CN116091157A - Resource pushing method and device, storage medium and computer equipment - Google Patents
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Abstract
The application discloses a resource pushing method and device, a storage medium and computer equipment, wherein the method comprises the following steps: acquiring historical order information of a vehicle charging service platform, counting historical charging records of each historical user according to the historical user information and the historical charging information, and mapping the historical users into a plurality of preset categories according to the historical charging records; constructing a classification model training sample according to historical user information corresponding to a plurality of preset categories, and training a user classification model through the classification model training sample; responding to the access signal of the vehicle charging service platform, classifying the target access users according to the target access user information through the trained user classification model, pushing the preferential resources according to the target access user types, automatically dividing different types by classifying the target access users, and pushing different preferential strategies for different user types, thereby improving the convenience and accuracy of pushing the preferential resources.
Description
Technical Field
The present invention relates to the field of internet technologies, and in particular, to a method and apparatus for pushing resources, a storage medium, and a computer device.
Background
With the development of new energy technologies, new energy automobiles are increasingly popularized, demands of charging stations are increasingly larger, and due to the fact that charging time of the new energy automobiles is longer, problems such as crowding of charging vehicles occur in individual charging stations, and in order to benefit mutually, the charging stations cooperate with each electronic commerce platform, the electronic commerce platform usually attracts users through sending electronic coupon information to push the coupons, and in the related art, the electronic commerce platform pushes the coupons through sending the coupons to each user, but the utilization rate of users participating in the coupons is lower, and the utilization frequency of the users and the experience of the users are not improved.
Disclosure of Invention
In view of the above, the present application provides a resource pushing method and apparatus, a storage medium, and a computer device, which implement that target access users can be classified only by acquiring target access information of the target access users, different user types are automatically divided, and different preference policies are pushed for different user types, so that convenience and accuracy of preference resource pushing are improved, and further experience of the users is improved.
According to one aspect of the present application, there is provided a resource pushing method, the method including:
Acquiring historical order information of a vehicle charging service platform, wherein the historical order information comprises historical user information and historical charging information;
according to the historical user information and the historical charging information, counting the historical charging record of each historical user, and according to the historical charging record, mapping the historical user into a plurality of preset categories;
constructing a classification model training sample according to historical user information corresponding to a plurality of preset categories, and training a user classification model through the classification model training sample;
and responding to the access signal of the vehicle charging service platform, classifying the target access user according to the target access user information through the trained user classification model, and pushing preferential resources according to the target access user category.
Optionally, the historical charging information includes a historical charging electricity price, and a plurality of preset categories are respectively preset with a corresponding charging frequency range and charging electricity price characteristics;
the step of counting the historical charging records of each historical user according to the historical user information and the historical charging information, and mapping the historical users into a plurality of preset categories according to the historical charging records, comprises the following steps:
According to the historical user information and the historical charging electricity prices, historical charging frequency and historical charging electricity price statistics data of each historical user are counted, wherein the historical charging records comprise the historical charging frequency and the historical charging electricity price statistics data, and the historical charging electricity price statistics data are any one of historical charging electricity price average values, historical charging electricity price median values and historical charging electricity price distribution curves;
for any historical user, determining candidate categories in a plurality of preset categories according to the historical charging frequency of the any historical user, and mapping the any historical user into matched candidate categories according to the historical charging price statistics data of the any historical user and the charging price characteristics of the candidate categories.
Optionally, the constructing a training sample of the classification model according to the historical user information corresponding to the plurality of preset categories includes:
for any preset category, acquiring historical user information mapped to the preset category, and constructing a classification model training sample corresponding to the preset category according to the historical user information and a category label of the preset category, wherein the historical user information comprises historical user identity information and historical user vehicle information;
Accordingly, the classifying the target access user according to the target access user information through the trained user classification model comprises the following steps:
acquiring target access user information, wherein the target access user information comprises registration identity information and registration vehicle information of a target access user;
and inputting the target access user information into a trained user classification model, obtaining a target class label output by the user classification model, and determining a preset class corresponding to the target class label as the target access user class.
Optionally, the pushing the preferential resource according to the target access user category includes:
obtaining a preferential strategy corresponding to the target access user category, wherein the preferential strategy comprises preferential resources corresponding to at least one access stage, and the multiple access stages comprise at least one of an initial access stage, a charging service browsing stage, an order achievement stage and an access ending stage;
pushing the preferential resources corresponding to the initial access stage in the preferential strategy to the target access user, and pushing the preferential resources according to the access stage which the target access user enters when the target access user enters other access stages.
Optionally, the acquiring the target access user information includes:
judging whether the target access user is a new user of the vehicle charging service platform;
if the target access user is a new user of the vehicle charging service platform, acquiring target access user information;
if the target access user is not a new user of the vehicle charging service platform, acquiring first reference order information submitted by the target access user in a preset history period, counting first reference charging records of the target access user according to the first reference order information, determining a first reference category of the target access user according to the first reference charging records, and pushing preferential resources matched with the first reference category.
Optionally, when the target access user enters other access phases, pushing the preferential resource according to the access phase entered by the target access user includes:
collecting second reference order information submitted by the target access user in a preset future period, counting second reference charging records of the target access user according to the second reference order information, and determining a second reference category of the target access user according to the second reference charging records;
And when the second reference category is different from the target access user category, pushing preferential resources to the target access user according to the second reference category.
Optionally, the method further comprises:
acquiring a plurality of preset charging frequency ranges and a plurality of preset charging electricity price characteristics;
combining any preset charging frequency range with any preset charging electricity price characteristic, and determining a plurality of preset categories according to a combination result;
setting a corresponding preferential strategy for each preset category.
According to another aspect of the present application, there is provided a resource pushing device, the device comprising:
the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring historical order information of a vehicle charging service platform, and the historical order information comprises historical user information and historical charging information;
the mapping module is used for counting the historical charging record of each historical user according to the historical user information and the historical charging information, and mapping the historical user into a plurality of preset categories according to the historical charging record;
the training module is used for constructing a classification model training sample according to historical user information corresponding to a plurality of preset categories, and training a user classification model through the classification model training sample;
And the pushing module is used for responding to the access signal of the vehicle charging service platform, classifying the target access user according to the target access user information through the trained user classification model, and pushing preferential resources according to the target access user category.
Optionally, the historical charging information includes a historical charging electricity price, and a plurality of preset categories are respectively preset with a corresponding charging frequency range and charging electricity price characteristics;
the mapping module is further configured to count historical charging frequency and historical charging price statistics data of each historical user according to the historical user information and the historical charging price, where the historical charging record includes the historical charging frequency and the historical charging price statistics data, and the historical charging price statistics data is any one of a historical charging price average value, a historical charging price median value and a historical charging price distribution curve;
for any historical user, determining candidate categories in a plurality of preset categories according to the historical charging frequency of the any historical user, and mapping the any historical user into matched candidate categories according to the historical charging price statistics data of the any historical user and the charging price characteristics of the candidate categories.
Optionally, the training module is further configured to obtain, for any preset category, historical user information mapped to the preset category, and construct a classification model training sample corresponding to the preset category according to the historical user information and a category label of the preset category, where the historical user information includes historical user identity information and historical user vehicle information;
correspondingly, the device further comprises: a classification module for:
acquiring target access user information, wherein the target access user information comprises registration identity information and registration vehicle information of a target access user;
and inputting the target access user information into a trained user classification model, obtaining a target class label output by the user classification model, and determining a preset class corresponding to the target class label as the target access user class.
Optionally, the pushing module is further configured to:
obtaining a preferential strategy corresponding to the target access user category, wherein the preferential strategy comprises preferential resources corresponding to at least one access stage, and the multiple access stages comprise at least one of an initial access stage, a charging service browsing stage, an order achievement stage and an access ending stage;
Pushing the preferential resources corresponding to the initial access stage in the preferential strategy to the target access user, and pushing the preferential resources according to the access stage which the target access user enters when the target access user enters other access stages.
Optionally, the acquiring module is further configured to:
judging whether the target access user is a new user of the vehicle charging service platform;
if the target access user is a new user of the vehicle charging service platform, acquiring target access user information;
if the target access user is not a new user of the vehicle charging service platform, acquiring first reference order information submitted by the target access user in a preset history period, counting first reference charging records of the target access user according to the first reference order information, determining a first reference category of the target access user according to the first reference charging records, and pushing preferential resources matched with the first reference category.
Optionally, the pushing module is further configured to:
collecting second reference order information submitted by the target access user in a preset future period, counting second reference charging records of the target access user according to the second reference order information, and determining a second reference category of the target access user according to the second reference charging records;
And when the second reference category is different from the target access user category, pushing preferential resources to the target access user according to the second reference category.
Optionally, the apparatus further comprises: a setting module for:
acquiring a plurality of preset charging frequency ranges and a plurality of preset charging electricity price characteristics;
combining any preset charging frequency range with any preset charging electricity price characteristic, and determining a plurality of preset categories according to a combination result;
setting a corresponding preferential strategy for each preset category.
According to still another aspect of the present application, there is provided a storage medium having stored thereon a computer program which when executed by a processor implements the above-described resource pushing method.
According to still another aspect of the present application, there is provided a computer device including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, the processor implementing the above-mentioned resource pushing method when executing the program.
By means of the technical scheme, the resource pushing method, the resource pushing device, the storage medium and the computer equipment are used for acquiring the historical order information of the vehicle charging service platform, wherein the historical order information comprises historical user information and historical charging information; according to the historical user information and the historical charging information, counting the historical charging record of each historical user, and mapping the historical users into a plurality of preset categories according to the historical charging record; constructing a classification model training sample according to historical user information corresponding to a plurality of preset categories, and training a user classification model through the classification model training sample; in response to the access signal of the vehicle charging service platform, the target access user is classified according to the target access user information through the trained user classification model, and preferential resource pushing is carried out according to the target access user category, so that the purposes that the target access user can be classified only by acquiring the target access information of the target access user, different user types are automatically classified, different preferential strategies are pushed according to the different user types, and convenience and accuracy of preferential resource pushing are improved.
The foregoing description is only an overview of the technical solutions of the present application, and may be implemented according to the content of the specification in order to make the technical means of the present application more clearly understood, and in order to make the above-mentioned and other objects, features and advantages of the present application more clearly understood, the following detailed description of the present application will be given.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
fig. 1 shows a flow diagram of a resource pushing method provided in an embodiment of the present application;
fig. 2 is a schematic flow chart of another resource pushing method according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a resource pushing device according to an embodiment of the present application;
fig. 4 shows a schematic device structure of a computer device according to an embodiment of the present application.
Detailed Description
The present application will be described in detail hereinafter with reference to the accompanying drawings in conjunction with embodiments. It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other.
In this embodiment, a method for pushing resources is provided, as shown in fig. 1, where the method includes:
The embodiment of the application can be applied to any vehicle charging service platform to push preferential resources for users. In the embodiment of the application, first, historical order information of a vehicle charging service platform is obtained, wherein the historical order information comprises historical user information and historical charging information. Specifically, the historical order information of the vehicle charging service platform is obtained, wherein the historical order information includes historical user information and historical charging information, for example, which users charge on the vehicle charging service platform, which time period the users charge, the charging time, the charging price and other historical order information are prepared for the next mapping establishment.
And then, according to the historical user information and the historical charging information, counting the historical charging record of each historical user, and according to the historical charging record, mapping the historical user into a plurality of preset categories. Specifically, according to the obtained historical user information and the historical charging information, statistics of the historical charging record of each user in the vehicle charging service platform includes: and mapping each historical user into a corresponding preset category according to the historical charging records so as to classify the users at a later stage.
and then, constructing a classification model training sample according to historical user information corresponding to a plurality of preset categories, and training a user classification model through the classification model sample. Specifically, the user classification model comprises a plurality of preset categories, a classification model training sample is established according to the historical user information corresponding to each preset category, the user classification model is trained according to the classification model training sample, the crowd change of daily transaction users is effectively observed, different users are divided into different preset types, and the user classification model is convenient to push preferential resources for different types of users.
And 104, responding to the access signal of the vehicle charging service platform, classifying the target access user according to the target access user information through the trained user classification model, and pushing preferential resources according to the target access user type.
Then, in response to the access signal to the vehicle charging service platform, classifying the target access user according to the target access information through the trained user classification model, and pushing preferential resources according to the target access user category, specifically, the user can enter the vehicle charging service platform through an application program installed on the smart phone, and the vehicle charging service platform comprises: fast, special, ten thousand city, etc., for example: the user enters the quick electric vehicle charging service platform by installing the quick electric vehicle charging application program, when the user accesses the quick electric vehicle charging service platform, the quick electric vehicle charging service platform judges the attribute of the target access user through the target access information by using the trained user classification model to classify, pushes different preferential resources according to different user classifications, and achieves the purpose of designating different preferential strategies for different user types.
By applying the technical scheme of the embodiment, the historical order information of the vehicle charging service platform is obtained, wherein the historical order information comprises historical user information and historical charging information; according to the historical user information and the historical charging information, counting the historical charging record of each historical user, and mapping the historical users into a plurality of preset categories according to the historical charging record; constructing a classification model training sample according to historical user information corresponding to a plurality of preset categories, and training a user classification model through the classification model training sample; in response to the access signal of the vehicle charging service platform, the target access users are classified according to the target access user information through the trained user classification model, and preferential resource pushing is carried out according to the target access user types, so that the purposes that the target access users can be classified only by acquiring the target access information of the target access users, different user types are automatically classified, different preferential strategies are pushed for different users, and convenience and accuracy of preferential resource pushing are improved.
Further, as a refinement and extension of the foregoing embodiment, in order to fully describe a specific implementation process of the embodiment, another resource pushing method is provided, where the historical charging information includes a historical charging electricity price, and a plurality of preset categories are preset with a corresponding charging frequency range and charging electricity price characteristics, as shown in fig. 2, and the method includes:
In the foregoing embodiment of the present application, first, historical order information of a vehicle charging service platform is obtained, where the historical order information includes historical user information and historical charging information, the historical user information includes a user name and vehicle information of a user, the historical charging information includes a historical charging position of the user, a historical charging time, a historical charging price, and the like, and according to the historical user information and the historical charging price, historical charging frequency and historical charging price statistics data of each historical user are counted, where the historical charging record further includes the historical charging frequency and the historical charging price statistics data, and the historical charging price statistics data may be any one of a historical charging price average value, a historical charging price and a historical charging price distribution curve; for any one of the history users, determining a candidate category in the plurality of preset categories according to the history charging frequency of the any one of the history users, for example, the candidate category in the preset categories includes: the method comprises the steps of determining that a high-frequency price user, a high-frequency price middle user, a high-frequency price low user, a medium-frequency price high user, a medium-frequency price middle user, a medium-frequency price low user, a low-frequency user and the like are medium-frequency users in the preset categories according to the fact that the historical charging frequency of the users is 18 times in 30 days, determining which candidate category of the medium-frequency users the historical users belong to according to historical charging electricity price statistical data of the historical users and charging electricity price characteristics of the medium-frequency users in the candidate categories, and mapping the historical users into the matched candidate categories. And determining candidate categories in a plurality of preset categories corresponding to the historical user through the historical charging frequency of any one historical user, mapping the historical user into a matched candidate category according to the historical charging price statistical data and charging price characteristics of the historical user, and further dividing the user and matching the category suitable for the user.
Next, for any preset category, acquiring historical user information of each historical user mapped to the preset category, wherein the historical user information comprises historical user identity information and historical user vehicle information, constructing a classification model training sample corresponding to the preset category according to the historical user information and category labels of the preset category, and training a user classification model through the classification model training sample. For example, the candidate categories in the preset categories include: the method comprises the steps of obtaining historical user information of each historical user under a high-frequency high-user type, constructing a classification model training sample of the high-frequency high-user type according to the historical user information of each high-frequency high-user and a label of high-frequency high-user, training a user classification model by utilizing the classification model training sample so as to classify the user by utilizing the user classification model, further obtaining different user classification models by utilizing different samples, and conveniently formulating different preferential strategies for different types of users.
And then, in response to an access signal to the vehicle charging service platform, acquiring target access user information, wherein the target access user information comprises registered identity information and registered vehicle information of a target access user, inputting the target access user information into a trained user classification model, acquiring a target class label output by the user classification model, and determining a preset class corresponding to the target class label as the target access user class. And responding to the access signal of the rapid electric vehicle charging service platform, acquiring target access user information, inputting the target access user information into a trained user classification model, for example, acquiring a target class label of the target user A as high-frequency high-price, and determining a high-frequency high-price user type corresponding to the high-frequency high-price as the target access user class of the target user A.
Step 204, obtaining the preferential strategy corresponding to the category of the target access user, pushing preferential resources corresponding to the initial access stage in the preferential strategy to the target access user, and pushing the preferential resources according to the access stage entered by the target access user when the target access user enters other access stages.
Next, obtaining a preferential policy corresponding to the target access user category, for example, the target access user category includes price sensitivity, subsidies can be issued for the user of the type, the target access user category also includes non-member high-frequency type, member guidance can be performed for the user of the type, member related preferential and interests are pushed, and different preferential policies are pushed for different user categories; the preferential strategy comprises preferential resources corresponding to at least one access stage, and the access stages comprise at least one of an initial access stage, a charging service browsing stage, an order achievement stage and an access ending stage; pushing the preferential resources corresponding to the initial access stage in the preferential strategy to the target access user, and pushing the preferential resources corresponding to the access stage entered by the target access user when the target access user enters other access stages.
Optionally, the "obtaining the target access user information" in step 203 includes: judging whether the target access user is a new user of the vehicle charging service platform; if the target access user is a new user of the vehicle charging service platform, acquiring target access user information; if the target access user is not a new user of the vehicle charging service platform, acquiring first reference order information submitted by the target access user in a preset history period, counting first reference charging records of the target access user according to the first reference order information, determining a first reference category of the target access user according to the first reference charging records, and pushing preferential resources matched with the first reference category.
In the embodiment, acquiring target access user information, and judging whether the target access user is a new user of the vehicle charging service platform; if the target access user is a new user, acquiring target access user information; if the target access user is not a new user, acquiring first reference order information submitted by the target access user in a preset history period, counting first reference charging records of the target access user according to the first reference order information, determining a first reference category of the target access user according to the first reference charging records, and pushing preferential resources matched with the first reference category. When the target access user is not a new user, the type of the target access user is determined by acquiring the first reference order information in the preset historical time period, and the corresponding preferential resource is pushed, so that the accuracy of pushing the matched preferential resource is improved.
Optionally, in step 204, "pushing preferential resources according to the access phase entered by the target access user when the target access user enters other access phases" includes: collecting second reference order information submitted by the target access user in a preset future period, counting second reference charging records of the target access user according to the second reference order information, and determining a second reference category of the target access user according to the second reference charging records; and when the second reference category is different from the target access user category, pushing preferential resources to the target access user according to the second reference category.
In the above embodiment of the present application, second reference order information submitted by the target access user in a preset future period is collected, a second reference charging record of the target access user is counted according to the second reference order information, and a second reference category of the target access user is determined according to the second reference charging record; when the second reference category is different from the target access user category, the preferential resource is pushed to the target access user according to the second reference category, so that the accuracy of pushing and matching the preferential resource is improved.
Optionally, the method further comprises: acquiring a plurality of preset charging frequency ranges and a plurality of preset charging electricity price characteristics; combining any preset charging frequency range with any preset charging electricity price characteristic, and determining a plurality of preset categories according to a combination result; setting a corresponding preferential strategy for each preset category.
In the above embodiment of the present application, the method further includes: acquiring a plurality of preset charging frequency ranges and a plurality of preset charging electricity price characteristics, combining any preset charging frequency range with any preset charging electricity price characteristic, and determining a plurality of preset categories according to a combination result; setting a corresponding preferential strategy for each preset category. Multiple preset categories can be obtained through different combinations, and each preset category is provided with a corresponding preferential strategy, so that different divisions are carried out on users, and the accuracy of pushing matched preferential resources for different users is improved.
By applying the technical scheme of the embodiment, the historical order information of the vehicle charging service platform is obtained, wherein the historical order information comprises historical user information and historical charging information; according to the historical user information and the historical charging information, counting the historical charging record of each historical user, and mapping the historical users into a plurality of preset categories according to the historical charging record; constructing a classification model training sample according to historical user information corresponding to a plurality of preset categories, and training a user classification model through the classification model training sample; in response to the access signal of the vehicle charging service platform, the target access users are classified according to the target access user information through the trained user classification model, and preferential resource pushing is carried out according to the target access user types, so that the purposes that the target access users can be classified only by acquiring the target access information of the target access users, different user types are automatically classified, different preferential strategies are pushed according to different user types and different access stages of the users, and convenience and accuracy of preferential resource pushing are improved.
Further, as a specific implementation of the method of fig. 1, an embodiment of the present application provides a resource pushing device, as shown in fig. 3, where the device includes:
the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring historical order information of a vehicle charging service platform, and the historical order information comprises historical user information and historical charging information;
the mapping module is used for counting the historical charging record of each historical user according to the historical user information and the historical charging information, and mapping the historical user into a plurality of preset categories according to the historical charging record;
the training module is used for constructing a classification model training sample according to historical user information corresponding to a plurality of preset categories, and training a user classification model through the classification model training sample;
and the pushing module is used for responding to the access signal of the vehicle charging service platform, classifying the target access user according to the target access user information through the trained user classification model, and pushing preferential resources according to the target access user category.
Optionally, the historical charging information includes a historical charging electricity price, and a plurality of preset categories are respectively preset with a corresponding charging frequency range and charging electricity price characteristics;
The mapping module is further configured to count historical charging frequency and historical charging price statistics data of each historical user according to the historical user information and the historical charging price, where the historical charging record includes the historical charging frequency and the historical charging price statistics data, and the historical charging price statistics data is any one of a historical charging price average value, a historical charging price median value and a historical charging price distribution curve;
for any historical user, determining candidate categories in a plurality of preset categories according to the historical charging frequency of the any historical user, and mapping the any historical user into matched candidate categories according to the historical charging price statistics data of the any historical user and the charging price characteristics of the candidate categories.
Optionally, the training module is further configured to obtain, for any preset category, historical user information mapped to the preset category, and construct a classification model training sample corresponding to the preset category according to the historical user information and a category label of the preset category, where the historical user information includes historical user identity information and historical user vehicle information;
Correspondingly, the device further comprises: a classification module for:
acquiring target access user information, wherein the target access user information comprises registration identity information and registration vehicle information of a target access user;
and inputting the target access user information into a trained user classification model, obtaining a target class label output by the user classification model, and determining a preset class corresponding to the target class label as the target access user class.
Optionally, the pushing module is further configured to:
obtaining a preferential strategy corresponding to the target access user category, wherein the preferential strategy comprises preferential resources corresponding to at least one access stage, and the multiple access stages comprise at least one of an initial access stage, a charging service browsing stage, an order achievement stage and an access ending stage;
pushing the preferential resources corresponding to the initial access stage in the preferential strategy to the target access user, and pushing the preferential resources according to the access stage which the target access user enters when the target access user enters other access stages.
Optionally, the acquiring module is further configured to:
Judging whether the target access user is a new user of the vehicle charging service platform;
if the target access user is a new user of the vehicle charging service platform, acquiring target access user information;
if the target access user is not a new user of the vehicle charging service platform, acquiring first reference order information submitted by the target access user in a preset history period, counting first reference charging records of the target access user according to the first reference order information, determining a first reference category of the target access user according to the first reference charging records, and pushing preferential resources matched with the first reference category.
Optionally, the pushing module is further configured to:
collecting second reference order information submitted by the target access user in a preset future period, counting second reference charging records of the target access user according to the second reference order information, and determining a second reference category of the target access user according to the second reference charging records;
and when the second reference category is different from the target access user category, pushing preferential resources to the target access user according to the second reference category.
Optionally, the apparatus further comprises: a setting module for:
acquiring a plurality of preset charging frequency ranges and a plurality of preset charging electricity price characteristics;
combining any preset charging frequency range with any preset charging electricity price characteristic, and determining a plurality of preset categories according to a combination result;
setting a corresponding preferential strategy for each preset category.
It should be noted that, for other corresponding descriptions of each functional unit related to the resource pushing device provided in the embodiment of the present application, reference may be made to corresponding descriptions in the methods of fig. 1 to fig. 2, which are not repeated herein.
The embodiment of the application also provides a computer device, which may be a personal computer, a server, a network device, etc., as shown in fig. 4, where the computer device includes a bus, a processor, a memory, a communication interface, and may further include an input/output interface and a display device. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is for storing location information. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement the steps in the method embodiments.
Those skilled in the art will appreciate that the structures shown in FIG. 4 are block diagrams only and do not constitute a limitation of the computer device on which the present aspects apply, and that a particular computer device may include more or less components than those shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer readable storage medium is provided, which may be non-volatile or volatile, and on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of the method embodiments described above.
In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of the method embodiments described above.
It should be noted that, user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), 5 ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can take many forms, such as static random access Memory (Static Random Access Memory, SRAM) or dynamic random access Memory (Dynamic Random Access Memory, DRAM), among others. The databases involved in the embodiments provided herein may include relationships
At least one of a system type database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.
5 the technical features of the above embodiments may be arbitrarily combined, and for brevity of description, all of the possible combinations of the technical features of the above embodiments are not described, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the present application, which are described in detail and detail
Thin, but should not be construed as limiting the scope of the claims. It should be noted that it will be apparent to those of ordinary skill in the art that the following descriptions are also possible without departing from the spirit of the present application
Dry deformation and modification, all of which are within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.
Claims (16)
1. A method for pushing resources, the method comprising:
acquiring historical order information of a vehicle charging service platform, wherein the historical order information comprises historical user information and historical charging information;
according to the historical user information and the historical charging information, counting the historical charging record of each historical user, and according to the historical charging record, mapping the historical user into a plurality of preset categories;
constructing a classification model training sample according to historical user information corresponding to a plurality of preset categories, and training a user classification model through the classification model training sample;
and responding to the access signal of the vehicle charging service platform, classifying the target access user according to the target access user information through the trained user classification model, and pushing preferential resources according to the target access user category.
2. The method of claim 1, wherein the historical charging information comprises historical charging rates, and a plurality of preset categories are respectively preset with corresponding charging frequency ranges and charging rate characteristics;
the step of counting the historical charging records of each historical user according to the historical user information and the historical charging information, and mapping the historical users into a plurality of preset categories according to the historical charging records, comprises the following steps:
According to the historical user information and the historical charging electricity prices, historical charging frequency and historical charging electricity price statistics data of each historical user are counted, wherein the historical charging records comprise the historical charging frequency and the historical charging electricity price statistics data, and the historical charging electricity price statistics data are any one of historical charging electricity price average values, historical charging electricity price median values and historical charging electricity price distribution curves;
for any historical user, determining candidate categories in a plurality of preset categories according to the historical charging frequency of the any historical user, and mapping the any historical user into matched candidate categories according to the historical charging price statistics data of the any historical user and the charging price characteristics of the candidate categories.
3. The method of claim 1, wherein constructing the classification model training samples based on historical user information corresponding to a plurality of preset categories comprises:
for any preset category, acquiring historical user information mapped to the preset category, and constructing a classification model training sample corresponding to the preset category according to the historical user information and a category label of the preset category, wherein the historical user information comprises historical user identity information and historical user vehicle information;
Accordingly, the classifying the target access user according to the target access user information through the trained user classification model comprises the following steps:
acquiring target access user information, wherein the target access user information comprises registration identity information and registration vehicle information of a target access user;
and inputting the target access user information into a trained user classification model, obtaining a target class label output by the user classification model, and determining a preset class corresponding to the target class label as the target access user class.
4. A method according to claim 3, wherein said pushing of preferential resources according to the target access user category comprises:
obtaining a preferential strategy corresponding to the target access user category, wherein the preferential strategy comprises preferential resources corresponding to at least one access stage, and the multiple access stages comprise at least one of an initial access stage, a charging service browsing stage, an order achievement stage and an access ending stage;
pushing the preferential resources corresponding to the initial access stage in the preferential strategy to the target access user, and pushing the preferential resources according to the access stage which the target access user enters when the target access user enters other access stages.
5. The method of claim 4, wherein the obtaining the target access user information comprises:
judging whether the target access user is a new user of the vehicle charging service platform;
if the target access user is a new user of the vehicle charging service platform, acquiring target access user information;
if the target access user is not a new user of the vehicle charging service platform, acquiring first reference order information submitted by the target access user in a preset history period, counting first reference charging records of the target access user according to the first reference order information, determining a first reference category of the target access user according to the first reference charging records, and pushing preferential resources matched with the first reference category.
6. The method of claim 4, wherein the pushing of the preferential resource according to the access phase entered by the target access user when the target access user enters other access phases comprises:
collecting second reference order information submitted by the target access user in a preset future period, counting second reference charging records of the target access user according to the second reference order information, and determining a second reference category of the target access user according to the second reference charging records;
And when the second reference category is different from the target access user category, pushing preferential resources to the target access user according to the second reference category.
7. The method according to any one of claims 2 to 6, further comprising:
acquiring a plurality of preset charging frequency ranges and a plurality of preset charging electricity price characteristics;
combining any preset charging frequency range with any preset charging electricity price characteristic, and determining a plurality of preset categories according to a combination result;
setting a corresponding preferential strategy for each preset category.
8. A resource pushing device, the device comprising:
the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring historical order information of a vehicle charging service platform, and the historical order information comprises historical user information and historical charging information;
the mapping module is used for counting the historical charging record of each historical user according to the historical user information and the historical charging information, and mapping the historical user into a plurality of preset categories according to the historical charging record;
the training module is used for constructing a classification model training sample according to historical user information corresponding to a plurality of preset categories, and training a user classification model through the classification model training sample;
And the pushing module is used for responding to the access signal of the vehicle charging service platform, classifying the target access user according to the target access user information through the trained user classification model, and pushing preferential resources according to the target access user category.
9. The apparatus of claim 8, wherein the historical charging information comprises historical charging rates, and a plurality of preset categories are respectively preset with corresponding charging frequency ranges and charging rate characteristics;
the mapping module is further configured to count historical charging frequency and historical charging price statistics data of each historical user according to the historical user information and the historical charging price, where the historical charging record includes the historical charging frequency and the historical charging price statistics data, and the historical charging price statistics data is any one of a historical charging price average value, a historical charging price median value and a historical charging price distribution curve;
for any historical user, determining candidate categories in a plurality of preset categories according to the historical charging frequency of the any historical user, and mapping the any historical user into matched candidate categories according to the historical charging price statistics data of the any historical user and the charging price characteristics of the candidate categories.
10. The apparatus of claim 8, wherein the training module is further configured to obtain, for any preset category, historical user information mapped to the preset category, and construct a classification model training sample corresponding to the preset category according to the historical user information and a category label of the preset category, where the historical user information includes historical user identity information and historical user vehicle information;
correspondingly, the device further comprises: a classification module for:
acquiring target access user information, wherein the target access user information comprises registration identity information and registration vehicle information of a target access user;
and inputting the target access user information into a trained user classification model, obtaining a target class label output by the user classification model, and determining a preset class corresponding to the target class label as the target access user class.
11. The apparatus of claim 10, wherein the push module is further configured to:
obtaining a preferential strategy corresponding to the target access user category, wherein the preferential strategy comprises preferential resources corresponding to at least one access stage, and the multiple access stages comprise at least one of an initial access stage, a charging service browsing stage, an order achievement stage and an access ending stage;
Pushing the preferential resources corresponding to the initial access stage in the preferential strategy to the target access user, and pushing the preferential resources according to the access stage which the target access user enters when the target access user enters other access stages.
12. The apparatus of claim 11, wherein the acquisition module is further configured to:
judging whether the target access user is a new user of the vehicle charging service platform;
if the target access user is a new user of the vehicle charging service platform, acquiring target access user information;
if the target access user is not a new user of the vehicle charging service platform, acquiring first reference order information submitted by the target access user in a preset history period, counting first reference charging records of the target access user according to the first reference order information, determining a first reference category of the target access user according to the first reference charging records, and pushing preferential resources matched with the first reference category.
13. The apparatus of claim 11, wherein the push module is further configured to:
Collecting second reference order information submitted by the target access user in a preset future period, counting second reference charging records of the target access user according to the second reference order information, and determining a second reference category of the target access user according to the second reference charging records;
and when the second reference category is different from the target access user category, pushing preferential resources to the target access user according to the second reference category.
14. The apparatus according to any one of claims 9 to 13, further comprising: a setting module for:
acquiring a plurality of preset charging frequency ranges and a plurality of preset charging electricity price characteristics;
combining any preset charging frequency range with any preset charging electricity price characteristic, and determining a plurality of preset categories according to a combination result;
setting a corresponding preferential strategy for each preset category.
15. A storage medium having stored thereon a computer program, which when executed by a processor implements the resource pushing method of any of claims 1 to 7.
16. A computer device comprising a storage medium, a processor and a computer program stored on the storage medium and executable on the processor, characterized in that the processor implements the resource pushing method of any of claims 1 to 7 when executing the computer program.
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| CN117745350A (en) * | 2024-01-16 | 2024-03-22 | 广东星云开物科技股份有限公司 | Charging preferential scheme pushing method and device, electronic equipment and storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117745350A (en) * | 2024-01-16 | 2024-03-22 | 广东星云开物科技股份有限公司 | Charging preferential scheme pushing method and device, electronic equipment and storage medium |
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