CN112269925B

CN112269925B - Method and device for obtaining geographic position point information

Info

Publication number: CN112269925B
Application number: CN202011117316.0A
Authority: CN
Inventors: 黄际洲; 张昊
Original assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Current assignee: Beijing Baidu Netcom Science and Technology Co Ltd
Priority date: 2020-10-19
Filing date: 2020-10-19
Publication date: 2024-03-22
Anticipated expiration: 2040-10-19
Also published as: CN112269925A

Abstract

The application discloses a method and a device for acquiring geographic position point information, and relates to the technical field of big data. The specific implementation scheme is as follows: acquiring a newly generated spatial relationship list, wherein the spatial relationship list comprises more than one piece of spatial relationship data, and the spatial relationship data comprises spatial relationship information between two adjacent geographic position points; concatenating the spatial relationship data in the spatial relationship list to obtain at least one concatenated set; if at least one spatial relationship data exists in the existing knowledge base in the series set, writing the spatial relationship data in the series set into the knowledge base; and analyzing the geographic position points contained in the spatial relationship data of the newly written knowledge base to obtain geographic position point information contained in the spatial relationship data of the newly written knowledge base. The method and the device can realize automatic discovery of the changed geographic position point information.

Description

Method and device for obtaining geographic position point information

Technical Field

The application relates to the technical field of computer application, in particular to a method and a device for acquiring geographic position point information in the technical field of big data.

Background

The main goal of map products is to describe the real world, thereby helping users to inquire the information of geographic location points and further meeting various travel demands. However, information of geographical location points in reality may be changed for various reasons. If the information of the geographical position points acquired by the map-type product is inaccurate, the user cannot find the destination as required.

The current method for acquiring the geographic position point information commonly used in the industry adopts mass source acquisition and manual verification. The method relies on information of geographical location points reported by various channels, such as shop reports, user uploads, internet informations and the like, and then manually audits and takes effect online based on various information by internal staff familiar with the business. However, this method relies heavily on manpower, which brings problems of low efficiency, untimely information update, low coverage, and the like.

Disclosure of Invention

In view of this, the present application provides a method and apparatus for obtaining geographic location point information, so as to implement automatic discovery of geographic location point information.

In a first aspect, the present application provides a method for obtaining geographic location point information, including:

Acquiring a newly generated spatial relationship list, wherein the spatial relationship list comprises more than one piece of spatial relationship data, and the spatial relationship data comprises spatial relationship information between two geographic position points;

concatenating the spatial relationship data in the spatial relationship list to obtain at least one concatenated set;

if at least one spatial relationship data exists in the existing knowledge base in the series set, writing the spatial relationship data in the series set into the knowledge base;

and analyzing the geographic position points contained in the spatial relationship data of the newly written knowledge base to obtain geographic position point information contained in the spatial relationship data of the newly written knowledge base.

In a second aspect, the present application provides an apparatus for obtaining geographic location point information, including:

the system comprises a spatial relationship acquisition unit, a storage unit and a storage unit, wherein the spatial relationship acquisition unit is used for acquiring a newly generated spatial relationship list, the spatial relationship list comprises more than one piece of spatial relationship data, and the spatial relationship data comprises spatial relationship information between two geographic position points;

the spatial relation serial connection unit is used for connecting the spatial relation data in the spatial relation list in series to obtain at least one serial collection;

The knowledge base processing unit is used for writing the spatial relationship data in the serial set into the knowledge base if at least one spatial relationship data in the serial set exists in the existing knowledge base;

and the information generating unit is used for analyzing the geographic position points contained in the spatial relationship data of the newly written knowledge base to obtain geographic position point information contained in the spatial relationship data of the newly written knowledge base.

In a third aspect, the present application provides an electronic device, including:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method described above.

In a fourth aspect, the present application provides a non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the above-described method.

In a fifth aspect, the present application also provides a computer program product comprising a computer program which, when executed by a processor, implements a method according to any of the preceding claims.

Through the above-mentioned technical scheme that this application provided, can realize the automatic discovery of geographical position point information, greatly reduced to the dependence of manpower, improved efficiency and reduced the human cost.

Other effects of the above alternative will be described below in connection with specific embodiments.

Drawings

The drawings are for better understanding of the present solution and do not constitute a limitation of the present application. Wherein:

FIG. 1 illustrates an exemplary system architecture in which methods or apparatus of embodiments of the present application may be applied;

FIG. 2 is a flow chart of a main method provided in an embodiment of the present application;

FIG. 3 is a flowchart of a detailed method according to an embodiment of the present application;

FIG. 4 is a flowchart of a method for generating a spatial relationship list according to an embodiment of the present application;

fig. 5 is a schematic diagram of calculating coordinates of a geographic location point by using shooting parameters according to an embodiment of the present application;

FIG. 6 is a flowchart of another method for generating a spatial relationship list according to an embodiment of the present application;

FIG. 7 is a schematic structural diagram of a geographic location point spatial relationship extraction model according to an embodiment of the present application;

FIG. 8 is a block diagram of an apparatus according to an embodiment of the present application;

fig. 9 is a block diagram of an electronic device used to implement an embodiment of the present application.

Detailed Description

Exemplary embodiments of the present application are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present application to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

FIG. 1 illustrates an exemplary system architecture in which the methods or apparatus of embodiments of the present application may be applied. As shown in fig. 1, the system architecture may include terminal devices 101 and 102, a network 103, and a server 104. The network 103 is the medium used to provide communication links between the terminal devices 101, 102 and the server 104. The network 103 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.

A user may interact with server 104 through network 103 using terminal devices 101 and 102. Various applications, such as a map-type application, a web browser application, a communication-type application, and the like, may be installed on the terminal devices 101 and 102.

The terminal devices 101 and 102 may be various types of user devices capable of running map-type applications. Including but not limited to smartphones, tablets, PCs, smart televisions, and the like. The device for acquiring the geographic location point information provided by the application can be set and run in the server 104, or can be run in a device independent of the server 104. Which may be implemented as multiple software or software modules (e.g., to provide distributed services), or as a single software or software module, without limitation. The server 104 may interact with the map database 105, and in particular, the server 104 may obtain data from the map database 105, or may store data in the map database 105. The map database 105 stores therein relevant data including geographical location points, such as status, coordinate information, and the like.

For example, the device for acquiring the geographic location point information is set and operated in the server 104, and the server 104 acquires the geographic location point information by adopting the method provided in the embodiment of the present application, and then updates the map database 105 by using the acquired geographic location point information. The server 104 is capable of querying the map database 105 in response to a query request from the terminal device 101, 102, and returning to the terminal device 101, 102 related information of the queried geographical location point, including the state of the geographical location point, coordinate information, route query information based on the geographical location point information, navigation information, and the like.

The server 104 may be a single server or a server group composed of a plurality of servers. In addition, 104 may be other computer systems or processors with higher computing capabilities, in addition to being in the form of servers. It should be understood that the number of terminal devices, networks, servers and databases in fig. 1 are merely illustrative. There may be any number of terminal devices, networks, servers, and databases, as desired for implementation.

The geographic location point referred to in the present application refers to a geographic location point in a map application, where the geographic location point may be used for a user to query, browse, display to the user, and the like. These geographic location points have basic attributes of coordinates (e.g., latitude and longitude), name, administrative address, type, status, etc. Wherein the geographic location points may include, but are not limited to, POI (Point Of Interest, points of Interest), AOI (Area of Interest), ROI (Regin of Interest, region of Interest), etc. In the following embodiments, POI is taken as an example. POIs are a term in geographic information systems that generally refers to everything that can be abstracted into points, a POI can be a house, a business, a post, a bus stop, a school, a hospital, etc. The main purpose of POIs is to describe the location of things or events, thereby enhancing the descriptive and querying capabilities of the location of things or events.

Fig. 2 is a flow chart of a main method provided in an embodiment of the present application, and as shown in fig. 2, the method may include the following steps:

in 201, a newly generated list of spatial relationships is obtained.

The newly generated spatial relationship list is obtained by extracting spatial relationship information between geographic position points from at least one of a live-action image acquired by a professional, a live-action image acquired by a crowd source and internet text.

The acquired spatial relationship list comprises more than one spatial relationship data, and the spatial relationship data comprises spatial relationship information between two geographic position points. As a preferred embodiment, the spatial relationship data may comprise spatial relationship information between two adjacent geographical location points.

For example, the spatial relationship data may be represented in the form of four tuples, where the four tuples r= < S, O, P, a >, where S and O are information of the geographic location point, for example, a unique ID of the geographic location point may be used, P is a spatial relationship type, and a is a spatial relationship value.

The types of spatial relationships mainly include some azimuthal spatial relationship types such as east, south, west, north, southeast, northeast, southwest, northwest, left, right, upstairs, downstairs, and the like. The values may include a distance value, a floor value, and so on. For example, the quadruple < Qinghua technical garden, south east gate, south, 100 meters of Qinghua university > means "Qinghua technical garden is 100 meters south east gate of Qinghua university".

At 202, the spatial relationship data in the newly generated list of spatial relationships is concatenated to obtain at least one concatenated set.

In this step, when the spatial relationship data are concatenated, if two spatial relationship data contain a same geographic location point, the two spatial relationship data may be concatenated, and so on, and a plurality of spatial relationship data may be concatenated to form a concatenated set. If one spatial relationship data cannot be connected in series with other spatial relationship data in the newly generated spatial relationship list, the spatial relationship data forms a series set.

For example, assume that the newly generated list of spatial relationships contains the following quaternion:

<S,O,P,A>、<S1,S,P1,A1>、<O,O1,P2,A2>、<S2,O2,P3,A3>

then, < S, O, P, A >, < S1, S, P1, A1>, < O, O1, P2, A2> constitute a series set; < S2, O2, P3, A3> constitutes a series set.

If at least one spatial relationship data exists in the existing knowledge base in the series, the spatial relationship data in the series is written into the knowledge base 203.

In the embodiment of the application, the spatial relationship data is stored in the knowledge base, and the trusted spatial relationship data determined each time is stored as the spatial relationship data. For a concatenated set of newly generated lists of spatial relationships, if at least one spatial relationship data exists in an existing knowledge base, then it is stated that the at least one spatial relationship is trusted. Each spatial relationship in the series set is in series connection with the trusted spatial relationship, so that the spatial relationship data in the series set can be considered to be trusted and written into the knowledge base.

In 204, the geographical location points included in the spatial relationship data of the newly written knowledge base are analyzed to obtain geographical location point information included in the spatial relationship data of the newly written knowledge base.

The geographical location point information obtained in this step may include coordinate information of the geographical location point and/or status information of the geographical location point. Wherein the status information is mainly represented by changes of geographic location points, such as addition, closing, change, and the like.

As a preferred embodiment, the coordinate information of other geographical location points in the spatial relationship data of the newly written knowledge base is obtained by using the known coordinate information of at least one geographical location point contained in the spatial relationship data of the newly written knowledge base. The known coordinate information can be obtained from the geographic database or from a live-action image acquired by a professional.

As a preferred implementation manner, the spatial relationship data newly written into the knowledge base can be compared with the spatial relationship data of the existing knowledge base to obtain the geographic position point state information of the region corresponding to the spatial relationship data newly written into the knowledge base.

In this embodiment of the present application, the map database may store information about the geographic location points, so that the information about each geographic location point determined in this step is also stored in the geographic database.

It can be seen that the application can realize the automatic discovery of the geographic position point information by utilizing the newly generated spatial relationship data for processing, greatly reduces the dependence on manpower, improves the efficiency and reduces the manpower cost.

The traditional method relies on manual reporting of the geographical position point information and manual auditing, timeliness and information coverage rate are completely dependent on manually collected content, and the method provided by the application determines the geographical position information based on spatial relationship data, so that timeliness and information coverage rate are remarkably improved.

The traditional mode of manually reporting the geographical position point information and manually auditing the geographical position point information can cause inaccuracy of the geographical position point information due to errors of user behaviors, errors of user equipment and the like, and the mode provided by the application reduces the dependence on the user behaviors and the user equipment and improves the accuracy of the geographical position point information.

Fig. 3 is a flowchart of a detailed method provided in an embodiment of the present application, and as shown in fig. 3, the method may include the following steps:

in 301, spatial relationship information between adjacent geographic location points is extracted from at least one of a professionally acquired live-action image, a crowd-sourced acquired live-action image, and internet text, resulting in a newly generated spatial relationship list.

The preferred implementation of the extraction of spatial relationship information between adjacent geographical location points involved in this step will be described in detail in the following examples.

At 302, spatial relationship data in a newly generated list of spatial relationships is concatenated to obtain at least one concatenated set.

The step is the same as step 202 in the second embodiment, and will not be described here.

The following steps are then performed for each series set separately:

in 303, determining whether at least one spatial relationship data exists in the current concatenated set in the existing knowledge base, and if so, executing 304; otherwise, execution 306 proceeds.

As a preferred embodiment, the geographical location area may be divided into cells in advance before performing this step, with overlapping areas between adjacent cells. The spatial relationship data in the knowledge base is pre-corresponding to at least one cell according to the geographic location of the included geographic location points.

Since positioning accuracy may reach errors of more than hundred meters, a geographical location area may be divided into cells such as 1km x 1km with some overlap between adjacent cells, e.g. 0.5 km. Therefore, the coordinate of any geographic position point falls in the range of the cell, and the problem that adjacent geographic position points cannot fall in the same cell due to the fact that the geographic position points are positioned at the edges of the cell can be effectively avoided.

Each cell may be numbered and indexed using spatial relationship data corresponding to adjacent geographic location points whose coordinates fall within the cell. For example, a certain four-tuple data R _x It contains two geographical location points whose coordinates fall in the cell S _i Then consider the four-tuple data R _x Corresponding cell S _i 。

For any one spatial relation data, namely the quadruple, fuzzy coordinate information of two adjacent geographic position points contained in the data can be obtained. Because there is generally a problem of positioning accuracy about the coordinate information of the geographical location point collected by other devices except the professional device, in the embodiment of the present application, one positioning accuracy may be uniformly taken for the coordinate information of the geographical location point collected by the terminal device, for example, only the last bit of the decimal point is reserved, and the coordinate information is considered as fuzzy coordinate information. In the present application, when the positioning accuracy of the coordinate information is ambiguous, the corresponding determination may be performed according to the size adopted by the above-mentioned cells in the division.

As a preselected embodiment, this step may be performed separately for each spatial relationship data in the current series set as current spatial relationship data: determining the area grid of the geographic position point contained in the current spatial relationship data; inquiring current spatial relationship data in the spatial relationship data corresponding to the area lattice in the knowledge base, and if so, determining that the current spatial relationship data exists in the existing knowledge base; otherwise, determining that the current spatial relationship data does not exist in the existing knowledge base.

In the preferred embodiment provided in the present application, because the adjacent geographic location points included in the spatial relationship data are necessarily located in the same area grid, the current spatial relationship data can be queried in the spatial relationship data corresponding to the area grid in the knowledge base. When determining the cells to which the geographic position points included in the current spatial relationship belong, the cells to which the geographic position points included in the current spatial relationship belong can be determined according to the fuzzy coordinate information of the geographic position points included in the current spatial relationship.

At 304, the spatial relationship data in the concatenated set is written to a knowledge base.

In 305, it is determined whether there are more unprocessed series sets, and if so, proceed to execution 303 for the next series set, otherwise execute 308.

If a certain spatial relationship data in the concatenated set exists in the existing knowledge base, the spatial relationship data contained in the concatenated set can be considered correct because the spatial relationship data stored in the knowledge base is considered correct spatial relationship data and each spatial relationship data in the concatenated set is reasonably concatenated with the correct spatial relationship data, so that the spatial relationship data contained in the concatenated set can be considered correct and can be written into the knowledge base.

For example, in the newly generated spatial relationship data list, < S, O, P, A >, < S1, S, P1, A1>, < O, O1, P2, A2> form a series set, and if < O, O1, P2, A2> exists in the existing knowledge base, < S, O, P, A >, < S1, S, P1, A1>, < O, O1, P2, A2> is written into the knowledge base.

In 306, judging whether the current serial collection has spatial relationship data obtained by the professionally acquired live-action images, if so, executing 304; otherwise, 307 is performed.

If some spatial relationship data in the tandem set does not exist in the existing knowledge base, it can be further judged whether or not the live-action image acquired by the profession exists in the current tandem set. The live-action image acquired for the specialty is considered to be reliable and accurate in terms of equipment accuracy on personnel quality, so that if certain spatial relationship data in the current tandem set is obtained from the live-action image acquired for the specialty, the spatial relationship data can be considered to be correct, and each spatial relationship data in the tandem set is reasonably in tandem with the correct spatial relationship data, so that the spatial relationship data contained in the tandem set can be considered to be correct and can be written into a knowledge base.

In 307, the spatial relationship data in the concatenated set is written to the to-be-verified list and proceeds to execution 305.

If the spatial relationship data in the concatenated set does not exist in the existing knowledge base and the spatial relationship data resulting from the professionally acquired live-action images does not exist, the spatial relationship data in the concatenated set may be written into the to-be-verified list. And the professional acquisition team can be further notified, and information of each geographic position point of the corresponding area in the list to be verified is acquired and verified by the professional acquisition team later.

After all the serial sets are processed, the step 308 is executed, that is, the coordinate information of other geographic position points in the spatial relationship data of the newly written knowledge base is obtained by using the known coordinate information of at least one geographic position point contained in the spatial relationship data of the newly written knowledge base.

The above known coordinate information refers to accurate coordinate information whose positioning accuracy is higher than that of the above ambiguous coordinate information.

As a preferred embodiment, if the spatial relationship data newly written into the knowledge base includes spatial relationship data obtained from a live-action image acquired by a professional, coordinate information of a geographic location point carried by the live-action image acquired by the professional is utilized to calculate other geographic location points included in the spatial relationship data newly written into the knowledge base based on the spatial relationship, so as to obtain coordinate information of other geographic location points, and the coordinate information is written into the map database.

Because the spatial relationship data contains the spatial relationship information between two adjacent geographic position points, if the coordinate information of one geographic position point is known, the coordinate of the other geographic position point can be obtained by calculation based on the spatial relationship. The spatial relationship data newly written into the knowledge base has a serial relationship, so that the coordinate information of the geographic position point contained in the spatial relationship data newly written into the knowledge base can be obtained by calculating based on a plurality of spatial relationship data.

As another preferred embodiment, if the geographical location points included in the spatial relationship data of the newly written knowledge base have accurate coordinate information in the existing map database, the geographical location points having the accurate coordinate information are used to calculate other geographical location points included in the spatial relationship data of the newly written knowledge base based on the spatial relationship, so as to obtain the coordinate information of the other geographical location points, and the coordinate information is written into the map database.

In the embodiment of the application, geographic position points with known accurate coordinate information are stored in a map database, and the coordinate information in the map database is used when a map product is on line. If the spatial relationship data of the newly written knowledge base has accurate coordinate information of a certain geographic position point in the existing map database, and the spatial relationship data of the newly written knowledge base has serial relationship, the coordinate information of other geographic position points can be obtained based on the calculation of the spatial relationship.

The coordinate information of a batch of geographic position points can be obtained based on the step. In some scenarios, in addition to the coordinate information of the geographic location point, it is also necessary to know the state change of the geographic location point in time. Then further execution 309 may be performed, i.e. determining state change information for the geographical location point in the spatial relationship data of the newly written knowledge base.

In a preferred embodiment, if two adjacent geographic location points included in the spatial relationship data newly written into the knowledge base are not adjacent in the existing knowledge base, determining that the state of the geographic location point between the two adjacent geographic location points in the existing knowledge base is closed, and deleting the spatial relationship data including the geographic location point whose state is closed.

For example, if the spatial relationship data newly written into the knowledge base includes < S, O, P, A >, and the geographical location points S and O in the existing knowledge base are not adjacent, but exist < S, S4, P4, A4> and < S4, O, P5, A5>, then it is indicated that the geographical location point S4 is not already present, i.e., is in the off state. The knowledge base may be further deleted to contain S4 spatial relationship data.

As a preferred embodiment, if the coordinate information of the geographic position point a included in the spatial relationship data newly written into the knowledge base overlaps with the coordinate information of another geographic position point B in the existing map database, the state of the geographic position point B is determined to be changed, the state of the geographic position point a is newly added, and the spatial relationship data of the geographic position point whose state is changed is deleted from the knowledge base.

In a preferred embodiment, if the geographical location point included in the spatial relationship data newly written in the knowledge base does not exist in the existing map database, the state of the geographical location point is determined to be newly added.

For the specific manner of newly generating the spatial relationship list in steps 201 and 301 in the above embodiments, two embodiments are listed for the detailed description.

FIG. 4 is a flowchart of a method for generating a spatial relationship list according to an embodiment of the present application, as shown in FIG. 4, the method may include the following steps:

in 401, a signboard is identified on a live-action image acquired by each terminal device, and a geographic position point pair included in the live-action image is determined.

In the application, a real image obtained by shooting the geographic position points by the terminal equipment is utilized to determine the spatial relationship between the geographic position points. The live-action image obtained by shooting the geographic position point by the terminal equipment can be a live-action image acquired from a professional or a live-action image acquired from a public source.

After the live-action images acquired by the terminal devices are acquired, the live-action images can be identified, and the live-action images comprising at least two signs are screened out. And then, carrying out character recognition on the live-action image containing at least two signs, and determining geographic position point pairs contained in the live-action image. The pair of geographic location points referred to in this application is made up of two different geographic location points.

The live-action image refers to an image obtained by shooting a physical position point in the field by the terminal equipment. The live-action image used in the application needs to comprise at least two signs, so that the shooting parameters of the live-action image are used for determining the spatial relationship between the geographic position points corresponding to the two signs. The sign refers to a plate which is hung in front of a building door corresponding to a geographical location point and serves as a sign. Such as a store name sign hanging at a store entrance, a school name sign at a school entrance, etc.

In the identification of a signboard on a live-action image, a signboard identification model obtained by training in advance may be used. Firstly, the real image is divided into areas, and because the signboard in the real image is a closed area in general, the real image can be identified and divided into areas, a signboard judging model is input into the determined closed area, and a judging result of whether the closed area is the signboard area or not is output by the signboard judging model.

Wherein the signboard judging model is actually a classifying model, a plurality of live-action images can be collected in advance, a signboard area and a non-signboard area are marked in the live-action images and respectively used as positive and negative samples, and then the classifying model is trained to obtain the signboard judging model.

When character recognition of a signboard is carried out on a live-action image containing at least two signboards, geographic position point pairs contained in the live-action image are determined, the screened live-action images can be clustered based on the positioning distance between the live-action images to obtain more than one similar positioning cluster. And then clustering the images in the similar positioning clusters based on the content similarity to obtain more than one similar content cluster, so that the live-action images in the similar positioning clusters are close to each other in shooting position. And clustering the images in each similar positioning cluster based on the content similarity to obtain more than one similar content cluster. And then respectively judging the actual images in the similar content clusters to determine the signboard areas. And (3) carrying out ID (identification) uniqueness processing on the signboard area determined in each live-action image. And determining a signboard region ID sequence contained in each live-action image and acquiring a frequent item sequence from the signboard region ID sequence. And then carrying out character recognition on the signboard area corresponding to each ID in the frequent item sequence. For a live-action image containing a frequent item sequence, n-1 geographic position point pairs are selected from the frequent item sequence, a set formed by the n-1 geographic position point pairs contains geographic position points corresponding to all signboard IDs in the frequent item sequence, the sum of the signboard distances corresponding to each geographic position point pair in the live-action image is minimum, and n is the number of the signboards contained in the frequent item sequence.

In 402, at least two live-action images acquired by the same terminal device and including the same geographic location point pair are acquired.

After the geographic position point pairs of each live-action image are mined, the inverted index of the live-action image can be established by utilizing each geographic position point pair. The step can acquire the live-action images of the same geographic position point pair by searching the inverted index, but the acquired live-action images are required to be ensured to be acquired by the same terminal equipment, and the number of the live-action images is at least two.

In 403, the spatial relationship of the same geographic location point pair is determined using the shooting parameters of at least two live-action images.

The shooting parameters involved in this step mainly include:

1) The positioning coordinates of the live-action image are the coordinates of the shooting point for shooting the live-action image, and usually, when the terminal equipment shoots the image, the current positioning coordinates of the terminal equipment are obtained as the positioning coordinates of the shot image.

2) Shooting angles and shooting distances of signs of geographic position point pairs in live-action images.

Some live-action images have the above-mentioned shooting parameters because of the setting or function of the shooting device, and some live-action images do not have the above-mentioned shooting parameters. In the present application, only live-action images with the above-mentioned shooting parameters are acquired and utilized to determine the spatial relationship of the geographic location point pairs.

In the step, the shooting parameters of the live-action image are mainly utilized, and calculation is carried out based on geometric relations such as sine theorem and cosine theorem, so that coordinates of two geographic position points in the geographic position point pair are obtained; based on the coordinates of the two geographic location points, a spatial relationship of the two geographic location points is determined.

Taking fig. 5 as an example, assume that two live-action images shot by the same terminal device each include a geographic location point pair formed by a geographic location point M and a geographic location point N. The corresponding shooting position coordinates in the first live-action image are shooting points A, and included angles alpha and beta in the image can be determined by shooting angles. The corresponding shooting position coordinates in the second live-action image are shooting points B, and included angles gamma and delta in the image can be determined by shooting angles. The distance x between two shooting points can be obtained from the positioning coordinates of two live-action images.

According to the sine theorem, the distance P between the geographic position point M and the shooting point A and the distance Q between the geographic position point N and the shooting point A can be obtained:

according to the distance information, the included angle information and the positioning coordinates of the shooting points A and B, the coordinates of two geographic position points can be determined.

In addition, it should be noted that, since the same terminal device may capture more than two live-action images including the same geographic location point pair (M, N), in this manner, the coordinates of the geographic location points M and N may be determined by actually using the live-action images of two pairs. For this case, the coordinates of the geographic location point M may be obtained by processing the coordinates of the determined geographic location point M in such a manner as averaging, clustering, median, and the like. And in the same way, the coordinates of the geographic position point N are obtained after the determined coordinates of the geographic position point N are processed in modes such as averaging, clustering center obtaining, median obtaining and the like.

After the coordinates of the two geographic location points are obtained, the spatial relative position relationship, such as the relationship in the direction, the distance relationship and the like, of the two geographic location points can be determined.

The information about the spatial relationship involved in the embodiment of the present application may include: the type and value of the spatial relationship. The types of spatial relationships mainly include some azimuthal spatial relationship types such as east, south, west, north, southeast, northeast, southwest, northwest, left, right, upstairs, downstairs, and the like. The values may include a distance value, a floor value, and so on. It can be seen that the spatial relationship of the geographic location points is relative.

FIG. 6 is a flowchart of another method for generating a spatial relationship list according to an embodiment of the present application, as shown in FIG. 6, the method may include the following steps:

in 601, text containing geographic location point information is obtained from the Internet.

In the application, the text containing the information of the geographic location point can be obtained from a official network associated with the geographic location point, for example, the text of "six layers of five-color city shopping centers in the ocean floor Beijing-fished ocean lake area clear river" is obtained from the ocean floor fisher network, and the text of "200 meters in the south of the east door of the Qinghai university, the Beijing Qinghai garden branch ocean lake area clear science and technology park, the B layer of the science and technology building, and the like" is obtained from a salvintage bank.

In addition to the data sources described above, text containing geographic location point information may also be obtained from other data sources.

In 602, inputting the text into a pre-trained geographic position point spatial relationship extraction model, and obtaining information of spatial relationship output by the geographic position point spatial relationship extraction model; wherein the geographic location spatial relationship extraction model comprises an embedding layer, a transducer layer and a mapping layer.

The structure of the geographic location point spatial relationship extraction model referred to in the embodiments of the present application may be as shown in fig. 7, and the embedding layer may include a plurality of embedding layers.

First, for a text, which can be regarded as a sequence of at least one sentence, a separator [ CLS ] can be added before the text first]Increasing separators between statements [ SEP ]]Each character and separator acts as a Token, respectively. The input sequence X can be expressed as x= { X ₁ ,x ₂ ,…,x _n N is the number of Token, x _i Representing one of the Token. It should be noted that, the embedded layer in the application uses characters as granularity as Token, so that the problem of long tail words can be effectively solved.

A first Embedding layer, denoted as Token Embedding, is used for character encoding of each Token (element) in the text, where the Token may include characters and separators in the text.

A second embedded layer, denoted as Position Embedding, is configured to perform position coding on each Token, and may be configured to perform position coding on each Token in the text, for example, by sequentially performing position coding on each Token, and then performing position coding on each position number.

A third embedding layer, denoted as Sentence Embedding in the figure, is used for encoding the sentence identifier to which each Token belongs. For example, sentences in the text are numbered sequentially as sentence identifications, and sentence identifications to which each Token belongs are encoded.

After passing through the embedded layers, each Token, location information and statement identification of the Token are converted into a dense vector representation. Wherein e _i A vector representation representing the ith Token,the vector representation representing the ith Token as a character is obtained by looking up a word vector matrix, converting the character into a dense vector. />The vector representation representing the position of the ith Token is obtained by looking up a word vector matrix, converting the position into a dense vector. />The vector representation representing the sentence identification of the ith Token is obtained by searching a word vector matrix and converting the sentence representation into a dense vector.

The encoding result of each embedded layer is output to a transform layer (shown as multi-layer Transformer), and the transform layer outputs a hidden vector after performing multi-layer Attention mechanism processing. For example, a dense vector sequence E= { E ₁ ，e ₂ ，...，e _n The output is a sequence of hidden vectors h=Φ containing context information } _θ (E)＝{h ₁ ，h ₂ ，...，h _n }. Where n is the length of the input sequence, i.e., the number of tokens involved.

The mapping layer may include a CRF (Conditional Random Field ) for predicting information of spatial relationships contained in the text of the input model using hidden vectors output by the Transformer layer.

In the sequence h= { h where the hidden vector is obtained ₁ ，h ₂ ，...，h _n After } we use CRF predictive labels to get the model output y= { Y ₁ ，y ₂ ，…，y _n -wherein y _i Is the corresponding input x _i Is a predictive label of (a).

For each token x _i We can derive a probability distribution by the following formula

Wherein the method comprises the steps ofI.e. a vector in d x c dimensions, which is a weight parameter vector, c represents the number of output labels.

Then for each predicted sequence y= { Y ₁ ，y ₂ ，...，y _n We can get a score for this sequence:

finally, we can use the softmax (full junction layer) layer to derive the probability P for each predicted sequence Y _r ：

Wherein,refers to any of the resulting predicted sequences.

And finally, taking a predicted sequence Y with the highest probability, wherein the predicted sequence comprises the prediction of the spatial relationship information of the geographic position points, and comprises the type and the value of the spatial relationship. Still further, predictions of geographic location points are included in the prediction sequence. Finally, the four-element combination can be expressed as a four-element combination R= < S, O, P, A >, wherein S and O are geographic position points, P is a spatial relationship type, and A is a spatial relationship value.

After the above-mentioned geographical position point spatial relation extraction model, the text "six-layer" of the street five-color city shopping center in the sea lake area of the Beijing-for-sea fishing city "is input, the spatial relation type of the geographical position point" submarine fishing "and" five-color city "is extracted from the text" floor ", the value is" 6-layer ", and the text" submarine fishing "and" five-color city "can be expressed as a four-element group R= < submarine fishing, five-color city, floor and 6-layer >.

The text is input, namely, the space position relation type of the 'business bank' and the 'university of bloom' is 'south', the value is '200 meters', and the text can be expressed as four groups R= < business bank, university of bloom, south and 200 meters ', wherein the business bank is the branch island area of the Beijing bloom garden, the science and technology building is the B seat G layer, and the space position relation type of the' business bank 'and the' university of bloom 'is the south from the east gate of the university of bloom' is the 200 meters.

As can be seen from this embodiment, the present application is capable of extracting the spatial relationship information of the geographic location points from the text containing the information of the geographic location points in the internet.

In addition, a description system for representing the spatial relationship is defined in the embodiment of the application, and similar to the triplet < entity 1, entity 2 and relationship > in the common sense class knowledge graph, the expression of the spatial relationship is more standard and uniform by adopting < geographic position point 1, geographic position point 2, spatial relationship type and spatial relationship value >, so that systematic calculation, reasoning and storage of the spatial relationship knowledge are possible.

In the process of extracting the spatial relationship information of the geographic position points, the spatial relationship extraction model of the geographic position points is one of the important points.

The foregoing is a detailed description of the methods provided herein, and the apparatus provided herein is described in detail below.

Fig. 8 is a block diagram of a device for obtaining geographic location point information according to an embodiment of the present application, where the device may be an application located at a server, or may also be a functional unit such as a plug-in unit or a software development kit (Software Development Kit, SDK) located in the application at the server, or may also be located in a computer system, which is not limited in particular in the embodiment of the present invention. As shown in fig. 8, the apparatus may include: a spatial relationship acquisition unit 01, a spatial relationship concatenation unit 02, a knowledge base processing unit 03, and an information generation unit 04. Wherein, the main functions of each constituent unit are as follows:

the spatial relationship obtaining unit 01 is configured to obtain a newly generated spatial relationship list, where the spatial relationship list includes more than one spatial relationship data, and the spatial relationship data includes spatial relationship information between two geographic location points.

The newly generated spatial relationship list is obtained by extracting spatial relationship information between adjacent geographic position points from at least one of a live-action image acquired by a professional, a live-action image acquired by a crowd source and an Internet text.

And the spatial relation concatenation unit 02 is configured to concatenate the spatial relation data in the spatial relation list to obtain at least one concatenated set.

When the spatial relationship data are connected in series, if two spatial relationship data contain the same geographic position point, the two spatial relationship data can be connected in series, and the like, and a plurality of spatial relationship data can be connected in series to form a series set. If one spatial relationship data cannot be connected in series with other spatial relationship data in the newly generated spatial relationship list, the spatial relationship data forms a series set.

The knowledge base processing unit 03 is configured to write the spatial relationship data in the serial set into the knowledge base if at least one spatial relationship data in the serial set exists in the existing knowledge base.

As a preferred embodiment, the knowledge base processing unit 03 may perform, as the current spatial relationship data, each spatial relationship data in the concatenated set:

determining the area grid of the geographic position point contained in the current spatial relationship data;

inquiring current spatial relationship data in the spatial relationship data corresponding to the area lattice in the knowledge base, and if so, determining that the current spatial relationship data exists in the existing knowledge base; otherwise, determining that the current spatial relationship data does not exist in the existing knowledge base.

Wherein, the geographical position area is divided into cells in advance, and an overlapping area exists between adjacent cells; the knowledge base processing unit 03 may correspond spatial relationship data in the knowledge base to at least one cell in advance according to the geographic location of the geographic location point.

As a preferred embodiment, when determining the cell to which the geographic location point included in the current spatial relationship belongs, the knowledge base processing unit 03 may determine the cell to which the geographic location point included in the current spatial relationship belongs according to the fuzzy coordinate information of the geographic location point included in the current spatial relationship; the known coordinate information includes accurate coordinate information; wherein the accuracy of the fuzzy coordinate information is less than the accurate coordinate information.

Further, if all the spatial relationship data in the serial set do not exist in the existing knowledge base, the knowledge base processing unit 03 determines whether the spatial relationship data obtained from the live-action image acquired by the professional is present in the serial set, and if so, writes the spatial relationship data in the serial set into the knowledge base.

Further, if there is no spatial relationship data obtained from the live-action image acquired by the professional in the series set, the knowledge base processing unit 03 may write the spatial relationship data in the series set into the to-be-verified list. And the professional acquisition team can be further notified, and information of each geographic position point of the corresponding area in the list to be verified is acquired and verified by the professional acquisition team later.

And the information generating unit 04 is used for analyzing the geographic position points contained in the spatial relationship data of the newly written knowledge base to obtain geographic position point information contained in the spatial relationship data of the newly written knowledge base.

The information generating unit 04 may obtain the coordinate information of other geographic location points in the spatial relationship data of the newly written knowledge base by using the known coordinate information of at least one geographic location point included in the spatial relationship data of the newly written knowledge base.

As a preferred embodiment, if the spatial relationship data newly written into the knowledge base includes spatial relationship data obtained from a live-action image acquired by a professional, the information generating unit 04 calculates other geographic location points included in the spatial relationship data newly written into the knowledge base based on spatial relationship by using coordinate information of the geographic location points carried by the live-action image acquired by the professional, obtains coordinate information of the other geographic location points, and writes the coordinate information into the map database.

As a preferred embodiment, if the geographical location points included in the spatial relationship data newly written in the knowledge base have accurate coordinate information in the existing map database, the information generating unit 04 calculates other geographical location points included in the spatial relationship data newly written in the knowledge base based on the spatial relationship by using the geographical location points having the accurate coordinate information, obtains coordinate information of the other geographical location points, and writes the coordinate information into the map database.

In addition, the information generating unit 04 may perform at least one of the following ways to determine state information of the geographical location point contained in the spatial relationship data newly written in the knowledge base:

if two adjacent geographic position points contained in the spatial relationship data written in the knowledge base are not adjacent in the existing knowledge base, determining that the state of the geographic position point between the two adjacent geographic position points in the existing knowledge base is closed, and deleting the spatial relationship data containing the geographic position point with the closed state in the knowledge base.

If the coordinate information of one geographical position point contained in the spatial relation data written in the knowledge base is overlapped with the coordinate information of another geographical position point in the existing map database, determining that the state of the other geographical position point is changed, the state of the one geographical position point is newly increased, and deleting the spatial relation data of the geographical position point with the changed state contained in the knowledge base.

If the geographic position point contained in the spatial relation data written in the knowledge base is not existed in the existing map database, determining the state of the geographic position point as new addition.

After the coordinate information and the state change information of the newly-put geographic position point are obtained in the mode provided by the embodiment of the application, the method can be applied to various scenes. Such as when a location query request from a terminal device is acquired, a query may be made based on the updated map database and corresponding location information returned. For another example, after obtaining the navigation request from the terminal device, the query may be performed based on the updated map database and the navigation result may be returned. For another example, when a route query request from the terminal device is acquired, a query may be made based on the updated map database and a route result may be returned. Etc.

According to embodiments of the present application, an electronic device and a readable storage medium are also provided.

As shown in fig. 9, a block diagram of an electronic device of a method for obtaining geographic location point information according to an embodiment of the present application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the application described and/or claimed herein.

As shown in fig. 9, the electronic device includes: one or more processors 901, memory 902, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions executing within the electronic device, including instructions stored in or on memory to display graphical information of the GUI on an external input/output device, such as a display device coupled to the interface. In other embodiments, multiple processors and/or multiple buses may be used, if desired, along with multiple memories and multiple memories. Also, multiple electronic devices may be connected, each providing a portion of the necessary operations (e.g., as a server array, a set of blade servers, or a multiprocessor system). In fig. 9, a processor 901 is taken as an example.

Memory 902 is a non-transitory computer-readable storage medium provided herein. Wherein the memory stores instructions executable by the at least one processor to cause the at least one processor to perform the methods of obtaining geographic location point information provided herein. The non-transitory computer readable storage medium of the present application stores computer instructions for causing a computer to perform the methods of obtaining geographic location point information provided herein.

The memory 902 is used as a non-transitory computer readable storage medium for storing non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/units corresponding to the methods for obtaining geographic location point information in the embodiments of the present application. The processor 901 performs various functional applications of the server and data processing, that is, implements the method of acquiring the geographical location point information in the above-described method embodiment, by running non-transitory software programs, instructions, and units stored in the memory 902.

The memory 902 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, at least one application program required for a function; the storage data area may store data created according to the use of the electronic device, etc. In addition, the memory 902 may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory 902 optionally includes memory remotely located relative to processor 901, which may be connected to the electronic device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.

The electronic device may further include: an input device 903 and an output device 904. The processor 901, memory 902, input devices 903, and output devices 904 may be connected by a bus or other means, for example in fig. 9.

The input device 903 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device, such as a touch screen, keypad, mouse, trackpad, touchpad, pointer stick, one or more mouse buttons, trackball, joystick, and like input devices. The output means 904 may include a display device, auxiliary lighting means (e.g., LEDs), tactile feedback means (e.g., vibration motors), and the like. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device may be a touch screen.

Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASIC (application specific integrated circuit), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

These computing programs (also referred to as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), and the internet.

The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present application may be performed in parallel, sequentially, or in a different order, provided that the desired results of the technical solutions disclosed in the present application can be achieved, and are not limited herein.

The above embodiments do not limit the scope of the application. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application are intended to be included within the scope of the present application.

Claims

1. A method of obtaining geographic location point information, comprising:

the spatial relationship data in the spatial relationship list are connected in series to obtain at least one series set, and the spatial relationship data forming each series set comprises the same geographic position point;

analyzing geographic position points contained in the spatial relationship data of the newly written knowledge base to obtain geographic position point information contained in the spatial relationship data of the newly written knowledge base, wherein the geographic position point information comprises coordinate information of the geographic position points and/or state information of the geographic position points; wherein,

The analyzing the geographical location points contained in the spatial relationship data of the new writing knowledge base to obtain geographical location point information contained in the spatial relationship data of the new writing knowledge base includes:

obtaining the coordinate information of other geographic position points in the spatial relationship data of the newly written knowledge base by utilizing the known coordinate information of at least one geographic position point contained in the spatial relationship data of the newly written knowledge base; and/or

And comparing the spatial relationship data newly written into the knowledge base with the spatial relationship data of the existing knowledge base to obtain the state information of the geographic position points of the region corresponding to the spatial relationship data of the newly written knowledge base.

2. The method of claim 1, wherein the newly generated list of spatial relationships is obtained after extracting spatial relationship information between geographic location points from at least one of professionally acquired live-action images, crowd-sourced acquired live-action images, and internet text.

3. The method of claim 1, wherein upon determining that at least one spatial relationship data in the concatenated set exists in an existing knowledge base, each spatial relationship data in the concatenated set is executed as current spatial relationship data:

inquiring the current spatial relationship data in the spatial relationship data corresponding to the area lattice in the knowledge base, and if so, determining that the current spatial relationship data exists in the existing knowledge base; otherwise, determining that the current spatial relationship data does not exist in the existing knowledge base.

4. A method according to claim 3, wherein the geographical location area is pre-divided into cells, there is an overlap area between adjacent cells, and the spatial relationship data in the knowledge base is pre-mapped to at least one cell in dependence upon the geographical location of the included geographical location point.

5. The method of claim 3, wherein the determining the cell to which the geographic location point to which the current spatial relationship pertains comprises: determining the affiliated area grid according to the fuzzy coordinate information of the geographic position points contained in the current spatial relationship;

the known coordinate information utilized in the analysis includes precise coordinate information;

wherein the accuracy of the fuzzy coordinate information is less than the accurate coordinate information.

6. The method of claim 1, further comprising:

if all the spatial relationship data in the series set do not exist in the existing knowledge base, determining whether the spatial relationship data obtained by the professionally acquired live-action images exist in the series set, and if so, writing the spatial relationship data in the series set into the knowledge base.

7. The method of claim 6, further comprising:

and if the spatial relationship data obtained by the professionally acquired live-action images does not exist in the serial set, the spatial relationship data in the serial set is written into a list to be verified.

8. The method according to any one of claims 1 to 7, wherein the analyzing the geographical location points included in the spatial relationship data of the newly written knowledge base to obtain geographical location point information included in the spatial relationship data of the newly written knowledge base includes:

if the spatial relationship data written in the knowledge base contains the spatial relationship data obtained by the professional acquired live-action image, calculating other geographic position points contained in the spatial relationship data written in the knowledge base based on the spatial relationship by utilizing the coordinate information of the geographic position points carried by the professional acquired live-action image, obtaining the coordinate information of the other geographic position points and writing the coordinate information into the map database; and/or the number of the groups of groups,

if the geographical position points contained in the spatial relation data of the newly written knowledge base have accurate coordinate information in the existing map database, calculating other geographical position points contained in the spatial relation data of the newly written knowledge base based on spatial relation by using the geographical position points with the accurate coordinate information, obtaining the coordinate information of the other geographical position points and writing the coordinate information into the map database.

9. The method according to any one of claims 1 to 7, wherein the analyzing the geographical location points included in the spatial relationship data of the newly written knowledge base to obtain geographical location point information included in the spatial relationship data of the newly written knowledge base includes:

if two adjacent geographic position points contained in the spatial relationship data newly written into the knowledge base are not adjacent in the existing knowledge base, determining that the state of the geographic position point between the two adjacent geographic position points is closed, and deleting the spatial relationship data containing the geographic position point with the closed state in the knowledge base; and/or the number of the groups of groups,

if the coordinate information of one geographic position point contained in the spatial relation data written in the knowledge base is overlapped with the coordinate information of another geographic position point in the existing map database, determining that the state of the other geographic position point is changed, wherein the state of the one geographic position point is newly added, and deleting the spatial relation data of the geographic position point with the changed state contained in the knowledge base; and/or the number of the groups of groups,

10. An apparatus for obtaining geographic location point information, comprising:

the spatial relation series connection unit is used for carrying out series connection on the spatial relation data in the spatial relation list to obtain at least one series connection set, and the spatial relation data forming each series connection set comprises the same geographic position point;

the information generation unit is used for analyzing the geographic position points contained in the spatial relationship data of the newly written knowledge base to obtain geographic position point information contained in the spatial relationship data of the newly written knowledge base, wherein the geographic position point information comprises coordinate information of the geographic position points and/or state information of the geographic position points; wherein,

the information generating unit is specifically used for

11. The apparatus of claim 10, wherein the newly generated list of spatial relationships is derived from extracting spatial relationship information between geographic location points from at least one of professionally acquired live-action images, crowd-sourced acquired live-action images, and internet text.

12. The apparatus according to claim 10, wherein the knowledge base processing unit is specifically configured to perform, as current spatial relationship data, each spatial relationship data in the series set respectively:

13. The apparatus of claim 12, wherein the geographic location area is pre-divided into cells, with overlapping areas between adjacent cells;

the knowledge base processing unit is further configured to correspond spatial relationship data in the knowledge base to at least one cell in advance according to a geographic location of the geographic location point.

14. The apparatus of claim 12, wherein the knowledge base processing unit, when determining a cell to which a geographic location point included in the current spatial relationship belongs, is specifically configured to: determining the affiliated area grid according to the fuzzy coordinate information of the geographic position points contained in the current spatial relationship;

15. The apparatus according to claim 10, wherein the knowledge base processing unit is further configured to determine whether the spatial relationship data obtained from the live-action image acquired by the professional is present in the tandem set if all the spatial relationship data in the tandem set does not exist in the existing knowledge base, and if so, write the spatial relationship data in the tandem set into the knowledge base.

16. The apparatus of claim 15, wherein the knowledge base processing unit is further configured to write the spatial relationship data in the concatenated set to the list to be verified if there is no spatial relationship data in the concatenated set derived from the professionally acquired live action images.

17. The apparatus according to any one of claims 10 to 16, wherein the information generating unit is specifically configured to:

18. The apparatus according to any one of claims 10 to 16, wherein the information generating unit is specifically configured to:

19. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein,

The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-9.

20. A non-transitory computer readable storage medium storing computer instructions for causing the computer to perform the method of any one of claims 1-9.

21. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any of claims 1-9.