Freight screening result display method and computer readable storage medium

Abstract

The invention provides a freight screening result display method and a computer readable storage medium, and terminal equipment receives freight search information on a freight search interface, and sends a freight search request carrying the freight search information to a server after receiving a search operation on the freight search interface. The server determines a plurality of recall modes according to the freight search information and information of a first user corresponding to the terminal equipment, and sends the recall modes to the terminal equipment according to preference degree information of the first user for recall precision and / or preference degree information of the first user for historical search results obtained by the plurality of recall modes; determining recall numbers corresponding to the plurality of recall modes; a screening result is obtained based on the recall numbers corresponding to the recall modes, the server sends the screening result to the terminal device, and the terminal device displays the screening result. According to preferences of different drivers for transportation demand orders, screening results displayed for the drivers are determined in a personalized manner, so that the order receiving efficiency of the drivers is improved, and the order reaching efficiency is improved.

Description

Technical Field

[0001] The present disclosure relates to the field of intelligent transportation technology, and in particular to a method for displaying freight screening results and a computer-readable storage medium. Background Art

[0002] In the scenario of intelligent transportation, users can search and obtain the transportation requirements submitted by the current shipper through terminal devices. Users can accept orders in the transportation requirements, and the shipper and user can reach an order and carry out subsequent transportation.

[0003] However, currently, after the transportation requirements submitted by the shippers are shown to users, the efficiency of drivers accepting orders is not high. Summary of the invention

[0004] The present disclosure provides a method for displaying freight screening results and a computer-readable storage medium to solve the problem of low efficiency in accepting orders by drivers.

[0005] In a first aspect, the present disclosure provides a method for displaying freight screening results, the method comprising:

[0006] receiving a freight search request sent by a terminal device, wherein the freight search request includes freight search information;

[0007] In response to the freight search request, determining a plurality of recall methods according to the freight search information and information of a first user corresponding to the terminal device;

[0008] Determining the recall quantities corresponding to the multiple recall methods respectively according to the first user's preference information for recall accuracy and / or the first user's preference information for historical search results obtained by the multiple recall methods respectively;

[0009] Based on the recall quantities respectively corresponding to the multiple recall methods, determining the transport demand orders that meet the conditions of the multiple recall methods from all current transport demand orders to obtain a screening result;

[0010] The screening result is sent to the terminal device so that the terminal device displays the screening result.

[0011] In some embodiments, the method further comprises:

[0012] Determining the first user's preference score for the precise transportation demand orders according to the historical number of precise transportation demand orders viewed by the first user and the historical number of precise transportation demand orders for which the first user has placed orders;

[0013] The first user's preference score for the accurate transportation demand order is used as the first user's preference degree information for recall accuracy.

[0014] In some embodiments, determining the first user's preference score for the precise transportation demand order based on the historical number of precise transportation demand orders viewed by the first user and the historical number of precise transportation demand orders for which the first user has placed orders includes:

[0015] Obtaining the historical number of precise transportation demand orders viewed by the first user, the total historical number of transportation demand orders viewed by the first user, the historical number of precise transportation demand orders for which the first user has placed an order, and the total historical number of transportation demand orders for which the first user has placed an order within a first preset time period;

[0016] The first user's preference score for precise transportation demand orders is obtained by taking the weighted sum of the historical number of precise transportation demand orders viewed by the first user and the historical number of precise transportation demand orders for which the first user has placed orders, and dividing the weighted sum by the total historical number of transportation demand orders viewed by the first user and the total historical number of transportation demand orders for which the first user has placed orders.

[0017] In some embodiments, determining the recall quantities corresponding to the multiple recall methods respectively according to the first user's preference information for recall accuracy and / or the first user's preference information for historical search results obtained by the multiple recall methods respectively includes:

[0018] If the preference score of the first user for the precise transport demand order is greater than or equal to a first threshold, the initial recall quantity is increased by a first quantity to obtain a recall quantity corresponding to a precise recall method among the multiple recall methods; and the recall quantity corresponding to an inaccurate recall method among the multiple recall methods is determined as the initial recall quantity;

[0019] If the preference score of the first user for the precise transport demand order is less than or equal to a second threshold, the initial recall quantity is increased by a second quantity to obtain a recall quantity corresponding to the non-precise recall method among the multiple recall methods; and the recall quantity corresponding to the precise recall method among the multiple recall methods is determined as the initial recall quantity;

[0020] If the first user's preference score for the accurate transportation demand order is less than the first threshold and greater than the second threshold, it is determined that the recall quantities corresponding to the multiple recall methods are respectively the initial recall quantities.

[0021] In some embodiments, the method further comprises:

[0022] For each of the multiple recall methods, the following processing is performed respectively: according to the processing behavior information of the first user on the historical search results obtained by the recall method within the second preset time period, the preference score of the first user for the recall method is determined;

[0023] The first user's preference score for the recall method is used as the first user's preference level information for the historical search results obtained by the recall method.

[0024] In some embodiments, the first user's processing behavior information on the historical search results obtained by the recall method includes at least one of the following: the number of non-exposures and / or the number of exposures, the proportion of non-exposures and / or the proportion of exposures, the number of clicks, the exposure click rate, the number of transactions, and the exposure transaction rate;

[0025] The number of non-exposures is the number of historical search results obtained by the recall method that are not displayed to the first user;

[0026] The number of exposures is the number of historical search results obtained by the recall method displayed to the first user;

[0027] The non-exposure times ratio is a ratio of the non-exposure times to the total number of non-exposure times and the exposure times;

[0028] The exposure times ratio is the ratio of the exposure times to the total number of non-exposure times and the exposure times;

[0029] The number of clicks is the number of historical search results obtained by the first user viewing the recall method;

[0030] The exposure click rate is the ratio of the number of clicks to the number of exposures;

[0031] The number of transactions is the number of completed orders in the historical search results obtained by the first user in the recall method;

[0032] The exposure-to-conclusion ratio is the ratio of the number of transactions to the number of exposures.

[0033] In some embodiments, determining the recall quantities corresponding to the multiple recall methods respectively according to the first user's preference information for recall accuracy and / or the first user's preference information for historical search results obtained by the multiple recall methods respectively includes:

[0034] For each of the multiple recall methods, obtaining a first quantile and a second quantile of preference scores of all users for the recall method, respectively; the first quantile is greater than the second quantile;

[0035] If the first user's preference score for the recall method is greater than or equal to the first quantile, increasing the initial recall quantity by a third quantity to obtain the recall quantity corresponding to the recall method;

[0036] If the first user's preference score for the recall method is less than or equal to the second quantile, reducing the initial recall quantity by a fourth quantity to obtain the recall quantity corresponding to the recall method;

[0037] If the first user's preference score for the recall method is less than the first quantile and greater than the second quantile, the recall quantity corresponding to the recall method is determined to be the initial recall quantity.

[0038] In some embodiments, based on the recall quantities respectively corresponding to the multiple recall methods, determining the transport demand orders that meet the conditions of the multiple recall methods from all current transport demand orders to obtain the screening results includes:

[0039] Based on the recall quantities respectively corresponding to the multiple recall methods, determining a transport demand order that meets the conditions of the multiple recall methods from all current transport demand orders;

[0040] If the number of transport demand orders corresponding to the multiple recall methods reaches a cutoff condition, the preference score of the first user for accurate transport demand orders is greater than a third threshold, the number of all current transport demand orders is greater than or equal to a fourth number, and there are transport demand orders with a first generalization level among the transport demand orders corresponding to the multiple recall methods, then some or all of the transport demand orders with the first generalization level are deleted to obtain the screening result;

[0041] If the number of the transport demand orders corresponding to the multiple recall methods does not reach the cut-off condition, the transport demand orders respectively corresponding to the multiple recall methods are determined as the screening results.

[0042] In a second aspect, the present disclosure provides a method for displaying freight screening results, the method comprising:

[0043] Receive freight search information in the freight search interface;

[0044] After receiving the search operation on the freight search interface, sending a freight search request to a server, wherein the freight search request includes the freight search information;

[0045] Receive the screening result sent by the server, the screening result is that the server determines multiple recall methods according to the freight search information and the information of the first user corresponding to the terminal device; determines the recall quantities corresponding to the multiple recall methods according to the first user's preference information for recall accuracy and / or the first user's preference information for the historical search results obtained by the multiple recall methods; and determines the transport demand orders that meet the conditions of the multiple recall methods from all current transport demand orders based on the recall quantities corresponding to the multiple recall methods;

[0046] The filtering results are displayed.

[0047] In a third aspect, the present disclosure provides a server, comprising a memory and a processor, wherein the memory stores a computer program executable on the processor, and when the processor executes the program, the method described in the first aspect is implemented.

[0048] In a fourth aspect, the present disclosure provides a terminal device, including a memory and a processor, wherein the memory stores a computer program executable on the processor, and when the processor executes the program, the method described in the second aspect is implemented.

[0049] In a fifth aspect, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect above.

[0050] In a sixth aspect, the present disclosure provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the second aspect above.

[0051] The method for displaying freight screening results and the computer-readable storage medium provided by the embodiment of the present disclosure are as follows: the terminal device receives the freight search information input by the user in the freight search interface, and after receiving the search operation in the freight search interface, sends a freight search request carrying the freight search information to the server. In response to the freight search request, the server determines multiple recall methods according to the freight search information and the information of the first user corresponding to the terminal device, and determines the recall quantity corresponding to the multiple recall methods according to the first user's preference degree information for the recall accuracy and / or the first user's preference degree information for the historical search results obtained by the multiple recall methods; based on the recall quantity corresponding to the multiple recall methods, the transport demand orders that meet the conditions of the multiple recall methods are determined from all current transport demand orders to obtain the screening results, and the server sends the screening results to the terminal device, and the terminal device displays the screening results, and the user can view the screening results. Thus, according to the preferences of different drivers for the recalled transport demand orders, the freight screening results displayed to the driver are determined in a personalized manner, and the driver can quickly find a satisfactory transport demand, which improves the efficiency of the driver's order acceptance, thereby improving the efficiency of the shipper and the driver in reaching an order, and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 An architectural diagram of a freight screening result display system provided in an embodiment of the present disclosure;

[0053] Figure 2 An interactive schematic diagram of a method for displaying freight screening results provided by an embodiment of the present disclosure;

[0054] Figure 3 It is a flowchart of a method for displaying freight screening results provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0055] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0056] In the present disclosure, "at least one" refers to one or more, and "plurality" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a alone, b alone, or c alone can represent: a alone, b alone, c alone, a and b in combination, a and c in combination, b and c in combination, or a, b, and c in combination, where a, b, and c can be single or multiple. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance.

[0057] The directions or positional relationships indicated by terms such as "center", "longitudinal", "lateral", "up", "down", "left", "right", "front", and "back" are based on the directions or positional relationships shown in the accompanying drawings and are only for the convenience of describing the present disclosure and simplifying the description. They do not indicate or imply that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore should not be understood as a limitation on the present disclosure.

[0058] The terms "connected" and "connected" should be understood in a broad sense. For example, the "connected" or "connected" of a circuit structure may refer to not only a physical connection, but also an electrical connection or a signal connection. For example, it may be a direct connection, i.e. a physical connection, or it may be an indirect connection through at least one intermediate element, as long as the circuit is connected. It may also be the internal connection of two elements. In addition to signal connection through a circuit, signal connection may also refer to signal connection through a media medium, such as radio waves. For those of ordinary skill in the art, the specific meanings of the above terms in this disclosure may be understood according to specific circumstances.

[0059] The method for displaying freight screening results provided in this application can be applied to a freight screening result display system. Figure 1 , Figure 1The architecture diagram of a freight screening result display system provided in an embodiment of the present disclosure includes a server 102 and a terminal device 101. The server 102 and the terminal device 101 are connected via a network. Among them, the server 102 can be a server 102, or a server cluster composed of two or more servers. The terminal device 101 can include but is not limited to a terminal device, a terminal, a user equipment (UE), a mobile station, a mobile terminal, etc. The terminal device 101 can specifically be a mobile phone, a tablet computer, a computer with wireless transceiver function, a wearable device, a robot, a smart home device, etc.

[0060] Usually, the terminal device 101 can receive the freight search information input by the user in the freight search interface. After receiving the user's click operation at the search control, the terminal device 101 sends the freight search request carrying the freight search information to the server 102. The server 102 searches the current transportation demand list according to the freight search information, obtains the screening results, and sends the screening results to the terminal device 101. The terminal device 101 displays the screening results. After seeing the screening results, the user can click on any transportation demand list in the screening results on the freight search interface to accept the order. The cargo owner and the driver can then sign the order for subsequent transportation. Among them, the transportation demand list can also be called the source of goods. The transportation demand list usually contains the transportation demand information filled in by the cargo owner. For example, the transportation demand information may include loading place information, unloading place information, cargo weight, cargo volume, required vehicle model, required vehicle length, etc.

[0061] The present disclosure provides a method for displaying freight screening results, wherein a terminal device receives freight search information input by a user in a freight search interface, and after receiving a search operation in the freight search interface, sends a freight search request carrying the freight search information to a server. The server responds to the freight search request, determines multiple recall methods according to the freight search information and the information of the first user corresponding to the terminal device, and determines the recall quantities corresponding to the multiple recall methods according to the first user's preference information for recall accuracy and / or the first user's preference information for historical search results obtained by the multiple recall methods; based on the recall quantities corresponding to the multiple recall methods, a transport demand order that meets the conditions of the multiple recall methods is determined from all current transport demand orders to obtain a screening result, thereby determining the freight screening results displayed to the driver in a personalized manner according to the preferences of different drivers for the recalled transport demand orders, so that the driver can quickly find a satisfactory transport demand, thereby improving the driver's order acceptance efficiency, thereby improving the efficiency of the shipper and the driver in reaching an order, and improving the user experience.

[0062] See also Figure 2 , Figure 2The method provided in this embodiment can be applied to a display system for freight screening results, and the display system for freight screening results can be the above-mentioned Figure 1 The freight estimation system in the embodiment shown. Figure 2 As shown, the method provided in this embodiment may include the following steps 201 to 207.

[0063] Step 201: The terminal device receives freight search information on the freight search interface.

[0064] The freight search interface refers to an interface for searching for a transport demand form. The freight search interface can receive freight search information, which refers to condition information for searching for a transport demand form input by a user, so that the transport demand form is searched and displayed according to the user input. The freight search interface can be an interface in an application installed on a terminal device, or an interface displayed on the World Wide Web (web), and the present disclosure does not limit this.

[0065] Furthermore, the freight search information may include departure information and destination information.

[0066] The departure place information refers to the address information of the vehicle loading as indicated by the user. The departure place information can be one or more, that is, the driver can fill in one or more departure places. The departure place information can also be province, city, district or specific location information.

[0067] The destination information refers to the address information of the vehicle unloading indicated by the user. The destination information can be one or more, that is, the user can fill in one or more destinations. The destination information can also be province, city, district or specific location information.

[0068] Furthermore, the freight search information may also include at least one of the following: vehicle information, search load-bearing range, cargo category information, and vehicle type, etc.

[0069] The vehicle information refers to relevant information of the vehicle to be used to transport the goods indicated by the transportation demand. The vehicle information may include the search vehicle length and / or the search vehicle model. The search vehicle model may be vehicle type information, for example, the search vehicle model may be the model of the vehicle. Since there may be multiple vehicle lengths for the same model of vehicle, the vehicle information also includes the search vehicle length, so as to distinguish different vehicle types.

[0070] The search load-bearing range refers to the range of load that the current first user's vehicle can carry.

[0071] The cargo category information refers to the type of cargo to be transported. The packaging method refers to the packaging method of the cargo to be transported during transportation. For example, the packaging method may be bulk, carton packaging, foam box packaging, or basket packaging.

[0072] The vehicle type can be a full truckload or less-than-load. A full truckload means that the entire vehicle is required for transportation. Less-than-load means that part of the vehicle can be used for transportation, for example, you can share a vehicle with other people for transportation.

[0073] Step 202: After receiving the search operation on the freight search interface, the terminal device sends a freight search request to the server.

[0074] The freight search request includes freight search information.

[0075] Usually, the freight request interface also has a search control, that is, after the user enters the freight search information, he can click the search control to confirm the search, and the terminal device sends the freight search request to the server. After the server completes the search, it sends the screening results to the terminal device, and the corresponding screening results can be displayed on the freight search interface of the terminal device. The user can select the transportation demand form in the screening results to complete the transportation order.

[0076] Step 203: The server determines a plurality of recall methods in response to the freight search request according to the freight search information and the information of the first user corresponding to the terminal device.

[0077] The information of the first user may refer to a user name and a password.

[0078] Before the terminal device operates the freight search interface, it is usually necessary to log in, wherein the terminal device logs in as the first user. After receiving the search operation, the terminal device can carry the first user's information in the freight search request and send it to the server; the terminal device can also send the received first user's information to the server before the user operates the freight search interface, and the server will match the terminal device with the first user's information. After that, when the server receives the freight search request sent by the terminal device, it will automatically associate the freight search request with the first user's information.

[0079] Among them, the recall method refers to searching all current transportation demand orders according to different search conditions to obtain screening results.

[0080] Since the freight search information for each user or each time the user searches may be different, multiple recall methods for searching may be determined based on the freight search information and the information of the first user. For example, one or more recall methods are determined based on the departure information and the destination information; or one or more recall methods are determined based on the departure information, the destination information, and the vehicle information, etc. The present disclosure does not limit the determined recall methods.

[0081] Step 204: The server determines the recall quantities corresponding to the multiple recall methods according to the first user's preference information for recall accuracy and / or the first user's preference information for historical search results obtained by the multiple recall methods.

[0082] The recall accuracy refers to the degree to which the recall method meets the original search condition. The preference information of the first user for the recall accuracy refers to the recall accuracy of the recall method preferred by the first user.

[0083] Furthermore, the recall accuracy may include precise recall and generalized recall. Precise recall refers to a recall method in which the search condition meets the freight search information input by the user. Generalized recall refers to a recall method in which the search condition partially meets the freight search information input by the user.

[0084] The information about the first user's preference for historical search results obtained by multiple recall methods is used to indicate: for each of the multiple recall methods, the first user's preference for the screening results obtained when searching in the past. For example, based on the viewing and transaction status of the screening results obtained by a recall method when searching in the past by the first user, the first user's preference for the historical search results obtained by the recall method can be determined.

[0085] Among them, the recall quantity refers to the number of transportation demand orders obtained through the recall method.

[0086] In a possible implementation, the server may determine the recall quantities corresponding to the multiple recall methods according to the first user's preference information for recall accuracy.

[0087] In another possible implementation, the server may also determine the recall quantities corresponding to the multiple recall methods according to the first user's preference information for the historical search results obtained by the multiple recall methods.

[0088] In another possible implementation, the server may determine the recall quantities corresponding to the multiple recall methods according to the first user's preference information for recall accuracy and the first user's preference information for historical search results obtained by the multiple recall methods.

[0089] Step 205: The server determines the transport demand orders that meet the conditions of the multiple recall methods from all current transport demand orders based on the recall quantities corresponding to the multiple recall methods, and obtains a screening result.

[0090] Among them, all current transportation demand orders refer to the transportation demands proposed by the current cargo owner and have not been accepted by any user.

[0091] Through step 204, the server determines the recall quantities corresponding to the multiple recall methods, and for each recall method, the server obtains the transport demand sheet of the recall quantity according to the recall quantity corresponding to the recall method. All the obtained transport demand sheets are the screening results.

[0092] For example, the recall quantity corresponding to recall method A is 200. Assuming that the screening result obtained by recall method A is 300 transport demand orders, 200 transport demand orders are obtained from the 300 transport demand orders as the screening result of recall method A.

[0093] Furthermore, the server may sort all the transportation demand orders obtained above to obtain screening results.

[0094] Furthermore, when sorting all the transportation demand orders obtained above, the server may sort them according to the first user's preference information for recall accuracy and / or the first user's preference information for historical search results obtained by multiple recall methods.

[0095] Exemplarily, the server may sort the transport demand orders through a sorting model, which is a trained model for sorting the transport demand orders. All the transport demand orders obtained above may be input into the sorting model, and the first user's preference score for recall accuracy and / or the first user's preference score for historical search results obtained by multiple recall methods may be input into the sorting model to obtain a screening result.

[0096] Step 206: The server sends the screening result to the terminal device.

[0097] Step 207: The terminal device displays the screening results.

[0098] The terminal device can display the filtering results on the freight search interface, and can also jump from the freight search interface to the filtering result display interface to display the filtering results.

[0099] Furthermore, the terminal device can display the transport demand lists in the screening results in the order in which they are arranged by the server.

[0100] In this embodiment, the terminal device receives the freight search information input by the user in the freight search interface, and after receiving the search operation in the freight search interface, sends a freight search request carrying the freight search information to the server. In response to the freight search request, the server determines multiple recall methods according to the freight search information and the information of the first user corresponding to the terminal device, and determines the recall quantity corresponding to the multiple recall methods according to the first user's preference information for recall accuracy and / or the first user's preference information for the historical search results obtained by the multiple recall methods; based on the recall quantity corresponding to the multiple recall methods, the transport demand orders that meet the conditions of the multiple recall methods are determined from all current transport demand orders to obtain the screening results, and the server sends the screening results to the terminal device, and the terminal device displays the screening results, and the user can view the screening results. Therefore, according to the preferences of different drivers for the recalled transport demand orders, the freight screening results displayed to the driver are determined in a personalized manner, and the driver can quickly find a satisfactory transport demand, which improves the efficiency of the driver's order acceptance, thereby improving the efficiency of the shipper and the driver in reaching an order, and improving the user experience.

[0101] In some embodiments, the following steps 208 and 209 may be included before step 204 .

[0102] Step 208: The server determines the first user's preference score for the precise transportation demand orders based on the historical number of precise transportation demand orders viewed by the first user and the historical number of precise transportation demand orders for which the first user has placed orders.

[0103] Among them, the precise transportation demand order refers to the transportation demand order with precise recall accuracy.

[0104] The historical number of accurate transportation demand orders viewed by the first user refers to the number of accurate transportation demand orders viewed by the first user in previous search processes. Usually, viewing of a transportation demand order is determined by the user clicking on a corresponding transportation demand order.

[0105] The historical number of accurate transportation demand orders for which the first user has completed an order refers to the number of accurate transportation demand orders that the first user has viewed and accepted during previous searches. Usually, accepting an order means that the user confirms to accept the transportation demand order, thereby completing an order.

[0106] Further, step 208 may include the following steps 2081 and 2082 .

[0107] Step 2081, the server obtains the historical number of precise transportation demand orders viewed by the first user within the first preset time period, the total historical number of transportation demand orders viewed by the first user, the historical number of precise transportation demand orders for which the first user has placed orders, and the total historical number of transportation demand orders for which the first user has placed orders.

[0108] The first preset time period is a preset time period, which refers to the first preset time period before the current time. For example, the first preset time period may be 30 days.

[0109] The total historical number of transport demand orders viewed by the first user refers to the number of transport demand orders viewed by the first user in previous search processes. Usually, viewing of a transport demand order is determined by the user clicking on the corresponding transport demand order.

[0110] Among them, the total historical number of transportation demand orders for which the first user has completed an order refers to the number of transportation demand orders that the first user has viewed and accepted during previous searches. Usually, accepting an order means that the user confirms to accept the transportation demand order, thereby completing an order.

[0111] Step 2082: The server obtains the first user's preference score for precise transportation demand orders by taking the weighted sum of the historical number of precise transportation demand orders viewed by the first user and the historical number of precise transportation demand orders for which the first user has placed orders, and dividing the result by the weighted sum of the total historical number of transportation demand orders viewed by the first user and the total historical number of transportation demand orders for which the first user has placed orders.

[0112] For example, assuming that under the search conditions of driver A in the past 30 days, the number of clicks on precise transportation demand orders is A, the total number of clicks on transportation demand orders is B, the number of completed precise transportation demand orders is C, and the total number of completed transportation demand orders is D. And assuming that the weight of the number of clicks is 1, and the weight of the number of completed transactions is 100, that is, 1 transaction is equivalent to 100 clicks.

[0113] Driver A's preference score for accurate transport demand orders can be obtained using the following formula (1).

[0114] S=(A+C*100) / (B+D*100) Formula (1)

[0115] Among them, S is the preference score of driver A for accurate transportation demand orders.

[0116] Furthermore, the preference score of driver A for the generalized transport demand order is (1-the preference score of driver A for the precise transport demand order).

[0117] It can be understood that the value range of driver A's preference score for precise transportation demand orders is [0,1]. The higher the preference score of driver A for precise transportation demand orders, the greater the degree of driver A's preference for precise transportation demand orders. Conversely, the lower the preference score of driver A for precise transportation demand orders, the greater the degree of driver A's preference for generalized transportation demand orders.

[0118] Step 209: The server uses the first user's preference score for the accurate transportation demand list as the first user's preference degree information for recall accuracy.

[0119] In this embodiment, the server can determine the first user's preference score for precise transportation demand orders by viewing the historical number of precise transportation demand orders viewed by the first user and the historical number of precise transportation demand orders for which the first user has completed orders. The first user's preference score for precise transportation demand orders is used as the first user's preference information for recall accuracy. Subsequently, the recall quantities corresponding to the multiple recall methods are determined based on the first user's preference information for recall accuracy and / or the first user's preference information for historical search results obtained for multiple recall methods. Based on the recall quantities corresponding to the multiple recall methods, the transportation demand orders that meet the conditions of the multiple recall methods are determined from all current transportation demand orders to obtain screening results, thereby personalizing the freight screening results displayed to the driver based on the preferences of different drivers for the recalled transportation demand orders. The driver can quickly find satisfactory transportation needs, which improves the driver's efficiency in accepting orders, thereby improving the efficiency of the shipper and the driver in reaching an order, and improving the user experience.

[0120] Furthermore, in a possible implementation of step 204, the server determines the recall quantities corresponding to the multiple recall methods according to the first user's preference information for recall accuracy. This can be implemented in the following manner.

[0121] Step 2041: The server determines whether the first user's preference score for the accurate transportation demand order is greater than or equal to a first threshold.

[0122] The first threshold is a preset value that is less than 1 and greater than 0. For example, the first threshold may be 0.7 or 0.8, etc., and the present disclosure does not limit the value of the first threshold.

[0123] If yes, continue to execute step 2042; if no, continue to execute step 2043.

[0124] Step 2042: The server increases the initial recall quantity by a first quantity to obtain a recall quantity corresponding to a precise recall method among the multiple recall methods, and determines that a recall quantity corresponding to a non-precise recall method among the multiple recall methods is the initial recall quantity.

[0125] The first number is a preset value.

[0126] Step 2043: The server determines whether the first user's preference score for the accurate transportation demand order is less than or equal to a second threshold.

[0127] The second threshold is a preset value that is less than 1 and greater than 0. The second threshold is less than the first threshold. For example, the second threshold may be 0.2 or 0.3, etc., and the present disclosure does not limit the value of the second threshold.

[0128] If yes, continue to execute step 2044; if no, continue to execute step 2045.

[0129] Step 2044: The server increases the initial recall quantity by a second quantity to obtain a recall quantity corresponding to the non-precise recall method among the multiple recall methods, and determines the recall quantity corresponding to the precise recall method among the multiple recall methods as the initial recall quantity.

[0130] Step 2045: The server determines that the recall quantities corresponding to the multiple recall methods are respectively the initial recall quantities.

[0131] For example, assume that the recall methods corresponding to the freight search information input by driver B are respectively recall method 1, recall method 2, recall method 3, recall method 4 and recall method 5. Among them, recall method 1, recall method 2 and recall method 3 are all precise recalls, and multiple recalls are performed in accordance with the driver's search conditions. Recall method 4 and recall method 5 are both generalized recalls. When there are few precise transport demand orders and many generalized transport demand orders, or when driver B has a high preference for generalized transport demand orders, more generalized transport demand orders can be displayed to driver B.

[0132] If driver B has a relatively high preference for precise transport demand orders, the recall quantity of the precise recall method can be increased, that is, a certain recall quantity can be added on the basis of the initial recall quantity of each precise recall method. For example, recall method 1 adds 100 transport demand orders, recall method 2 adds 50 transport demand orders, and recall method 3 adds 80 transport demand orders. The recall quantity of other recall methods remains unchanged and is the initial recall quantity.

[0133] If driver B has a relatively high preference for generalized transport demand orders, the recall quantity of the generalized recall method can be increased, that is, a certain recall quantity can be added on the basis of the initial recall quantity of each generalized recall method. For example, recall method 4 adds 50 transport demand orders, and recall method 5 adds 70 transport demand orders. The recall quantity of other recall methods remains unchanged and is the initial recall quantity.

[0134] In this embodiment, the recall quantity of each recall method is adjusted based on the initial recall quantity according to the first user's preference for the precise transport demand order. This makes the recall quantity consistent with the user's preference for the precise transport demand order and the generalized transport demand order, and the freight screening results displayed to the driver are determined in a personalized manner. The driver can quickly find satisfactory transport needs, which improves the driver's order acceptance efficiency, thereby improving the efficiency of the shipper and the driver in reaching an order, and improving the user experience.

[0135] In some embodiments, before step 204, the following steps may also be included.

[0136] Step 210: The server performs the following processing on each of the multiple recall methods: determining the first user's preference score for the recall method based on the first user's processing behavior information on the historical search results obtained by the recall method within the second preset time period.

[0137] The second preset time period is a preset time period, which refers to a second preset time period before the current time. For example, the second preset time period may be 30 days. The second preset time period may be the same as or different from the first preset time period.

[0138] The first user's processing behavior information on the historical search results obtained by the recall method refers to the first user's processing behavior information on the screening results obtained by the recall method. Exemplarily, the first user's processing behavior information on the historical search results obtained by the recall method includes at least one of the following: the number of non-exposures and / or the number of exposures, the proportion of non-exposures and / or the proportion of exposures, the number of clicks, the exposure click rate, the number of transactions, and the exposure transaction rate.

[0139] The number of non-exposures is the number of historical search results obtained by the recall method that were not displayed to the first user.

[0140] The number of exposures is the number of historical search results obtained by the recall method displayed to the first user.

[0141] The non-exposure ratio is the ratio of non-exposures to the total number of non-exposures and exposures.

[0142] The exposure ratio is the ratio of the number of exposures to the total number of non-exposures and exposures.

[0143] The number of clicks is the number of historical search results obtained by the first user viewing the recall method.

[0144] The impression click-through rate is the ratio of clicks to impressions.

[0145] The number of transactions is the number of completed orders in the historical search results obtained by the first user in the recall method.

[0146] The exposure-to-conversion rate is the ratio of the number of transactions to the number of exposures.

[0147] The first user's preference score for each recall method is determined through the first user's processing behavior information for the historical search results obtained by each recall method.

[0148] Exemplarily, the first user's processing behavior information on the historical search results obtained by the recall method includes the number of non-exposures, the number of exposures, the proportion of non-exposures, the number of clicks, the exposure click rate, the number of transactions, and the exposure transaction rate. The first user's processing behavior information on the historical search results obtained by the recall method is normalized, and then the first user's preference score for the recall method can be obtained by the following formula (2).

[0149] The first user's preference score for the recall method = normalized value of non-exposure times + normalized value of exposure times + normalized value of non-exposure ratio + normalized value of click times + normalized value of exposure click rate + normalized value of transaction times + normalized value of exposure transaction rate Formula (2)

[0150] The calculation result may be in the form of: first user ID, recall method ID, recall method preference score, which represents: the preference score of the first user ID for the recall method ID.

[0151] Step 211: The server uses the first user's preference score for the recall method as the first user's preference level information for the historical search results obtained by the recall method.

[0152] In this embodiment, the first user's preference score for each recall method is determined through the first user's processing behavior information for the historical search results obtained by each recall method, and the first user's preference score for the recall method is used as the first user's preference degree information for the historical search results obtained by the recall method to determine the recall quantity corresponding to each of the multiple recall methods. Based on the recall quantities corresponding to each of the multiple recall methods, the transport demand orders that meet the conditions of the multiple recall methods are determined from all current transport demand orders to obtain the screening results, thereby personalizing the freight screening results displayed to the driver based on the preferences of different drivers for the recalled transport demand orders, so that the driver can quickly find satisfactory transportation needs, which improves the driver's efficiency in accepting orders, thereby improving the efficiency of the shipper and the driver in reaching an order, and improving the user experience.

[0153] Furthermore, in another possible implementation of step 204, the server may also determine the recall quantities corresponding to the multiple recall methods according to the first user's preference information for the historical search results obtained by the multiple recall methods. This may be implemented as follows.

[0154] Step 204a: For each of the multiple recall methods, the server obtains the first quantile and the second quantile of the preference scores of all users for the recall method.

[0155] The first quantile is greater than the second quantile. For example, the first quantile may be the 80th quantile, and the second quantile may be the 20th quantile.

[0156] Step 204b: The server determines whether the first user's preference score for the recall method is greater than or equal to the first quantile.

[0157] If yes, continue to execute step 204c; if no, continue to execute step 204d.

[0158] Step 204c: The server increases the initial recall quantity by a third quantity to obtain a recall quantity corresponding to the recall method.

[0159] Step 204d: The server determines whether the first user's preference score for the recall method is less than or equal to the second quantile.

[0160] If yes, continue to execute step 204e; if no, continue to execute step 204f.

[0161] Step 204e: The server reduces the initial recall quantity by a fourth quantity to obtain a recall quantity corresponding to the recall method.

[0162] Step 204f: The server determines that the recall quantity corresponding to the recall method is the initial recall quantity.

[0163] For example, assuming that the first quantile may be the 80th quantile and the second quantile may be the 20th quantile, the quantiles of all users' preference scores for each recall path are counted to obtain the 20th quantile and the 80th quantile.

[0164] When the preference score of driver C for the recall method is less than or equal to the 20th percentile, the recall quantity of driver C for the recall method is reduced by M; M is an integer greater than 0, and M is obtained according to the recall method. It can be understood that M can be adapted according to different recall methods, and the same value can be set for different recall methods.

[0165] When the preference score of driver C for the recall method is greater than or equal to the 80th percentile, the recall quantity of driver C for the recall method increases by N; N is an integer greater than 0, and N is obtained according to the recall method. It can be understood that N can be adapted according to different recall methods, and the same value can be set for different recall methods.

[0166] For example, assume that the recall methods corresponding to the input freight search information of driver C are respectively recall method 1, recall method 2, recall method 3, recall method 4 and recall method 5. After statistical analysis, the 20th percentile and 80th percentile of the preference scores of recall method 1, recall method 2, recall method 3, recall method 4 and recall method 5 are shown in Table 1 below.

[0167] Table 1. 20th and 80th percentiles of the recall route preference scores

[0168] Recall method 20th percentile 80th percentile 1st Road 0.3 1.5 2-way 1.0 2.2 3-Way 0.1 0.7 4-way 0.5 1.2 5-way 1.5 3.5

[0169] Driver C's preference scores for recall method 1, recall method 2, recall method 3, recall method 4 and recall method 5 are 0.5, 2.8, 1.5, 0.1 and 2.0 respectively. The recall quantity for each recall method of driver C is adjusted as follows: the recall quantity for recall method 1 is increased by 0, i.e. unchanged; the recall quantity for recall method 2 is increased by 100; the recall quantity for recall method 3 is increased by 100; the recall quantity for recall method 4 is decreased by 50; the recall quantity for recall method 5 is increased by 0, i.e. unchanged.

[0170] In this embodiment, for each recall method among multiple recall methods, the server obtains the first quantile and the second quantile of all users' preference scores for the recall method; if the first quantile is greater than the second quantile and the first user's preference score for the recall method is greater than or equal to the first quantile, the initial recall quantity is increased by the third quantity to obtain the recall quantity corresponding to the recall method; if the first user's preference score for the recall method is less than or equal to the second quantile, the initial recall quantity is reduced by the fourth quantity to obtain the recall quantity corresponding to the recall method; if the first user's preference score for the recall method is less than the first quantile and greater than the second quantile, the recall quantity corresponding to the recall method is determined to be the initial recall quantity. Thus, according to the preference information of the first user for the historical search results obtained for the multiple recall methods, the recall quantities corresponding to the multiple recall methods are determined; based on the recall quantities corresponding to the multiple recall methods, the transport demand orders that meet the conditions of the multiple recall methods are determined from all current transport demand orders to obtain the screening results, thereby according to the preferences of different drivers for the recalled transport demand orders, the freight screening results displayed to the drivers are personalized, the drivers can quickly find satisfactory transportation needs, the driver's order acceptance efficiency is improved, thereby improving the efficiency of the shipper and the driver to reach an order, and improving the user experience.

[0171] In some embodiments, in another possible implementation of step 204, the recall quantity corresponding to the recall method can be adjusted by combining the above two possible implementations, which will not be described in detail here.

[0172] In some embodiments, step 205 may be implemented through steps 2051 to 2054 as follows.

[0173] Step 2051: The server determines a transport demand order that meets the conditions of multiple recall methods from all current transport demand orders based on the recall quantities corresponding to the multiple recall methods.

[0174] Step 2052: determine whether the number of transport demand orders corresponding to the multiple recall methods reaches the cutoff condition, the first user's preference score for accurate transport demand orders is greater than the third threshold, and the number of all current transport demand orders is greater than or equal to

[0175] In the fourth quantity, among the transportation demand orders corresponding to the plurality of recall methods, there is a transportation demand order whose generalization level is the first level.

[0176] If yes, continue to execute step 2053; if no, continue to execute step 2054.

[0177] The third threshold value may be the same as or different from the first threshold value. For example, the third threshold value may be 0.8.

[0178] The fourth number is a preset value.

[0179] Among them, the generalized transportation demand order can determine the generalization level according to the generalization degree. The larger the generalization level, the lower the generalization degree. For example, the first level, the second level and the third level can be set, among which the first level has the largest generalization degree.

[0180] Step 2053: Delete some or all of the transportation demand orders at the first generalization level to obtain a screening result.

[0181] Step 2054: determine the transport demand orders corresponding to the multiple recall methods as the screening results.

[0182] Furthermore, after step 2051, the transport demand orders corresponding to the multiple recall methods may be deduplicated to obtain a deduplicated transport demand order. The transport demand orders corresponding to the multiple recall methods in step 2052 are deduplicated transport demand orders.

[0183] In some embodiments, before step 2052, the server may also determine the generalization levels corresponding to the transport demand orders corresponding to the multiple recall methods according to the freight search information input by the user and the transport demand orders corresponding to the multiple recall methods.

[0184] The following describes in a specific manner how to obtain the generalization level of the transportation demand order.

[0185] The method of this embodiment may include the following steps 1 and 2.

[0186] Step 1: According to the freight search information and the transportation demand information in the transportation demand sheet, determine the generalization level of each category of information.

[0187] In this embodiment, the generalization level of each category of information is set to the first level, the second level and the third level, wherein the generalization degree of the first level is the largest, and the generalization degree of the second level is greater than that of the third level.

[0188] Step 2: Determine the generalization level of the transport demand form based on the generalization level of each category.

[0189] Exemplarily, if there are three or more first levels in the generalization levels of each category of information, it is determined that the generalization level of the transportation demand sheet is the first level.

[0190] Furthermore, step 1 can be implemented as follows:

[0191] The freight search information included in the freight search request includes departure information and destination information. In the case where the departure information is the departure location, step 1 of the method provided in this embodiment may include the following steps 11 and 12.

[0192] Step 11: Determine the generalization level of the departure place of the transport demand order based on the departure place information in the freight search information and the loading place information in the transport demand order.

[0193] With respect to the departure place information in the freight search information and the loading place information in the transport demand sheet, the generalization degree value of the departure place of the transport demand sheet may be determined.

[0194] In a possible implementation, the departure information in the freight search information is the departure location, and the user can fill in one or more departure locations, for example, the user can fill in up to 3 departure locations. The departure location is usually in the province / city / district dimension, and step 11 can be implemented through the following steps 111-116.

[0195] Step 111, determine the coordinate position of the departure point according to the departure point.

[0196] The coordinate position of the departure place can be expressed by the longitude and latitude of the departure place. The following description will be made using the coordinate position of the departure place as the longitude and latitude of the departure place.

[0197] If the departure location in the freight search information is in the province dimension, the longitude and latitude of the provincial administrative center can be taken as the longitude and latitude of the departure location; if the departure location in the freight search information is in the city / district dimension, the longitude and latitude of the city / district administrative center can be taken as the longitude and latitude of the departure location.

[0198] Step 112: Obtain a first empty driving distance between the coordinate position of the departure place and the coordinate position of the loading place in the transportation demand list.

[0199] Exemplarily, the unit of the first idle driving distance may be km.

[0200] It should be noted that if there are multiple departure locations in the freight search information, the distance between the coordinate position of each departure location and the coordinate position of the loading location in the transportation demand list is calculated, and the smallest distance is taken as the first empty driving distance. If the coordinate position is expressed in longitude and latitude, the distance between the longitude and latitude of each departure location and the longitude and latitude of the loading location in the transportation demand list is calculated, and the smallest distance is taken as the first empty driving distance.

[0201] Step 113: Obtain the transportation distance between the loading place and the unloading place in the transportation demand sheet.

[0202] For example, the unit of the transport distance may be km.

[0203] Step 114: Obtain the upper limit of the generalized distance of the departure place.

[0204] Furthermore, the upper limit of the generalized distance of the departure point can be obtained by the following formula (3).

[0205] Upper limit of generalized distance of departure place = min{transportation distance*10%+10km,200km} Formula (3)

[0206] Step 115: Determine a generalization degree value of the departure place according to the first empty driving distance and the upper limit of the generalization distance of the departure place.

[0207] Furthermore, the generalization degree value of the departure place can be obtained by the following formula (4).

[0208] x1= D / Generalized distance upper limit formula of departure place (4)

[0209] Among them, x1 is the generalization degree value of the departure place, and D is the first empty driving distance.

[0210] Step 116: Determine the generalization level of the departure place according to the generalization degree value of the departure place.

[0211] If the value of the generalization degree of the departure place is less than or equal to 1, it is determined that the generalization level of the departure place is the third level.

[0212] If the generalization degree value of the departure place is greater than 1 and less than or equal to 2, it is determined that the generalization level of the departure place is the second level.

[0213] If the value of the generalization degree of the departure place is greater than or equal to 2, it is determined that the generalization level of the departure place is the first level.

[0214] In a possible implementation, the departure place information in the freight search information includes a departure place search vicinity range. The departure place search vicinity range refers to a range within a certain range around the departure place as the departure place. For example, the departure place search vicinity range may be 20km, 50km, 100km or 200km around the departure place. Further, step 11 may be performed through the following steps 11a to 11c.

[0215] Step 11a: Obtain a second empty driving distance between the coordinate position of the departure place and the coordinate position of the loading place in the transportation demand list.

[0216] If the coordinate position is longitude and latitude, the second empty driving distance between the longitude and latitude of the departure place and the longitude and latitude of the loading place in the transportation demand list is obtained.

[0217] Step 11a is similar to the above step 112. The longitude and latitude of the departure place refers to the longitude and latitude of the departure place location input by the user.

[0218] Step 11b: Determine a generalization degree value of the search near the departure place according to the second empty driving distance and the search near the departure place.

[0219] Furthermore, the generalization degree value of the initial departure point search nearby can be obtained by the following formula (5).

[0220] x3=D / driver search generalization distance numerical formula (5)

[0221] Among them, x3 is the generalization degree value of the search near the initial departure point, and D is the second empty driving distance.

[0222] If the search range near the departure point is 20km, and the second empty driving distance D <= 50km, then the generalization degree value of the search near the departure point is min{2.0, x3};

[0223] If the search range near the departure point is 200km, and the second empty driving distance D>250km, the generalization degree value of the search near the departure point is 3.0;

[0224] In all cases other than the above, the generalization value of the departure point search nearby is x3.

[0225] Step 11c: Determine the generalization level of the departure place search according to the generalization degree value of the departure place search.

[0226] If the generalization degree value of the departure place search nearby is less than or equal to 1, it is determined that the generalization level of the departure place search nearby is the third level.

[0227] If the generalization degree value of the departure place search nearby is greater than 1 and less than or equal to 2, it is determined that the generalization level of the departure place search nearby is the second level.

[0228] If the generalization degree value of the departure place search nearby is greater than or equal to 2, it is determined that the generalization level of the departure place search nearby is the first level.

[0229] Step 12: Determine the destination generalization level of the transport demand sheet according to the destination information in the freight search information and the unloading place information in the transport demand sheet.

[0230] With respect to the destination information in the freight search information and the loading place information in the transport demand sheet, a destination generalization degree value of the transport demand sheet may be determined.

[0231] In a possible implementation, the destination information in the freight search information includes a destination point, and the user can fill in one or more destination points. For example, the user can fill in up to 5 destination points. The destination point is usually a province / city / district dimension, wherein if the dimension of the destination point is nationwide, the destination generalization degree value may not be calculated. Step 12 can be implemented by the following steps 121-126.

[0232] Step 121: Determine the coordinate position of the destination according to the destination point.

[0233] The destination coordinate position may be represented by the destination longitude and latitude, and the following description will be made using the destination coordinate position as the destination longitude and latitude.

[0234] If the dimension of the destination point in the freight search information is province, the longitude and latitude of the provincial administrative center can be taken as the longitude and latitude of the departure point; if the dimension of the destination point in the freight search information is city / district, the longitude and latitude of the city / district administrative center can be taken as the longitude and latitude of the departure point.

[0235] Step 122: Determine the third empty driving distance between the destination coordinate position and the unloading place coordinate position in the transportation demand list.

[0236] If the coordinate position is expressed in longitude and latitude, determine the third empty driving distance between the longitude and latitude of the destination and the longitude and latitude of the unloading place in the transportation demand sheet.

[0237] Exemplarily, the unit of the third idle driving distance may be km.

[0238] It should be noted that if there are multiple destination points in the freight search information, the distances between the longitude and latitude of each destination and the longitude and latitude of the unloading place in the transportation demand list are traversed and calculated, and the shortest distance is taken as the third empty driving distance.

[0239] Step 123: Obtain the transportation distance between the loading place and the unloading place in the transportation demand sheet.

[0240] For example, the unit of the transport distance may be km.

[0241] Step 124: Obtain the upper limit of the generalized distance of the destination.

[0242] Furthermore, the upper limit of the destination generalization distance can be obtained by the following formula (6).

[0243] Destination generalization distance upper limit = transportation distance * 20% + 20km Formula (6)

[0244] Step 125: Determine a destination generalization degree value according to the third empty driving distance and the upper limit of the destination generalization distance.

[0245] Furthermore, if the dimension of the destination point in the freight search information is a province, and the unloading place in the transport demand sheet belongs to the province, then the generalization degree x2 = 1.0. In other cases, the destination generalization degree value can be obtained by the following formula (7).

[0246] x2 = D / destination generalization distance upper limit formula (7)

[0247] Among them, x2 is the destination generalization degree value, and D is the third empty driving distance.

[0248] Step 126: Determine the destination generalization level according to the destination generalization degree value.

[0249] If the destination generalization degree value is less than or equal to 1, it is determined that the destination generalization level is the third level.

[0250] If the destination generalization degree value is greater than 1 and less than or equal to 2, it is determined that the destination generalization level is the second level.

[0251] If the destination generalization degree value is greater than or equal to 2, it is determined that the destination generalization level is the first level.

[0252] In another possible implementation, the destination information includes a destination search range. The destination search range refers to a range within a certain range around the destination as the destination. For example, the destination search range may be within 20 km, 50 km, 100 km or 200 km of the destination. Step 12 may include the following steps 12a to 12c.

[0253] Step 12a: Obtain a fourth empty driving distance between the coordinate position of the destination and the coordinate position of the unloading place in the transportation demand list.

[0254] If the coordinate position is expressed in longitude and latitude, the fourth empty driving distance between the longitude and latitude of the destination and the longitude and latitude of the unloading place in the transportation demand sheet is obtained.

[0255] Step 12a is similar to step 11a. The longitude and latitude of the destination refers to the longitude and latitude of the destination location input by the user.

[0256] Step 12b: Determine a generalization degree value of the destination search neighborhood according to the fourth empty driving distance and the destination search neighborhood range.

[0257] Furthermore, the generalization degree value of the initial destination search nearby can be obtained by the following formula (8).

[0258] x4=D / driver search generalization distance numerical formula (8)

[0259] Among them, x4 is the generalization degree value of the initial destination search vicinity, and D is the fourth empty driving distance.

[0260] If the destination search vicinity range is 20 km, and the fourth empty driving distance D<=50 km, then the destination search vicinity generalization degree value is min{2.0, x4}.

[0261] If the destination search vicinity range is 200km, and the fourth empty driving distance D>250km, the destination search vicinity generalization degree value is 3.0.

[0262] In all cases other than the above, the generalization value of the destination search nearby is x4.

[0263] Step 12c: Determine the generalization level of the destination search according to the generalization degree value of the destination search.

[0264] If the destination search nearby generalization degree value is less than or equal to 1, it is determined that the destination search nearby generalization level is the third level.

[0265] If the destination search nearby generalization degree value is greater than 1 and less than or equal to 2, it is determined that the destination search nearby generalization level is the second level.

[0266] If the destination search nearby generalization degree value is greater than or equal to 2, it is determined that the destination search nearby generalization level is the first level.

[0267] In some embodiments, the vehicle information may include one or more searched vehicle lengths, and the vehicle length generalization level may be determined based on the searched vehicle lengths. In addition, the transport demand list may also include one or more required vehicle lengths. The method of this embodiment may also include the following step 13.

[0268] Step 13: Determine the generalization level of the vehicle length according to the searched vehicle length and the required vehicle length in the transport demand sheet.

[0269] In a possible implementation, step 13 may be implemented through the following steps 131 to 135.

[0270] Step 131: determine the maximum value of the searched vehicle lengths in the freight search information as the maximum searched vehicle length; determine the minimum value of the searched vehicle lengths in the freight search information as the minimum searched vehicle length.

[0271] Step 132: determine the maximum value of the required vehicle lengths in the transport demand list as the maximum required vehicle length; determine the minimum value of the required vehicle lengths in the transport demand list as the minimum required vehicle length.

[0272] Step 133: Determine the generalization degree value of the initial vehicle length according to the maximum search vehicle length, the minimum search vehicle length, the maximum required vehicle length and the minimum required vehicle length.

[0273] Furthermore, the generalization degree value of the initial vehicle length can be obtained by the following formula (9).

[0274] z = max{z1,z2} Formula (9)

[0275] z1 = minimum vehicle length required / maximum vehicle length searched;

[0276] z2 = search minimum vehicle length / required maximum vehicle length;

[0277] Among them, z is the generalization degree value of the initial vehicle length.

[0278] Step 134 , obtaining a vehicle length generalization degree value according to the first user's historical freight search request, historically viewed transportation demand orders, historically completed transportation demand orders, and the initial vehicle length generalization degree value.

[0279] The largest number of N vehicle lengths among the vehicle lengths in the first user's historical freight search requests, the vehicle lengths in the historically viewed transport demand orders, and the vehicle lengths in the historically completed transport demand orders are obtained. N is an integer greater than 0, for example, N may be 3.

[0280] Furthermore, the generalization degree value of the initial vehicle length can be adjusted in the following manner to obtain the generalization degree value of the vehicle length:

[0281] If the freight search information searched by the first user includes searching for vehicle length, the initial vehicle length generalization degree value z>1.0, and the required vehicle length in the transport demand order does not belong to the above N types of vehicle lengths, then the vehicle length generalization degree value is max{2.5, z}.

[0282] If the freight search information searched by the first user includes the search for vehicle length, and the initial vehicle length generalization degree value z>1.0, and the required vehicle length in the transport demand form belongs to the above N types of vehicle lengths, then the vehicle length generalization degree value is z.

[0283] If the freight search information searched by the first user includes searching for vehicle length, and the initial vehicle length generalization degree value z<=1.0, then the vehicle length generalization degree value is z.

[0284] If the freight search information searched by the first user does not include the search vehicle length, and the required vehicle length in the transport demand list belongs to the above N types of vehicle lengths, then the generalization degree value of the vehicle length is 0.0.

[0285] The freight search information searched by the first user does not include the search vehicle length, and the required vehicle length in the transport demand form belongs to the above N types of vehicle lengths, then the generalization degree value of the vehicle length is 2.5.

[0286] Step 135: Determine the generalization level of the vehicle length according to the generalization degree value of the vehicle length.

[0287] If the vehicle length generalization degree value is less than or equal to 1, it is determined that the vehicle length generalization level is the third level.

[0288] If the vehicle length generalization degree value is greater than 1 and less than or equal to 2, it is determined that the vehicle length generalization level is the second level.

[0289] If the vehicle length generalization degree value is greater than or equal to 2, it is determined that the vehicle length generalization level is the first level.

[0290] In another possible implementation, the vehicle length generalization degree value may be obtained through the following steps 13a to 13g.

[0291] Step 13a: The server obtains the M types of vehicle lengths with the largest number from among the vehicle lengths in the first user's historical freight search requests, the vehicle lengths in the historically viewed transport demand orders, and the vehicle lengths in the historically completed order transport demand orders.

[0292] Here, M is an integer greater than 0, for example, M may be 5.

[0293] Step 13b: determine whether the required vehicle length in the transport demand sheet meets the searched vehicle length in the freight search information, or whether the required vehicle length in the transport demand sheet meets one of the M types of vehicle lengths.

[0294] If yes, proceed to step 13c; if no, proceed to step 13d.

[0295] Step 13c: Determine that the vehicle length generalization value is 0.

[0296] Step 13d: determine whether the required vehicle length in the transport demand sheet does not match the searched vehicle length in the freight search information, and whether the required vehicle length in the transport demand sheet does not match any of the M types of vehicle lengths.

[0297] If yes, proceed to step 13e; if no, proceed to step 13f.

[0298] Step 13e, determine that the generalization degree value of the vehicle length is 2.

[0299] It should be noted that if the first user does not search for the vehicle length, that is, the vehicle length is not searched in the freight search information, it is determined whether the required vehicle length in the transport demand sheet meets any of the M types of vehicle lengths.

[0300] Step 13f, determine that the generalization degree value of the vehicle length is 0.

[0301] Step 13g: Determine the generalization level of the vehicle length according to the generalization degree value of the vehicle length.

[0302] If the vehicle length generalization degree value is equal to 0, it is determined that the vehicle length generalization level is the third level.

[0303] If the vehicle length generalization degree value is equal to 2, it is determined that the vehicle length generalization level is the first level.

[0304] In some embodiments, the vehicle information may include one or more searched vehicle models, and the vehicle model generalization degree value may be determined according to the searched vehicle models. In addition, the transportation demand list may also include one or more required vehicle models. The method of this embodiment may also include the following step 14.

[0305] Step 14: Determine the vehicle type generalization value based on the searched vehicle type and the required vehicle type in the transport demand sheet.

[0306] In a possible implementation, step 14 can be implemented through the following steps 141 to 149.

[0307] Step 141: Obtain the M largest number of vehicle models from among the vehicle models in the first user's historical freight search requests, the vehicle models in the historically viewed transportation demand orders, and the vehicle models in the transportation demand orders of historically completed orders.

[0308] Wherein, M is an integer greater than 0.

[0309] Step 142: Determine whether the searched vehicle model is the same as the required vehicle model in the transportation demand sheet.

[0310] If yes, continue to execute step 143; if no, continue to execute step 146.

[0311] Step 143: Determine whether the required vehicle type in the transportation demand list belongs to the above-mentioned M types of vehicle types.

[0312] If yes, continue to execute step 144; if no, continue to execute step 145.

[0313] Step 144: Determine that the vehicle type generalization degree value is a first value. Then proceed to step 149.

[0314] Exemplarily, the first value may be 0.

[0315] Step 145: Determine that the vehicle type generalization degree value is a second value. Then proceed to step 149.

[0316] The second value is greater than the first value.

[0317] Exemplarily, the first value may be 0.1.

[0318] Step 146: Determine whether the required vehicle type in the transportation demand form belongs to the above-mentioned M types of vehicle types.

[0319] If yes, continue to step 147; if no, continue to step 148.

[0320] Step 147: Determine that the vehicle type generalization degree value is a third value. Then proceed to step 149.

[0321] The third value is greater than the second value.

[0322] Exemplarily, the third value may be 0.5.

[0323] Step 148: Determine that the vehicle type generalization degree value is a fourth value. Then proceed to step 149.

[0324] The fourth value is greater than the third value.

[0325] Exemplarily, the fourth value may be 2.

[0326] Step 149: Determine the vehicle type generalization level according to the vehicle type generalization degree value.

[0327] If the vehicle type generalization degree value is less than or equal to 1, it is determined that the vehicle type generalization level is the third level.

[0328] If the vehicle type generalization degree value is greater than 1 and less than or equal to 2, it is determined that the vehicle type generalization level is the second level.

[0329] If the vehicle type generalization degree value is greater than or equal to 2, it is determined that the vehicle type generalization level is the first level.

[0330] In another possible implementation, the server may determine the vehicle model generalization degree value through the following steps 14a to 14f.

[0331] Step 14a: The server obtains the M largest number of vehicle models from among the vehicle models in the first user's historical freight search request, the vehicle models in the historically viewed transportation demand orders, and the vehicle models in the transportation demand orders of historically completed orders.

[0332] Here, M is an integer greater than 0, for example, M may be 5.

[0333] Step 14b: determine whether the required vehicle model in the transport demand form matches the search vehicle model in the freight search information, or whether the required vehicle model in the transport demand form matches one of the M vehicle models.

[0334] If yes, proceed to step 14c; if no, proceed to step 14d.

[0335] Step 14c: determine that the vehicle type generalization degree value is 0.

[0336] Step 14d: determine whether the required vehicle model in the transport demand sheet does not match the search vehicle model in the freight search information, and whether the required vehicle model in the transport demand sheet does not match one of the M vehicle models.

[0337] If yes, proceed to step 14e; if no, proceed to step 14f.

[0338] Step 14e: Determine that the vehicle model generalization degree value is 2.

[0339] It should be noted that if the first user does not search for a vehicle model, that is, there is no search vehicle model in the freight search information, it is determined whether the required vehicle model in the transportation demand form meets any one of the M vehicle models.

[0340] Step 14f, determine that the vehicle model generalization degree value is 0.

[0341] Step 14g: Determine the vehicle type generalization level according to the vehicle type generalization degree value.

[0342] If the vehicle type generalization degree value is equal to 0, it is determined that the vehicle type generalization level is the third level.

[0343] If the vehicle type generalization degree value is equal to 2, it is determined that the vehicle type generalization level is the first level.

[0344] In some embodiments, if the freight search information includes a search for a load-bearing range, the load-bearing generalization level can be determined based on the search for the load-bearing range. In addition, the transport demand sheet can also include one or more required load-bearing ranges. The method of this embodiment can also include the following step 15.

[0345] Step 15: Determine the load-bearing generalization level based on the search load-bearing range and the required load-bearing range in the transportation demand sheet.

[0346] Further, step 15 can be implemented through the following steps 151 to 154.

[0347] Step 151: Obtain the maximum value in the search load-bearing range as the search maximum load-bearing.

[0348] Step 152: Obtain the minimum value in the required load-bearing range in the transport demand sheet as the required minimum load-bearing.

[0349] Step 153: Obtain the ratio of the required minimum load-bearing capacity to the searched maximum load-bearing capacity as the load-bearing generalization degree value.

[0350] Step 154: Determine the load-bearing generalization level according to the load-bearing generalization degree value.

[0351] If the load-bearing generalization degree value is less than or equal to 1, it is determined that the load-bearing generalization level is the third level.

[0352] If the load-bearing generalization degree value is greater than 1 and less than or equal to 2, it is determined that the load-bearing generalization level is the second level.

[0353] If the load-bearing generalization degree value is greater than or equal to 2, it is determined that the load-bearing generalization level is the first level.

[0354] In this embodiment, by characterizing the generalization level of the transport demand orders, if there are too many transport demand orders in the screening results, the transport demand orders with a higher degree of generalization in the screening results are deleted. The obtained screening results are more in line with the user's search needs and usage habits, thereby improving the user experience.

[0355] Further, in step 205, the server determines the transport demand orders that meet the conditions of the multiple recall methods from all current transport demand orders based on the recall quantities corresponding to the multiple recall methods, and can sort the recalled transport demand orders to obtain screening results.

[0356] Exemplarily, the recalled transport demand orders may be sorted based on information about the degree to which each recalled transport demand order meets the expectations of the first user and information about the degree of generalization of each recalled transport demand order to obtain a screening result.

[0357] The information on the degree to which the recalled transport demand form meets the expectations of the first user refers to the degree to which the first user is expected to be willing to click on and place an order when the recalled transport demand form is displayed to the first user for viewing.

[0358] The generalization degree information of the recalled transport demand form is used to indicate the degree to which the recalled transport demand form does not meet the search condition input by the first user.

[0359] Among them, all current transportation demand orders refer to the transportation demands proposed by the current cargo owner and have not been accepted by any user.

[0360] Since each time a user searches, the user may only browse a portion of the previously displayed transport demand orders from the front to the back for the screening results displayed on the terminal device, it is necessary to sort the recalled transport demand orders and put the transport demand orders that better meet the user's expectations at the front. The server sorts the recalled transport demand orders based on the degree information of each recalled transport demand order meeting the first user's expectations and the generalization degree information of each recalled transport demand order, so as to obtain a screening result that better meets the user's expectations.

[0361] In this embodiment, the terminal device receives freight search information input by the user in the freight search interface, and after receiving the search operation in the freight search interface, sends a freight search request carrying the freight search information to the server. In response to the freight search request, the server performs a recall operation on all current transport demand orders according to the freight search information and the information of the first user corresponding to the terminal device, and obtains the recalled transport demand orders; based on the degree information of each recalled transport demand order meeting the expectations of the first user, and the generalization degree information of each recalled transport demand order, the recalled transport demand orders are sorted to obtain the screening results. The server sends the screening results to the terminal device, and the terminal device displays the screening results. If the recalled transport demand orders are more in line with the driver's expectations, the driver will be more inclined to click on and complete the order. The different degrees of generalization of the recalled transport demand orders will also affect the driver's click and completion of the order. Therefore, according to the degree to which different recalled transport demand orders meet the driver's expectations and the generalization degree information of each recalled transport demand order, the freight screening results displayed to the driver are personalized. The driver can quickly find satisfactory transportation needs, which improves the driver's order acceptance efficiency, thereby improving the efficiency of shippers and drivers in completing orders and improving the user experience.

[0362] The method provided by the present disclosure is described below with specific examples.

[0363] See also Figure 3 , Figure 3 FIG. 1 is a flow chart of a method for displaying freight screening results provided by an embodiment of the present disclosure. Figure 3 As shown, the method of this embodiment includes the following steps:

[0364] Step a: The driver triggers a search operation on the freight search interface of the terminal device, and the terminal device sends a freight search request to the server.

[0365] Among them, the driver corresponds to the first user in the above embodiment.

[0366] Step b: The server determines whether the driver's preference score for precise cargo is greater than or equal to 0.7.

[0367] The precise cargo corresponds to the precise transportation demand form in the above embodiment, and the precise cargo preference score corresponds to the preference score of the first user for the precise transportation demand form in the above embodiment.

[0368] In this example, the first threshold is assumed to be 0.7.

[0369] If yes, proceed to step c; if no, proceed to step d.

[0370] Step c: The server increases the precise path recall amount by M quotas. Then proceed to step f.

[0371] The precise path recall quantity corresponds to the recall quantity of the precise recall method in the above embodiment. M corresponds to the first quantity in the above embodiment, and M can be adapted according to different recall paths.

[0372] Step d: The server determines whether the driver's preference score for accurate cargo is less than 0.2.

[0373] In this example, the second threshold is assumed to be 0.2.

[0374] If yes, proceed to step e; if no, proceed to step f.

[0375] Step e: The server increases the generalized path recall amount by N quotas. Continue to step f.

[0376] The generalized recall quantity corresponds to the recall quantity of the generalized recall method in the above embodiment. N corresponds to the second quantity in the above embodiment, and N can be adapted according to different recall circuits.

[0377] Step f: The server determines whether the driver's preference score for each recall route meets a specified threshold.

[0378] The driver's preference scores for each recall route correspond to the preference scores for the recall method of the first user in the above embodiment, and the threshold corresponds to the above first quantile and second quantile.

[0379] If yes, proceed to step g.

[0380] Step g: The server adjusts the recall quota of each recall circuit according to the threshold adaptation.

[0381] The recall path corresponds to the recall method in the above embodiment. The recall quota refers to the amount of adjustment of the recall quantity.

[0382] Step g corresponds to step 204a to step 204f in the above steps.

[0383] Step h: The server recalls the source of goods and removes duplicate sources of goods.

[0384] According to step g, the recall quantity of each subsequent recall route is adjusted to recall the source of goods, wherein the source of goods corresponds to the current transportation demand list in the above embodiment.

[0385] Since the sources of goods recalled through different recall routes may be the same, the recalled sources are deduplicated.

[0386] Step i: The server determines whether the supply quantity exceeds the total recall quantity or meets the truncation conditions.

[0387] If yes, continue to step j; if no, the recall phase ends.

[0388] Step j: The server determines whether the driver's preference score for accurate cargo is greater than or equal to 0.8, whether the online cargo volume is greater than or equal to G, and whether the cargo source is heavily generalized.

[0389] If yes, continue to step k; if no, the recall phase ends.

[0390] Step k: After the server suppresses the heavily generalized supply to the end, it cuts off the supply.

[0391] Among them, the heavily generalized source of goods corresponds to the first-level transportation demand order in the above embodiment.

[0392] The server adjusts the heavily generalized sources to the end of the recalled sources, and cuts off the sources from the end to the front. When deleting too many sources, the heavily generalized sources are deleted first to obtain the screening results, thus ending the recall phase.

[0393] In this embodiment, the server dynamically adjusts the driver's recall quotas for each route based on the driver's acceptance of precise goods and generalized goods, as well as the calculated generalization of the source of goods. According to time factors, supply and demand conditions, the driver's acceptance of generalized goods, and the online effects of each route recall, the server also considers the total recall quantity limit and the recall route performance constraint when adjusting the recall quota, and realizes personalized dynamic adjustment of multiple recall quotas, in order to find the best solution to improve the recall efficiency, which has an important impact on the subsequent rough sorting and fine sorting modules. Drivers can quickly find satisfactory cargo orders, which improves the driver's order acceptance efficiency, thereby improving the efficiency of cargo owners and drivers in reaching orders and improving user experience.

[0394] Based on the method for displaying freight screening results described in any of the above embodiments, the embodiment of the present disclosure further provides a computer-readable storage medium, for example, the non-temporary computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, and an optical data storage device, etc. The storage medium stores computer instructions for executing the method for displaying freight screening results described in any of the above embodiments, which will not be described in detail herein.

[0395] A person skilled in the art will understand that all or part of the steps to implement the above embodiments may be accomplished by hardware, or by a program to instruct the relevant hardware, and the program may be stored in a computer-readable storage medium, and the above-mentioned storage medium may be a read-only memory, a disk or an optical disk, etc.

[0396] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the disclosure disclosed herein. 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 that are not disclosed in the present disclosure. The description and examples are intended to be exemplary only, and the true scope and spirit of the present disclosure are indicated by the following claims.

Claims

1. A method for displaying freight screening results, characterized in that: The method comprises: receiving a freight search request sent by a terminal device, wherein the freight search request includes freight search information; In response to the freight search request, determining a plurality of recall methods according to the freight search information and information of a first user corresponding to the terminal device; Determining the recall quantities corresponding to the multiple recall methods respectively according to the first user's preference information for recall accuracy and / or the first user's preference information for historical search results obtained by the multiple recall methods respectively; Based on the recall quantities respectively corresponding to the multiple recall methods, determining the transport demand orders that meet the conditions of the multiple recall methods from all current transport demand orders to obtain a screening result; The screening result is sent to the terminal device so that the terminal device displays the screening result.

2. The method according to claim 1, characterized in that: The method further comprises: Determining the first user's preference score for the precise transportation demand orders according to the historical number of precise transportation demand orders viewed by the first user and the historical number of precise transportation demand orders for which the first user has placed orders; The first user's preference score for the accurate transportation demand order is used as the first user's preference degree information for recall accuracy.

3. The method according to claim 2, characterized in that The determining the preference score of the first user for the precise transportation demand orders according to the historical number of precise transportation demand orders viewed by the first user and the historical number of precise transportation demand orders for which the first user has placed orders comprises: Obtaining the historical number of precise transportation demand orders viewed by the first user, the total historical number of transportation demand orders viewed by the first user, the historical number of precise transportation demand orders for which the first user has placed an order, and the total historical number of transportation demand orders for which the first user has placed an order within a first preset time period; The first user's preference score for precise transportation demand orders is obtained by taking the weighted sum of the historical number of precise transportation demand orders viewed by the first user and the historical number of precise transportation demand orders for which the first user has placed orders, and dividing the weighted sum by the total historical number of transportation demand orders viewed by the first user and the total historical number of transportation demand orders for which the first user has placed orders.

4. The method according to claim 2, characterized in that: Determining the recall quantities corresponding to the multiple recall methods respectively according to the first user's preference information for recall accuracy and / or the first user's preference information for historical search results obtained by the multiple recall methods respectively includes: If the preference score of the first user for the precise transport demand order is greater than or equal to a first threshold, the initial recall quantity is increased by a first quantity to obtain a recall quantity corresponding to a precise recall method among the multiple recall methods; and the recall quantity corresponding to an inaccurate recall method among the multiple recall methods is determined as the initial recall quantity; If the preference score of the first user for the precise transport demand order is less than or equal to a second threshold, the initial recall quantity is increased by a second quantity to obtain a recall quantity corresponding to the non-precise recall method among the multiple recall methods; and the recall quantity corresponding to the precise recall method among the multiple recall methods is determined as the initial recall quantity; If the first user's preference score for the accurate transportation demand order is less than the first threshold and greater than the second threshold, it is determined that the recall quantities corresponding to the multiple recall methods are respectively the initial recall quantities.

5. The method according to claim 1, characterized in that: The method further comprises: For each of the multiple recall methods, the following processing is performed respectively: according to the processing behavior information of the first user on the historical search results obtained by the recall method within the second preset time period, the preference score of the first user for the recall method is determined; The first user's preference score for the recall method is used as the first user's preference level information for the historical search results obtained by the recall method.

6. The method according to claim 5, characterized in that The processing behavior information of the first user on the historical search results obtained by the recall method includes at least one of the following: the number of non-exposures and / or the number of exposures, the proportion of non-exposures and / or the proportion of exposures, the number of clicks, the exposure click rate, the number of transactions and the exposure transaction rate; The number of non-exposures is the number of historical search results obtained by the recall method that are not displayed to the first user; The number of exposures is the number of historical search results obtained by the recall method displayed to the first user; The non-exposure times ratio is a ratio of the non-exposure times to the total number of non-exposure times and the exposure times; The exposure times ratio is the ratio of the exposure times to the total number of non-exposure times and the exposure times; The number of clicks is the number of historical search results obtained by the first user viewing the recall method; The exposure click rate is the ratio of the number of clicks to the number of exposures; The number of transactions is the number of completed orders in the historical search results obtained by the first user in the recall method; The exposure-to-conclusion ratio is the ratio of the number of transactions to the number of exposures.

7. The method according to claim 5, characterized in that Determining the recall quantities corresponding to the multiple recall methods respectively according to the first user's preference information for recall accuracy and / or the first user's preference information for historical search results obtained by the multiple recall methods respectively includes: For each of the multiple recall methods, obtaining a first quantile and a second quantile of preference scores of all users for the recall method, respectively; the first quantile is greater than the second quantile; If the first user's preference score for the recall method is greater than or equal to the first quantile, increasing the initial recall quantity by a third quantity to obtain the recall quantity corresponding to the recall method; If the first user's preference score for the recall method is less than or equal to the second quantile, reducing the initial recall quantity by a fourth quantity to obtain the recall quantity corresponding to the recall method; If the first user's preference score for the recall method is less than the first quantile and greater than the second quantile, the recall quantity corresponding to the recall method is determined to be the initial recall quantity.

8. The method according to any one of claims 1 to 7, characterized in that: The method of determining, based on the recall quantities respectively corresponding to the multiple recall methods, a transport demand order that meets the conditions of the multiple recall methods from all current transport demand orders, and obtaining a screening result includes: Based on the recall quantities respectively corresponding to the multiple recall methods, determining a transport demand order that meets the conditions of the multiple recall methods from all current transport demand orders; If the number of transport demand orders corresponding to the multiple recall methods reaches a cutoff condition, the preference score of the first user for accurate transport demand orders is greater than a third threshold, the number of all current transport demand orders is greater than or equal to a fourth number, and there are transport demand orders with a first generalization level among the transport demand orders corresponding to the multiple recall methods, then some or all of the transport demand orders with the first generalization level are deleted to obtain the screening result; If the number of the transport demand orders corresponding to the multiple recall methods does not reach the cut-off condition, the transport demand orders respectively corresponding to the multiple recall methods are determined as the screening results.

9. A method for displaying freight screening results, characterized in that: The method comprises: Receive freight search information in the freight search interface; After receiving the search operation on the freight search interface, sending a freight search request to a server, wherein the freight search request includes the freight search information; Receive the screening result sent by the server, the screening result is that the server determines multiple recall methods according to the freight search information and the information of the first user corresponding to the terminal device; determines the recall quantities corresponding to the multiple recall methods according to the first user's preference information for recall accuracy and / or the first user's preference information for the historical search results obtained by the multiple recall methods; and determines the transport demand orders that meet the conditions of the multiple recall methods from all current transport demand orders based on the recall quantities corresponding to the multiple recall methods; The filtering results are displayed.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

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