Region familiarity confirmation method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides an area familiarity degree confirmation method and device, electronic equipment and a storage medium, and the method comprises the steps: determining an effective delivery area in a target delivery area, obtaining the historical running track data of a delivery party in the target delivery area, and determining the familiarity degree of the delivery party based on the historical running track data, and determining a unit area access feature of the delivery party in the effective delivery area, and determining a familiarity degree of the delivery party to the target delivery area based on the unit area access feature.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to methods, apparatus, electronic devices and storage media for determining regional familiarity. Background Technology

[0002] With the rapid development of e-commerce, food delivery, and other industries, on-demand delivery services have experienced explosive growth. Exploring efficient capacity scheduling models is becoming increasingly important for improving the service quality of on-demand delivery services. In the field of data mining, accurately understanding the delivery capabilities and location-based relationships of delivery providers has become a crucial means to improve scheduling efficiency. Furthermore, understanding how delivery providers can effectively operate in different geographical areas is a key focus of this research. Summary of the Invention

[0003] The main objective of this application is to provide a method, apparatus, electronic device, and storage medium for confirming area familiarity, aiming to verify the delivery party's familiarity with the delivery area. The technical solution is as follows:

[0004] In a first aspect, embodiments of this application provide a method for confirming regional familiarity, including:

[0005] Determine the effective delivery area within the target delivery area;

[0006] Obtain historical running trajectory data of the delivery person within the target delivery area;

[0007] Based on the historical running trajectory data, the delivery party's access characteristics per unit area within the effective delivery area are determined;

[0008] The familiarity of the delivery party with the target delivery area is determined based on the unit area access characteristics.

[0009] Secondly, embodiments of this application provide a device for confirming regional familiarity, comprising:

[0010] The area confirmation module is used to determine the valid delivery area within the target delivery area;

[0011] The trajectory acquisition module is used to acquire historical running trajectory data of the delivery person within the target delivery area;

[0012] The feature confirmation module is used to determine the delivery party's access characteristics per unit area within the effective delivery area based on the historical running trajectory data.

[0013] The familiarity verification module is used to determine the delivery party's familiarity with the target delivery area based on the unit area access characteristics.

[0014] Thirdly, embodiments of this application provide an electronic device, the electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the method described above.

[0015] Fourthly, embodiments of this application provide a storage medium storing a computer program, which, when executed by a processor, implements the steps of the method described above.

[0016] In this embodiment, by determining an effective delivery area within the target delivery area, historical movement trajectory data of the delivery person within that area is obtained. Based on this historical movement trajectory data, the delivery person's unit-area access characteristics within the effective delivery area are determined, and the delivery person's familiarity with the target delivery area is determined based on these unit-area access characteristics. Standardizing the delivery person's historical movement trajectory data using the effective delivery area within the target delivery area resolves the erroneous relationship that larger areas equate to higher familiarity, thus enabling a more accurate assessment of the delivery person's familiarity with the delivery area based on unit-area access characteristics. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram illustrating the application of a method for confirming regional familiarity provided in an embodiment of this application;

[0019] Figure 2 This is a flowchart illustrating a method for confirming regional familiarity according to an embodiment of this application;

[0020] Figure 3 This is a flowchart illustrating a method for confirming regional familiarity according to an embodiment of this application;

[0021] Figure 4 This is an example schematic diagram of a method for confirming regional familiarity provided in an embodiment of this application;

[0022] Figure 5 This is an example schematic diagram of a method for confirming regional familiarity provided in an embodiment of this application;

[0023] Figure 6 This is an example schematic diagram of a method for confirming regional familiarity provided in an embodiment of this application;

[0024] Figure 7 This is an example schematic diagram of a method for confirming regional familiarity provided in an embodiment of this application;

[0025] Figure 8 This is a schematic diagram of the structure of a region familiarity confirmation device provided in an embodiment of this application;

[0026] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0027] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this specification.

[0028] In the description of this specification, it should be understood that the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. In the description of this specification, it should be noted that, unless otherwise expressly specified and limited, "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or devices. Those skilled in the art can understand the specific meaning of the above terms in this specification based on the specific circumstances. Furthermore, in the description of this specification, unless otherwise stated, "multiple" means two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship.

[0029] The area familiarity confirmation device in this application embodiment can be a terminal device such as a mobile phone, computer, tablet computer or vehicle-mounted device, or it can be a module in the terminal device used to implement the area familiarity confirmation method. The area familiarity confirmation device can determine the effective delivery area in the target delivery area, obtain the historical running trajectory data of the delivery party in the target delivery area, and then determine the unit area access characteristics of the delivery party in the effective delivery area based on the historical running trajectory data, and determine the delivery party's familiarity with the target delivery area based on the unit area access characteristics.

[0030] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, stored data, displayed data, etc.), and signals involved in the embodiments of this specification are all authorized by the user or fully authorized by all parties, and the collection, use, and processing of related data must comply with the relevant laws, regulations, and standards of the relevant countries and regions. For example, historical running trajectory data and historical order data involved in this specification were obtained with full authorization.

[0031] Please see also Figure 1 This application provides an schematic diagram illustrating the application of a method for confirming familiarity with a given area. The familiarity confirmation device can confirm familiarity with a given area by measuring the area within the target delivery area. Figure 1 The effective delivery area is determined within the black line box in the target delivery area. The historical running trajectory data of the delivery party within the target delivery area is obtained. Then, based on the historical running trajectory data of the delivery party, the unit area access characteristics of the delivery party within the effective delivery area are determined. Based on the unit area access characteristics, the familiarity of the delivery party with the target delivery area is determined.

[0032] The method for confirming regional familiarity provided in this specification will be described in detail below with reference to specific embodiments.

[0033] Please see Figure 2 This is a flowchart illustrating a method for confirming regional familiarity in an embodiment of this application. Figure 2 As shown, the method described in this application embodiment may include the following steps S101-S104.

[0034] S101, Determine the effective delivery area within the target delivery area;

[0035] In one embodiment, the area familiarity confirmation method provided in this application can be applied to retail logistics scenarios, instant delivery scenarios, etc. It is understood that this area familiarity confirmation method can also be applied to taxi / ride-hailing dispatch scenarios, where the delivery party can be a driver and the delivery area can be an operating area, thus using this method to confirm the driver's familiarity with a certain operating area.

[0036] The target delivery area can include, but is not limited to, cities, districts, communities, business districts, etc. Specifically, the map can be divided according to actual needs, and the target delivery area can be selected. It is understandable that, generally speaking, as the target delivery area increases, the number of orders completed by delivery personnel within that area will also increase. Therefore, when determining familiarity based on the number of completed orders, the result will be that delivery personnel are more familiar with larger delivery areas, which is clearly biased. Therefore, in this embodiment, an effective delivery area is identified within the target delivery area, and the historical movement trajectory data of delivery personnel is standardized based on the area of ​​the effective delivery area. The effective delivery area is the area within the target delivery area where orders have recently been generated.

[0037] S102, Obtain historical running trajectory data of the delivery person within the target delivery area;

[0038] In one embodiment, the delivery person's running trajectory data consists of individual trajectory points. During the delivery person's work, information is reported every preset time interval (e.g., 5 seconds). This information includes the delivery person's current latitude and longitude location information, as well as the delivery person's status information. For delivery persons requiring familiarity verification, all of the delivery person's historical running trajectory data can be obtained, and then the delivery person's historical running trajectory data generated within the target delivery area can be verified from all the historical running trajectory data.

[0039] Optionally, since the latitude and longitude location information collected by GPS is subject to drift, the trajectory data needs to be cleaned to remove outliers. Then, for each trajectory coordinate point of the delivery person, the coordinate point is assigned to its corresponding spatial unit, for example, mapped to a pre-divided hexagonal grid, thus obtaining the mapping relationship between historical running trajectory data and the grid.

[0040] S103, Based on the historical running trajectory data, determine the unit area access characteristics of the delivery party within the effective delivery area;

[0041] In one embodiment, the delivery party's access characteristics per unit area within the effective delivery area are determined based on the confirmed historical movement trajectory data. It is understood that the delivery party's entry into the effective delivery area and its delivery trajectory within that area can be confirmed based on the historical movement trajectory data. Therefore, the number of times the delivery party enters and exits the effective delivery area and its delivery trajectory within the area can be used as the delivery party's access characteristics to the effective delivery area. Dividing these access characteristics by the area of ​​the effective delivery area yields the access characteristics per unit area.

[0042] S104, determine the delivery party's familiarity with the target delivery area based on the unit area access characteristics.

[0043] In one embodiment, the familiarity of the delivery party with the target delivery area is determined based on the delivery party's access characteristics per unit area. These unit area access characteristics characterize the delivery party's access behavior within the effective delivery area; for example, they can be the number of visits per unit area or the duration of visits per unit area. A higher number of visits per unit area indicates greater familiarity, and similarly, a longer visit duration per unit area also indicates greater familiarity.

[0044] Understandably, once the delivery provider's familiarity with the target delivery area is confirmed, their regional capabilities are characterized. Under high-pressure logistics scenarios, delivery providers can conduct deliveries within familiar areas, improving delivery efficiency; during off-peak periods, delivery providers can explore unfamiliar areas to accumulate experience and improve their familiarity with other areas.

[0045] In this embodiment, by determining an effective delivery area within the target delivery area, historical movement trajectory data of the delivery person within that area is obtained. Based on this historical movement trajectory data, the delivery person's unit-area access characteristics within the effective delivery area are determined, and the delivery person's familiarity with the target delivery area is determined based on these unit-area access characteristics. Standardizing the delivery person's historical movement trajectory data using the effective delivery area within the target delivery area resolves the erroneous relationship that larger areas equate to higher familiarity, thus enabling a more accurate assessment of the delivery person's familiarity with the delivery area based on unit-area access characteristics.

[0046] Please see Figure 3 This is a flowchart illustrating a method for confirming regional familiarity according to an embodiment of this application. Figure 3 As shown, the method described in this application embodiment may include the following steps S201-S211.

[0047] S201, Obtain historical order data for the target delivery area;

[0048] In one embodiment, when confirming a valid delivery area, historical order data for the target delivery area can be obtained first. Historical order data refers to delivery orders placed by historical users. This data may include entity object data corresponding to the historical orders, delivery party historical behavior data, and user data. Entity object data refers to data related to the entity to be delivered, user data refers to data related to the user who placed the order, and delivery party historical behavior data may include delivery party data for historical orders and delivery party movement trajectory data. Optionally, the historical order data may be recent historical order data, which better reflects the order characteristics of the target delivery area.

[0049] S202, Based on the historical order data, confirm the order production area in the target delivery area, and confirm the order production area as a valid delivery area;

[0050] Specifically, historical order data can identify areas within the target delivery region that have generated orders. These order-generating areas can be regions where users place orders or where merchants accept orders / provide physical goods. Identifying these order-generating areas as valid delivery regions allows for a more accurate assessment of the delivery provider's familiarity with those areas. Understandably, order-generating areas are the primary focus within the target delivery region. Other areas within the target delivery region typically lack user orders, merchants, and cargo stations; therefore, delivery providers usually do not visit these areas, nor is it necessary to confirm their familiarity with them.

[0051] Optionally, in one embodiment, the method for confirming regional familiarity provided in this application further includes the following steps S2021-S2023:

[0052] S2021, Obtain the order pickup location and order delivery location of the historical order data;

[0053] Specifically, the order pick-up and delivery locations are confirmed in the historical order data corresponding to the target delivery area. The order start location can be a store, a delivery point, or other various starting locations, while the order delivery location can be a user's delivery address, a locker, or other various ending locations.

[0054] S2022, A geocoding system is used to map the order pickup location and the order delivery location to obtain a first mapping area corresponding to the order pickup location and a second mapping area corresponding to the order delivery location;

[0055] In one embodiment, to facilitate the determination of the order production area, the order pick-up location can be mapped to a corresponding first mapping area, and the order delivery location can be mapped to a corresponding second mapping area. That is, the first mapping area is a region to which the order pick-up location belongs, and the second mapping area is a region to which the order delivery location belongs.

[0056] For example, the GeoHash algorithm can be used for region division, with each region corresponding to a GeoHash. The GeoHash algorithm converts two-dimensional latitude and longitude into strings, with each string representing a rectangular region. This means that all points within this rectangular region share the same GeoHash string. Therefore, after determining the order pickup and delivery locations, it's possible to identify which rectangular region each location falls into, designating the corresponding rectangular region as either the first or second mapping region.

[0057] S2023, deduplicate the first mapping region and the second mapping region to obtain the order production region, and confirm the order production region as the valid delivery region.

[0058] In one embodiment, the obtained first and second mapping regions may overlap. Therefore, the first and second mapping regions are deduplicated to obtain the order production region, which is then confirmed as the valid delivery region. Please refer to [link to relevant documentation]. Figure 4 , Figure 4 This is an example illustration of a method for confirming regional familiarity provided in an embodiment of this application. After confirming the mapping area corresponding to the trajectory point, duplicate trajectory points in the same mapping area can be deduplicated. Taking GeoHash using a resolution of 9 to map the order pick-up point and the order delivery point as an example, in this case, each bit of the GeoHash code with a length of 9 can provide an accuracy of approximately 4.8 meters x 4.8 meters, that is, the size of each rectangular area is 4.8 meters x 4.8 meters. The effective delivery area occupies 11 rectangular areas, so the area of ​​the effective delivery area is 11 * 4.8 * 4.8 = 253.4 square meters.

[0059] S203, Obtain historical running trajectory data of the delivery person within the target delivery area;

[0060] For details, please refer to the description of step S104 in the above embodiment of the specification, which will not be repeated here.

[0061] S204, Based on the historical running trajectory data, confirm the entry trajectory point of the delivery person entering the effective delivery area and the exit trajectory point of the delivery person leaving the effective delivery area;

[0062] In one embodiment, the entry trajectory point for the delivery person entering the effective delivery area and the departure trajectory point for leaving the effective delivery area are determined based on the delivery person's historical running trajectory data. It is understood that once the effective delivery area is defined, the entry and departure trajectory points can be determined based on the coordinates of the historical running trajectory data, the generation time of the trajectory data, and the movement direction of the trajectory data. For example, for a historical running trajectory, the trajectory point that first appears within the effective delivery area is the entry trajectory point. Similarly, for a historical running trajectory with trajectory points within the effective delivery area, when a trajectory point first appears outside the effective delivery area, that trajectory point outside the effective delivery area can be considered the departure trajectory point. Alternatively, the nearest trajectory point within the effective delivery area to that trajectory point that first appears outside the effective delivery area can be identified as the departure trajectory point. For details, please refer to [link to relevant documentation]. Figure 5 , Figure 5 This is an example diagram illustrating a method for confirming regional familiarity provided in an embodiment of this application. The historical running trajectory includes 13 trajectory points from the starting point to the end point. Among them, trajectory point 3 is the entry trajectory point that first appears in the effective delivery area, and trajectory point 11 is the departure trajectory point that first appears outside the effective delivery area. Optionally, trajectory point 10 can also be confirmed as the departure trajectory point.

[0063] S205, determine the number of times the delivery party visits the effective delivery area based on the entry trajectory point;

[0064] In one embodiment, the number of entry points is defined as the number of times the delivery party accesses the valid delivery area.

[0065] S206, Based on the entry trajectory point and the exit trajectory point, determine the duration of the delivery party's stay within the effective delivery area;

[0066] In one embodiment, the difference between the first generation time of entering the trajectory point and the second generation time of leaving the trajectory point is determined as the duration of the delivery person's stay within the effective delivery area. The interaction characteristics (number of visits and visit duration) between the delivery person and the space are calculated using all historical movement trajectory data of the delivery person, thus solving the problem that relying on recent order completion statistics makes it impossible to accurately depict the impact of the delivery person's long-term behavior on familiarity.

[0067] S207, determine the number of visits per unit area and the visit duration per unit area based on the number of visits, the dwell time, and the area of ​​the effective delivery area;

[0068] In one embodiment, the number of visits is divided by the area of ​​the effective delivery area to obtain the number of visits per unit area, and the dwell time is divided by the area of ​​the effective delivery area to obtain the visit time per unit area. Furthermore, the interaction features are standardized using the effective delivery area of ​​the region, which resolves the erroneous relationship that larger areas have higher familiarity rates and improves the accuracy of familiarity characterization.

[0069] S208, determine the first numerical score based on the number of visits per unit area and the first logarithmic function;

[0070] In one embodiment, the unit area access characteristics include the number of visits per unit area and the duration of visits per unit area. Determining the delivery party's familiarity with the target delivery area based on these unit area access characteristics can be achieved using a first logarithmic function. Please refer to [link to relevant documentation]. Figure 6 , Figure 6 This is an example diagram illustrating a method for confirming regional familiarity according to an embodiment of this application. Figure 6 The diagram shows a learning curve, a graphical representation of the relationship between proficiency and experience in a task. Proficiency (measured on the vertical axis) typically increases with experience (on the horizontal axis); that is, the more times an individual, group, company, or industry performs a task, the better they perform. Therefore, the method for confirming a delivery party's familiarity with their effective delivery area can also be set up using a learning curve. A logarithmic function can be used as the function to fit the delivery party's unit area visit characteristics and familiarity, and the learning curve can be applied to standardize the spatial dwell time and number of spatial visits. Please see the following formula:

[0071] g(x) = loga(xb), (a>1)

[0072] Here, x represents the number of visits per unit area or the duration of visits per unit area. Since the rate of change of the logarithmic function g(x) varies greatly depending on the base and the interval of x, we can use function visualization tools to select a function that better reflects our ideal experience, that is, to confirm the base a and parameter b of the logarithmic function.

[0073] Furthermore, the logarithmic function can be normalized to its maximum and minimum values ​​using the following formula, compressing the data into a smaller range while preserving the relative magnitudes of the data. The normalized result y is used as the familiarity level of the delivery party. That is, the first logarithmic function can include the aforementioned g(x) and its corresponding y.

[0074]

[0075] Where y represents the level of familiarity. When the input x is the number of visits per unit area, the output y represents the level of familiarity score determined based on the number of visits per unit area, which is also the score for the first count.

[0076] S209, determine the first duration score based on the access time per unit area and the first logarithmic function;

[0077] Similarly, the first duration score is determined based on the first logarithmic function for the visit duration per unit area. When the input x is the visit duration per unit area, the output y represents the familiarity score determined based on the visit duration per unit area, which is the first duration score.

[0078] S210, the first frequency score and the first duration score are weighted to obtain the delivery party's familiarity with the target delivery area;

[0079] Specifically, based on the above method, the relationship between the number of visits per unit area and the level of familiarity can be derived. Similarly, the relationship between the visit duration per unit area and the level of familiarity can also be derived. Considering that the correlation between the number of visits and the visit duration is not very high and they cannot be substituted for each other, it is necessary to integrate the two familiarity indicators. The simplest linear weighting method can be adopted: F = w1y1 + w2y2 (w1 + w2 = 1), where y1 can be the score of the first visit, y2 can be the score of the first duration, w1 is the weight corresponding to the score of the first visit, and w2 is the weight corresponding to the score of the first duration. The resulting F is the level of familiarity of the delivery party with the target delivery area.

[0080] S211, determine the second numerical score based on the number of visits per unit area and the piecewise function;

[0081] In one embodiment, the unit area visit characteristics include the number of visits per unit area and the duration of visits per unit area. Determining the delivery party's familiarity with the target delivery area based on these unit area visit characteristics can be achieved using a piecewise function. This piecewise function includes a linear function and a second logarithmic function. Since directly using a logarithmic function to confirm familiarity requires significant work to determine the parameters a and b, the function is simplified by transforming the normalized logarithmic function into a piecewise function. Furthermore, using piecewise linear and logarithmic functions to approximate the learning curve ensures that familiarity and behavior are not simply linearly related, but rather more in line with objective laws. Please refer to [link to relevant documentation]. Figure 7 , Figure 7 This is an example diagram illustrating a method for confirming regional familiarity according to an embodiment of this application. Figure 7 The diagram shows a piecewise function. When the familiarity level is less than 0.8, a linear function is used to fit the learning curve, and when the familiarity level is greater than 0.8, a logarithmic function is used to fit the learning curve.

[0082] For example, a piecewise function is as follows:

[0083]

[0084] Wherein, parameter 'a' represents the number of visits per unit area, and parameter 'b' represents the maximum number of visits per unit area. The number of visits per unit area refers to the number of visits / duration required to reach the desired level of familiarity; the maximum number of visits per unit area refers to the number of visits / duration required to reach the maximum level of familiarity. 'xi' represents the input visit feature per unit area, and 'yi' represents the familiarity level (score) corresponding to the visit feature per unit area. When the input 'x' is the visit duration per unit area, the output 'y' represents the familiarity score determined based on the visit duration per unit area, i.e., the second duration score. By statistically analyzing the distribution of the number of visits per unit area by delivery personnel, the parameters 'a' and 'b' can be roughly determined. For example, if we want 10% of delivery personnel to have a familiarity level of 0.8 or higher with the target delivery area, then 'a' can be taken as the 90th quantile. If we want 1% of delivery personnel to have a familiarity level of 1 with the target delivery area, then 'b' can be taken as the 99th quantile of the number of visits.

[0085] S212, determine the second duration score based on the access time per unit area and the piecewise function;

[0086] In one embodiment, when the input x is the visit duration per unit area, the output y represents the familiarity score determined based on the visit duration per unit area, which is also the second duration score.

[0087] S213, the second frequency score and the second duration score are weighted to obtain the delivery party's familiarity with the target delivery area;

[0088] In one embodiment, a linear weighting method can be adopted: F = w1y1 + w2y2 (w1 + w2 = 1), where y1 can be the second numerical score, y2 is the second duration score, w1 is the weight corresponding to the second numerical score, w2 is the weight corresponding to the second duration score, and the obtained F is the delivery party's familiarity with the target delivery area.

[0089] Optionally, in one embodiment, when determining the familiarity of a region based on a piecewise function, the following steps S2131-S2134 may be included:

[0090] S2131, if the number of visits per unit area is less than the number of requests per unit area, then the second score is determined based on the number of visits per unit area, the number of requests per unit area, and the linear function;

[0091] Specifically, if the number of visits per unit area is less than the number of requests per unit area, then the number of visits per unit area and the number of requests per unit area are substituted into the linear function to determine the second score.

[0092] S2132, if the number of visits per unit area is greater than the number of requests per unit area, then the second score is determined based on the number of visits per unit area, the number of requests per unit area, the maximum number of visits per unit area, and the second logarithmic function;

[0093] Specifically, if the number of visits per unit area is greater than the number of requests per unit area, then the number of visits per unit area, the number of requests per unit area, and the maximum number of visits per unit area are substituted into the second logarithmic function to obtain the second numerical score.

[0094] S2133, if the access time per unit area is less than the number of times required per unit area, then a second duration score is determined based on the access time per unit area, the number of times required per unit area, and the linear function;

[0095] Similarly, for the access time per unit area, if the access time per unit area is less than the number of times required per unit area, the access time per unit area and the number of times required per unit area are substituted into the linear function to determine the second duration score.

[0096] S2134, if the access duration per unit area is greater than the number of times the unit area is required, then a second duration score is determined based on the access duration per unit area, the number of times the unit area is required, the maximum number of times the unit area is used, and the second logarithmic function.

[0097] Specifically, if the access duration per unit area is greater than the number of times required per unit area, the access duration per unit area, the number of times required per unit area, and the maximum number of times per unit area are substituted into the second logarithmic function to determine the second duration score.

[0098] In this embodiment, historical order data for the target delivery area is obtained, and the order production area is confirmed within the target delivery area based on the historical order data. The order production area is then confirmed as a valid delivery area. Historical movement trajectory data of the delivery person within the target delivery area is obtained, and the entry trajectory point and departure trajectory point of the delivery person are confirmed based on the historical movement trajectory data. The number of times the delivery person visits the valid delivery area is determined based on the entry trajectory point, and the duration of stay within the valid delivery area is determined based on the entry and departure trajectory points. Subsequently, the number of visits per unit area and the duration of stay are determined based on the number of visits, the duration of stay, and the area of ​​the valid delivery area. At the same time, two methods are provided to confirm the familiarity score corresponding to the number of visits per unit area and the duration of stay per unit area. The familiarity of the delivery person with the target delivery area is determined based on the score corresponding to the number of visits per unit area and the score corresponding to the duration of stay per unit area. By identifying effective delivery areas within the target delivery region based on order output, and standardizing the number of visits and visit duration according to the size of the geographically effective delivery area, the resulting visit duration and number of visits per unit area are used as core factors to characterize familiarity. This more realistically reflects the delivery party's familiarity with the area. Furthermore, by using piecewise and logarithmic functions to approximate the learning curve, the relationship between familiarity and behavior is not a simple linear one, but rather more in line with objective laws, thus producing more accurate familiarity assessment results.

[0099] The following will be combined with the appendix Figure 8 This application provides a detailed description of the area familiarity confirmation device provided in its embodiments. It should be noted that... Figure 8 The area familiarity verification device in this manual is used to perform the functions described herein. Figures 2-7 The methods shown in the embodiments are illustrated for ease of explanation, showing only the parts relevant to the embodiments of this application. For specific technical details not disclosed, please refer to this specification. Figures 2-7 The example shown.

[0100] Please see Figure 8 This illustration shows a schematic diagram of a region familiarity verification device provided in an exemplary embodiment of this application. The region familiarity verification device can be implemented as all or part of a device through software, hardware, or a combination of both. The device 1 includes a region verification module 11, a trajectory acquisition module 12, a feature verification module 13, and a familiarity verification module 14.

[0101] The area confirmation module 11 is used to determine the valid delivery area within the target delivery area;

[0102] The trajectory acquisition module 12 is used to acquire historical running trajectory data of the delivery person within the target delivery area;

[0103] The feature confirmation module 13 is used to determine the delivery party's access characteristics per unit area within the effective delivery area based on the historical running trajectory data.

[0104] Familiarity confirmation module 14 is used to determine the delivery party's familiarity with the target delivery area based on the unit area access characteristics.

[0105] Optionally, the area confirmation module 11 is specifically used to obtain historical order data for the target delivery area;

[0106] Based on the historical order data, the order production area is confirmed in the target delivery area, and the order production area is confirmed as a valid delivery area.

[0107] Optionally, the area confirmation module 11 is further used to obtain the order pick-up location and order delivery location of the historical order data;

[0108] A geocoding system is used to map the order pickup location and the order delivery location to obtain a first mapping area corresponding to the order pickup location and a second mapping area corresponding to the order delivery location;

[0109] The first mapping region and the second mapping region are deduplicated to obtain the order production region, and the order production region is confirmed as the valid delivery region.

[0110] Optionally, the unit area access feature includes the number of unit area accesses and the unit area access duration. The feature confirmation module 13 is specifically used to confirm the entry trajectory point of the delivery party entering the effective delivery area and the exit trajectory point of the delivery party leaving the effective delivery area based on the historical running trajectory data.

[0111] The number of times the delivery party visits the effective delivery area is determined based on the entry trajectory points;

[0112] Based on the entry trajectory point and the exit trajectory point, the duration of the delivery party's stay within the effective delivery area is determined;

[0113] The number of visits per unit area and the duration of visits per unit area are determined based on the number of visits, the duration of stay, and the area of ​​the effective delivery area.

[0114] Optionally, the unit area access characteristics include the number of unit area accesses and the unit area access duration, and the familiarity confirmation module 14 is specifically used to determine the first numerical score based on the number of unit area accesses and the first logarithmic function;

[0115] The first duration score is determined based on the access time per unit area and the first logarithmic function;

[0116] The first frequency score and the first duration score are weighted to obtain the delivery party's familiarity with the target delivery area.

[0117] Optionally, the unit area access characteristics include the number of unit area accesses and the unit area access duration. The familiarity confirmation module 14 is specifically used to determine the second numerical score based on the number of unit area accesses and the piecewise function. The piecewise function includes a linear function and a second logarithmic function.

[0118] The second duration score is determined based on the access time per unit area and the piecewise function;

[0119] The second frequency score and the second duration score are weighted to obtain the delivery party's familiarity with the target delivery area.

[0120] Optionally, the familiarity confirmation module 14 is specifically used to determine a second score based on the number of visits per unit area, the number of demands per unit area, and the linear function if the number of visits per unit area is less than the number of demands per unit area.

[0121] If the number of visits per unit area is greater than the number of requests per unit area, then the second score is determined based on the number of visits per unit area, the number of requests per unit area, the maximum number of visits per unit area, and the second logarithmic function.

[0122] If the access time per unit area is less than the number of times required per unit area, then a second duration score is determined based on the access time per unit area, the number of times required per unit area, and the linear function.

[0123] If the access duration per unit area is greater than the number of times the unit area is required, then the second numerical score is determined based on the access duration per unit area, the number of times the unit area is required, the maximum number of times per unit area, and the second logarithmic function.

[0124] It should be noted that the area familiarity confirmation device provided in the above embodiments is only illustrated by the division of the above functional modules when executing the area familiarity confirmation method. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the area familiarity confirmation device and the area familiarity confirmation method embodiments provided in the above embodiments belong to the same concept, and the implementation process is detailed in the method embodiments, which will not be repeated here.

[0125] The sequence numbers of the embodiments described above are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments. In some cases, the actions or steps described in the claims can be performed in a different order than that shown in the embodiments and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0126] This application embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements the above-described functionality. Figures 2-7 The method described in the illustrated embodiment can be found in the following document for a detailed execution process. Figures 2-7 The specific details of the illustrated embodiments will not be elaborated here.

[0127] Please refer to Figure 9 This diagram illustrates the structure of an electronic device provided in an exemplary embodiment of this specification. The electronic device in this specification may include one or more components such as a processor 110, a memory 120, an input device 130, an output device 140, and a bus 150. The processor 110, memory 120, input device 130, and output device 140 may be connected via the bus 150.

[0128] Processor 110 may include one or more processing cores. Processor 110 connects to various parts of the electronic device using various interfaces and lines, and executes various functions of terminal 100 and processes data by running or executing instructions, programs, code sets, or instruction sets stored in memory 120, and by calling data stored in memory 120. Optionally, processor 110 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). Processor 110 may integrate one or more of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user page, and applications; the GPU is responsible for rendering and drawing the displayed content; and the modem handles wireless communication. It is understood that the modem may also not be integrated into processor 110 and may be implemented separately using a communication chip.

[0129] The memory 120 may include random access memory (RAM) or read-only memory (ROM). Optionally, the memory 120 may include non-transitory computer-readable storage medium. The memory 120 may be used to store instructions, programs, code, code sets, or instruction sets. The memory 120 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for implementing at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the various method embodiments described above, etc. The operating system may be the Android system, including systems deeply developed based on the Android system, the iOS system developed by Apple Inc., including systems deeply developed based on the iOS system, or other systems.

[0130] The memory 120 can be divided into operating system space and user space. The operating system runs in the operating system space, while native and third-party applications run in user space. To ensure that different third-party applications can achieve good running performance, the operating system allocates corresponding system resources for each application. However, different application scenarios within the same third-party application have different requirements for system resources. For example, in local resource loading scenarios, third-party applications have high requirements for disk read speed; in animation rendering scenarios, third-party applications have high requirements for GPU performance. Since the operating system and third-party applications are independent of each other, the operating system often cannot promptly perceive the current application scenario of a third-party application, resulting in the operating system's inability to adapt system resources accordingly.

[0131] In order for the operating system to distinguish the specific application scenarios of third-party applications, it is necessary to establish data communication between the third-party applications and the operating system. This would allow the operating system to obtain the current scenario information of the third-party applications at any time, and then perform targeted system resource adaptation based on the current scenario.

[0132] The input device 130 is used to receive input instructions or data, and includes, but is not limited to, a keyboard, mouse, camera, microphone, or touch device. The output device 140 is used to output instructions or data, and includes, but is not limited to, a display device and a speaker. In one example, the input device 130 and the output device 140 can be combined, and the input device 130 and the output device 140 are a touch display screen. The touch display screen can be designed as a full-screen, curved screen, or irregularly shaped screen. The touch display screen can also be designed as a combination of a full-screen and a curved screen, or a combination of an irregularly shaped screen and a curved screen; this application embodiment does not limit this.

[0133] In addition, those skilled in the art will understand that the structure of the electronic device shown in the above figures does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have different component arrangements. For example, the electronic device may also include radio frequency circuits, input units, sensors, audio circuits, WiFi modules, power supplies, Bluetooth modules, etc., which will not be described in detail here.

[0134] exist Figure 9 In the illustrated electronic device, the processor 110 can be used to call computer applications stored in the memory 120 and specifically perform the following operations:

[0135] Determine the effective delivery area within the target delivery area;

[0136] Obtain historical running trajectory data of the delivery person within the target delivery area;

[0137] Based on the historical running trajectory data, the delivery party's access characteristics per unit area within the effective delivery area are determined;

[0138] The familiarity of the delivery party with the target delivery area is determined based on the unit area access characteristics.

[0139] In one embodiment, when the processor 110 determines a valid delivery area in the target delivery area, it specifically performs the following operations:

[0140] Obtain historical order data for the target delivery area;

[0141] Based on the historical order data, the order production area is confirmed in the target delivery area, and the order production area is confirmed as a valid delivery area.

[0142] In one embodiment, when the processor 110 confirms the order production area in the target delivery area based on the historical order data and identifies the order production area as a valid delivery area, it specifically performs the following operations:

[0143] Obtain the order pickup location and order delivery location from the historical order data;

[0144] A geocoding system is used to map the order pickup location and the order delivery location to obtain a first mapping area corresponding to the order pickup location and a second mapping area corresponding to the order delivery location;

[0145] The first mapping region and the second mapping region are deduplicated to obtain the order production region, and the order production region is confirmed as the valid delivery region.

[0146] In one embodiment, the unit area access characteristics include the number of unit area visits and the unit area visit duration. When the processor 110 determines the unit area access characteristics of the delivery party within the effective delivery area based on the historical running trajectory data, it specifically performs the following operations:

[0147] Based on the historical running trajectory data, the entry trajectory point of the delivery person into the effective delivery area and the exit trajectory point of the delivery person from the effective delivery area are confirmed.

[0148] The number of times the delivery party visits the effective delivery area is determined based on the entry trajectory points;

[0149] Based on the entry trajectory point and the exit trajectory point, the duration of the delivery party's stay within the effective delivery area is determined;

[0150] The number of visits per unit area and the duration of visits per unit area are determined based on the number of visits, the duration of stay, and the area of ​​the effective delivery area.

[0151] In one embodiment, the unit area access characteristics include the number of visits per unit area and the unit area visit duration. When the processor 110 executes the operation of determining the delivery party's familiarity with the target delivery area based on the unit area access characteristics, it specifically performs the following operations:

[0152] The first numerical score is determined based on the number of visits per unit area and the first logarithmic function.

[0153] The first duration score is determined based on the access time per unit area and the first logarithmic function;

[0154] The first frequency score and the first duration score are weighted to obtain the delivery party's familiarity with the target delivery area.

[0155] In one embodiment, the unit area access characteristics include the number of visits per unit area and the unit area visit duration. When the processor 110 executes the operation of determining the delivery party's familiarity with the target delivery area based on the unit area access characteristics, it specifically performs the following operations:

[0156] The second numerical score is determined based on the number of visits per unit area and the piecewise function; the piecewise function includes a linear function and a second logarithmic function.

[0157] The second duration score is determined based on the access time per unit area and the piecewise function;

[0158] The second frequency score and the second duration score are weighted to obtain the delivery party's familiarity with the target delivery area.

[0159] In one embodiment, when the processor 110 determines the second numerical score based on the number of visits per unit area and the piecewise function, it specifically performs the following operations:

[0160] If the number of visits per unit area is less than the number of requests per unit area, then the second score is determined based on the number of visits per unit area, the number of requests per unit area, and the linear function.

[0161] If the number of visits per unit area is greater than the number of requests per unit area, then the second score is determined based on the number of visits per unit area, the number of requests per unit area, the maximum number of visits per unit area, and the second logarithmic function.

[0162] In one embodiment, when the processor 110 determines the second duration score based on the unit area access time and the piecewise function, it specifically performs the following operations:

[0163] If the access time per unit area is less than the number of times required per unit area, then a second duration score is determined based on the access time per unit area, the number of times required per unit area, and the linear function.

[0164] If the access duration per unit area is greater than the number of times the unit area is required, then the second numerical score is determined based on the access duration per unit area, the number of times the unit area is required, the maximum number of times per unit area, and the second logarithmic function.

[0165] In this embodiment, by determining an effective delivery area within the target delivery area, historical movement trajectory data of the delivery person within that area is obtained. Based on this historical movement trajectory data, the delivery person's unit-area access characteristics within the effective delivery area are determined, and the delivery person's familiarity with the target delivery area is determined based on these unit-area access characteristics. Standardizing the delivery person's historical movement trajectory data using the effective delivery area within the target delivery area resolves the erroneous relationship that larger areas equate to higher familiarity, thus enabling a more accurate assessment of the delivery person's familiarity with the delivery area based on unit-area access characteristics.

[0166] Furthermore, by acquiring historical order data for the target delivery area, the order production area is identified within the target delivery area based on the historical order data, and the order production area is confirmed as the effective delivery area. Historical movement trajectory data of the delivery person within the target delivery area is acquired, and the entry trajectory point and departure trajectory point of the delivery person are identified based on the historical movement trajectory data. The number of times the delivery person visits the effective delivery area is determined based on the entry trajectory point, and the dwell time of the delivery person within the effective delivery area is determined based on the entry and departure trajectory points. Then, based on the number of visits, dwell time, and the area of ​​the effective delivery area, the number of visits per unit area and the visit time per unit area are determined. Simultaneously, two methods are provided to confirm the familiarity score corresponding to the number of visits per unit area and the visit time per unit area. The delivery person's familiarity with the target delivery area is determined based on the score corresponding to the number of visits per unit area and the score corresponding to the visit time per unit area. By identifying effective delivery areas within the target delivery region based on order output, and standardizing the number of visits and visit duration according to the size of the geographically effective delivery area, the resulting visit duration and number of visits per unit area are used as core factors to characterize familiarity. This more realistically reflects the delivery party's familiarity with the area. Furthermore, by using piecewise and logarithmic functions to approximate the learning curve, the relationship between familiarity and behavior is not a simple linear one, but rather more in line with objective laws, thus producing more accurate familiarity assessment results.

[0167] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. The storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0168] The above-disclosed embodiments are merely preferred embodiments of this specification and should not be construed as limiting the scope of this specification. Therefore, any equivalent variations made in accordance with the claims of this specification shall still fall within the scope of this specification.

Claims

1. A method for confirming regional familiarity, characterized in that, include: Determine the effective delivery area within the target delivery area; Obtain historical running trajectory data of the delivery person within the target delivery area; Based on the historical running trajectory data, the delivery party's access characteristics per unit area within the effective delivery area are determined; The familiarity of the delivery party with the target delivery area is determined based on the unit area access characteristics.

2. The method as described in claim 1, characterized in that, The determination of the effective delivery area within the target delivery area includes: Obtain historical order data for the target delivery area; Based on the historical order data, the order production area is confirmed in the target delivery area, and the order production area is confirmed as a valid delivery area.

3. The method as described in claim 2, characterized in that, The step of confirming the order origination area within the target delivery area based on the historical order data, and confirming the order origination area as a valid delivery area, includes: Obtain the order pickup location and order delivery location from the historical order data; A geocoding system is used to map the order pickup location and the order delivery location to obtain a first mapping area corresponding to the order pickup location and a second mapping area corresponding to the order delivery location; The first mapping region and the second mapping region are deduplicated to obtain the order production region, and the order production region is confirmed as the valid delivery region.

4. The method as described in claim 1, characterized in that, The access characteristics per unit area include the number of accesses per unit area and the access duration per unit area; The determination of the delivery party's unit area access characteristics within the effective delivery area based on the historical running trajectory data includes: Based on the historical running trajectory data, the entry trajectory point of the delivery person into the effective delivery area and the exit trajectory point of the delivery person from the effective delivery area are confirmed. The number of times the delivery party visits the effective delivery area is determined based on the entry trajectory points; Based on the entry trajectory point and the exit trajectory point, the duration of the delivery party's stay within the effective delivery area is determined; The number of visits per unit area and the duration of visits per unit area are determined based on the number of visits, the duration of stay, and the area of ​​the effective delivery area.

5. The method as described in claim 1, characterized in that, The access characteristics per unit area include the number of accesses per unit area and the access duration per unit area; The determination of the delivery party's familiarity with the target delivery area based on the unit area access characteristics includes: The first numerical score is determined based on the number of visits per unit area and the first logarithmic function. The first duration score is determined based on the access time per unit area and the first logarithmic function; The first frequency score and the first duration score are weighted to obtain the delivery party's familiarity with the target delivery area.

6. The method as described in claim 1, characterized in that, The access characteristics per unit area include the number of accesses per unit area and the access duration per unit area; The determination of the delivery party's familiarity with the target delivery area based on the unit area access characteristics includes: The second numerical score is determined based on the number of visits per unit area and the piecewise function; the piecewise function includes a linear function and a second logarithmic function. The second duration score is determined based on the access time per unit area and the piecewise function; The second frequency score and the second duration score are weighted to obtain the delivery party's familiarity with the target delivery area.

7. The method as described in claim 6, characterized in that, The determination of the second score based on the number of visits per unit area and the piecewise function includes: If the number of visits per unit area is less than the number of requests per unit area, then the second score is determined based on the number of visits per unit area, the number of requests per unit area, and the linear function. If the number of visits per unit area is greater than the number of requests per unit area, then the second score is determined based on the number of visits per unit area, the number of requests per unit area, the maximum number of visits per unit area, and the second logarithmic function. The determination of the second duration score based on the access time per unit area and the piecewise function includes: If the access time per unit area is less than the number of times required per unit area, then a second duration score is determined based on the access time per unit area, the number of times required per unit area, and the linear function. If the access duration per unit area is greater than the number of times the unit area is required, then the second numerical score is determined based on the access duration per unit area, the number of times the unit area is required, the maximum number of times per unit area, and the second logarithmic function.

8. A device for confirming familiarity with a region, characterized in that, The device includes: The area confirmation module is used to determine the valid delivery area within the target delivery area; The trajectory acquisition module is used to acquire historical running trajectory data of the delivery person within the target delivery area; The feature confirmation module is used to determine the delivery party's access characteristics per unit area within the effective delivery area based on the historical running trajectory data. The familiarity verification module is used to determine the delivery party's familiarity with the target delivery area based on the unit area access characteristics.

9. An electronic device, characterized in that, include: Processor and memory; The memory stores a computer program adapted to be loaded by the processor and to execute the steps of the method as described in any one of claims 1 to 7.

10. A storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the steps of the method as described in any one of claims 1 to 7.

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