that the present application is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the application. Therefore, although the present application has been described in more detail with reference to the above embodiments, the present application is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present application, and the scope of the present application is determined by the scope of the appended claims.
Claims (10)
1. A message push blocking method, comprising:
determining target characteristics of a push object according to the push object of the message push request; wherein the target features comprise base features and behavior features;
taking the target characteristics as input, and training the target characteristics by using a pre-trained message blocking model to obtain an output result;
and if the output result meets the preset threshold constraint condition, carrying out message pushing blocking.
2. The method of claim 1, wherein the training process of the message blocking model comprises:
acquiring historical message push logs of a preset number of users, and determining data to be processed according to the historical message push logs;
preprocessing the data to be processed to obtain training sample data;
inputting the training sample data into an initial model, and training the initial model according to a pushing result label of the training sample data to obtain a message blocking model.
3. The method of claim 1, wherein determining the target characteristic of the push object according to the push object of the message push request comprises:
determining a pushing object ID according to the message pushing request;
and calling the target characteristics of the push object from a user resource database and a push result database according to the ID of the push object.
4. The method of claim 1, wherein after performing message push blocking, the method further comprises:
storing the message information, the output result and the blocking result of the push message to a push log; wherein the message information of the push message is determined according to the message push request.
5. The method of claim 4, wherein after saving the message information, the output result, and the blocking result of the push message to a push log, the method further comprises:
if the preset message blocking model optimization period is reached, optimizing a message blocking model according to the push log;
alternatively, the first and second electrodes may be,
if the number of the push logs reaches the preset message blocking model optimization number, optimizing a message blocking model according to the push logs;
alternatively, the first and second electrodes may be,
if the push log comprises a preset message blocking model optimization factor, optimizing a message blocking model according to the push log; and the message blocking model optimization factor comprises the blocking result of blocking.
6. The method of claim 1, wherein the base features include a push feature, an information feature, and a resume feature;
wherein the push characteristics comprise at least one of a terminal system type, a push time, and a push content;
the information characteristic comprises at least one of gender, age, educational background and wedding status;
the resume features include at least one of resume integrity, job hunting status, job hunting industry, expected salary, and job hunting type.
7. The method of claim 1, wherein the behavioral characteristics include an active time characteristic, a delivery characteristic, a communication characteristic, a search position characteristic, and a login characteristic;
wherein the active time characteristics comprise at least one of resume modification time, resume viewing time, resume refreshing time, resume delivery time and IM communication time;
the delivery characteristics comprise delivery resume times in a preset time period;
the communication characteristics comprise communication initiating times within a preset time period;
the search position characteristics comprise the number of search position times in a preset time period;
the login characteristics include login times within a preset time period.
8. A message push blocking device, comprising:
the target characteristic determining module is used for determining the target characteristics of the push object according to the push object of the message push request; wherein the target features comprise base features and behavior features;
an output result obtaining module, configured to train the target feature by using a pre-trained message blocking model with the target feature as an input to obtain an output result;
and the message pushing blocking module is used for carrying out message pushing blocking if the output result meets the constraint condition of a preset threshold value.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the message push blocking method according to any one of claims 1 to 7.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the message push blocking method according to any one of claims 1 to 7 when executing the computer program.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202110351698.1A CN112989201A (en) | 2021-03-31 | 2021-03-31 | Message pushing blocking method and device, storage medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN103778228A (en) * | 2014-01-24 | 2014-05-07 | 五八同城信息技术有限公司 | Method for realizing directional promotion of resume information by utilizing instant messaging system |
| CN104462594A (en) * | 2014-12-29 | 2015-03-25 | 北京奇虎科技有限公司 | Method and device for providing user personalized resource message pushing |
| CN109558529A (en) * | 2018-10-22 | 2019-04-02 | 平安科技（深圳）有限公司 | Method, apparatus, computer equipment and the storage medium of resume audit |
| CN111478963A (en) * | 2020-04-07 | 2020-07-31 | 北京奇艺世纪科技有限公司 | Message pushing method and device, electronic equipment and computer readable storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN103778228A (en) * | 2014-01-24 | 2014-05-07 | 五八同城信息技术有限公司 | Method for realizing directional promotion of resume information by utilizing instant messaging system |
| CN104462594A (en) * | 2014-12-29 | 2015-03-25 | 北京奇虎科技有限公司 | Method and device for providing user personalized resource message pushing |
| CN109558529A (en) * | 2018-10-22 | 2019-04-02 | 平安科技（深圳）有限公司 | Method, apparatus, computer equipment and the storage medium of resume audit |
| CN111478963A (en) * | 2020-04-07 | 2020-07-31 | 北京奇艺世纪科技有限公司 | Message pushing method and device, electronic equipment and computer readable storage medium |
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