CN114416900A

CN114416900A - Method and device for analyzing track stop point

Info

Publication number: CN114416900A
Application number: CN202210002103.6A
Authority: CN
Inventors: 郭贵凤; 齐战胜; 王金山; 周新波; 孙玉峰; 慕荣臻
Original assignee: Xiamen Meiya Pico Information Co Ltd
Current assignee: Xiamen Meiya Pico Information Co Ltd
Priority date: 2022-01-04
Filing date: 2022-01-04
Publication date: 2022-04-29

Abstract

The application provides a method for analyzing a track stop point, which comprises the following steps: s1, acquiring data information of a target user mobile terminal identification group in a target time period, and constructing a signaling track data set according to the acquired data information; s2, preprocessing the signaling track data; s3, abstracting the track data of the target user mobile terminal identification into small area identification sequence data; s4, setting a small area residence time threshold value, and screening out a target small area identification set; s5, clustering the adjacent target small regions into a family, namely clustering the target small regions; s6, respectively calculating the geographical center points of the families based on the base stations in the target small area of each family; and S7, converting the geographical center point address into the stop point of the target user. The method and the device have the advantages that through virtual-real linkage, the tracks which are virtual, cannot be hidden and cannot be separated from the images and the images are associated with real, refined and strong-adhesion drop addresses, mutual verification and mutual complementation are achieved, and fresh and accurate dwell point information of a user group in a given time period is provided.

Description

Method and device for analyzing track stop point

Technical Field

The application belongs to the technical field of positioning service, and particularly relates to a method and a device for analyzing a track stop point.

Background

At present, the method for judging the user dwell point mainly focuses on setting a threshold value for analysis by using single space-time characteristics such as travel speed, direction change, track density and the like, and has simple logic algorithm and larger error; some base stations which are searched for mobile phones of users to access are adopted, and the weighted mass center is calculated to position the staying point of the user according to the longitude and latitude of the base stations and the frequency of the base stations accessed by the users, however, the staying point of people is in the radiation range of the base stations but is not always located at the base stations, so that the position of the base station closest to the weighted mass center is used as the staying point of the user, and the position is inaccurate.

In summary, when the user trajectory is located by the method, the position of the user's stay point cannot be accurately obtained, and an ideal effect is difficult to achieve.

In view of this, it is very meaningful to provide a method and an apparatus for analyzing a trajectory stop point.

Content of application

In order to solve the problem that the user track cannot be accurately positioned in the prior art, the method and the device for analyzing the track stopping point are provided to solve the technical defect problem.

The application provides a method for analyzing a track stop point, which comprises the following steps:

s1, acquiring data information of a target user mobile terminal identification group in a target time period, and constructing a signaling track data set according to the acquired data information;

s2, preprocessing the signaling track data;

s3, abstracting the track data of the target user mobile terminal identification into small area identification sequence data;

s4, setting a small area residence time threshold value, and screening out a target small area identification set;

s5, clustering the adjacent target small regions into a family, namely clustering the target small regions;

s6, respectively calculating the geographical center points of the families based on the base stations in the target small area of each family;

and S7, converting the geographical center point address into the stop point of the target user.

Inquiring and storing signaling track data of a target user in a given time period from a big data platform, and carrying out processing such as filtering, checking, duplicate removal, serialization, aggregation and the like on the acquired signaling data; abstracting the prepared signaling track data set into small area identification sequence data; then screening out small area identification sets with longer retention time, and clustering adjacent small area identification sets; then respectively calculating the geographical center points of all the families; and finally, converting the geographical center point into an address name with readability and strong practicability to serve as a stop point. Through the linkage of the virtual and the real, the track which can not be hidden and can not be separated from the image is associated with the real, the refined and the highly adhesive drop address, and the mutual verification and the mutual supplement are realized, thereby providing the fresh and accurate stop point information of the user group in a given time period.

Further preferably, the preprocessing in S2 includes cleaning, timing, aggregating, and performing associated backfill on the signaling trace data.

Further preferably, the pretreatment specifically comprises:

a, filtering the service key field without null, and cleaning the signaling track data by grouping and de-duplicating the service field;

b, grouping according to the mobile terminal identification of the target user, and sequencing the signaling track data in an access time group;

c, aggregating data continuously accessing the same base station, marking the frequency of continuous access, and merging the signaling track data by the first access time and the last access time;

and d, based on a base station related knowledge base, relevant backfilling the longitude and latitude of the base station in the signaling track data.

Preferably, S3 specifically includes dividing the target area into a plurality of grids, identifying each grid, and marking the base station in the grid with a grid identifier according to the time sequence of the target user mobile terminal accessing the base station.

It is further preferred that the target area id with the small area staying time greater than or equal to the threshold is screened in S4. The threshold parameter can be optimized and adjusted according to different construction of provincial, urban and rural base stations.

Further preferably, S5 includes grouping the base stations of adjacent target small regions into a family.

Further preferably, in S7, the geographical center point is addressed as a dwell point and divided into a matchable associated address and an unmatched associated address, which specifically includes querying an address name associated with the mobile terminal identifier of the target user.

In a second aspect, the present application discloses an apparatus for trajectory stop point analysis, which is characterized in that the apparatus comprises:

data query and save module: the system is used for setting query parameters to acquire target data and allowing the result to be stored in a library;

a data processing module: the system is used for realizing the operations of checking, filtering and lattice transformation on the acquired target data;

the data management module: the system is used for implementing the operations of duplicate removal, serialization, aggregation and associated backfill on the acquired target data;

a latitude and longitude data coding identification module: the latitude and longitude point data coding method is used for coding latitude and longitude point data of a given longitude according to a certain rule and marking the latitude and longitude point by a coding character string mark;

identified neighborhood calculation module: a neighboring cell identity for calculating a given cell code identity;

a data collision module: the collision mode calculation module is used for calculating and outputting a result after collision according to data input by a user and the set collision mode;

the geographic center point calculation module: the system comprises a three-dimensional coordinate system, a three-dimensional coordinate system and a three-dimensional coordinate system, wherein the three-dimensional coordinate system is used for converting longitude and latitude point set data input by a user into three-dimensional coordinate values, searching a central point in the 3D coordinate system, and decoding the central point coordinate into corresponding longitude and latitude points and outputting the corresponding longitude and latitude points;

an associable address query module: the system is used for realizing the checking of other identity information of the input identity elements and displaying the address name set information associated with the identity summarizing elements, and comprises longitude and latitude information corresponding to the address;

spherical distance calculation module: for calculating the distance between the two latitude and longitude points.

In a third aspect, an embodiment of the present application provides an electronic device, including: one or more processors; storage means for storing one or more programs; the one or more programs are executed by the one or more processors such that the one or more processors implement the method as described in any implementation of the first aspect.

In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, which, when executed by a processor, implements the method as described in any implementation manner of the first aspect.

Compared with the prior art, the beneficial results of this application lie in:

(1) through the linkage of the virtual and the real, the track which can not be hidden and can not be separated from the image is associated with the real, the refined and the highly adhesive drop address, and the mutual verification and the mutual supplement are realized, thereby providing the fresh and accurate stop point information of the user group in a given time period.

(2) The method has the advantages that the track data output by various types of equipment such as a special positioning terminal and a personal mobile terminal are processed, only single-cycle traversal is performed on the data in the processing process, and the operation efficiency is greatly improved.

Drawings

The accompanying drawings are included to provide a further understanding of the embodiments and are incorporated in and constitute a part of this specification. The drawings illustrate embodiments and together with the description serve to explain the principles of the application. Other embodiments and many of the intended advantages of embodiments will be readily appreciated as they become better understood by reference to the following detailed description. The elements of the drawings are not necessarily to scale relative to each other. Like reference numerals designate corresponding similar parts.

FIG. 1 is an exemplary device architecture diagram in which one embodiment of the present application may be applied;

FIG. 2 is a schematic flow chart illustrating a method for trajectory stop point analysis according to an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of a specific flow of a method for analyzing a trajectory stop point according to an embodiment of the present application;

FIG. 4 is a schematic flow chart of an apparatus for trajectory stop point analysis according to an embodiment of the present application;

fig. 5 is a schematic structural diagram of a computer device suitable for implementing an electronic apparatus according to an embodiment of the present application.

Detailed Description

In the following detailed description, reference is made to the accompanying drawings, which form a part hereof, and in which is shown by way of illustration specific embodiments in which the application may be practiced. In this regard, directional terminology, such as "top," "bottom," "left," "right," "up," "down," etc., is used with reference to the orientation of the figures being described. Because components of embodiments can be positioned in a number of different orientations, the directional terminology is used for purposes of illustration and is in no way limiting. It is to be understood that other embodiments may be utilized and logical changes may be made without departing from the scope of the present application. The following detailed description is, therefore, not to be taken in a limiting sense, and the scope of the present application is defined by the appended claims.

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.

Fig. 1 illustrates an exemplary system architecture 100 to which a method for processing information or an apparatus for processing information of embodiments of the present application may be applied.

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 various communication client applications installed thereon, such as a web browser application, a shopping application, a search application, an instant messaging tool, a mailbox client, social platform software, and the like.

The

terminal devices

101, 102, 103 may be various electronic devices having communication functions, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.

The server 105 may be a server that provides various services, such as a background information processing server that processes check request information transmitted by the

terminal apparatuses

101, 102, 103. The background information processing server may analyze and perform other processing on the received verification request information, and obtain a processing result (e.g., verification success information used to represent that the verification request is a legal request).

It should be noted that the method for processing information provided in the embodiment of the present application is generally performed by the server 105, and accordingly, the apparatus for processing information is generally disposed in the server 105. In addition, the method for sending information provided by the embodiment of the present application is generally executed by the

terminal equipment

101, 102, 103, and accordingly, the apparatus for sending information is generally disposed in the

terminal equipment

101, 102, 103.

The server may be hardware or software. When the server is hardware, it may be implemented as a distributed server cluster formed by multiple servers, or may be implemented as a single server. When the server 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 multiple software modules. And is not particularly limited herein.

Fig. 2 shows a schematic flow diagram of a method for analyzing a trajectory stop point disclosed in an embodiment of the present application, fig. 3 shows a schematic specific flow structure diagram of the method for analyzing a trajectory stop point disclosed in an embodiment of the present application, and referring to fig. 2 and fig. 3, the method includes the following steps:

in a specific embodiment, historical signaling trajectory data of a target user group in the period of time is inquired according to the target time period and the target user mobile terminal identification group, and necessary field information is selected to construct a data set and stored.

S2, preprocessing the signaling track data;

in a specific embodiment, the preprocessing includes cleaning, time sequencing, aggregating, and backfilling the signaling trace data.

The specific preprocessing of the signaling trace data includes:

b, grouping according to the mobile terminal identification of the target user, and sequencing in the access time group to carry out time sequence signaling track data;

specifically, a target area is divided into a plurality of grids, each grid is identified, and then base stations in the grids are marked by grid identifications according to the time sequence of the target user mobile terminal accessing the base station.

In this embodiment, a target area, such as beijing, is divided into a plurality of small areas according to a certain rule, and each small area is identified by a code string; coding a base station longitude and latitude set in the trajectory data, such as a base station longitude and latitude set accessed by a group of mobile terminals of special users who stay in Beijing, according to the same rule; obviously, when the longitude and latitude point of the base station is in a certain small area, the code identification of the base station is the same as the code identification of the corresponding small area; and replacing or marking the longitude and latitude points of the base station in the area by the small area coding identifier, so that the track data can be abstracted into small area identification sequence data.

in a specific embodiment, the residence time of each small area is counted in groups by the mobile terminal identifier of the target user and the small area identifier of the track, and the target area identifier with the residence time of the small area being greater than or equal to the threshold is further screened out. The threshold parameter can be optimized and adjusted according to different construction of provincial, urban and rural base stations.

specifically, the method comprises the steps of calculating an adjacent small area identifier of each target small area identifier X, and forming a corresponding X-adjacent small area identifier set; each X-adjacent small region identification set is collided with the coding identification set in the track, and the X-adjacent small region identification sets are adjacent to each other and are classified into a family, so that a plurality of adjacent small region identification families are obtained; and calculating the stay time, the starting time and the ending time of each identification family.

calculating the geographic center point for each family class includes: associating and acquiring base station points of each adjacent small area identification family, wherein the base station points comprise longitude and latitude data, so that a base station longitude and latitude point list corresponding to each family is acquired; calculating the geographical center point of the base station longitude and latitude point list corresponding to each family; further forming an intermediate data set of information such as user mobile terminal identification, family identification, geographic center point of the family, stay time in the family area, start time, end time and the like.

In a specific embodiment, the geographical center point is addressed as a stop point and divided into a matchable associated address and an unmatched associated address, and specifically comprises the step of inquiring an address name associated with the mobile terminal identifier of a target user, such as an address of logistics, takeaway and the like;

address expansion, namely performing identity drop checking according to the mobile terminal identification of a target user to obtain other identity information of the target user, and then inquiring related address names such as addresses of internet bars, houses, hotels and the like according to the newly obtained other identity information; it should be noted that the above address names all carry corresponding longitude and latitude information;

matching the geographic center point with the associated address of the target user, and judging the address name matched with the geographic center point by calculating the spherical distance between the geographic center point and the associated address; when the address name can be matched, associating the address name with the geographic central point to serve as a stop point of a target user; when the address name cannot be matched, the address name closest to the geographical center point, such as a cell name, is associated with the geographical center point as a dwell point.

The solution disclosed in this application may be applicable to a number of stopping points for a censored user and may further recommend the nearest stopping location. The method can be specifically executed by a big data platform system and a track stop point analysis device.

In the embodiment of the invention, a signaling track data set of a target user group is prepared, specifically, the signaling track data of the target user in a given time period is inquired and stored from a big data platform, and the acquired signaling data is subjected to processing such as filtering, checking, duplicate removal, serialization, aggregation and the like; abstracting the prepared signaling track data set into small area identification sequence data; then screening out small area identification sets with longer retention time, and clustering adjacent small area identification sets; then calculating the geographical center points of various families; and finally, converting the geographical center point into an address name with readability and strong practicability to serve as a stop point.

Through the linkage of the virtual and the real, the track which can not be hidden and can not be separated from the image is associated with the real, the refined and the highly adhesive drop address, and the mutual verification and the mutual supplement are realized, thereby providing the fresh and accurate stop point information of the user group in a given time period. The method has the advantages that the track data output by various types of equipment such as a special positioning terminal and a personal mobile terminal are processed, only single-cycle traversal is carried out on the data in the processing process, and the operation efficiency is greatly improved.

The embodiment of the invention can also be used in places where the mobile phone positioning service software cannot reach, such as the stop point positioning of special personnel.

Fig. 4 shows a schematic flow chart of an apparatus for analyzing a trajectory stop point according to an embodiment of the present application, as shown in fig. 4.

In a second aspect, an embodiment of the present application discloses an apparatus for trajectory stop point analysis, the apparatus including:

a latitude and longitude data coding identification module: the system is used for coding the data of the given longitude and latitude point according to a certain rule and marking the longitude and latitude point by a coded character string identifier;

spherical distance calculation module: configured to calculate the distance between the two latitude and longitude points.

Referring now to fig. 5, a schematic diagram of a computer device 600 suitable for use in implementing an electronic device (e.g., the server or terminal device shown in fig. 1) according to an embodiment of the present application is shown. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.

As shown in fig. 5, the computer apparatus 600 includes a Central Processing Unit (CPU)601 and a Graphics Processing Unit (GPU)602, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)603 or a program loaded from a storage section 609 into a Random Access Memory (RAM) 606. In the RAM 604, various programs and data necessary for the operation of the apparatus 600 are also stored. The CPU 601, GPU602, ROM 603, and RAM 604 are connected to each other via a bus 605. An input/output (I/O) interface 606 is also connected to bus 605.

The following components are connected to the I/O interface 606: an input portion 607 including a keyboard, a mouse, and the like; an output section 608 including a display such as a Liquid Crystal Display (LCD) and a speaker; a storage section 609 including a hard disk and the like; and a communication section 610 including a network interface card such as a LAN card, a modem, or the like. The communication section 610 performs communication processing via a network such as the internet. The driver 611 may also be connected to the I/O interface 606 as needed. A removable medium 612 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 611 as necessary, so that a computer program read out therefrom is mounted into the storage section 609 as necessary.

In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such embodiments, the computer program may be downloaded and installed from a network via the communication section 610, and/or installed from the removable media 612. The computer programs, when executed by a Central Processing Unit (CPU)601 and a Graphics Processor (GPU)602, perform the above-described functions defined in the methods of the present application.

It should be noted that the computer readable medium described herein can be a computer readable signal medium or a computer readable medium or any combination of the two. The computer readable medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor device, apparatus, or any combination of the foregoing. More specific examples of the computer readable medium may include, but are not limited to: an electrical connection having 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. In the present application, a computer readable medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution apparatus, device, or apparatus. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution apparatus, device, or apparatus. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based devices that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The modules described in the embodiments of the present application may be implemented by software or hardware. The modules described may also be provided in a processor.

As another aspect, the present application also provides a computer-readable medium, which may be contained in the electronic device described in the above embodiments; or may exist separately without being assembled into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to perform a method of trajectory stagnation point analysis.

The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention herein disclosed is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the invention. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.

Claims

1. A method for analyzing a locus stagnation point is characterized by comprising the following steps:

s2, preprocessing the signaling track data;

2. The method of trajectory stop point analysis of claim 1, wherein said preprocessing comprises washing, time sequencing, aggregating, correlating and backfilling said signaling trajectory data at S2.

3. The method of trajectory stop point analysis according to claim 2, characterized in that the preprocessing specifically comprises:

4. The method according to claim 3, wherein S3 specifically comprises dividing the target area into a plurality of grids, identifying each grid, and marking the base stations in the grids with grid identifications according to the timing sequence of the target user mobile terminal accessing the base station.

5. The method of trajectory dwell point analysis as claimed in claim 4, wherein target zone identifications having a small zone dwell time greater than or equal to the threshold are screened out in S4.

6. The method of trajectory stop point analysis as claimed in claim 5, wherein S5 includes grouping the base sites of adjacent target small regions into a family.

7. The method for analyzing trajectory stop point according to claim 6, wherein the geographic center point is addressed in S7 to divide the stop point into a matchable associated address and an unmatched associated address, and specifically includes querying an address name associated with the mobile terminal identifier of the target user.

8. An apparatus for trajectory stop point analysis, the apparatus comprising:

a latitude and longitude data coding identification module: the system is used for coding the given longitude and latitude point data according to a certain rule and marking the longitude and latitude point by a coding character string identifier;

9. An electronic device, comprising:

one or more processors;

storage means for storing one or more programs;

the one or more programs are executed by the one or more processors such that the one or more processors implement the method of any of claims 1-7.

10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-7.