CN114898060A - Method, apparatus, device, medium and product for processing data - Google Patents
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Abstract
The present disclosure provides a method, apparatus, device, medium, and product for processing data, relating to the technical field of big data, in particular to the technical field of data processing. The specific implementation scheme is as follows: acquiring first map data; determining data coding information corresponding to the first map data; determining second map data matched with the first map data in the map data set based on the data coding information and preset parent-child relationship information; outputting the second map data. The implementation mode can improve the data calculation efficiency.
Description
Technical Field
The present disclosure relates to the field of big data technologies, and in particular, to the field of data processing technologies.
Background
At present, with the continuous development of internet technology, a large amount of map application software appears to provide relevant map services for users.
During the use of map application software, data processing on large-scale map data is often required, for example, analysis is performed on the map data to recommend points of interest that may be of interest to a user. However, the map data of the present day is huge in scale, and there is a problem that the calculation efficiency is low when the data calculation is performed.
Disclosure of Invention
The present disclosure provides a method, apparatus, device, medium, and article of manufacture for processing data.
According to an aspect of the present disclosure, there is provided a method for processing data, including: acquiring first map data; determining data coding information corresponding to the first map data; determining second map data matched with the first map data in the map data set based on the data coding information and preset parent-child relationship information; outputting the second map data.
According to another aspect of the present disclosure, there is provided an apparatus for processing data, including: a data acquisition unit configured to acquire first map data; an encoding determination unit configured to determine data encoding information corresponding to the first map data; a data determination unit configured to determine second map data matching the first map data in the map data set based on the data encoding information and preset parent-child relationship information; a data output unit configured to output the second map data.
According to another aspect of the present disclosure, there is provided an electronic device including: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement a method for processing data as any one of the above.
According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing a computer to perform the method for processing data as any one of the above.
According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program which, when executed by a processor, implements a method for processing data as any one of the above.
According to the technology of the present disclosure, a method for processing data is provided, which can improve data calculation efficiency.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
FIG. 1 is an exemplary system architecture diagram in which one embodiment of the present disclosure may be applied;
FIG. 2 is a flow diagram for one embodiment of a method for processing data according to the present disclosure;
FIG. 3 is a schematic diagram of one application scenario of a method for processing data according to the present disclosure;
FIG. 4 is a flow diagram of another embodiment of a method for processing data according to the present disclosure;
FIG. 5 is a schematic block diagram illustrating one embodiment of an apparatus for processing data according to the present disclosure;
FIG. 6 is a block diagram of an electronic device for implementing a method for processing data of an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those 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 disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
It should be noted that, in the present disclosure, the embodiments and features of the embodiments may be combined with each other without conflict. The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
As shown in fig. 1, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have map application software installed therein, and the map application software may include a map data set composed of a large amount of map data. The terminal apparatuses 101, 102, 103 can transmit the map data set to the server 105 through the network 104 for distributed management. Moreover, the terminal devices 101, 102, and 103 may also accept a human-computer interaction operation with the user, respond to a map data recommendation instruction triggered by the user for the first map data, send the first map data to the server 105 through the network 104, so that the server 105 returns the matched second map data, and output the second map data.
The terminal apparatuses 101, 102, and 103 may be hardware or software. When the terminal devices 101, 102, 103 are hardware, they may be various electronic devices including, but not limited to, mobile phones, computers, tablets, and the like. When the terminal apparatuses 101, 102, 103 are software, they can be installed in the electronic apparatuses listed above. It may be implemented as multiple pieces of software or software modules (e.g., to provide distributed services) or as a single piece of software or software module. And is not particularly limited herein.
The server 105 may be a server providing various services, for example, the server 105 may receive first map data sent by the terminal devices 101, 102, 103 through the network 104, and determine data encoding information corresponding to the first map data; determining second map data matched with the first map data in the map data set based on the data coding information and preset parent-child relationship information; the second map data is output and returned to the terminal devices 101, 102, 103 via the network 104. And the server 105 may receive the map data sets sent by the terminal devices 101, 102, 103 through the network 104, store each map data in the map data sets to a preset distributed storage system, and perform distributed data management on the map data.
The server 105 may be hardware or software. When the server 105 is hardware, it may be implemented as a distributed server cluster composed of a plurality of servers, or may be implemented as a single server. When the server 105 is software, it may be implemented as multiple pieces of software or software modules (e.g., to provide distributed services), or as a single piece of software or software module. And is not particularly limited herein.
It should be noted that, the method for processing data provided in the embodiment of the present disclosure may be executed by the terminal devices 101, 102, and 103, or may be executed by the server 105, and the apparatus for processing data may be disposed in the terminal devices 101, 102, and 103, or may be disposed in the server 105, which is not limited in the embodiment of the present disclosure.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
With continued reference to FIG. 2, a flow 200 of one embodiment of a method for processing data in accordance with the present disclosure is shown. The method for processing data of the embodiment comprises the following steps:
in step 201, first map data is obtained.
In the present embodiment, an executing subject (such as the server 105 or the terminal devices 101, 102, 103 in fig. 1) may acquire the first map data for point of interest recommendation from an electronic device that locally stores or previously establishes a connection. The first map data may be map data in a map data set, and may be specifically represented as a map interest point. In addition, the map data set can be stored in a distributed storage system, and the data management efficiency can be improved and the data consistency can be ensured by managing each map data in the map data set in a distributed manner.
In some optional implementations of this embodiment, the obtaining the first map data may include: and determining the map data corresponding to the target interest point as the first map data in response to detecting that the user triggers a preset instruction on the target interest point in the map application software. The preset instruction may include, but is not limited to, a view instruction, a collection instruction, a click instruction, and the like, which is not limited in this embodiment. By implementing the optional implementation mode, under the condition that the user triggers a preset instruction on the target interest point on the map, the map data corresponding to the target interest point can be determined as the first map data, and the corresponding second map data which is possibly interested by the user is pushed for the first map data.
In this embodiment, the execution subject may encode each map data in the map data set in advance to obtain data encoding information corresponding to each map data. The data coding information can be used for distinguishing map data of different geographic positions, and the representation form of the data coding information can be a character string. And, the similarity between the data encoding information may reflect the distance between the map data, wherein the higher the character string similarity of the data encoding information is, the closer the distance between the map data is.
Alternatively, the execution body may divide each map data into at least one location area based on the location coordinates of each map data, and set prefix character strings in data encoding information corresponding to these map data as the same character strings matching the location areas for map data of the same location area. Based on this, the execution subject may determine the closest map data based on finding the same prefix character string when finding the map data closest to the first map data.
And step 203, determining second map data matched with the first map data in the map data set based on the data coding information and preset parent-child relationship information.
In this embodiment, the execution subject may store, in advance, parent-child relationship information for each Map data in the Map data set, where the parent-child relationship information may be determined based on correspondence between multiple rounds of Map Reduce (a programming model) calculation and the interest point parent-child relationship tree. The calculation of parent-child relationships in the distributed storage system can be realized through the corresponding relationship.
Specifically, the execution subject may preset a specified number of layers for the parent-child relationship information, and calculate a layer in the parent-child relationship tree corresponding to the interest point for each round of Map Reduce according to the number of layers. Wherein the height of the interest point parent-child relationship tree corresponds to the number of layers.
And when the parent-child relationship information corresponding to the first map data needs to be determined, the execution subject may determine path information corresponding to the first map data from preset parent-child relationship information, where the path information may be a path formed between nodes in the parent-child relationship tree of the interest point. The execution subject can determine to obtain a plurality of interest points having a parent-child relationship with the first map data based on the parent-child relationship information corresponding to the first map data. Then, the execution subject may use the map data having a closer relationship with the first map data as the recommended second map data.
And the execution body can also determine the position information of the first map data based on the data coding information, determine the relation information of the first map data based on preset parent-child relation information, and determine the second map data which is closer to the first map data and has closer relation in the map data set based on the position information and the relation information. Wherein the number of the second map data is at least one.
And step 204, outputting the second map data.
In this embodiment, the execution subject may directly output the second map data, or output the second map data to the electronic device with which the connection is established in advance, for recommendation to the user.
With continued reference to fig. 3, a schematic diagram of one application scenario of a method for processing data according to the present disclosure is shown. In the application scenario of fig. 3, the execution subject may obtain the point of interest a in the map application in response to the user initiating a relevant operation behavior for the point of interest a. Thereafter, the execution subject may determine data encoding information 301 and parent-child relationship information 302 for point of interest a. And, the execution subject may determine other interest points closer to the interest point a based on the data encoding information 301 of the interest point a, and may determine other interest points closer to the interest point a based on the parent-child relationship information 302 of the interest point a. And determining an interest point B close to the interest point A by combining the distance and the relationship, and pushing the interest point B to the user. It is to be understood that the point of interest a herein corresponds to the first map data described above, and the point of interest B herein corresponds to the second map data described above.
According to the method for processing data provided by the embodiment of the disclosure, the second map data matched with the first map data can be quickly determined as the map data recommended to the user based on the data coding information and the preset parent-child relationship information. The map data with close distance can be quickly found by carrying out data coding on the map data, the map data with close relation can be quickly found by preset parent-child relation information, and the second map data is determined by adopting the mode, so that the data calculation efficiency can be improved.
With continued reference to FIG. 4, a flow 400 of another embodiment of a method for processing data in accordance with the present disclosure is shown. As shown in fig. 4, the method for processing data of the present embodiment may include the steps of:
In this embodiment, the execution subject may obtain each map data corresponding to the map application software from the electronic device which establishes a connection locally or in advance, that is, the map data set described above. The map data set may include the first map data and the second map data.
And 402, storing the map data set to a preset distributed storage system.
In this embodiment, the execution subject may store each map data in the map data set to a preset distributed storage system, and perform data management and data calculation in the distributed storage system. By managing a large amount of map data by the distributed storage system, data management efficiency can be improved, and consistency between map data can be improved.
At step 403, first map data is obtained.
In this embodiment, please refer to the detailed description of step 201 for the detailed description of step 403, which is not repeated herein.
In this embodiment, please refer to the detailed description of step 202 for the detailed description of step 404, which is not repeated herein.
In this embodiment, the execution subject may determine the distance information between each map data and the first map data based on the similarity between the data encoding information, wherein the higher the similarity, the closer the distance, the lower the similarity, and the further the distance.
In some optional implementations of the embodiment, determining distance information between each map data in the map data set and the first map data based on the data encoding information may include: and for each map data in the map data set, carrying out character string matching on the data coding information corresponding to the map data and the data coding information to obtain distance information between the map data and the first map data.
In this implementation, the execution subject may perform character string matching on the data encoding information of the map data and the data encoding information of the first map data for each map data to obtain a matching degree. And determining distance information between the map data and the first map data based on the proportional relation between the matching degree and the distance value. Wherein, the higher the matching degree, the closer the distance, and the lower the matching degree, the farther the distance.
In this embodiment, the execution subject may determine, from the preset parent-child relationship information, map data corresponding to nodes such as a parent node, a child node, and an ancestor node that match the first map data, and establish relationship information between the map data and the first map data.
In some optional implementation manners of this embodiment, determining, based on preset parent-child relationship information, relationship information between each map data in the map data set and the first map data includes: determining each layer of relation map data corresponding to the first map data based on preset parent-child relation information; wherein each layer of relationship map data at least comprises one of the following items: father relation map data, child relation map data and ancestor relation map data; for each map data in the map data set, in response to determining that the map data is data in each layer of relational map data, determining that the relational information between the map data and the first map data is a corresponding relationship; wherein the relationship includes at least one of: parent relationships, child relationships, ancestor relationships.
In this implementation manner, the execution subject may determine, based on preset parent-child relationship information, a node position of the first map data in the interest point parent-child relationship tree, and then determine each layer of nodes corresponding to the node position, such as a parent node, a child node, and an ancestor node. Wherein each node corresponds to a respective point of interest, i.e. to the floorplan data. Then, the execution subject may determine the map data corresponding to the parent node as the parent relation map data, determine the map data corresponding to the child node as the child relation map data, and determine the map data corresponding to the ancestor node as the ancestor relation map data.
And for each map data, if the map data is corresponding to the parent node, the child node or the ancestor node, determining that the map data is data in each layer of relationship map data, and determining that the relationship information between the map data and the first map data is corresponding parent relationship, child relationship or ancestor relationship.
In other optional implementations of this embodiment, the method further includes: for each map data in the set of map data, in response to determining that the map data is not data in the respective layer relationship map data, determining that the relationship information between the map data and the first map data is not parent-child relationship.
In this implementation, for each map data, if the map data is not data corresponding to the parent node, the child node, or the ancestor node, it is determined that the map data is not data in the map data of each layer, and it is determined that the relationship information between the map data and the first map data is not in a parent-child relationship.
In step 407, in the map data set, second map data matching the first map data is determined based on the distance information and the relationship information.
In this embodiment, the execution subject may preferably select, as the second map data, map data that is closer in distance and closer in relationship.
In some optional implementations of the embodiment, determining, in the set of map data, second map data that matches the first map data based on the distance information and the relationship information includes: for each map data in the map data set, determining a distance score corresponding to the map data based on distance information between the map data and the first map data; determining a relationship score corresponding to the map data based on the relationship information between the map data and the first map data; determining a matching weight corresponding to the map data based on the distance score and the relation score corresponding to the map data; and determining second map data matched with the first map data based on the matching weight of each map data in the map data set.
In this implementation, the execution subject may determine a distance score based on distance information between map data, where the closer the distance, the higher the distance score, and the farther the distance, the lower the distance score. And the execution subject may further determine a relationship score based on relationship information between the map data, wherein the relationship information indicates that the closer the relationship is, the higher the relationship score is, and the relationship information indicates that the closer the relationship is, the lower the relationship score is. Then, the execution subject may synthesize the relationship score and the distance score of each map data to obtain the matching weight of the map data. The integration mode may be direct addition, weighted summation, or the like, and this embodiment does not limit this. Then, the execution subject may select at least one second map data in an order of the matching weights from high to low.
At step 408, the second map data is output.
In this embodiment, for the detailed description of step 408, please refer to the detailed description of step 204, which is not repeated herein.
The method for processing data provided by the above embodiment of the present disclosure may further determine distance information between map data based on the data encoding information, so as to determine the closest map data, determine relationship information between map data based on the preset parent-child relationship information, so as to determine the map data with the closest relationship, and select the second map data according to the distance and the relationship, thereby improving the determination accuracy of the second map data. And when the map data are coded, the distance is represented by using the similarity degree between the data coding information, so that the distance information between the map data can be conveniently and rapidly and accurately acquired. And when determining the parent-child relationship information, constructing the parent-child relationship information of the limited layer by combining the corresponding relationship between the distributed computing step and the parent-child relationship tree, and realizing the use of the parent-child relationship information in the distributed storage system.
With further reference to fig. 5, as an implementation of the methods shown in the above-mentioned figures, the present disclosure provides an embodiment of an apparatus for processing data, which corresponds to the method embodiment shown in fig. 2, and which is particularly applicable to electronic devices such as a terminal device, a server, and the like.
As shown in fig. 5, the apparatus 500 for processing data of the present embodiment includes: a data acquisition unit 501, an encoding determination unit 502, a data determination unit 503, and a data output unit 504.
A data acquisition unit 501 configured to acquire first map data.
The encoding determination unit 502 is configured to determine data encoding information corresponding to the first map data.
A data determining unit 503 configured to determine second map data matching the first map data in the map data set based on the data encoding information and preset parent-child relationship information.
A data output unit 504 configured to output the second map data.
In some optional implementations of this embodiment, the data determining unit 503 is further configured to: determining distance information between each map data in the map data set and the first map data based on the data encoding information; determining relation information between each map data in the map data set and the first map data based on preset parent-child relation information; in the map data set, second map data that matches the first map data is determined based on the distance information and the relationship information.
In some optional implementations of this embodiment, the data determining unit 503 is further configured to: and for each map data in the map data set, carrying out character string matching on the data coding information and the data coding information corresponding to the map data to obtain distance information between the map data and the first map data.
In some optional implementations of this embodiment, the data determining unit 503 is further configured to: determining each layer of relation map data corresponding to the first map data based on preset parent-child relation information; wherein each layer of relationship map data at least comprises one of the following items: father relation map data, child relation map data and ancestor relation map data; for each map data in the map data set, in response to determining that the map data is data in each layer of relational map data, determining that the relational information between the map data and the first map data is a corresponding relationship; wherein the relationship includes at least one of: parent relationships, child relationships, ancestor relationships.
In some optional implementations of this embodiment, the data determining unit 503 is further configured to: for each map data in the set of map data, in response to determining that the map data is not data in the respective layer relationship map data, determining that the relationship information between the map data and the first map data is not parent-child relationship.
In some optional implementations of this embodiment, the data determining unit 503 is further configured to: for each map data in the map data set, determining a distance score corresponding to the map data based on distance information between the map data and the first map data; determining a relationship score corresponding to the map data based on the relationship information between the map data and the first map data; determining a matching weight corresponding to the map data based on the distance score and the relation score corresponding to the map data; and determining second map data matched with the first map data based on the matching weight of each map data in the map data set.
In some optional implementations of this embodiment, the method further includes: the data storage unit is configured to acquire a map data set matched with the map application software, wherein the map data set comprises first map data and second map data; and storing the map data set to a preset distributed storage system.
It should be understood that the units 501 to 504, which are recorded in the apparatus 500 for processing data, correspond to the respective steps in the method described with reference to fig. 2. Thus, the operations and features described above for the method for processing data are equally applicable to the apparatus 500 and the units included therein and will not be described again here.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
FIG. 6 illustrates a schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure. 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 phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 6, the apparatus 600 includes a computing unit 601, which can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)602 or a computer program loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the RAM603, various programs and data required for the operation of the device 600 can also be stored. The calculation unit 601, the ROM 602, and the RAM603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
A number of components in the device 600 are connected to the I/O interface 605, including: an input unit 606 such as a keyboard, a mouse, or the like; an output unit 607 such as various types of displays, speakers, and the like; a storage unit 608, such as a magnetic disk, optical disk, or the like; and a communication unit 609 such as a network card, modem, wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 601 performs the respective methods and processes described above, such as a method for processing data. For example, in some embodiments, the method for processing data may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 600 via the ROM 602 and/or the communication unit 609. When the computer program is loaded into RAM603 and executed by the computing unit 601, one or more steps of the method for processing data described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured by any other suitable means (e.g. by means of firmware) to perform the method for processing data.
In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the related information all conform to the regulations of related laws and regulations and do not violate the customs of the public order.
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
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 a pointing device (e.g., a mouse or a 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 can 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, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end 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 back-end, 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 clients and servers. A client and server are generally 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. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (17)
1. A method for processing data, comprising:
acquiring first map data;
determining data coding information corresponding to the first map data;
determining second map data matched with the first map data in a map data set based on the data coding information and preset parent-child relationship information;
outputting the second map data.
2. The method of claim 1, wherein the determining, in the set of map data, second map data that matches the first map data based on the data encoding information and preset parent-child relationship information comprises:
determining distance information between each map data in the map data set and the first map data based on the data encoding information;
determining relationship information between each map data in the map data set and the first map data based on the preset parent-child relationship information;
determining, in the set of map data, the second map data that matches the first map data based on the distance information and the relationship information.
3. The method of claim 2, wherein the determining distance information between each map data of the set of map data and the first map data based on the data encoding information comprises:
and for each map data in the map data set, carrying out character string matching on the data coding information corresponding to the map data and the data coding information to obtain distance information between the map data and the first map data.
4. The method of claim 2, wherein the determining relationship information between each map data in the set of map data and the first map data based on the preset parent-child relationship information comprises:
determining each layer of relation map data corresponding to the first map data based on the preset parent-child relation information; wherein the map data of each layer relationship at least includes one of: father relation map data, child relation map data and ancestor relation map data;
for each map data in the map data set, in response to determining that the map data is data in the map data of each layer relationship, determining that the relationship information between the map data and the first map data is a corresponding relationship; wherein the relationship comprises at least one of: parent relationships, child relationships, ancestor relationships.
5. The method of claim 4, further comprising:
for each map data in the set of map data, determining that the relationship information between the map data and the first map data is not in parent-child relationship in response to determining that the map data is not data in the respective layer of relationship map data.
6. The method of claim 2, wherein the determining, in the set of map data, the second map data that matches the first map data based on the distance information and the relationship information comprises:
for each map data in the map data set, determining a distance score corresponding to the map data based on distance information between the map data and the first map data; determining a relationship score corresponding to the map data based on the relationship information between the map data and the first map data;
determining a matching weight corresponding to the map data based on the distance score and the relation score corresponding to the map data;
and determining the second map data matched with the first map data based on the matching weight of each map data in the map data set.
7. The method of any of claims 1 to 6, further comprising:
acquiring the map data set matched with map application software, wherein the map data set comprises the first map data and the second map data;
and storing the map data set to a preset distributed storage system.
8. An apparatus for processing data, comprising:
a data acquisition unit configured to acquire first map data;
an encoding determination unit configured to determine data encoding information corresponding to the first map data;
a data determination unit configured to determine second map data matching the first map data in a map data set based on the data encoding information and preset parent-child relationship information;
a data output unit configured to output the second map data.
9. The apparatus of claim 8, wherein the data determination unit is further configured to:
determining distance information between each map data in the map data set and the first map data based on the data encoding information;
determining relationship information between each map data in the map data set and the first map data based on the preset parent-child relationship information;
determining, in the set of map data, the second map data that matches the first map data based on the distance information and the relationship information.
10. The apparatus of claim 9, wherein the data determination unit is further configured to:
and for each map data in the map data set, carrying out character string matching on the data coding information corresponding to the map data and the data coding information to obtain distance information between the map data and the first map data.
11. The apparatus of claim 9, wherein the data determination unit is further configured to:
determining each layer of relation map data corresponding to the first map data based on the preset parent-child relation information; wherein the map data of each layer relationship at least includes one of: father relation map data, child relation map data and ancestor relation map data;
for each map data in the map data set, in response to determining that the map data is data in the map data of each layer relationship, determining that the relationship information between the map data and the first map data is a corresponding relationship; wherein the relationship comprises at least one of: parent relationships, child relationships, ancestor relationships.
12. The apparatus of claim 11, wherein the data determination unit is further configured to:
for each map data in the set of map data, determining that the relationship information between the map data and the first map data is not in parent-child relationship in response to determining that the map data is not data in the respective layer of relationship map data.
13. The apparatus of claim 9, wherein the data determination unit is further configured to:
for each map data in the map data set, determining a distance score corresponding to the map data based on distance information between the map data and the first map data; determining a relationship score corresponding to the map data based on the relationship information between the map data and the first map data;
determining a matching weight corresponding to the map data based on the distance score and the relation score corresponding to the map data;
and determining the second map data matched with the first map data based on the matching weight of each map data in the map data set.
14. The apparatus of any of claims 8 to 13, further comprising:
a data storage unit configured to acquire the map data set matched with map application software, wherein the map data set includes the first map data and the second map data; and storing the map data set to a preset distributed storage system.
15. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
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 1-7.
16. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-7.
17. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-7.
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Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2017191277A1 (en) * | 2016-05-06 | 2017-11-09 | Here Global B.V. | Stitching mixed-version map tiles in hybrid navigation for partial map updates |
| US20180112995A1 (en) * | 2015-04-15 | 2018-04-26 | Tom Tom Navigation B.V. | Methods of obtaining point of interest data |
| CN108875013A (en) * | 2018-06-19 | 2018-11-23 | 百度在线网络技术（北京）有限公司 | Handle the method and device of map datum |
| CN110149804A (en) * | 2018-05-28 | 2019-08-20 | 北京嘀嘀无限科技发展有限公司 | System and method for determining the parent-child relationship of point of interest |
| CN111160471A (en) * | 2019-12-30 | 2020-05-15 | 腾讯云计算（北京）有限责任公司 | Method and device for processing point of interest data, electronic equipment and storage medium |
| CN112860996A (en) * | 2021-02-07 | 2021-05-28 | 北京百度网讯科技有限公司 | Interest point processing method and device, electronic equipment and medium |
| US20210240745A1 (en) * | 2020-01-30 | 2021-08-05 | Here Global B.V. | Matching location-related information with name information of points of interest |
| US20220107199A1 (en) * | 2020-10-01 | 2022-04-07 | Honda Motor Co., Ltd. | Search device, search method, and storage medium |
| CN114329244A (en) * | 2021-12-28 | 2022-04-12 | 北京百度网讯科技有限公司 | Map interest point query method, map interest point query device, map interest point query equipment, storage medium and program product |
| CN114491200A (en) * | 2022-01-24 | 2022-05-13 | 深圳依时货拉拉科技有限公司 | Method and device for matching heterogeneous interest points based on graph neural network |
-
2022
- 2022-05-24 CN CN202210571384.7A patent/CN114898060A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20180112995A1 (en) * | 2015-04-15 | 2018-04-26 | Tom Tom Navigation B.V. | Methods of obtaining point of interest data |
| WO2017191277A1 (en) * | 2016-05-06 | 2017-11-09 | Here Global B.V. | Stitching mixed-version map tiles in hybrid navigation for partial map updates |
| CN110149804A (en) * | 2018-05-28 | 2019-08-20 | 北京嘀嘀无限科技发展有限公司 | System and method for determining the parent-child relationship of point of interest |
| CN108875013A (en) * | 2018-06-19 | 2018-11-23 | 百度在线网络技术（北京）有限公司 | Handle the method and device of map datum |
| CN111160471A (en) * | 2019-12-30 | 2020-05-15 | 腾讯云计算（北京）有限责任公司 | Method and device for processing point of interest data, electronic equipment and storage medium |
| US20210240745A1 (en) * | 2020-01-30 | 2021-08-05 | Here Global B.V. | Matching location-related information with name information of points of interest |
| US20220107199A1 (en) * | 2020-10-01 | 2022-04-07 | Honda Motor Co., Ltd. | Search device, search method, and storage medium |
| CN112860996A (en) * | 2021-02-07 | 2021-05-28 | 北京百度网讯科技有限公司 | Interest point processing method and device, electronic equipment and medium |
| CN114329244A (en) * | 2021-12-28 | 2022-04-12 | 北京百度网讯科技有限公司 | Map interest point query method, map interest point query device, map interest point query equipment, storage medium and program product |
| CN114491200A (en) * | 2022-01-24 | 2022-05-13 | 深圳依时货拉拉科技有限公司 | Method and device for matching heterogeneous interest points based on graph neural network |
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