A method and system for extracting geographic information features

Abstract

The embodiment of the present application discloses a method and system for extracting geographic information features. The method includes: obtaining historical order data; querying geographic information associated with the historical order data based on the historical order data to obtain geographic information corresponding to the historical order data; splicing the historical order data with the geographic information corresponding to the historical order data to obtain an order sample containing geographic information features. The present application solves the time delay problem during data query calls by associating heterogeneous data from different data sources with order data and outputting them in multiple encoding forms, thereby improving data portability; at the same time, the road ID in the order data can also be updated to avoid road coding misalignment.

Description

Technical Field

[0001] The present application relates to the field of geographic information, and in particular to a method and system for extracting geographic information features. Background Art

[0002] Geographic data is data directly or indirectly related to a certain location on the earth. It is a file of elements of natural and social phenomena that represent geographical location and distribution characteristics. Geographic information refers to information related to spatial geographical distribution. It is a general term for numbers, texts, graphics, images, etc. that represent the inherent data, quality, distribution characteristics, connections and laws of surface objects and environment.

[0003] The application of geographic information is essential in the field of digital maps. In the current GPS industry, there are a lot of massive geographic data, and the geographic information from different information sources has different description information and different description granularity. Therefore, it is necessary to provide a method and system for extracting geographic information features. Summary of the invention

[0004] One of the embodiments of the present application provides a method for extracting geographic information features. The method includes: obtaining historical order data; querying geographic information associated with the historical order data based on the historical order data to obtain geographic information corresponding to the historical order data; and splicing the historical order data with the geographic information corresponding to the historical order data to obtain an order sample containing geographic information features.

[0005] One of the embodiments of the present application provides a geographic information feature extraction system. The system includes: a first acquisition module, a first query module and a first splicing module; wherein: the first acquisition module is used to acquire historical order data; the first query module is used to query the geographic information associated with the historical order data based on the historical order data to obtain the geographic information corresponding to the historical order data; the first splicing module is used to splice the historical order data with the geographic information corresponding to the historical order data to obtain an order sample containing geographic information features.

[0006] One of the embodiments of the present application provides a method for extracting geographic information features. The method includes: obtaining current order data; querying geographic information associated with the current order data based on the current order data to obtain geographic information corresponding to the current order data; and splicing the current order data with the geographic information corresponding to the current order data to obtain a current order sample containing geographic information features.

[0007] One of the embodiments of the present application provides a geographic information feature extraction system. The system includes: a second acquisition module, a second query module, and a second splicing module; wherein: the second acquisition module is used to acquire current order data; the second query module is used to query the geographic information associated with the current order data based on the current order data to obtain the geographic information corresponding to the current order data; the second splicing module is used to splice the current order data with the geographic information corresponding to the current order data to obtain a current order sample containing geographic information features.

[0008] One of the embodiments of the present application provides a device for extracting geographic information features, which includes at least one processor and at least one storage device, wherein the storage device is used to store instructions, and when the at least one processor executes the instructions, the method described in any embodiment of the present application is implemented.

[0009] One of the embodiments of the present application provides a computer-readable storage medium, wherein the storage medium stores computer instructions, and when a computer reads the computer instructions in the storage medium, the computer executes the method described in any embodiment of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] The present application will be further described in the form of exemplary embodiments, which will be described in detail by way of the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0011] Figure 1 is a schematic diagram of an application scenario of a geographic information feature extraction system according to some embodiments of the present application;

[0012] Figure 2 is a schematic diagram of an exemplary computing device according to some embodiments of the present application;

[0013] Figure 3 is a module diagram of a geographic information feature extraction system according to some embodiments of the present application;

[0014] Figure 4 is a module diagram of a geographic information feature extraction system according to another embodiment of the present application;

[0015] Figure 5 is an exemplary flow chart of a geographic information feature extraction method according to some embodiments of the present application;

[0016] Figure 6 is an exemplary flow chart of a method for extracting geographic information features according to another embodiment of the present application;

[0017] Figure 7is an exemplary schematic diagram of road attributes according to some embodiments of the present application;

[0018] Figure 8 is an exemplary schematic diagram of intersection attributes according to some embodiments of the present application; and

[0019] Fig. 9 It is a schematic diagram of an exemplary format of an order sample containing geographic information features according to some embodiments of the present application. DETAILED DESCRIPTION

[0020] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of the present application. For ordinary technicians in this field, the present application can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0021] It should be understood that the "system", "device", "unit" and / or "module" used herein are a method for distinguishing different components, elements, parts, portions or assemblies at different levels. However, if other words can achieve the same purpose, the words can be replaced by other expressions.

[0022] As shown in this application and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "comprises" and "includes" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0023] Flowcharts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the preceding or following operations are not necessarily performed accurately in order. On the contrary, the various steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0024] The embodiments of the present application can be applied to different transportation systems, for example, taxis, special cars, ride-sharing, buses, and designated drivers. The "passengers", "passenger terminals", "user terminals", "customers", "demanders", "service demanders", "consumers", "consumers", "user demanders", etc. described in this application are interchangeable and refer to the party that needs or orders services, which can be an individual or a tool. Similarly, the "driver", "driver terminal", "provider", "supplier", "service provider", "service provider", "service provider", etc. described in this application are also interchangeable and refer to individuals, tools or other entities that provide services or assist in providing services. In addition, the "user" described in this application can be a party that needs or orders services, or a party that provides services or assists in providing services.

[0025] Figure 1 1 is a schematic diagram of an application scenario of the geographic information feature extraction system 100 shown in some embodiments of the present application. The geographic information feature extraction system 100 can splice the order data with the geographic information corresponding to the order data, obtain an order sample containing geographic information features and output it in a variety of coding forms, solve the time delay problem caused by querying and calling multiple dimensional data together, and improve the portability of the data. The geographic information feature extraction system 100 can be a service platform for the Internet or other networks. For example, the geographic information feature extraction system 100 can be an offline service platform that provides services for transportation. In some embodiments, the geographic information feature extraction system 100 can be applied to online car-hailing services, such as taxi calls, express calls, special car calls, minibus calls, carpooling, bus services, driver hiring and pick-up services, etc. In some embodiments, the geographic information feature extraction system 100 can also be applied to driving, express delivery, takeout, etc. In other embodiments, the geographic information feature extraction system 100 can also be applied to housekeeping services, travel (such as tourism) services, education (such as offline education) services and other fields. The geographic information feature extraction system 100 may include a server 110 , one or more service requester terminals 120 , a storage device 130 , one or more service provider terminals 140 , a network 150 , and an information source 160 . The server 110 may include a processing engine 112 .

[0026] In some embodiments, the server 110 may be a single server or a server group. The server group may be centralized or distributed (for example, the server 110 may be a distributed system). In some embodiments, the server 110 may be local or remote. For example, the server 110 may access information and / or data stored in the storage device 130 or the service requester terminal 120 through the network 150. For another example, the server 110 may be directly connected to the storage device 130 or the service requester terminal 120 to access the stored information and / or data. In some embodiments, the server 110 may be implemented on a cloud platform. Just to give an example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, between clouds, multiple clouds, etc., or any combination of the above examples. In some embodiments, the server 110 may be on a cloud platform connected to the present application. Figure 2 For example, server 110 may be implemented on a computing device such as Figure 2 The processing engine 112 is implemented on a computing device 200 shown in the figure, including one or more components in the computing device 200. In some embodiments, the processing engine 112 may process data and / or information related to the extraction of geographic information features to perform one or more functions described in the present application. For example, the processing engine 112 may query the geographic information associated with the historical order data, and splice the historical order data with the geographic information corresponding to the historical order data to obtain an order sample containing geographic information features. In some embodiments, the processing engine 112 may obtain historical or current order data. In some embodiments, the processing engine 112 may query the geographic information associated with the historical or current order data based on the historical or current order data. In some embodiments, the processing engine 112 may splice the historical or current order data with the geographic information corresponding to the historical or current order data to obtain an order sample containing geographic information features. In some embodiments, if the road ID in the road information is not included in the historical or current order data, the processing engine 112 may update the road ID in the historical or current order data.

[0027] In some embodiments, the user of the service requester terminal 120 may be the service requester himself. In some embodiments, the user of the service requester terminal 120 may be someone other than the service requester. For example, in an online car-hailing service, the user of the service requester terminal 120 may be the passenger himself, or the passenger's relative, friend, or other person who helps the passenger place an order. For another example, in a food delivery service, the user of the service requester terminal 120 may be the target object to which the food delivery is delivered, or the person who helps the target object order the food delivery. For another example, in a housekeeping service, the user of the service requester terminal 120 may be the actual person in need of the housekeeping service, or the person who helps the person in need purchase the housekeeping service.

[0028] In some embodiments, the user of the service provider terminal 140 may be the service provider himself. In some embodiments, the user of the service provider terminal 140 may be someone other than the service provider. For example, in an online car-hailing service, the user of the service provider terminal 140 may be the driver himself, or the person who helps the driver to take orders. For another example, in a food delivery service, the user of the service provider terminal 140 may be the food delivery person himself, or the person who helps the delivery person to take orders. For another example, in a housekeeping service, the user of the service provider terminal 140 may be the actual service personnel of the housekeeping service (such as maintenance personnel, cleaners, etc.), or the person who helps the service personnel to take orders.

[0029] In some embodiments, the service requester terminal 120 may include but is not limited to a desktop computer 120-1, a laptop computer 120-2, a vehicle-mounted built-in device 120-3, a mobile device 120-4, etc. or any combination thereof. In some embodiments, the vehicle-mounted built-in device 120-3 may include but is not limited to a vehicle-mounted computer, a vehicle-mounted head-up display (HUD), an onboard automatic diagnostic system (OBD), etc. or any combination thereof. In some embodiments, the mobile device 120-4 may include but is not limited to a smart phone, a personal digital assistant (PDA), a tablet computer, a handheld game console, smart glasses, a smart watch, a wearable device, a virtual display device, a display enhancement device, etc. or any combination thereof. In some embodiments, the service requester terminal 120 may send the transportation service demand to one or more devices in the geographic information feature extraction system 100. For example, the service requester terminal 120 may send the transportation service demand to the server 110 for processing.

[0030] In some embodiments, the service provider terminal 140 may be a device similar to or the same as the service requester terminal 120. In some embodiments, the service provider terminal 140 may be a device with positioning technology to determine the location of the service provider and / or the service provider terminal 140. In some embodiments, the service requester terminal 120 and / or the service provider terminal 140 may communicate with other positioning devices to determine the location of the service requester, the service requester terminal 120, the service provider, or the service provider terminal 140. In some embodiments, the service requester terminal 120 and / or the service provider terminal 140 may send positioning information to the server 110.

[0031] The storage device 130 may store data and / or instructions. In some embodiments, the storage device 130 may store data obtained from the service requester terminal 120. In some embodiments, the storage device 130 may store data and / or instructions for execution or use by the server 110, and the server 110 may implement the exemplary method described in this application by executing or using the data and / or instructions. In some embodiments, the storage device 130 may be connected to the network 150 to implement communication with one or more components (e.g., the server 110, the service requester terminal 120, etc.) in the geographic information feature extraction system 100. One or more components of the geographic information feature extraction system 100 may access the data or instructions stored in the storage device 130 through the network 150. In some embodiments, the storage device 130 may be directly connected or communicated with one or more components (e.g., the server 110, the service requester terminal 120, etc.) of the geographic information feature extraction system 100. In some embodiments, the storage device 130 may be part of the server 110.

[0032] The network 150 can facilitate the exchange of information and / or data. In some embodiments, one or more components in the geographic information feature extraction system 100 (e.g., the server 110, the storage device 130, and the service requester terminal 120, etc.) can send information and / or data to other components in the geographic information feature extraction system 100 through the network 150. For example, the server 110 can obtain / get data information from the service requester terminal 120 through the network 150. In some embodiments, the network 150 can be any one of a wired network or a wireless network, or a combination thereof. For example, the network 150 can include a cable network, a wired network, an optical fiber network, a telecommunications network, an intranet, the Internet, a local area network (LAN), a wide area network (WAN), a wireless local area network (WLAN), a metropolitan area network (MAN), a public switched telephone network (PSTN), a Bluetooth network, a ZigBee network, a near field communication (NFC) network, etc., or any combination of the above examples. In some embodiments, the network 150 can include one or more network access points. For example, the network 150 may include wired or wireless network access points, such as base stations and / or Internet exchange points 150-1, 150-2, etc. Through the access points, one or more components of the geographic information feature extraction system 100 may be connected to the network 150 to exchange data and / or information.

[0033] The information source 160 is a source that provides other information for the geographic information feature extraction system 100. The information source 160 can be used to provide the system with information related to order information, such as service time, service location, legal and regulatory information, news information, life information, life guide information, etc. The information source 160 can exist in the form of a single central server, or in the form of multiple servers connected through a network, or in the form of a large number of personal devices. When the information source 160 exists in the form of a large number of personal devices, these devices can be generated by a user (user-generated contents) method, such as uploading text, voice, image, video, etc. to the cloud server, so that the cloud server is connected to the many personal devices connected to it to form the information source 160.

[0034] Figure 2 2 is a schematic diagram of an exemplary computing device 200 according to some embodiments of the present application. The server 110 and the storage device 130 can be implemented on the computing device 200. For example, the processing engine 112 can be implemented on the computing device 200 and configured to implement the functions disclosed in the present application.

[0035] The computing device 200 may include any components used to implement the system described in this application. For example, the processing engine 112 may be implemented on the computing device 200 through its hardware, software program, firmware, or a combination thereof. For convenience, only one computer is drawn in the figure, but the computing functions related to the geographic information feature extraction system 100 described in this application can be implemented in a distributed manner by a group of similar platforms to disperse the processing load of the system.

[0036] The computing device 200 may include a communication port 250 connected to a network for data communication. The computing device 200 may include a processor (e.g., CPU) 220, which may execute program instructions in the form of one or more processors. An exemplary computer platform may include an internal bus 210, different forms of program memory and data memory including, for example, a hard disk 270, a read-only memory (ROM) 230 or a random access memory (RAM) 240, for storing various data files processed and / or transmitted by the computer. An exemplary computing device may include program instructions executed by the processor 220 stored in the read-only memory 230, the random access memory 240 and / or other types of non-temporary storage media. The method and / or process of the present application may be implemented in the form of program instructions. The computing device 200 also includes an input / output component 260 for supporting input / output between the computer and other components. The computing device 200 may also receive the program and data in the present disclosure through network communication.

[0037] For ease of understanding, Figure 2 Only one processor is drawn as an example. However, it should be noted that the computing device 200 in the present application may include multiple processors, so the operations and / or methods implemented by one processor described in the present application may also be implemented jointly or independently by multiple processors. For example, if in the present application, the processor of the computing device 200 performs steps 1 and 2, it should be understood that steps 1 and 2 may also be performed jointly or independently by two different processors of the computing device 200 (for example, the first processor performs step 1, the second processor performs step 2, or the first and second processors perform steps 1 and 2 jointly).

[0038] Figure 3 is a module diagram of a geographic information feature extraction system according to some embodiments of the present application. Figure 3 As shown, the geographic information feature extraction system 300 may include a first acquisition module 310, a first query module 320, a first splicing module 330, and an updating module 340. In some embodiments, the first acquisition module 310, the first query module 320, the first splicing module 330, and the updating module 340 may be included in Figure 1 The processing engine 112 is shown.

[0039] The first acquisition module 310 can be used to acquire historical order data.

[0040] In some embodiments, historical orders may include online car-hailing service orders (e.g., taxi orders, express orders, carpooling orders, ride-sharing orders, and bus orders, etc.). In some embodiments, historical order data may include data related to historical orders. Specifically, historical order data may include a road ID and one or more of the following: driver information, passenger information, weather, order time, area information, path information, and intersection information.

[0041] In some embodiments, the historical order data may be stored in the storage device 130. In some embodiments, the first acquisition module 310 may acquire the historical order data from the storage device 130.

[0042] The first query module 320 can be used to query the geographic information associated with the historical order data based on the historical order data to obtain the geographic information corresponding to the historical order data. In some embodiments, the geographic information corresponding to the historical order data may include road information and traffic information.

[0043] like Figure 3As shown, the first query module 320 may further include a road information query unit 321 and a traffic information query unit 322. The road information query unit 321 may be used to query road information in a road network database based on a road ID in the historical order data to obtain road information corresponding to the historical order data. In some embodiments, the road network database may store road information such as road ID, road width, and road length. In some embodiments, the road information may include road attributes and / or intersection attributes, and the road information may come from surveying and mapping data.

[0044] The traffic information query unit 322 can be used to query the traffic information in the traffic database based on the road ID in the historical order data to obtain the traffic information corresponding to the historical order data. In some embodiments, the traffic database can store information such as road ID, road travel time, and traffic light waiting time. In some embodiments, the traffic information includes one or more of road driving speed, road travel time, and traffic light waiting time. In some embodiments, the traffic information in the traffic database can be obtained through other historical order statistics or through model training, and this application does not limit this.

[0045] In some embodiments, the historical order data and the geographic information may be heterogeneous data. Heterogeneous data refers to data sources having different encoding formats, for example, the historical order data may be in binary encoding format, and the geographic information may be in text encoding format.

[0046] In some embodiments, the road information and traffic information may be stored in the storage device 130, and the first query module 320 may obtain the data to perform feature extraction.

[0047] The first splicing module 330 can be used to splice the historical order data with the geographic information corresponding to the historical order data to obtain an order sample containing geographic information features.

[0048] In some embodiments, the order sample containing geographic information features may be a geographic information feature code. In some embodiments, the coding form of the order sample containing geographic information features may include one or more of binary coding, text coding, HTML5 and ASCII coding. By splicing the historical order data with the corresponding geographic information, different coding forms are output, which can be used as feature samples for different models or platforms.

[0049] The updating module 340 may be configured to update the road ID in the historical order data if the road ID in the road information is not included in the historical order data.

[0050] It should be understood that Figure 3The system and its modules shown can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented by hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or a dedicated design hardware. Those skilled in the art will understand that the above methods and systems can be implemented using computer executable instructions and / or included in processor control codes, such as carrier media such as disks, CDs or DVD-ROMs, programmable memories such as read-only memories (firmware), or data carriers such as optical or electronic signal carriers. Such codes are provided on. The system and its modules of the present application can be implemented not only by hardware circuits such as ultra-large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above hardware circuits and software (e.g., firmware).

[0051] It should be noted that the above description of the geographic information feature extraction system and its modules is for convenience of description only and does not limit the present application to the scope of the embodiments cited. It is understandable that for those skilled in the art, after understanding the principle of the system, it is possible to arbitrarily combine the various modules or form a subsystem connected with other modules without deviating from this principle. For example, the update module 340 and the first query module 320 can be the same module, and the first query module 320 can simultaneously query the geographic information associated with the historical order data and update the road ID in the historical order data. Such variations are within the scope of protection of the present application.

[0052] Figure 4 FIG. 1 is a module diagram of a geographic information feature extraction system according to another embodiment of the present application. Figure 4 As shown, the geographic information feature extraction system 400 may include a second acquisition module 410, a second query module 420, and a second splicing module 430. In some embodiments, the second acquisition module 410, the second query module 420, and the second splicing module 430 may be included in Figure 1 The processing engine 112 is shown.

[0053] The second acquisition module 410 can be used to acquire current order data.

[0054] In some embodiments, the current order may include an online car-hailing service order (e.g., a taxi order, an express order, a carpooling order, a ride-sharing order, and a bus order, etc.). In some embodiments, the current order data may include data related to the current order. Specifically, the current order data may include a road ID and one or more of the following: driver information, passenger information, weather, order time, area information, path information, and intersection information.

[0055] In some embodiments, the current order data may be stored in the storage device 130. In some embodiments, the second acquisition module 410 may acquire the current order data from the storage device 130.

[0056] The second query module 420 may be used to query the geographic information associated with the current order data based on the current order data to obtain the geographic information corresponding to the current order data.

[0057] In some embodiments, the geographic information corresponding to the current order data may include road information and traffic information. In some embodiments, querying the geographic information associated with the current order data based on the current order data may include querying the road information in the road network database based on the road ID in the current order data to obtain the road information corresponding to the current order data. In some embodiments, the road network database may store road information such as road ID, road width, and road length. More descriptions of road information and traffic information may be found elsewhere in this application (e.g., in the flow chart). Figure 5 and its related descriptions) and will not be described here.

[0058] In some embodiments, the current order data and the geographic information may be heterogeneous data. Heterogeneous data refers to data sources having different encoding forms, for example, the current order data may be in binary encoding form, and the geographic information may be in text encoding form.

[0059] In some embodiments, the road information and traffic information may be stored in the storage device 130, and the second query module 420 may obtain the data to perform feature extraction.

[0060] The second splicing module 430 can be used to splice the current order data with the geographic information corresponding to the current order data to obtain an order sample containing geographic information features.

[0061] In some embodiments, the order sample containing geographic information features may be a geographic information feature encoding. In some embodiments, the encoding form of the order sample containing geographic information features may include one or more of binary encoding, text encoding, HTML5 and ASCII encoding.

[0062] It should be understood that Figure 4The system and its modules shown can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented by hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or a dedicated design hardware. Those skilled in the art will understand that the above methods and systems can be implemented using computer executable instructions and / or included in processor control codes, such as carrier media such as disks, CDs or DVD-ROMs, programmable memories such as read-only memories (firmware), or data carriers such as optical or electronic signal carriers. Such codes are provided on. The system and its modules of the present application can be implemented not only by hardware circuits such as ultra-large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but can also be implemented by software executed by various types of processors, and can also be implemented by a combination of the above hardware circuits and software (e.g., firmware).

[0063] It should be noted that the above description of the real-time extraction system of geographic information features and its modules is only for the convenience of description and does not limit the present application to the scope of the embodiments cited. It is understandable that for those skilled in the art, after understanding the principle of the system, it is possible to arbitrarily combine the various modules or form a subsystem to connect with other modules without deviating from this principle. For example, the second query module 420 and the second splicing module 430 can be the same module, and the second query module 420 can immediately splice the geographic information with the current order data after querying the geographic information associated with the current order data. Such variations are all within the scope of protection of the present application.

[0064] Figure 5 is an exemplary flow chart of a geographic information feature extraction method according to some embodiments of the present application. In some embodiments, process 500 may be performed by processing logic, which may include hardware (e.g., circuits, dedicated logic, programmable logic, microcode, etc.), software (instructions running on a processing device to perform hardware simulation), etc., or any combination thereof. Figure 5 One or more operations in the process 500 for extracting geographic information features can be performed by Figure 1 For example, the process 500 may be stored in the storage device 130 in the form of instructions and called and / or executed by the processing engine 112 (for example, Figure 2 220 of the computing device 200 shown).

[0065] In step 510 , historical order data may be obtained. Specifically, step 510 may be performed by the first obtaining module 310 .

[0066] In some embodiments, historical orders may include online car-hailing service orders (such as taxi orders, express orders, carpooling orders, ride-sharing orders, and bus orders, etc.). In some embodiments, historical order data may include data related to historical orders. Specifically, historical order data may include a road ID and one or more of the following: driver information, passenger information, weather, order time, area information, path information, and intersection information. In some embodiments, the road ID may be a unique code given to each road in order to distinguish each road. Through the road ID, the corresponding road can be quickly found on the digital map.

[0067] In some embodiments, the driver information or passenger information may include the driver's or passenger's historical records, the driver's or passenger's personal information, and the driver's or passenger's customized requirements for services. In some embodiments, the driver's or passenger's historical records may be the driver's or passenger's operating behavior on the platform. In some embodiments, the driver's or passenger's operating behavior on the platform may include the driver's or passenger's frequency of canceling orders, the timing of canceling orders, modifying orders, and other operations within a certain time range. For example, the frequency with which a passenger or driver cancels an order within a day, or the frequency with which a driver cancels an order after continuously grabbing an order within 10 minutes. In some embodiments, the driver's or passenger's historical records may also be the number of completed orders or the total number of completed orders by the driver or passenger within a certain time range. For example, the number of orders completed by a passenger or driver within a month.

[0068] In some embodiments, the personal information of the driver or passenger may include the gender of the driver or passenger, the registration time of the driver or passenger, the confidence of the driver or passenger's address, the confidence of the driver or passenger's workplace, the loan status of the driver or passenger, the education level of the driver or passenger, the number of complaints against the driver or passenger within a certain time range, and the evaluation of the driver or passenger within a certain time range. In some embodiments, the confidence of the driver or passenger's address and the confidence of the driver or passenger's workplace can be determined based on the confidence of the user's frequently visited places.

[0069] In some embodiments, the loan situation may include but is not limited to the number of loans, the amount of loans, the loan period, and the repayment situation. In some embodiments, the first acquisition module 310 may acquire the driver's or passenger's loan situation from a third-party database. The third-party database includes but is not limited to a bank database, a social security agency database, and a credit assessment agency database.

[0070] In some embodiments, the education level can be represented by a discrete value. For example, primary school education is represented by 0, junior high school education is represented by 1, high school education is represented by 2, and undergraduate education and above is represented by 3. In some embodiments, the education level can be represented by a binary value. For example, if the education level is above undergraduate, the education level is represented by 1, and if it is below undergraduate, the education level is represented by 0.

[0071] In some embodiments, the personal information of the driver or passenger may include the number of complaints against the driver or passenger within a certain time frame and / or the evaluation of the driver or passenger within a certain time frame. For example, the number of complaints against the driver or passenger within a month can be counted. In some embodiments, drivers or passengers can evaluate each other, with a full score of five stars and a minimum score of no stars or one star; or they can directly give good or bad reviews to evaluate each other. For example, the number of bad reviews received by the driver or passenger in a month, the number of good reviews received by the driver or passenger, or the number of orders with one-star reviews and the number of orders with five-star reviews can be counted in a month.

[0072] In some embodiments, the customized requirements of the driver or passenger for the service may include the customized requirements of the passenger for the service tool or the driver, and may also include the customized requirements of the driver or passenger for each other. For example, the passenger's requirements for the driver's gender, the number of good reviews for the driver, the brand of the vehicle, the model of the vehicle, or the price of the vehicle. Another example is the driver's or passenger's requirements for the other party's personal habits (e.g., not smoking).

[0073] In some embodiments, the weather information may include temperature, humidity, weather conditions (e.g., sunny, rainy, or cloudy), and air quality. In some embodiments, the order time may include an order time and an order execution time. In some embodiments, the order time may be the time when the service request order is submitted to the server, and the order execution time may be the time when the passenger gets on the bus. For example, the passenger's order time is 7:00 am, and the order execution time is 9:00 am.

[0074] In some embodiments, the regional information may include the province, city, district, street name and road name. In some embodiments, the path information and intersection information may include the route information of the historical order corresponding to the path information and intersection information, for example, the road Link and Node passed by the path. In some embodiments, the topological structure of the road in the electronic map is composed of line segments. Link is the basic unit of the road model in the electronic map, which can represent a section of road; Node represents the intersection of roads and roads, and Node and Link can be used to represent the topological structure of the entire road; the road model in the electronic map is directional, and the road model is similar to a mesh structure. The number corresponding to the road Link is the road ID.

[0075] In some embodiments, the historical order data may be stored in the storage device 130. In some embodiments, the first acquisition module 310 may acquire the historical order data from the storage device 130.

[0076] In step 520 , geographical information associated with the historical order data may be queried based on the historical order data to obtain geographical information corresponding to the historical order data. Specifically, step 520 may be performed by the first query module 320 .

[0077] In some embodiments, the geographic information corresponding to the historical order data may include road information and traffic information. In some embodiments, querying the geographic information associated with the historical order data based on the historical order data may include querying the road information in the road network database based on the road ID in the historical order data to obtain the road information corresponding to the historical order data. In some embodiments, the road network database may store road information such as road ID, road width, and road length. In some embodiments, the road information may include road attributes and / or intersection attributes, and the road information may come from surveying and mapping data. In some specific embodiments, such as Figure 7 As shown, the road attributes may include one or more of the following: map sheet ID, road ID, road width, road length, road grade, number of road grades, travel direction, and toll setting. Figure 8 As shown, intersection attributes may include one or more of map sheet ID, road ID, intersection level, number of intersection levels, intersection identification, traffic light information, intersection connection link number, intersection main point number, intersection sub-point number, adjacent point map sheet ID, adjacent point number, and connection link number.

[0078] In some embodiments, querying geographic information associated with the historical order data based on the historical order data may also include querying the traffic information in the traffic database based on the road ID in the historical order data to obtain the traffic information corresponding to the historical order data. In some embodiments, the traffic database may store information such as the road ID, road travel time, and traffic light waiting time. In some embodiments, the traffic information includes one or more of the road travel speed, road travel time, and traffic light waiting time. In some embodiments, the traffic information in the traffic database may be obtained through other historical order statistics or through model training, and the present application does not limit this.

[0079] In some embodiments, the historical order data and the geographic information may be heterogeneous data. Heterogeneous data refers to data sources having different encoding formats, for example, the historical order data may be in binary encoding format, and the geographic information may be in text encoding format.

[0080] In some embodiments, the road information and traffic information may be stored in the storage device 130, and the first query module 320 may obtain the data to perform feature extraction.

[0081] In step 530 , the historical order data and the geographic information corresponding to the historical order data may be spliced ​​to obtain order samples containing geographic information features. Specifically, step 530 may be performed by the first splicing module 330 .

[0082] In some embodiments, the order sample containing the geographic information feature may be a geographic information feature code. Fig. 9 As shown, the geographic information feature encoding may include three parts. Specifically, the first part of the geographic information feature encoding format (also referred to as part 1) may encode the data header starting with the road ID in the historical order data; the second part of the geographic information feature encoding format (also referred to as part 2) may encode the road information corresponding to the historical order data, such as road attributes and intersection attributes; the third part of the geographic information feature encoding format (also referred to as part 3) may encode the traffic information corresponding to the historical order data, such as road travel speed, road travel time, traffic light waiting time, etc. It should be noted that the three parts of the geographic information feature encoding are provided for illustration only, and the format of the geographic information feature encoding may include any number of parts. For example, the second part may be divided into two independent parts.

[0083] In some embodiments, the above parts in the geographic information feature code can be placed in a predetermined order. The predetermined order can be the order from part 1 to part 3 (e.g., part 1, part 2, part 3). Alternatively, except for part 1, the other two parts of the geographic information feature code can be randomly arranged (e.g., part 1, part 3, part 2).

[0084] In some embodiments, the first splicing module 330 may splice the data of the above-mentioned parts 1 to 3 to obtain an order sample containing geographic information features. In some embodiments, the encoding form of the order sample containing geographic information features may include one or more of binary encoding, text encoding, HTML5 and ASCII encoding. By splicing the historical order data with the corresponding geographic information (wherein the historical order data and the geographic information data may be heterogeneous data), different encoding forms are output, which can be used as feature samples for different models or platforms.

[0085] In some embodiments, step 540 may be further included, where if the road ID in the road information is not included in the historical order data, the road ID in the historical order data is updated. Specifically, step 540 may be performed by the updating module 340 .

[0086] In some embodiments, the road information is updated due to surveying and other reasons, and the road ID in the road information may not be included in the historical order data. Specifically, if the road ID of road M is not included in the historical order data (e.g., the road ID is "null"), the geographic information associated with the historical order data cannot be queried through the method of steps 510 to 530. At this time, the path of road M in the historical order data or the GPS point of the intersection can be used to query the geographic information associated with the historical order data. If the queried geographic information contains the road ID of road M (e.g., 0018), the road ID of road M in the historical order data is updated to 0018. If the historical order data already contains another road N with a road ID of 0018, it is sequentially numbered as the last digit in the historical order data. For example, if the current last digit in the historical order data is numbered 0250, road M is numbered 0251. By updating the road ID in the historical order data, calculation errors caused by coding misalignment can be avoided.

[0087] It should be noted that the above description of process 500 is only for example and explanation, and does not limit the scope of application of the present application. For those skilled in the art, various modifications and changes can be made to process 500 under the guidance of the present application. However, these modifications and changes are still within the scope of the present application. For example, step 520 can be divided into two steps, the first query module 320 can first query the road information in the road network database, and then query the traffic information in the traffic database; the first query module 320 can also first query the traffic information in the traffic database, and then query the road information in the road network database.

[0088] Figure 6 is an exemplary flow chart of a geographic information feature extraction method according to another embodiment of the present application. In some embodiments, process 600 may be executed by processing logic, which may include hardware (e.g., circuits, dedicated logic, programmable logic, microcode, etc.), software (instructions running on a processing device to perform hardware simulation), etc., or any combination thereof. Figure 6 One or more operations in the process 600 for extracting geographic information features can be performed by Figure 1 For example, the process 600 may be stored in the storage device 150 in the form of instructions and called and / or executed by the processing engine 112 (for example, Figure 2 220 of the computing device 200 shown).

[0089] In step 610 , current order data is obtained. Specifically, step 610 may be performed by the second obtaining module 410 .

[0090] In some embodiments, real-time orders may include online car-hailing service orders (e.g., taxi orders, express orders, carpooling orders, ride-sharing orders, and bus orders, etc.). In some embodiments, current order data may include data related to real-time orders. Specifically, current order data may include a road ID and one or more of the following: driver information, passenger information, weather, order time, area information, path information, and intersection information. More descriptions of order data may be found elsewhere in this application (e.g., process flow). Figure 5 and its related descriptions) and will not be described here.

[0091] In some embodiments, the current order data may be stored in the storage device 130 , and the second acquisition module 410 may acquire the current order data from the storage device 130 .

[0092] In step 620 , the geographic information associated with the current order data may be queried based on the current order data to obtain the geographic information corresponding to the current order data. Specifically, step 610 may be performed by the second query module 420 .

[0093] In some embodiments, the geographic information corresponding to the current order data may include road information and traffic information. In some embodiments, querying the geographic information associated with the current order data based on the current order data may include querying the road information in the road network database based on the road ID in the current order data to obtain the road information corresponding to the current order data. In some embodiments, the road network database may store road information such as road ID, road width, and road length. In some embodiments, querying the geographic information associated with the current order data based on the current order data may also include querying the traffic information in the traffic database based on the road ID in the current order data to obtain the traffic information corresponding to the current order data. In some embodiments, the traffic database may store information such as road ID, road travel time, and traffic light waiting time.

[0094] In some embodiments, the current order data and the geographic information may be heterogeneous data. Heterogeneous data refers to data sources having different encoding forms, for example, the current order data may be in binary encoding form, and the geographic information may be in text encoding form.

[0095] More description of querying geographic information can be found elsewhere in this application (such as the process Figure 5 In some embodiments, the road information and traffic information may be stored in the storage device 130, and the second query module 420 may obtain the data to perform feature extraction.

[0096] In step 630 , the current order data and the geographic information corresponding to the current order data may be spliced ​​to obtain a real-time order sample containing geographic information features. Specifically, step 630 may be performed by the second splicing module 430 .

[0097] In some embodiments, the real-time order sample containing geographic information features may be a geographic information feature code. Specifically, the geographic information feature code may include three parts. More descriptions of the geographic information feature code may be found elsewhere in this application (e.g., flow chart). Figure 5 and its related descriptions) and will not be described here.

[0098] In some embodiments, the second splicing module 430 may splice the geographic information with the current order data to obtain a real-time order sample containing geographic information features. In some embodiments, the encoding form of the real-time order sample containing geographic information features may include one or more of binary encoding, text encoding, HTML5 and ASCII encoding. By splicing the current order data with the corresponding geographic information (wherein the current order data and the geographic information data may be heterogeneous data), different encoding forms are output, which can be used as feature samples for different models or platforms.

[0099] The beneficial effects that may be brought about by the embodiments of the present application include but are not limited to: (1) By associating heterogeneous data from different data sources with order data, geographic information can be extracted conveniently and quickly, solving the time delay problem caused by querying and calling multiple dimensional data together; (2) By outputting multiple encoding forms, it can be applied to different models or platforms, improving the portability of data; (3) The road ID in the order data can be updated to avoid calculation errors caused by encoding misalignment. It should be noted that different embodiments may produce different beneficial effects. In different embodiments, the beneficial effects that may be produced may be any one or a combination of the above, or any other possible beneficial effects.

[0100] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of the present application. Although not explicitly stated herein, those skilled in the art may make various modifications, improvements and amendments to the present application. Such modifications, improvements and amendments are suggested in the present application, so such modifications, improvements and amendments still belong to the spirit and scope of the exemplary embodiments of the present application.

[0101] At the same time, the present application uses specific words to describe the embodiments of the present application. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of the present application. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, some features, structures or characteristics in one or more embodiments of the present application can be appropriately combined.

[0102] In addition, it will be understood by those skilled in the art that various aspects of the present application may be illustrated and described by a number of patentable categories or situations, including any new and useful process, machine, product or combination of substances, or any new and useful improvements thereto. Accordingly, various aspects of the present application may be performed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above hardware or software may be referred to as "data blocks", "modules", "engines", "units", "components" or "systems". In addition, various aspects of the present application may be represented as a computer product located in one or more computer-readable media, which includes computer-readable program code.

[0103] A computer storage medium may include a propagated data signal containing computer program code, for example, in baseband or as part of a carrier wave. The propagated signal may be in a variety of forms, including electromagnetic, optical, etc., or a suitable combination. A computer storage medium may be any computer-readable medium other than a computer-readable storage medium, which can be connected to an instruction execution system, device or apparatus to communicate, propagate or transmit the program for use. The program code on the computer storage medium may be transmitted via any suitable medium, including radio, cable, fiber optic cable, RF, or similar media, or any combination of the above media.

[0104] The computer program codes required for the operation of each part of the present application can be written in any one or more programming languages, including object-oriented programming languages ​​such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB.NET, Python, etc., conventional procedural programming languages ​​such as C language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages ​​such as Python, Ruby and Groovy, or other programming languages, etc. The program code can be run entirely on the user's computer, or run on the user's computer as an independent software package, or run partially on the user's computer and partially on a remote computer, or run entirely on a remote computer or server. In the latter case, the remote computer can be connected to the user's computer through any network form, such as a local area network (LAN) or a wide area network (WAN), or connected to an external computer (e.g., via the Internet), or in a cloud computing environment, or used as a service such as software as a service (SaaS).

[0105] In addition, unless explicitly stated in the claims, the order of the processing elements and sequences described in this application, the use of alphanumeric characters, or the use of other names are not intended to limit the order of the processes and methods of this application. Although the above disclosure discusses some invention embodiments that are currently considered useful through various examples, it should be understood that such details are only for illustrative purposes, and the attached claims are not limited to the disclosed embodiments. On the contrary, the claims are intended to cover all modifications and equivalent combinations that are consistent with the essence and scope of the embodiments of this application. For example, although the system components described above can be implemented by hardware devices, they can also be implemented only by software solutions, such as installing the described system on an existing server or mobile device.

[0106] Similarly, it should be noted that in order to simplify the description of the disclosure of this application and thus help understand one or more embodiments of the invention, in the above description of the embodiments of this application, multiple features are sometimes combined into one embodiment, figure or description thereof. However, this disclosure method does not mean that the features required by the object of this application are more than the features mentioned in the claims. In fact, the features of the embodiments are less than all the features of the single embodiment disclosed above.

[0107] In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used for the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which can be changed according to the required features of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the method of general digit retention. Although the numerical domains and parameters used to confirm the breadth of the range in some embodiments of the present application are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0108] Each patent, patent application, patent application disclosure, and other materials, such as articles, books, instructions, publications, documents, etc., cited in this application is hereby incorporated by reference in its entirety. Except for application history documents that are inconsistent with or conflicting with the content of this application, documents that limit the broadest scope of the claims of this application (currently or later attached to this application) are also excluded. It should be noted that if the description, definition, and / or use of terms in the attached materials of this application are inconsistent or conflicting with the content described in this application, the description, definition, and / or use of terms in this application shall prevail.

[0109] Finally, it should be understood that the embodiments described in this application are only used to illustrate the principles of the embodiments of the present application. Other variations may also fall within the scope of the present application. Therefore, as an example and not a limitation, the alternative configurations of the embodiments of the present application may be considered to be consistent with the teachings of the present application. Accordingly, the embodiments of the present application are not limited to the embodiments explicitly introduced and described in the present application.

Claims

1. A method for extracting geographic information features, characterized in that: The method comprises: Acquire historical order data; the historical order data includes a road ID; Based on the historical order data, query the geographic information associated with the historical order data to obtain the geographic information corresponding to the historical order data; the geographic information includes road information corresponding to the road ID; Joining the historical order data with the geographic information corresponding to the historical order data to obtain an order sample containing geographic information features; In response to the road information being updated, determining whether a road ID of a road M in the updated road information is included in the historical order data; and In response to determining that the road ID of the road M in the updated road information is not included in the historical order data, the road ID in the historical order data is updated.

2. The method according to claim 1, characterized in that The historical order data further includes at least one of the following: Driver information, passenger information, weather information, order time, area information, route information and intersection information.

3. The method according to claim 2, characterized in that The querying of the geographic information associated with the historical order data based on the historical order data to obtain the geographic information corresponding to the historical order data includes: Based on the road ID in the historical order data, query the road information in the road network database to obtain the road information corresponding to the historical order data; Based on the road ID in the historical order data, query the traffic information in the traffic database to obtain the traffic information corresponding to the historical order data; The road network database at least stores information on road width and road length, and the traffic database at least stores information on road travel time and traffic light waiting time.

4. The method according to claim 3, characterized in that The road information includes road attributes and / or intersection attributes.

5. The method according to claim 4, characterized in that The road attributes include at least one of road ID, road width, road length, road grade, travel direction and charging settings.

6. The method according to claim 4, characterized in that The intersection attribute includes at least one of an intersection sign and traffic light information.

7. The method according to claim 3, characterized in that The traffic information includes at least one of road travel speed, road travel time, and traffic light waiting time.

8. The method according to claim 1, characterized in that The updating of the road ID in the historical order data includes: Based on the GPS of the path or intersection of road M, the geographic information associated with the historical order data is queried, and the road ID of the queried geographic information is updated to the road ID of road M.

9. The method according to claim 1, characterized in that The encoding form of the order sample containing geographic information features includes at least one of binary encoding, text encoding, HTML5 and ASCII encoding.

10. The method according to claim 1, characterized in that The historical order data and the geographic information are heterogeneous data.

11. A geographic information feature extraction system, characterized in that: It includes a first acquisition module, a first query module, a first splicing module and an update module; wherein: The first acquisition module is used to acquire historical order data; the historical order data includes a road ID; The first query module is used to query the geographic information associated with the historical order data based on the historical order data to obtain the geographic information corresponding to the historical order data; the geographic information includes road information corresponding to the road ID; The first splicing module is used to splice the historical order data with the geographic information corresponding to the historical order data to obtain an order sample containing geographic information features; The update module is used to In response to the road information being updated, determining whether a road ID of a road M in the updated road information is included in the historical order data; In response to determining that the road ID of the road M in the updated road information is not included in the historical order data, the road ID in the historical order data is updated.

12. The system according to claim 11, characterized in that The historical order data includes at least one of the following: Driver information, passenger information, weather information, order time, area information, route information and intersection information.

13. The system of claim 12, wherein: The first query module includes a road information query unit and a traffic information query unit; wherein: The road information query unit is used to query the road information in the road network database based on the road ID in the historical order data to obtain the road information corresponding to the historical order data; The traffic information query unit is used to query the traffic information in the traffic database based on the road ID in the historical order data to obtain the traffic information corresponding to the historical order data; The road network database at least stores information on road width and road length, and the traffic database at least stores information on road travel time and traffic light waiting time.

14. The system of claim 13, wherein: The road information includes road attributes and / or intersection attributes.

15. The system of claim 14, wherein: The road attributes include at least one of road ID, road width, road length, road grade, travel direction and charging settings.

16. The system of claim 14, wherein: The intersection attribute includes at least one of an intersection sign and traffic light information.

17. The system of claim 13, wherein: The traffic information includes at least one of road travel speed, road travel time, and traffic light waiting time.

18. The system of claim 11, wherein: The update module is used to: Based on the GPS of the path or intersection of road M, the geographic information associated with the historical order data is queried, and the road ID of the queried geographic information is updated to the road ID of road M.

19. The system of claim 11, wherein: The encoding form of the order sample containing geographic information features includes at least one of binary encoding, text encoding, HTML5 and ASCII encoding.

20. The system of claim 11, wherein: The historical order data and the geographic information are heterogeneous data.

21. A method for extracting geographic information features, characterized in that: The method comprises: Acquire current order data; the current order data includes a road ID; Based on the current order data, query the geographic information associated with the current order data to obtain the geographic information corresponding to the current order data; the geographic information includes the road information corresponding to the road ID; Joining the current order data with the geographic information corresponding to the current order data to obtain a current order sample containing geographic information features; In response to the road information being updated, determining whether a road ID of a road M in the updated road information is included in the current order data; and In response to determining that the road ID of the road M in the updated road information is not included in the current order data, the road ID in the current order data is updated.

22. A geographic information feature extraction system, characterized in that: It includes a second acquisition module, a second query module, a second splicing module and an update module; wherein: The second acquisition module is used to acquire current order data; the current order data includes a road ID; The second query module is used to query the geographic information associated with the current order data based on the current order data to obtain the geographic information corresponding to the current order data; the geographic information includes road information corresponding to the road ID; The second splicing module is used to splice the current order data with the geographic information corresponding to the current order data to obtain a current order sample containing geographic information features; The update module is used to In response to the road information being updated, determining whether a road ID of a road M in the updated road information is included in the current order data; In response to determining that the road ID of the road M in the updated road information is not included in the current order data, the road ID in the current order data is updated.

23. A geographic information feature extraction device, characterized in that: The apparatus comprises at least one processor and at least one storage device, wherein the storage device is used to store instructions. When the at least one processor executes the instructions, the method according to any one of claims 1 to 10 or 21 is implemented.

24. A computer-readable storage medium, wherein the storage medium stores computer instructions. When a computer reads the computer instructions in the storage medium, the computer executes the method according to any one of claims 1 to 10 or 21.

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