CN113888098A - Vehicle information recommendation method and device and electronic equipment - Google Patents
Vehicle information recommendation method and device and electronic equipment Download PDFInfo
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- CN113888098A CN113888098A CN202111299702.0A CN202111299702A CN113888098A CN 113888098 A CN113888098 A CN 113888098A CN 202111299702 A CN202111299702 A CN 202111299702A CN 113888098 A CN113888098 A CN 113888098A
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
Abstract
The application provides a vehicle information recommendation method, a vehicle information recommendation device and electronic equipment, wherein the method comprises the following steps: determining historical freight information matched with the freight information according to the freight information of the goods to be consigned, wherein the freight information comprises target freight parameters; if the historical vehicle information is detected to exist, recommending the historical vehicle information; if not, searching first vehicle information corresponding to the target freight parameter in a first mapping relation between the freight parameter range and the vehicle information for recommendation; if the first vehicle information is not found, second vehicle information corresponding to the target freight parameter is found in a second mapping relation between the freight parameter range and the vehicle information for recommendation; and the granularity of the freight parameter range in the second mapping relation is larger than that of the freight parameter range in the second mapping relation. The method can more intelligently recommend the vehicle information with higher accuracy to the shipper, so that the shipper can be matched with a more appropriate carrier vehicle.
Description
Technical Field
The application relates to the field of information processing, in particular to a vehicle information recommendation method and device and electronic equipment.
Background
Freight transportation, i.e. freight transportation. Cargo transportation is a derivative demand of economic and social development and a support for physical circulation of commodities, and along with the continuous increase of economy, the freight demand is larger and larger.
In the freight market, a shipper can serve as a shipper to search for a carrier to carry goods through a network platform; specifically, the shipper may publish the shipment information on the network platform, and the network platform may search for a suitable carrier according to the shipment information. After a successful shipper-carrier match is made, the carrier may carry the goods to transport the goods from the origin to the destination.
In the related art, after the shipper issues the shipping information on the network platform, there are the following cases of matching the carrier vehicles: (1) the shipper needs to select vehicle information such as load, vehicle type, vehicle length and the like according to the cargo condition of the shipper; but because the shipper lacks the experience of actual selection, situations often arise where a proper vehicle cannot be matched; (2) the network platform recommends the carrier vehicle according to the shipper's historical shipping orders, but because the goods shipped by the same shipper are not invariable, inaccurate recommendations often occur; (3) the network freight platform recommends a carrier vehicle according to the volume information, the type information and the weight information of the consignment; in such a recommendation, inaccurate recommendations may also occur due to error factors such as large weight estimation errors, large volume estimation errors, etc. in the cargo information filled in by the shipper.
Therefore, in the related art, when a carrier vehicle is recommended to a shipper, there are problems of low intelligence and low accuracy.
Disclosure of Invention
An object of the embodiments of the present application is to provide a vehicle information recommendation method, device and electronic device, which are used to recommend vehicle information with higher accuracy to a shipper more intelligently, so that the shipper can match with a more appropriate carrier vehicle.
In a first aspect, an embodiment of the present application provides a vehicle information recommendation method, where the method includes: determining historical freight information matched with the freight information according to the freight information of the goods to be consigned, wherein the freight information comprises target freight parameters; in response to detecting that historical vehicle information for carrying historical cargos corresponding to the historical freight information exists, recommending the historical vehicle information; in response to the fact that the historical vehicle information does not exist, first vehicle information corresponding to the target freight parameter is searched in a first mapping relation between a freight parameter range and the vehicle information and serves as recommended vehicle information; in response to that the first vehicle information is not found, second vehicle information corresponding to the target freight parameter is found in a second mapping relation between the freight parameter range and the vehicle information and serves as recommended vehicle information; the granularity of the freight parameter range in the second mapping relation is larger than the granularity of the freight parameter range in the first mapping relation. Thus, the vehicle information with higher accuracy can be more intelligently recommended to the shipper, so that the shipper can be matched with a more appropriate carrier vehicle.
Optionally, the historical vehicle information includes historical vehicle length information corresponding to the historical carrier vehicle; and recommending the historical vehicle information in response to detecting that the historical vehicle information for carrying the historical cargos corresponding to the historical freight information exists, wherein the recommending comprises: acquiring the historical adoption rate of the shipper corresponding to the goods to be shipped to the historical vehicle length information; judging whether the historical adoption rate is greater than a first preset adoption rate or not; the first preset adoption rate represents the adoption rate of similar historical vehicle length information recommended by the shipper for similar goods within a preset time length; and if the historical adoption rate is greater than the first preset adoption rate, recommending the historical vehicle length information to the shipper. Therefore, the historical vehicle length information to be recommended can be determined according to the first preset adoption rate, and the recommendation accuracy is improved.
Optionally, the historical vehicle length information includes a plurality of types of vehicle length information with different specifications; and recommending the historical vehicle information in response to detecting that the historical vehicle information for carrying the historical cargos corresponding to the historical freight information exists, further comprising: if the historical adoption rate is not greater than the first preset adoption rate, respectively calculating a single historical adoption rate corresponding to each vehicle length information in the historical vehicle length information by the shipper; recommending target vehicle length information corresponding to a single historical adoption rate larger than a second preset adoption rate to the shipper; the second preset adoption rate represents the adoption rate of the single historical vehicle length information recommended by the shipper for similar goods within the preset time length. Therefore, the single historical adoption rate can be determined from the perspective of the shipper, so that the vehicle length information determined based on the single historical adoption rate can better meet the consignment intention of the shipper, and the recommendation accuracy is improved.
Optionally, the target freight parameters include a target freight weight parameter and a target freight category parameter; and in response to the fact that the historical vehicle information does not exist, searching first vehicle information corresponding to the target freight parameter in a first mapping relation between a freight parameter range and the vehicle information as recommended vehicle information, wherein the steps of: searching the vehicle length information corresponding to the target cargo weight parameter in the first mapping relation for recommendation; and in response to the fact that the cargo type detail information exists in the first mapping relation, searching the vehicle length information corresponding to the target cargo type parameter for recommendation. Therefore, accurate recommendation can be performed based on the first mapping relation, and more accurate vehicle information can be recommended to the shipper.
Optionally, the searching for the vehicle length information corresponding to the target cargo weight parameter in the first mapping relationship for recommendation includes: if the detected value corresponding to the target cargo weight parameter is a single weight value, recommending the vehicle length information corresponding to the weight parameter range in which the weight value is located; and if the detected value corresponding to the weight parameter of the target cargo corresponds to the weight parameter range value, recommending the vehicle length information corresponding to the weight parameter range value, wherein the weight upper limit value and the weight lower limit value correspond to the weight parameter range value. Therefore, no matter the shipper provides a single weight value or a weight parameter range value in the freight information, the shipper can be matched with more appropriate vehicle information for recommendation, and the recommendation process is more intelligent.
Optionally, the historical vehicle information includes historical vehicle type information corresponding to historical carrier vehicles; the freight information comprises cargo type information; and recommending the historical vehicle information in response to detecting that the historical vehicle information for carrying the historical cargos corresponding to the historical freight information exists, wherein the recommending comprises: obtaining the information of the selected historical vehicle type when the shipper corresponding to the goods to be shipped historically ships the goods corresponding to the goods type information; recommending the historical vehicle type information selected historically. In this way, the probability of the shipper adopting the recommended vehicle information may be increased.
Optionally, the target freight parameters include a target freight type parameter, a target freight consignment distance parameter, and a target freight weight parameter; and in response to the fact that the historical vehicle information does not exist, searching first vehicle information corresponding to the target freight parameter in a first mapping relation between a freight parameter range and the vehicle information as recommended vehicle information, wherein the steps of: and searching in the first mapping relation according to the target cargo type parameter, the target cargo consignment distance parameter and the target cargo weight parameter. Therefore, the vehicle information with higher recommendation accuracy can be searched more accurately based on the first mapping relation.
In a second aspect, an embodiment of the present application provides a vehicle information recommendation device, including: the determining module is used for determining historical freight information matched with the freight information according to the freight information of the goods to be consigned, wherein the freight information comprises target freight parameters; the historical recommendation module is used for recommending the historical vehicle information in response to the fact that the historical vehicle information for carrying the historical cargos corresponding to the historical freight information exists; the first searching module is used for searching first vehicle information corresponding to the target freight parameter in a first mapping relation between a freight parameter range and the vehicle information as recommended vehicle information in response to the fact that the historical vehicle information does not exist; the second searching module is used for searching second vehicle information corresponding to the target freight parameter in a second mapping relation between the freight parameter range and the vehicle information in response to the first vehicle information not being searched, and the second vehicle information is used as recommended vehicle information; the granularity of the freight parameter range in the second mapping relation is larger than the granularity of the freight parameter range in the first mapping relation. Thus, the vehicle information with higher accuracy can be more intelligently recommended to the shipper, so that the shipper can be matched with a more appropriate carrier vehicle.
In a third aspect, an embodiment of the present application provides an electronic device, including a processor and a memory, where the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the method as provided in the first aspect are executed.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, performs the steps in the method as provided in the first aspect above.
Additional features and advantages of the present application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by the practice of the embodiments of the present application. The objectives and other advantages of the application may be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments of the present application will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and that those skilled in the art can also obtain other related drawings based on the drawings without inventive efforts.
Fig. 1 is a flowchart of a vehicle information recommendation method according to an embodiment of the present application;
fig. 2 is a block diagram of a vehicle information recommendation device according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device for executing a vehicle information recommendation method according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
It should be noted that the embodiments or technical features of the embodiments in the present application may be combined without conflict.
In the related art, when a shipper is recommended to a shipper, the problems of low intellectualization and low accuracy exist; in order to solve the problem, the application provides a vehicle information recommendation method, a vehicle information recommendation device and electronic equipment; furthermore, recommendation intelligence and recommendation accuracy of the carrier vehicle are improved by combining recommendation according to historical consignment order information, accurate recommendation according to freight information of goods to be consigned and bottom-in-pocket recommendation according to the freight information.
In some application scenarios, the vehicle information recommendation method can be applied to a computing device, and the computing device can receive freight information of goods to be consigned, and can recommend according to historical consignment order information, accurately recommend according to goods information, and recommend to the bottom of a purse; in other application scenarios, the vehicle information recommendation method may also be applied to a server side providing services for the computing device. The server side can receive the freight information of the goods to be consigned sent by the computing device and provide recommendation service. For example, the present application is applicable to computing device literary texts.
The above solutions in the related art are all the results of practical and careful study of the inventor, and therefore, the discovery process of the above problems and the solutions proposed by the following embodiments of the present invention to the above problems should be the contribution of the inventor to the present invention in the course of the present invention.
Referring to fig. 1, a flowchart of a vehicle information recommendation method according to an embodiment of the present application is shown. As shown in fig. 1, the vehicle information recommendation method includes the following steps 101 to 104.
The shipment information may include, for example, cargo weight information, cargo consignment distance information, cargo volume information, cargo type information, and the like of the cargo to be consigned, which substantially allows the carrier to specify whether or not the cargo to be consigned can be carried. In some application scenarios, the shipping information may include target shipping parameters. For example, shipping information for cargo weight information may include a target cargo weight parameter; the shipping information for the cargo consignment distance information may include a target cargo consignment distance parameter.
In some application scenarios, a shipper may send a shipping request that may include shipping information for a shipment to be shipped, and after receiving the shipping request, a computing device may look up whether there is historical shipping information that matches the shipping information. In these application scenarios, for example, whether the historical shipment information matches the shipment information may be determined by determining whether the historical shipment information corresponds to the historical shipment information that is the same as the type information, volume information, and/or weight information of the shipment to be consigned. For example, if the type information and volume information of the historical shipment corresponding to the historical shipment information are the same as the shipment to be consigned, it can be considered that the historical shipment information matches the shipment information of the shipment to be consigned.
In these application scenarios, the shipment information and the historical shipment information may be published by the same shipper, or may be published by different shippers. In this embodiment, in order to improve the rate of adoption of the recommended vehicle information by the shipper, matching may be performed in the historical shipment information issued by the same shipper.
102, recommending historical vehicle information in response to the detection that the historical vehicle information for carrying the historical cargos corresponding to the historical freight information exists;
after historical shipping information matching the shipping information is determined, it may be detected whether historical vehicle information exists for which the historical shipment was shipped, and if so, the historical vehicle information may be directly recommended to the shipper. For example, if the cargo to be shipped is wheat and the shipping weight parameter range is (20, 25) tons, after detecting the vehicle a carrying wheat within the weight parameter range, the vehicle information corresponding to the vehicle a may be recommended to the shipper.
in some application scenarios, if there is no historical vehicle information matching with the shipping information, the first vehicle information matching with the target shipping parameter may be searched in the first mapping relationship for accurate recommendation.
The first mapping relationship may be regarded as a relationship between different freight parameter ranges of different cargos and different vehicle length information or vehicle type information, which are stored in advance for different cargos. In this way, the computing device may recommend the first vehicle information to the shipper if the first vehicle information matching the target shipment parameter is found in the first mapping. Therefore, the accuracy of recommendation can be improved by accurately searching the first vehicle information matched with the target freight parameter in the first mapping relation.
The second mapping relationship may be regarded as a relationship between different freight parameter ranges of different cargos and different vehicle length information or vehicle type information, which are stored in advance for different cargos. And the granularity of the freight parameter range in the second mapping relation is larger than the granularity of the freight parameter range in the second mapping relation. For example, for the weight parameter range, if the weight parameter range in the first mapping is (20, 30) tons, the freight parameter range in the second mapping may be (10, 35) tons with a larger granularity of division.
In some application scenarios, if the first vehicle information is not found in the first mapping relationship, the bottom-of-pocket recommendation may be performed. Specifically, the second vehicle information matched with the target freight parameter may be searched for and recommended in the second mapping relationship with the larger division granularity. For example, for wheat with a weight parameter range of (15, 25) tons, if the matching first vehicle information is not found in the first mapping relationship, the second vehicle information with a larger division granularity corresponding to the weight parameter range, such as (10, 30) tons and (15, 35) tons, can be found in the second mapping relationship for recommendation.
In this embodiment, through the above steps 101 to 104, highly accurate vehicle information can be more intelligently recommended to the shipper, so that the shipper can match with a more appropriate carrier vehicle.
In some alternative implementations, the historical vehicle information includes historical vehicle length information corresponding to historical carrier vehicles; that is, a carrier vehicle with an appropriate vehicle length may be recommended to the shipper.
Thus, the step 102 may comprise the following sub-steps:
a substep 1021, acquiring the historical adoption rate of the shipper corresponding to the goods to be shipped to the historical vehicle length information;
in some application scenarios, when determining the historical vehicle length information, the vehicle length information that should be recommended currently may be determined according to the historical adoption rate of the shipper for the historical vehicle length information. Here, the historical adoption rate may be considered as the probability that the shipper selected the historical truck length information during the historical shipping process.
In these application scenarios, the computing device may record the shipping information, the carrier vehicle information, and the like corresponding to the shipment after the shipper completes one shipment, and may then obtain the historical vehicle information at the next shipment.
A substep 1022 of determining whether the historical adoption rate is greater than a first preset adoption rate; the first preset adoption rate represents the adoption rate of similar historical vehicle length information recommended by the shipper for similar goods within a preset time length;
in some application scenarios, after the historical adoption rate of the shipper for the historical vehicle length information is obtained, whether the historical adoption rate is greater than a first preset adoption rate or not can be further judged. Here, the first preset acceptance rate may represent an acceptance rate of similar historical vehicle length information recommended by the shipper for similar goods as the goods to be shipped over a preset time period, such as a week, a day, etc. That is, there may be a change in the first preset acceptance rate when the preset time period arrives. For example, the first preset acceptance rate corresponding to the previous week may be 0.33, and the first preset acceptance rate corresponding to the current week may be updated to 0.4.
And a substep 1023 of recommending the historical vehicle length information to the shipper if the historical adoption rate is greater than the first preset adoption rate.
That is, if it is determined that the historical adoption rate is greater than the first preset adoption rate, the historical vehicle length information corresponding to the historical adoption rate may be recommended to the shipper. For example, shipper A has 10 orders in the past week for shipping wheat, with shipping weight parameters ranging between (20, 25) tons, with 5 orders taking 9.6 and 13 meters of length information and 3 orders taking 9.6 meters of length information (assuming that the shipper can select no more than 3 lengths at a time). If the first preset acceptance rate is 0.33, the historical acceptance rate 0.5 aiming at the historical vehicle length information of 9.6 meters and 13 meters is greater than the first preset acceptance rate 0.33; the historical adoption rate of the historical vehicle length information for 9.6 meters is 0.3 less than the first preset adoption rate of 0.33. Historical vehicle length information of 9.6 meters and 13 meters can be recommended to the shipper.
Through the substep 1021 to the substep 1023, the historical vehicle length information to be recommended can be determined according to the first preset adoption rate, and the recommendation accuracy is improved.
In some optional implementations, the historical vehicle length information includes a plurality of types of vehicle length information with different specifications; for example, the shipper may take vehicle information for vehicle lengths of 9.6 meters and 13 meters. In this case, it can be considered that the goods to be consigned can be consigned by the vehicle with the vehicle length of 9.6 meters, and can also be consigned by the vehicle with the vehicle length of 13 meters.
Thus, the step 102 may further include the following sub-steps:
substep 1024, if the historical adoption rate is not greater than the first preset adoption rate, respectively calculating a single historical adoption rate corresponding to each vehicle length information in the historical vehicle length information by the shipper;
in some application scenarios, if the historical adoption rate is less than or equal to the first preset adoption rate, the historical vehicle length information corresponding to the historical adoption rate cannot be recommended to the shipper. At this time, individual historical adoption rates corresponding to various vehicle length information may be calculated, respectively. For example, 10 orders of the shipper B are shipping wheat, the shipping weight parameter range is (20, 25) tons, wherein 3 orders adopt 9.6 m and 13 m car length information, and 3 orders adopt 9.6 m car length information (assuming that the shipper can select no more than 3 car length information at a time), the historical adoption rate for 9.6 m and 13 m historical car length information is 0.3, the historical adoption rate for 9.6 m historical car length information is 0.3, and both the two historical adoption rates are smaller than the first preset adoption rate 0.33, at this time, the historical car length information can be split to obtain a single historical adoption rate corresponding to each kind of car length information. That is, the historical vehicle length information of 9.6 meters and 13 meters can be split into 3 orders adopting the historical vehicle length information of 9.6 meters and 3 orders adopting the historical vehicle length information of 13 meters. Thus, 6 orders adopt the information of the vehicle length of 9.6 meters, and 3 orders adopt the information of the vehicle length of 13 meters. Here, it should be noted that a single historical adoption rate may be considered as a probability that the shipper would like to select a carrier vehicle for certain length information. For example, if it is detected that 3 orders have been received with the information of the lengths of 9.6 meters and 13 meters, it can be considered that the shipper has 3 times of selection of the carrier vehicle with the length of 9.6 meters, and likewise has 3 times of selection of the carrier vehicle with the length of 13 meters. Then, 3 orders that adopt the information of the vehicle length of 9.6 meters and 13 meters can be split to obtain 3 orders that adopt the information of the vehicle length of 9.6 meters and 3 orders that adopt the information of the vehicle length of 13 meters.
Sub-step 1025, recommending target vehicle length information corresponding to a single historical adoption rate larger than a second preset adoption rate to the shipper; the second preset adoption rate represents the adoption rate of the single historical vehicle length information recommended by the shipper for similar goods within the preset time length.
The second preset acceptance rate may represent an acceptance rate of a single historical vehicle length information recommended by the shipper for similar goods to be shipped over a preset time period, such as a week, a day, etc. That is, there may be a change in the second preset acceptance rate when the preset duration arrives. For example, the second preset acceptance rate corresponding to the previous week may be 0.5, and the second preset acceptance rate corresponding to the current week may be updated to 0.4.
In some application scenarios, if it is detected that the single historical adoption rate is greater than the second preset adoption rate, target vehicle length information corresponding to the single historical adoption rate may be recommended to the shipper. For example, for the shipper B, the single historical acceptance rate for the 9.6 meter length information is 0.6, and the single historical acceptance rate for the 13 meter length information is 0.3. At this time, if the second preset acceptance rate is 0.5, the target vehicle length information of 9.6 m may be recommended to the shipper.
Through the sub-step 1024 and the sub-step 1025, a single historical adoption rate can be determined from the perspective of the shipper, so that the vehicle length information determined based on the single historical adoption rate can better meet the shipping intention of the shipper, and the recommendation accuracy is improved.
In some optional implementations, the target shipment parameter includes a target cargo weight parameter and a target cargo category parameter; and the above step 103 may comprise sub-step 1031: searching the vehicle length information corresponding to the target cargo weight parameter in the first mapping relation for recommendation; and in response to the fact that the cargo type detail information exists in the first mapping relation, searching the vehicle length information corresponding to the target cargo type parameter for recommendation.
In some application scenarios, if there is no historical vehicle information matching the shipping information, a precise lookup may be performed in the first mapping. For example, shipper C has 10 orders for shipping wheat, with shipping weight parameters ranging between (20, 25) tons, with 3 orders taking 13 meters of vehicle length information, 3 orders taking 9.6 meters of vehicle length information, 3 orders taking 17 and 6.8 meters of vehicle length information, and 1 order taking 13 and 6.8 meters of vehicle length information. At this time, the historical acceptance rate corresponding to each order is less than the first preset acceptance rate 0.33, and the single historical acceptance rate corresponding to each vehicle length information is less than the second preset acceptance rate 0.5, so that accurate search can be performed in the first mapping relationship.
In some application scenarios, the first mapping relationship may be, for example, a relationship between each weight parameter range and different vehicle length information as shown in the following table.
As shown in the above table, if the shipper requests that wheat having a weight parameter ranging between (20, 25) tons be shipped, vehicle information having a vehicle length of 13 meters may be recommended to the shipper.
In other application scenarios, for different types of goods, more accurate recommendation can be performed further according to detailed information of the goods types. For example, if the shipper requests that a mechanical device with 25 tons be shipped, the shipper may be recommended vehicle information with a vehicle length of 17.5 meters; if the shipper requests that wheat with a weight parameter in the range of (20, 25) tons be shipped, vehicle information with a vehicle length of 13 meters may be recommended.
In some application scenarios, if no matching vehicle length information is found in the table above, a bottom-of-pocket recommendation may be further employed. In these application scenarios, for example, suitable second vehicle information may be searched for and recommended in a second mapping relationship as shown in the following table.
As shown in the above table, if the shipper requests to ship wheat with a weight parameter in the range of (15, 25) tons, the first vehicle information cannot be accurately found in the first mapping relationship. At this time, the second vehicle information with a larger division granularity may be searched in the above table. At this time, vehicle information with a vehicle length of 13 m may be recommended to the shipper.
In some optional implementation manners, the finding, in the sub-step 1031, the truck length information corresponding to the target cargo weight parameter in the first mapping relationship for recommendation may further include the following sub-steps:
step 1, if the detected value corresponding to the weight parameter of the target cargo is a single weight value, recommending the vehicle length information corresponding to the weight parameter range in which the weight value is located;
in some application scenarios, the shipper may provide accurate weight information. For example, the cargo to be consigned is 10 tons of wheat, 15 tons of cement, and the like. At this time, the length information corresponding to the weight parameter range in which the weight value is located may be recommended to the shipper. For example, for 10 tons of wheat, the shipper may be recommended the vehicle length information that the vehicle length corresponding to the weight parameter range of (5, 15) tons is 9.6 meters.
And substep 2, if the detected value corresponding to the weight parameter of the target cargo corresponds to the weight parameter range value, recommending the vehicle length information corresponding to the weight parameter range value corresponding to the weight upper limit value and the weight lower limit value.
In other application scenarios, the shipper may not be able to provide accurate weight information, which may only provide one estimated weight parameter range value. For example, the cargo to be shipped is (13, 15) tons of wheat, (20, 30) tons of cement, or the like. At this time, the shipper may be recommended the vehicle length information corresponding to the weight parameter range including the upper limit value and the lower limit value of the weight parameter range value. For example, for wheat of (13, 15) tons, the shipper may be recommended the vehicle length information that the vehicle length corresponding to the weight parameter range of (12, 20) tons is 9.6 meters.
Through the substep 1 and the substep 2, no matter the shipper provides a single weight value or a weight parameter range value in the freight information, the shipper can be matched with more appropriate vehicle information for recommendation, and the recommendation process is more intelligent.
In some alternative implementations, the historical vehicle information includes historical vehicle type information corresponding to historical carrier vehicles; the freight information comprises cargo type information; and the step 102 may include: obtaining the information of the selected historical vehicle type when the shipper corresponding to the goods to be shipped historically ships the goods corresponding to the goods type information; recommending the historical vehicle type information selected historically.
In some application scenarios, in addition to recommending vehicle information to the shipper that is appropriate for the vehicle length, vehicle information may also be recommended to the shipper that is appropriate for the vehicle type.
In these application scenarios, the computing device may first obtain historical vehicle type information that the shipper has selected for the same type of cargo as the current cargo to be shipped during the historical shipping process. For example, if the shipper a selects a high-hurdle vehicle model to ship wheat during the historical shipping process, the shipper may recommend the high-hurdle vehicle model to the shipper a second time to ship wheat. In this way, since the shipper has once selected the high hurdle vehicle model to ship the wheat, there is a high possibility that the high hurdle vehicle model will be selected when shipping again. In turn, the probability of the shipper adopting the recommended vehicle information may be increased.
In some optional implementations, the target shipment parameter includes a target shipment type parameter, a target shipment consignment distance parameter, and a target shipment weight parameter; and the step 103 may include: and searching in the first mapping relation according to the target cargo type parameter, the target cargo consignment distance parameter and the target cargo weight parameter.
In some application scenarios, the target cargo type parameter, the target cargo consignment distance parameter, and the target cargo weight parameter can be found in the first mapping relationship more accurately. In these application scenarios, the first mapping relationship may be, for example, a relationship between various cargo types, various cargo consignment distance ranges, cargo weight parameter ranges, and different vehicle type information as shown in the following table.
As shown in the above table, if the shipper requests the shipment of 150 km, 20 t of office supplies, the shipper can be recommended the vehicle information whose vehicle type is the high column.
In some application scenarios, if no matching vehicle type information is found in the table above, bottom-in-pocket recommendation may be further employed. In these application scenarios, for example, suitable second vehicle information may be searched for and recommended in a second mapping relationship as shown in the following table.
As shown in the above table, if the shipper requests the shipment of office supplies having a weight parameter range of (1, 2) tons, second vehicle information whose vehicle type is a flat panel, a high column, or a van may be recommended to the shipper. In some application scenarios, the weight parameter range matched with the freight information can be searched in the first-level pocket bottom weight parameter range, and if the weight parameter range is not searched in the first-level pocket bottom weight parameter range, the weight parameter range can be continuously searched in the second-level pocket bottom weight parameter range, so that the probability of searching the vehicle of the matched vehicle type is further improved.
Please further refer to the following table, which shows partial acceptance rate data of the shipper for the recommended vehicle information by using the vehicle information recommendation method provided by the embodiment of the present application and the vehicle information recommendation method provided in the related art.
As can be seen from the above table, with the vehicle information recommendation method provided in the embodiment of the present application, that is, according to the freight information of the goods to be consigned, historical freight information matched with the freight information is determined, where the freight information includes the target freight parameter; in response to detecting that historical vehicle information for carrying historical cargos corresponding to the historical freight information exists, recommending the historical vehicle information; in response to the fact that the historical vehicle information does not exist, first vehicle information corresponding to the target freight parameter is searched in a first mapping relation between a freight parameter range and the vehicle information and serves as recommended vehicle information; in response to that the first vehicle information is not found, second vehicle information corresponding to the target freight parameter is found in a second mapping relation between the freight parameter range and the vehicle information and serves as recommended vehicle information; the granularity of the freight parameter range in the second mapping relation is larger than the granularity of the freight parameter range in the first mapping relation. Therefore, the vehicle length acceptance rate and the vehicle type acceptance rate are improved by combining three recommendation modes (recommending according to historical vehicle information, accurately recommending based on the first mapping relation and recommending the bottom of the vehicle based on the second mapping relation). Then, the vehicle information recommended by the vehicle information recommendation method based on the embodiment of the application can be proved to be more accurate than the recommended information in the related technology.
Referring to fig. 2, a block diagram of a vehicle information recommendation device provided in an embodiment of the present application is shown, where the vehicle information recommendation device may be a module, a program segment, or a code on an electronic device. It should be understood that the apparatus corresponds to the above-mentioned embodiment of the method of fig. 1, and can perform various steps related to the embodiment of the method of fig. 1, and the specific functions of the apparatus can be referred to the description above, and the detailed description is appropriately omitted here to avoid redundancy.
Optionally, the vehicle information recommendation apparatus includes a determination module 201, a history recommendation module 202, a first search module 203, and a second search module 204. The determining module 201 is configured to determine, according to freight information of a to-be-consigned cargo, historical freight information matched with the freight information, where the freight information includes a target freight parameter; a history recommending module 202, configured to recommend history vehicle information in response to detecting that there is history vehicle information for carrying history goods corresponding to the history freight information; the first searching module 203 is configured to search, in response to detecting that the historical vehicle information does not exist, first vehicle information corresponding to the target freight parameter in a first mapping relationship between a freight parameter range and the vehicle information as recommended vehicle information; the second searching module 204 is configured to search, in response to that the first vehicle information is not found, second vehicle information corresponding to the target freight parameter in a second mapping relationship between a freight parameter range and the vehicle information, as recommended vehicle information; the granularity of the freight parameter range in the second mapping relation is larger than the granularity of the freight parameter range in the first mapping relation.
Optionally, the historical vehicle information includes historical vehicle length information corresponding to the historical carrier vehicle; and the history recommendation module 202 is further configured to: acquiring the historical adoption rate of the shipper corresponding to the goods to be shipped to the historical vehicle length information; judging whether the historical adoption rate is greater than a first preset adoption rate or not; the first preset adoption rate represents the adoption rate of similar historical vehicle length information recommended by the shipper for similar goods within a preset time length; and if the historical adoption rate is greater than the first preset adoption rate, recommending the historical vehicle length information to the shipper.
Optionally, the historical vehicle length information includes a plurality of types of vehicle length information with different specifications; and the history recommendation module 202 is further configured to: if the historical adoption rate is not greater than the first preset adoption rate, respectively calculating a single historical adoption rate corresponding to each vehicle length information in the historical vehicle length information by the shipper; recommending target vehicle length information corresponding to a single historical adoption rate larger than a second preset adoption rate to the shipper; the second preset adoption rate represents the adoption rate of the single historical vehicle length information recommended by the shipper for similar goods within the preset time length.
Optionally, the target freight parameters include a target freight weight parameter and a target freight category parameter; and the first lookup module 203 is further configured to: searching the vehicle length information corresponding to the target cargo weight parameter in the first mapping relation for recommendation; and in response to the fact that the cargo type detail information exists in the first mapping relation, searching the vehicle length information corresponding to the target cargo type parameter for recommendation.
Optionally, the first lookup module 203 is further configured to: if the detected value corresponding to the target cargo weight parameter is a single weight value, recommending the vehicle length information corresponding to the weight parameter range in which the weight value is located; and if the detected value corresponding to the weight parameter of the target cargo corresponds to the weight parameter range value, recommending the vehicle length information corresponding to the weight parameter range value, wherein the weight upper limit value and the weight lower limit value correspond to the weight parameter range value.
Optionally, the historical vehicle information includes historical vehicle type information corresponding to historical carrier vehicles; the freight information comprises cargo type information; and the history recommendation module 202 is further configured to: obtaining the information of the selected historical vehicle type when the shipper corresponding to the goods to be shipped historically ships the goods corresponding to the goods type information; recommending the historical vehicle type information selected historically.
Optionally, the target freight parameters include a target freight type parameter, a target freight consignment distance parameter, and a target freight weight parameter; and the first lookup module 203 is further configured to: and searching in the first mapping relation according to the target cargo type parameter, the target cargo consignment distance parameter and the target cargo weight parameter.
It should be noted that, for the convenience and brevity of description, the specific working procedure of the above-described apparatus may refer to the corresponding procedure in the foregoing method embodiment, and the description is not repeated herein.
Referring to fig. 3, fig. 3 is a schematic structural diagram of an electronic device for executing a vehicle information recommendation method according to an embodiment of the present application, where the electronic device may include: at least one processor 301, e.g., a CPU, at least one communication interface 302, at least one memory 303, and at least one communication bus 304. Wherein the communication bus 304 is used for realizing direct connection communication of the components. The communication interface 302 of the device in the embodiment of the present application is used for performing signaling or data communication with other node devices. The memory 303 may be a high-speed RAM memory or a non-volatile memory (e.g., at least one disk memory). The memory 303 may optionally be at least one memory device located remotely from the aforementioned processor. The memory 303 stores computer readable instructions, and when the computer readable instructions are executed by the processor 301, the electronic device may execute the method process shown in fig. 1.
It will be appreciated that the configuration shown in fig. 3 is merely illustrative and that the electronic device may include more or fewer components than shown in fig. 3 or may have a different configuration than shown in fig. 3. The components shown in fig. 3 may be implemented in hardware, software, or a combination thereof.
Embodiments of the present application provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, may perform the method processes performed by an electronic device in the method embodiment shown in fig. 1.
Embodiments of the present application provide a computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, which when executed by a computer, enable the computer to perform the method provided by the above-mentioned method embodiments, for example, the method may include: determining historical freight information matched with the freight information according to the freight information of the goods to be consigned, wherein the freight information comprises target freight parameters; in response to detecting that historical vehicle information for carrying historical cargos corresponding to the historical freight information exists, recommending the historical vehicle information; in response to the fact that the historical vehicle information does not exist, first vehicle information corresponding to the target freight parameter is searched in a first mapping relation between a freight parameter range and the vehicle information and serves as recommended vehicle information; in response to that the first vehicle information is not found, second vehicle information corresponding to the target freight parameter is found in a second mapping relation between the freight parameter range and the vehicle information and serves as recommended vehicle information; the granularity of the freight parameter range in the second mapping relation is larger than the granularity of the freight parameter range in the first mapping relation.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and there may be other divisions when actually implemented, and for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
In addition, units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
Furthermore, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
In this document, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
The above description is only an example of the present application and is not intended to limit the scope of the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A vehicle information recommendation method, characterized by comprising:
determining historical freight information matched with the freight information according to the freight information of the goods to be consigned, wherein the freight information comprises target freight parameters;
in response to detecting that historical vehicle information for carrying historical cargos corresponding to the historical freight information exists, recommending the historical vehicle information;
in response to the fact that the historical vehicle information does not exist, first vehicle information corresponding to the target freight parameter is searched in a first mapping relation between a freight parameter range and the vehicle information and serves as recommended vehicle information;
in response to that the first vehicle information is not found, second vehicle information corresponding to the target freight parameter is found in a second mapping relation between the freight parameter range and the vehicle information and serves as recommended vehicle information; the granularity of the freight parameter range in the second mapping relation is larger than the granularity of the freight parameter range in the first mapping relation.
2. The method of claim 1, wherein the historical vehicle information comprises historical vehicle length information corresponding to historical carrier vehicles; and
the recommending the historical vehicle information in response to detecting that the historical vehicle information for carrying the historical cargos corresponding to the historical freight information exists comprises the following steps:
acquiring the historical adoption rate of the shipper corresponding to the goods to be shipped to the historical vehicle length information;
judging whether the historical adoption rate is greater than a first preset adoption rate or not; the first preset adoption rate represents the adoption rate of similar historical vehicle length information recommended by the shipper for similar goods within a preset time length;
and if the historical adoption rate is greater than the first preset adoption rate, recommending the historical vehicle length information to the shipper.
3. The method of claim 2, wherein the historical vehicle length information includes a plurality of types of vehicle length information of different specifications; and
the recommending the historical vehicle information in response to detecting that the historical vehicle information for carrying the historical cargos corresponding to the historical freight information exists, further comprises:
if the historical adoption rate is not greater than the first preset adoption rate, respectively calculating a single historical adoption rate corresponding to each vehicle length information in the historical vehicle length information by the shipper;
recommending target vehicle length information corresponding to a single historical adoption rate larger than a second preset adoption rate to the shipper; the second preset adoption rate represents the adoption rate of the single historical vehicle length information recommended by the shipper for similar goods within the preset time length.
4. The method of claim 1, wherein the target shipment parameters include a target cargo weight parameter and a target cargo type parameter; and
in response to the fact that the historical vehicle information does not exist, searching first vehicle information corresponding to the target freight parameter in a first mapping relation between a freight parameter range and the vehicle information as recommended vehicle information, wherein the steps of:
searching the vehicle length information corresponding to the target cargo weight parameter in the first mapping relation for recommendation; and
and in response to the detection that the detailed information of the cargo type exists in the first mapping relation, searching the vehicle length information corresponding to the target cargo type parameter for recommendation.
5. The method according to claim 4, wherein the step of searching for the vehicle length information corresponding to the target cargo weight parameter in the first mapping relationship for recommendation comprises:
if the detected value corresponding to the target cargo weight parameter is a single weight value, recommending the vehicle length information corresponding to the weight parameter range in which the weight value is located;
and if the detected value corresponding to the weight parameter of the target cargo corresponds to the weight parameter range value, recommending the vehicle length information corresponding to the weight parameter range value, wherein the weight upper limit value and the weight lower limit value correspond to the weight parameter range value.
6. The method of claim 1, wherein the historical vehicle information comprises historical vehicle type information corresponding to historical carrier vehicles; the freight information comprises cargo type information; and
the recommending the historical vehicle information in response to detecting that the historical vehicle information for carrying the historical cargos corresponding to the historical freight information exists comprises the following steps:
obtaining the information of the selected historical vehicle type when the shipper corresponding to the goods to be shipped historically ships the goods corresponding to the goods type information;
recommending the historical vehicle type information selected historically.
7. The method of claim 1, wherein the target shipment parameters include a target cargo type parameter, a target cargo consignment distance parameter, and a target cargo weight parameter; and
in response to the fact that the historical vehicle information does not exist, searching first vehicle information corresponding to the target freight parameter in a first mapping relation between a freight parameter range and the vehicle information as recommended vehicle information, wherein the steps of:
and searching in the first mapping relation according to the target cargo type parameter, the target cargo consignment distance parameter and the target cargo weight parameter.
8. A vehicle information recommendation device characterized by comprising:
the determining module is used for determining historical freight information matched with the freight information according to the freight information of the goods to be consigned, wherein the freight information comprises target freight parameters;
the historical recommendation module is used for recommending the historical vehicle information in response to the fact that the historical vehicle information for carrying the historical cargos corresponding to the historical freight information exists;
the first searching module is used for searching first vehicle information corresponding to the target freight parameter in a first mapping relation between a freight parameter range and the vehicle information as recommended vehicle information in response to the fact that the historical vehicle information does not exist;
the second searching module is used for searching second vehicle information corresponding to the target freight parameter in a second mapping relation between the freight parameter range and the vehicle information in response to the first vehicle information not being searched, and the second vehicle information is used as recommended vehicle information; the granularity of the freight parameter range in the second mapping relation is larger than the granularity of the freight parameter range in the first mapping relation.
9. An electronic device comprising a processor and a memory, the memory storing computer readable instructions that, when executed by the processor, perform the method of any of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 7.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117669996A (en) * | 2024-02-01 | 2024-03-08 | 天津小铁马科技有限公司 | Vehicle scheduling method and device, electronic equipment and storage medium |
| CN117669996B (en) * | 2024-02-01 | 2024-04-26 | 天津小铁马科技有限公司 | Vehicle scheduling method and device, electronic equipment and storage medium |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117669996A (en) * | 2024-02-01 | 2024-03-08 | 天津小铁马科技有限公司 | Vehicle scheduling method and device, electronic equipment and storage medium |
| CN117669996B (en) * | 2024-02-01 | 2024-04-26 | 天津小铁马科技有限公司 | Vehicle scheduling method and device, electronic equipment and storage medium |
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