Vehicle type data auxiliary input method, device and storage medium

Abstract

A vehicle model data assisted input method, device, and storage medium relate to the field of data input. The method comprises: in response to an operation for submitting vehicle model data, obtaining location information and historical submission data of an order submission device, where the order submission device is the device used by staff to submit vehicle model data; identifying a target merchant based on the location information; obtaining the merchant vehicle model supply data corresponding to the target merchant from a preset merchant database; obtaining a vehicle model selection probability sequence based on the merchant vehicle model supply data and historical submission data, the vehicle model selection probability sequence including vehicle model options, which are arranged in a preset order in the vehicle model selection probability sequence; and presenting the vehicle model selection probability sequence to staff to assist them in submitting vehicle model data. Implementing the technical solution provided by this application can solve the problem of low efficiency in submitting vehicle model data.

Description

Technical Field

[0001] The present application relates to the field of data input, and specifically to a vehicle model data auxiliary input method, device and storage medium. Background Art

[0002] When purchasing a commercial vehicle, customers can choose to purchase it in full or with a loan.

[0003] When a customer chooses to purchase a vehicle with a loan, the salesperson needs to submit not only the customer's financial loan information, but also various data information about the vehicle selected by the user, such as the vehicle's brand, series, length, and horsepower. In this scenario where a large number of types of data need to be submitted, it is easy for the salesperson to make errors when submitting the information, and then need to make repeated modifications, affecting the efficiency of submitting data, that is, there is a problem of low efficiency in submitting vehicle model data.

[0004] Therefore, there is an urgent need for a vehicle model data auxiliary input method, device and storage medium. Summary of the Invention

[0005] The present application provides a vehicle model data auxiliary input method, device and storage medium, which can solve the problem of low efficiency in submitting vehicle model data.

[0006] In a first aspect, the present application provides a method for assisted input of vehicle model data, the method comprising: in response to an operation for submitting vehicle model data, obtaining location information and historical submission data of an order submission device, where the order submission device is a device used by staff to submit vehicle model data; confirming a target merchant based on the location information; obtaining merchant vehicle model supply data corresponding to the target merchant from a preset merchant database; obtaining a vehicle model selection probability sequence based on the merchant vehicle model supply data and historical submission data, where the vehicle model selection probability sequence includes vehicle model options, and the vehicle model options are arranged in a preset order in the vehicle model selection probability sequence; and displaying the vehicle model selection probability sequence to the staff to assist the staff in submitting vehicle model data.

[0007] By adopting the above technical solution, the server can respond to the staff's operation of submitting vehicle model data, obtain the location information of the staff's device and historical submission data, and obtain the vehicle model data that can be provided by the merchant where the staff is currently located through the location information, that is, the merchant vehicle model supply data; then obtain the vehicle model selection probability sequence based on the historical submission data and the merchant vehicle model supply data, that is, predict the vehicle model data that the staff may choose to upload based on the staff's sales habits and the vehicle model data that the merchant can currently provide, and put the vehicle model data that the staff is more likely to choose at the front of the sequence to reduce the probability of the staff submitting vehicle model data that they are relatively unlikely to choose, thereby improving the accuracy and efficiency of the vehicle model data submitted by the staff.

[0008] Optionally, before obtaining the location information of the order device and historical submission data in response to the operation of submitting vehicle model data, the method also includes: in response to the staff's login operation, uploading the former staff data stored in the order device to the preset order database; deleting the former staff data from the order device; obtaining the staff's login information; obtaining the staff data in the preset order database based on the login information, and using the staff data as historical submission data.

[0009] By adopting the above technical solution, the server can respond to the staff's login operation, store the uploaded data previously stored in the order device into the database of the previous staff member, and delete the data locally after the upload is successful; download the historical data corresponding to the current staff member from the preset order database to the order device; this method can save and update the historical sales data of each staff member, so that different vehicle model selection probability sequences can be provided according to different staff members.

[0010] Optionally, the target merchant is confirmed based on the location information, specifically including: determining whether the order placement device is located in the area where the car dealer is located based on the location information; if the order placement device is not located in the area where the car dealer is located, obtaining a first distance and a second distance, the first distance being the distance between the first car dealer and the location information, and the second distance being the distance between the second car dealer and the location information; comparing the first distance and the second distance; if the first distance is smaller than the second distance, confirming the first car dealer as the target merchant.

[0011] By adopting the above technical solution, the server can automatically determine the car dealership where the staff member is currently located based on the location information provided by the order submission device. When there is a positioning deviation, that is, the location information shows that the order submission device is not in the area where the car dealership is located, the server can also default to the car dealership closest to the location information as the current merchant, thereby improving the efficiency of determining the merchant.

[0012] Optionally, if the first distance is less than the second distance, after confirming the first car dealer as the target merchant, the method further includes: displaying inquiry information to the staff, the inquiry information being used to inquire whether the current merchant is the target merchant; in response to the operation of confirming that the current merchant is not the target merchant, displaying a merchant list to the staff, the merchant list including the first car dealer, the first distance, the second car dealer and the second distance, wherein the first car dealer and the second car dealer are sorted from small to large distance.

[0013] By adopting the above technical solution, after the server selects the car dealer by default, it displays a prompt message to the staff to ask whether the currently selected car dealer is correct, thereby ensuring the correctness of the currently selected merchant; when the user confirms that the selection is incorrect, the merchant list is displayed to the user, and in the list, each car dealer is sorted from small to large according to the distance between the car dealer and the location information, thereby improving the efficiency of the staff in selecting the correct merchant.

[0014] Optionally, before obtaining the merchant vehicle model supply data corresponding to the target merchant in the preset merchant database, it also includes building a preset merchant database, and building the preset merchant database specifically includes: obtaining the merchant information of the target merchant, the merchant information includes the store name, address and business scope of the target merchant; obtaining the merchant vehicle model supply data, the merchant vehicle model supply data includes the target merchant's on-sale vehicle model data and the reserve quantity of on-sale vehicle models; building a corresponding relationship between the target merchant and the merchant vehicle model supply data; storing the target merchant, merchant information, merchant vehicle model supply data and the corresponding relationship in the preset merchant database to build the preset merchant database.

[0015] By adopting the above technical solution, the server can obtain the merchant information and merchant vehicle model supply data of the target merchant, build a corresponding relationship between the two, and store the target merchant, merchant information, merchant vehicle model supply data and the corresponding relationship into a preset merchant database to build a preset merchant database; when the server searches for information in the preset merchant database based on the merchant information, it can also obtain the merchant vehicle model supply data corresponding to the merchant information more efficiently based on the corresponding relationship.

[0016] Optionally, obtaining a vehicle model selection probability sequence based on the merchant vehicle model supply data and historical submission data specifically includes: classifying the merchant vehicle model supply data based on the historical submission data to obtain a first category of vehicles and a second category of vehicles, the first category of vehicles being vehicles that exist both in the historical submission data and in the merchant vehicle model supply data, and the second category of vehicles being vehicles that do not exist in the historical submission data but exist in the merchant vehicle model supply data; obtaining the total historical submission quantity of the first category of vehicles and the sub-historical submission quantity of the target vehicle model based on the historical submission data, the target vehicle model being any vehicle model in the first category; obtaining the target selection probability of the target vehicle model based on the sub-historical submission quantity and the total historical submission quantity; sorting the vehicles in the first category of vehicles in descending order according to the target selection probability to obtain a first category of vehicle model sequence; sorting the vehicles in the second category of vehicles in descending order according to the reserve quantity of vehicles on sale to obtain a second category of vehicle model sequence; connecting the second category of vehicle model sequence to the first category of vehicle model sequence to obtain a vehicle model selection probability sequence.

[0017] By adopting the above technical solution, the server can obtain a model selection probability sequence based on historical submission data and merchant model supply data; that is, based on the current merchant's existing model inventory, the models that the staff is more inclined to recommend are arranged at the front end of the model selection probability sequence through historical submission data, while those models that the staff have not uploaded but are currently provided by the merchant are arranged at the back end of the model selection probability sequence. In this way, the staff can give priority to submitting model data with a higher selection probability to reduce the probability of wrong selection.

[0018] Optionally, after displaying the vehicle model selection probability sequence to the staff to assist the staff in submitting the vehicle model data, the method also includes: in response to the staff's operation of submitting the vehicle model data, obtaining the currently selected vehicle model; judging whether there is a vehicle model in the merchant's vehicle model supply data whose configuration overlaps with the currently selected vehicle model by a degree greater than or equal to a preset threshold; if there is a vehicle model in the merchant's vehicle model supply data whose configuration overlaps with the currently selected vehicle model by a degree greater than or equal to a preset threshold, obtaining similar vehicle models and distinguishing information, the distinguishing information being the distinguishing configuration information between the currently selected vehicle model and the similar vehicle model; and displaying the similar vehicle models and distinguishing information to the staff.

[0019] By adopting the above technical solution, when there is a model with a similar configuration to the model currently selected by the staff in the merchant's model supply data, the information of the similar model and the difference information between the currently selected model can be obtained. Then, by displaying the similar model and the difference information to the staff, the staff is prompted to know that there is a similar model and whether the current model is selected correctly, thereby improving the accuracy of the model information uploaded by the staff.

[0020] In a second aspect, the present application provides a vehicle model data auxiliary input device, the device comprising an acquisition unit and a processing unit;

[0021] An acquisition unit is used to obtain the location information and historical submission data of an order submission device in response to an operation on submitting vehicle model data. The order submission device is a device used by staff to submit vehicle model data; it is also used to obtain the merchant vehicle model supply data corresponding to the target merchant in a preset merchant database; it is also used to obtain a vehicle model selection probability sequence based on the merchant vehicle model supply data and historical submission data. The vehicle model selection probability sequence includes vehicle model options, and the vehicle model options are arranged in a preset order in the vehicle model selection probability sequence.

[0022] The processing unit is used to confirm the target merchant based on the location information; it is also used to display the vehicle model selection probability sequence to the staff to assist the staff in submitting the vehicle model data.

[0023] Optionally, the processing unit is used to upload the former staff member's data stored in the order placement device to the preset order placement database in response to the staff member's login operation; delete the former staff member's data from the order placement device; the acquisition unit is used to obtain the staff member's login information; obtain the staff member data in the preset order placement database based on the login information, and submit the staff member data as historical data.

[0024] Optionally, the processing unit is used to determine whether the order placement device is located in the area where the car dealer is located based on the location information; compare the first distance and the second distance; if the first distance is smaller than the second distance, the first car dealer is confirmed as the target merchant; the acquisition unit is used to obtain the first distance and the second distance if the order placement device is not located in the area where the car dealer is located, the first distance being the distance between the first car dealer and the location information, and the second distance being the distance between the second car dealer and the location information.

[0025] Optionally, the processing unit is used to display inquiry information to the staff, and the inquiry information is used to inquire whether the current merchant is the target merchant; in response to the operation of confirming that the current merchant is not the target merchant, a merchant list is displayed to the staff, and the merchant list includes a first car seller, a first distance, a second car seller, and a second distance, wherein the first car seller and the second car seller are sorted from small to large distance.

[0026] Optionally, the acquisition unit is used to obtain the merchant information of the target merchant, the merchant information includes the store name, address and business scope of the target merchant; obtain the merchant vehicle model supply data, the merchant vehicle model supply data includes the target merchant's on-sale vehicle model data and the reserve quantity of on-sale vehicle models; the processing unit is used to construct a corresponding relationship between the target merchant and the merchant vehicle model supply data; the target merchant, merchant information, merchant vehicle model supply data and the corresponding relationship are stored in a preset merchant database to construct a preset merchant database.

[0027] Optionally, the processing unit is used to classify the merchant vehicle model supply data according to the historical submission data to obtain a first category of vehicle models and a second category of vehicle models, the first category of vehicle models are vehicle models that exist both in the historical submission data and in the merchant vehicle model supply data, and the second category of vehicle models are vehicle models that do not exist in the historical submission data but exist in the merchant vehicle model supply data; obtain the target selection probability of the target vehicle model according to the sub-historical submission quantity and the total historical submission quantity; sort the vehicle models in the first category of vehicle models in descending order according to the target selection probability to obtain a first category of vehicle model sequence; sort the vehicle models in the second category of vehicle models in descending order according to the reserve quantity of vehicle models on sale to obtain a second category of vehicle model sequence; connect the second category of vehicle model sequence to the first category of vehicle model sequence to obtain a vehicle model selection probability sequence; the acquisition unit is used to obtain the total historical submission quantity of the first category of vehicle models and the sub-historical submission quantity of the target vehicle model according to the historical submission data, the target vehicle model is any vehicle model in the first category of vehicle models.

[0028] Optionally, the acquisition unit is used to respond to the staff's operation of submitting vehicle model data and obtain the currently selected vehicle model; if there is a vehicle model in the merchant's vehicle model supply data whose configuration overlaps with the currently selected vehicle model greater than or equal to a preset threshold, then similar vehicle models and distinguishing information are obtained, and the distinguishing information is the distinguishing configuration information between the currently selected vehicle model and the similar vehicle model; the processing unit is used to determine whether there is a vehicle model in the merchant's vehicle model supply data whose configuration overlaps with the currently selected vehicle model greater than or equal to a preset threshold; and the similar vehicle models and distinguishing information are displayed to the staff.

[0029] In a third aspect, the present application provides an electronic device comprising a processor, a memory, a user interface, and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes the first aspect above or any possible implementation method of the first aspect.

[0030] In a fourth aspect, the present application provides a computer-readable storage medium, which stores a computer program. The computer program is executed by a processor as in the first aspect or any possible implementation method of the first aspect.

[0031] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0032] 1. The server can respond to the staff's operation of submitting vehicle model data, obtain the location information of the staff's device and historical submission data, and obtain the vehicle model data that can be provided by the staff's current merchant through the location information, that is, the merchant's vehicle model supply data; then obtain the vehicle model selection probability sequence based on the historical submission data and the merchant's vehicle model supply data, that is, predict the vehicle model data that the staff may choose to upload based on the staff's sales habits and the vehicle model data currently available from the merchant, and put the vehicle model data that the staff is more likely to choose at the front of the sequence to reduce the probability of the staff submitting vehicle model data that they are relatively unlikely to choose, thereby improving the accuracy and efficiency of the vehicle model data submitted by the staff.

[0033] 2. In response to a staff member's login operation, the server can store the uploaded data previously stored in the order device into the database of the previous staff member and delete the data locally after the upload is successful; the server can download the historical data corresponding to the current staff member from the preset order database to the order device; this method can save and update each staff member's historical sales data, so that different vehicle model selection probability sequences can be provided according to different staff members.

[0034] 3. The server can obtain a model selection probability sequence based on historical submission data and merchant model supply data. That is, based on the current merchant's existing model inventory, the model that the staff member is more inclined to recommend is arranged at the front of the model selection probability sequence through historical submission data, while those models that the staff member has not uploaded but are currently provided by the merchant are arranged at the back of the model selection probability sequence. This allows the staff member to prioritize the model data with a higher selection probability for submission, thereby reducing the probability of incorrect selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 This is a flow chart of a vehicle model data auxiliary input method provided in an embodiment of the present application.

[0036] Figure 2 This is a module schematic diagram of a vehicle model data auxiliary input device provided in an embodiment of the present application.

[0037] Figure 3 This is a structural diagram of an electronic device provided in an embodiment of the present application.

[0038] Description of the accompanying drawings: 201, acquisition unit; 202, processing unit; 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0039] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0040] In the description of the embodiments of this application, words such as "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "for example" or "for instance" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "for example" or "for instance" is intended to present the relevant concepts in a concrete manner.

[0041] In the description of the embodiments of the present application, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0042] When a customer chooses to purchase a vehicle with a loan, the salesperson must submit not only the customer's financial loan information but also various data about the vehicle selected by the user, such as the make, series, length, and horsepower. In this scenario where multiple types of data need to be submitted, the salesperson is prone to errors when submitting the information, which then requires repeated revisions, affecting the efficiency of data submission. This results in a low efficiency problem for submitting vehicle model data. Therefore, this embodiment provides a vehicle model data assisted input method, device, and storage medium.

[0043] The vehicle model data auxiliary input method provided in this application can be referred to Figure 1 , Figure 1 This is a flow chart of a vehicle model data auxiliary input method provided by an embodiment of the present application, which is applied to a server. The method includes steps S101 to S105.

[0044] S101. In response to an operation for submitting vehicle model data, obtain location information and historical submission data of an order submission device, where the order submission device is a device used by staff to submit vehicle model data.

[0045] In the above steps, the server responds to the staff member's operation on the vehicle model data submission and obtains the location information of the order submission device used by the staff member at that time. The location information here can be the current coordinates obtained through a positioning system such as GPS. The order submission device is the device used by the staff member to submit user payment information, vehicle model information, and other data after the customer determines the vehicle model to be purchased. While submitting data, the order submission device can also record this data, so the order submission device also stores historical submission data. The server also obtains this historical submission data for use in subsequent steps. The server is a server that controls the intelligent operation of the air conditioning equipment. The server can be a single server, a server cluster composed of multiple servers, or a cloud computing service center. The server can communicate with the user device via a wired or wireless network.

[0046] In one possible implementation, before obtaining the location information of the order device and historical submission data in response to an operation for submitting vehicle model data, the method further includes: in response to a staff member's login operation, uploading the former staff member's data stored in the order device to a preset order database; deleting the former staff member's data from the order device; obtaining the staff member's login information; obtaining the staff member's data in the preset order database based on the login information, and using the staff member's data as historical submission data.

[0047] Specifically, before submitting the vehicle model data, the staff can log in to the order submission device so that the order submission device can load their own historical submission data, so that the historical submission data always belongs to the staff member and will not be mixed with the submission data of other staff members, so that the vehicle model selection probability sequence obtained in the subsequent steps can fit the sales habits of the staff member as much as possible.

[0048] S102: Confirm the target merchant based on the location information.

[0049] In the above steps, the server confirms which car dealer the staff member is currently located at based on the acquired location information, and then correctly confirms the car model data currently being sold by the car dealer in subsequent steps.

[0050] In one possible implementation, confirming the target merchant based on location information specifically includes: determining whether the order placement device is located in the area where the car dealer is located based on the location information; if the order placement device is not located in the area where the car dealer is located, obtaining a first distance and a second distance, the first distance being the distance between the first car dealer and the location information, and the second distance being the distance between the second car dealer and the location information; comparing the first distance and the second distance; if the first distance is smaller than the second distance, confirming the first car dealer as the target merchant.

[0051] Specifically, the server first determines whether the obtained location information is within the building range of a certain car dealership. If it is within the building range, it confirms that the current car dealership is the merchant where the staff member is currently located; if it is determined that it is not within the building range, it may be because the location is indoors and inaccurate positioning occurs. At this time, the car dealership closest to the location information is obtained and the car dealership is used as the merchant where the staff member is currently located by default; in the step description, the first distance and the second distance are used to express the distance between multiple car dealers near the location information and the location information, rather than just randomly selecting two car dealers. This step is to express the retrieval of the car dealership closest to the location information; the location information here can be coordinates and other information indicating the current location of the staff member (this information may not be accurate due to the error of the positioning system).

[0052] In one possible embodiment, after confirming the first car dealer as the target merchant if the first distance is less than the second distance, the method further includes: displaying inquiry information to the staff, the inquiry information being used to inquire whether the current merchant is the target merchant; in response to the operation of confirming that the current merchant is not the target merchant, displaying a merchant list to the staff, the merchant list including the first car dealer, the first distance, the second car dealer, and the second distance, wherein the first car dealer and the second car dealer are sorted from smallest to largest distance.

[0053] Specifically, after the merchant is selected by default according to the location information, in order to ensure that the merchant is selected correctly, the server displays the inquiry information to the staff. The specific display method can be through the order reporting device or other methods; to ask the staff whether the merchant currently selected is correct. If it is correct, the staff will issue a confirmation instruction to proceed to the subsequent steps; if it is incorrect, the server will respond to the operation that the current merchant is not the target merchant and display the merchant list to the user. This merchant list is sorted and generated from near to far based on the distance of merchants near the location information. For example, merchant a is 100 meters away from the location information, merchant b is 80 meters away from the location information, and merchant c is 500 meters away from the location information. The generated merchant list is b, a, and c, and the merchant name, the corresponding summary information of the merchant, and the distance from the location information are displayed in the list for the staff's reference, so that the staff can see the correct merchant first and select it.

[0054] S103: Obtain merchant vehicle model supply data corresponding to the target merchant from a preset merchant database.

[0055] In the above steps, the server obtains the information on vehicle models that can be sold by the current merchant (ie, the target merchant), ie, the merchant vehicle model supply data, from the preset merchant database constructed in advance.

[0056] In a possible implementation, before obtaining the merchant vehicle model supply data corresponding to the target merchant in the preset merchant database, it also includes constructing the preset merchant database, and constructing the preset merchant database specifically includes: obtaining the merchant information of the target merchant, the merchant information includes the store name, address and business scope of the target merchant; obtaining the merchant vehicle model supply data, the merchant vehicle model supply data includes the target merchant's on-sale vehicle model data and the reserve quantity of on-sale vehicle models; constructing a corresponding relationship between the target merchant and the merchant vehicle model supply data; storing the target merchant, merchant information, merchant vehicle model supply data and the corresponding relationship in the preset merchant database to construct the preset merchant database.

[0057] Specifically, the server can input the merchant information of multiple car dealers. The merchant information may include the merchant's store name, address, and business scope. At the same time, the server can also input the vehicle model data that each car dealer can currently supply and the specific supply quantity. Then, a correspondence between the merchant information and the merchant vehicle model supply data is established. Each correspondence and the two types of data associated with the correspondence are saved or updated, thereby building a preset merchant database. When accessing the information in the database subsequently, the server can quickly retrieve the corresponding merchant vehicle model supply data through the correspondence based on the merchant information such as the store name.

[0058] S104. Obtain a vehicle model selection probability sequence based on the merchant vehicle model supply data and historical submission data. The vehicle model selection probability sequence includes vehicle model options. The vehicle model options are arranged in a preset order in the vehicle model selection probability sequence.

[0059] In the above steps, the server obtains the model selection probability sequence based on the merchant model supply data and historical submission data, that is, based on the model information that the current merchant can provide and the sales habits of the staff member, the server obtains the probability of each model on sale that the staff member may sell. These models can be sorted according to the size of the selection probability. For example, the models with a higher selection probability can be arranged in front. In this way, when the staff submits data, the probability of selecting similar or incorrect model information will be reduced, thereby achieving the effect of improving the efficiency of model data input.

[0060] In a possible implementation, obtaining a vehicle model selection probability sequence based on merchant vehicle model supply data and historical submission data specifically includes: classifying the merchant vehicle model supply data based on the historical submission data to obtain a first category of vehicle models and a second category of vehicle models, the first category of vehicle models being vehicle models that exist both in the historical submission data and in the merchant vehicle model supply data, and the second category of vehicle models being vehicle models that do not exist in the historical submission data but exist in the merchant vehicle model supply data; obtaining the total historical submission quantity of the first category of vehicle models and the sub-historical submission quantity of the target vehicle model based on the historical submission data, the target vehicle model being any vehicle model in the first category of vehicle models; obtaining a target selection probability of the target vehicle model based on the sub-historical submission quantity and the total historical submission quantity; sorting the vehicle models in the first category of vehicle models in descending order according to the target selection probability to obtain a first category of vehicle model sequence; sorting the vehicle models in the second category of vehicle models in descending order according to the reserve quantity of vehicle models on sale to obtain a second category of vehicle model sequence; connecting the second category of vehicle model sequence to the first category of vehicle model sequence to obtain a vehicle model selection probability sequence.

[0061] Specifically, the server first classifies the data based on historical submissions and the vehicle model supply data of the merchants, mainly focusing on the vehicle models that the merchants can currently provide, and selects the vehicle models that the current merchants can provide and that have been sold by the staff. These vehicle models are regarded as the first category of vehicle models, which can be sorted according to the historical submission data; the vehicle models that the merchants can currently provide but have never been submitted or sold by the staff are regarded as the second category of vehicle models, which can also be sorted according to the needs of the staff. For example, the vehicle models that can be supplied in large quantities can be arranged in front, and the vehicle models with relatively small supply can be arranged at the back of the sequence according to the quantity that the merchants can supply. The specific sorting method of the first category of vehicle models is mainly calculated and sorted by the total historical submission quantity and the sub-historical submission data. For example, Model A has been submitted for sale 10 times (that is, the sub-historical submission quantity of Model A). ), Model B has been submitted for sale 5 times (i.e., the number of sub-historical submissions of Model B), and Model C has been submitted for sale 7 times (i.e., the number of sub-historical submissions of Model C), then the total number of historical submissions is 22. By dividing the sub-historical submission data by the total historical submission data, the selection probability of each model in the first category can be obtained. For example, the selection probabilities of Model A, Model B, and Model C are 5 / 11, 5 / 22, and 7 / 22, respectively. At this time, the first category of models can be sorted in descending order of selection probability. After both categories of models have been sorted, the two sequences can be spliced to form a model selection probability sequence. The splicing method can be to place the sequence of the first category of models in front so that the staff can see the models they have submitted for sale first. Of course, the sequence of the second category of models can also be placed in front according to actual needs. This is not a restrictive explanation here.

[0062] S105. Display the vehicle model selection probability sequence to the staff to assist them in submitting vehicle model data.

[0063] In the above steps, the server displays the vehicle model selection probability sequence to the staff. The specific display method can be through the order submission device, thereby assisting the staff in selecting the vehicle model and submitting other data, thereby improving the accuracy and efficiency of the staff's submitted data.

[0064] In one possible implementation, after presenting the vehicle model selection probability sequence to the staff to assist the staff in submitting the vehicle model data, the method further includes: obtaining the currently selected vehicle model in response to the staff's operation of submitting the vehicle model data; determining whether there is a vehicle model in the merchant's vehicle model supply data whose configuration overlaps with the currently selected vehicle model by a degree greater than or equal to a preset threshold; if there is a vehicle model in the merchant's vehicle model supply data whose configuration overlaps with the currently selected vehicle model by a degree greater than or equal to a preset threshold, obtaining similar vehicle models and distinguishing information, the distinguishing information being the distinguishing configuration information between the currently selected vehicle model and the similar vehicle model; and presenting the similar vehicle models and distinguishing information to the staff.

[0065] Specifically, after displaying the model selection probability sequence, in order to prevent the staff from mistakenly selecting similar models, after the staff selects the model, the server searches the model data available from the current merchant to see whether there are models similar to the selected model. The similarity here refers to the similarity of various data of the model, such as the brand, horsepower, etc., that is, the similarity is judged by whether the configuration overlap is greater than the preset threshold; when there are similar models, the difference information between the two models is further obtained, and the difference information and the information of similar models are displayed to the staff for prompting.

[0066] This application also provides a vehicle model data auxiliary input device, referring to Figure 2 , the device includes an acquisition unit 201 and a processing unit 202.

[0067] The acquisition unit 201 is used to obtain the location information and historical submission data of the order submission device in response to the operation of submitting vehicle model data. The order submission device is a device used by staff to submit vehicle model data; it is also used to obtain the merchant vehicle model supply data corresponding to the target merchant in the preset merchant database; it is also used to obtain the vehicle model selection probability sequence based on the merchant vehicle model supply data and historical submission data. The vehicle model selection probability sequence includes vehicle model options, and the vehicle model options are arranged in a preset order in the vehicle model selection probability sequence.

[0068] The processing unit 202 is used to confirm the target merchant based on the location information; it is also used to display the vehicle model selection probability sequence to the staff to assist the staff in submitting the vehicle model data.

[0069] In one possible embodiment, the processing unit 202 is used to upload the former staff member's data stored in the order placement device to the preset order placement database in response to the staff member's login operation; delete the former staff member's data from the order placement device; the acquisition unit 201 is used to obtain the staff member's login information; obtain the staff member data in the preset order placement database based on the login information, and submit the staff member data as historical data.

[0070] In one possible implementation, the processing unit 202 is used to determine whether the order placement device is located in the area where the car dealer is located based on the location information; compare the first distance and the second distance; if the first distance is less than the second distance, the first car dealer is confirmed as the target merchant; the acquisition unit 201 is used to obtain the first distance and the second distance if the order placement device is not located in the area where the car dealer is located, the first distance being the distance between the first car dealer and the location information, and the second distance being the distance between the second car dealer and the location information.

[0071] In one possible embodiment, the processing unit 202 is used to display inquiry information to the staff, and the inquiry information is used to inquire whether the current merchant is the target merchant; in response to the operation of confirming that the current merchant is not the target merchant, a merchant list is displayed to the staff, and the merchant list includes a first car seller, a first distance, a second car seller, and a second distance, wherein the first car seller and the second car seller are sorted from small to large distance.

[0072] In one possible implementation, the acquisition unit 201 is used to acquire the merchant information of the target merchant, which includes the store name, address and business scope of the target merchant; obtain the merchant vehicle model supply data, which includes the target merchant's vehicle model data on sale and the reserve quantity of vehicle models on sale; the processing unit 202 is used to establish a correspondence between the target merchant and the merchant vehicle model supply data; and store the target merchant, merchant information, merchant vehicle model supply data and the correspondence in a preset merchant database to construct a preset merchant database.

[0073] In one possible embodiment, the processing unit 202 is used to classify the merchant vehicle model supply data according to the historical submission data to obtain a first category of vehicle models and a second category of vehicle models, where the first category of vehicle models are vehicle models that exist both in the historical submission data and in the merchant vehicle model supply data, and the second category of vehicle models are vehicle models that do not exist in the historical submission data but exist in the merchant vehicle model supply data; the target selection probability of the target vehicle model is obtained according to the sub-historical submission quantity and the total historical submission quantity; the vehicle models in the first category of vehicle models are sorted in descending order according to the target selection probability to obtain a first category of vehicle model sequence; the vehicle models in the second category of vehicle models are sorted in descending order according to the reserve quantity of vehicle models on sale to obtain a second category of vehicle model sequence; the second category of vehicle model sequence is connected to the first category of vehicle model sequence to obtain a vehicle model selection probability sequence; the acquisition unit 201 is used to obtain the total historical submission quantity of the first category of vehicle models and the sub-historical submission quantity of the target vehicle model according to the historical submission data, where the target vehicle model is any vehicle model in the first category of vehicle models.

[0074] In one possible implementation, the acquisition unit 201 is used to respond to the staff's operation of submitting vehicle model data to obtain the currently selected vehicle model; if there is a vehicle model in the merchant's vehicle model supply data whose configuration overlaps with the currently selected vehicle model greater than or equal to a preset threshold, then similar vehicle models and distinguishing information are obtained, and the distinguishing information is the distinguishing configuration information between the currently selected vehicle model and the similar vehicle model; the processing unit 202 is used to determine whether there is a vehicle model in the merchant's vehicle model supply data whose configuration overlaps with the currently selected vehicle model greater than or equal to a preset threshold; and the similar vehicle models and distinguishing information are displayed to the staff.

[0075] It should be noted that the above embodiments provide devices that implement their functions using only the division of the above functional modules as examples. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0076] The present application also provides a computer-readable storage medium storing instructions, which, when executed by one or more processors, enable an electronic device to execute one or more of the methods described in the above embodiments.

[0077] This application also provides an electronic device. Figure 3 , Figure 3 3. This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present application. The electronic device 300 may include: at least one processor 301, at least one communication bus 302, at least one user interface 303, a network interface 304, and a memory 305.

[0078] The communication bus 302 is used to implement the connection and communication between these components.

[0079] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0080] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0081] The processor 301 may include one or more processing cores. Using various interfaces and circuits, the processor 301 connects to various components within the server. It executes instructions, programs, code sets, or instruction sets stored in the memory 305, as well as accesses data stored in the memory 305, to perform various server functions and process data. Optionally, the processor 301 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 301 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing content displayed on the display screen; and the modem handles wireless communications. It is understood that the modem may not be integrated into the processor 301 but implemented as a separate chip.

[0082] Among them, the memory 305 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 305 may also optionally be at least one storage device located away from the aforementioned processor 301. Refer to Figure 3 , the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module and a vehicle model data auxiliary input application.

[0083] exist Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 301 can be used to call a vehicle model data auxiliary input application stored in the memory 305. When executed by one or more processors 301, the electronic device 300 executes one or more methods in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should know that this application is not limited to the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for this application.

[0084] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0085] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic, such as the division of units, which is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interface, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0086] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0087] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0088] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the various embodiments of the method of this application. The aforementioned memory includes various media that can store program code, such as USB flash drives, mobile hard drives, magnetic disks, or optical disks.

[0089] The foregoing is merely an exemplary embodiment of the present disclosure and is not intended to limit the scope of the present disclosure. In other words, any equivalent variations and modifications made in accordance with the teachings of the present disclosure are still within the scope of the present disclosure. Those skilled in the art will readily conceive of other embodiments of the present disclosure after considering the disclosure and the practical implications thereof.

[0090] This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not described herein. The description and examples are to be considered as exemplary only, and the scope and spirit of the present disclosure are to be defined by the claims.

Claims

1. A vehicle model data auxiliary input method, characterized in that: The method comprises: In response to an operation for submitting vehicle model data, obtaining location information and historical submission data of an order submission device, where the order submission device is a device used by a staff member to submit vehicle model data; confirming the target merchant based on the location information; Obtaining the merchant information of the target merchant, wherein the merchant information includes the store name, address, and business scope of the target merchant; Obtaining the merchant vehicle model supply data, wherein the merchant vehicle model supply data includes the target merchant's vehicle model data on sale and the number of vehicle models in reserve on sale; Establishing a corresponding relationship between the target merchant and the merchant's vehicle model supply data; Storing the target merchant, the merchant information, the merchant vehicle type supply data, and the corresponding relationship in a preset merchant database to construct the preset merchant database; Obtaining the merchant vehicle model supply data corresponding to the target merchant in a preset merchant database; Classifying the merchant vehicle model supply data according to the historically submitted data to obtain a first category of vehicle models and a second category of vehicle models, wherein the first category of vehicle models are vehicle models that exist in both the historically submitted data and the merchant vehicle model supply data, and the second category of vehicle models are vehicle models that do not exist in the historically submitted data but exist in the merchant vehicle model supply data; Obtaining, based on the historical submission data, a total historical submission quantity of the first category of vehicle models and a sub-historical submission quantity of a target vehicle model, where the target vehicle model is any vehicle model in the first category; Obtaining a target selection probability of the target vehicle model according to the sub-history submission quantity and the total history submission quantity; Sort the models in the first category of models according to the target selection probability from large to small to obtain a first category of model sequence; Sort the models in the second category of models according to the reserve quantity of the models on sale from largest to smallest, to obtain a second category model sequence; Connecting the second type vehicle model sequence to the first type vehicle model sequence to obtain the vehicle model selection probability sequence; The vehicle type selection probability sequence is presented to the staff to assist the staff in submitting vehicle type data.

2. The method according to claim 1, characterized in that Before obtaining the location information of the order placing device and the historical submission data in response to the operation on the vehicle model data submission, the method further includes: In response to the staff member's login operation, uploading the former staff member's data stored in the order placement device to a preset order placement database; Deleting the former staff member data from the order placement device; Obtaining login information of the staff member; The staff data is obtained in the preset order database according to the login information, and the staff data is used as the historical submission data.

3. The method according to claim 1, characterized in that The step of confirming the target merchant according to the location information specifically includes: determining, based on the location information, whether the order placing device is located in the area where the car dealer is located; If the order placing device is not located in the area where the car dealer is located, obtaining a first distance and a second distance, wherein the first distance is the distance between the first car dealer and the location information, and the second distance is the distance between the second car dealer and the location information; comparing the first distance and the second distance; If the first distance is less than the second distance, the first car dealer is confirmed as the target merchant.

4. The method according to claim 3, characterized in that After confirming the first car dealer as the target merchant if the first distance is less than the second distance, the method further includes: Displaying inquiry information to the staff, wherein the inquiry information is used to inquire whether the current merchant is the target merchant; In response to confirming that the current merchant is not the target merchant, a merchant list is displayed to the staff, the merchant list including the first car seller, the first distance, the second car seller, and the second distance, wherein the first car seller and the second car seller are sorted from smallest to largest distance.

5. The method according to claim 1, wherein After presenting the vehicle model selection probability sequence to the staff to assist the staff in submitting vehicle model data, the method further includes: In response to the staff member's operation of submitting vehicle model data, obtaining the currently selected vehicle model; Determine whether there is a model in the merchant's model supply data whose configuration overlaps with the currently selected model by a degree greater than or equal to a preset threshold; If there is a model in the merchant's model supply data whose configuration overlaps with the currently selected model by a degree greater than or equal to a preset threshold, then similar models and distinguishing information are obtained, where the distinguishing information is the distinguishing configuration information between the currently selected model and the similar model; The similar vehicle models and the distinguishing information are presented to the staff.

6. A vehicle model data auxiliary input device, characterized in that: The device comprises an acquisition unit (201) and a processing unit (202): The acquisition unit (201) is used to acquire the location information and historical submission data of the order submission device in response to the operation of submitting the vehicle model data, wherein the order submission device is a device used by the staff to submit the vehicle model data; The processing unit (202) is used to confirm the target merchant according to the location information; The acquisition unit (201) is further configured to acquire merchant information of the target merchant, wherein the merchant information includes the store name, address, and business scope of the target merchant; Obtaining the merchant vehicle model supply data, wherein the merchant vehicle model supply data includes the target merchant's vehicle model data on sale and the number of vehicle models in reserve on sale; Establishing a corresponding relationship between the target merchant and the merchant's vehicle model supply data; Storing the target merchant, the merchant information, the merchant vehicle type supply data, and the corresponding relationship in a preset merchant database to construct the preset merchant database; The acquisition unit (201) is further configured to acquire the merchant vehicle model supply data corresponding to the target merchant from a preset merchant database; The acquisition unit (201) is further configured to classify the merchant vehicle model supply data according to the historical submission data to obtain a first category of vehicle models and a second category of vehicle models, wherein the first category of vehicle models are vehicle models that exist both in the historical submission data and in the merchant vehicle model supply data, and the second category of vehicle models are vehicle models that do not exist in the historical submission data but exist in the merchant vehicle model supply data; Obtaining, based on the historical submission data, a total historical submission quantity of the first category of vehicle models and a sub-historical submission quantity of a target vehicle model, where the target vehicle model is any vehicle model in the first category; Obtaining a target selection probability of the target vehicle model according to the sub-history submission quantity and the total history submission quantity; Sort the models in the first category of models according to the target selection probability from large to small to obtain a first category of model sequence; Sort the models in the second category of models according to the reserve quantity of the models on sale from largest to smallest, to obtain a second category model sequence; Connecting the second type vehicle model sequence to the first type vehicle model sequence to obtain the vehicle model selection probability sequence; The processing unit (202) is further configured to present the vehicle model selection probability sequence to the staff member to assist the staff member in submitting vehicle model data.

7. An electronic device, characterized in that: The electronic device (300) comprises a processor (301), a memory (305), a user interface (303) and a network interface (304), wherein the memory (305) is used to store instructions, the user interface (303) and the network interface (304) are used to communicate with other devices, and the processor (301) is used to execute the instructions stored in the memory (305) so that the electronic device (300) executes the method according to any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 5 is implemented.

Images