CN110909262B - Method and device for determining companion relationship of identity information - Google Patents
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- CN110909262B CN110909262B CN201911200827.6A CN201911200827A CN110909262B CN 110909262 B CN110909262 B CN 110909262B CN 201911200827 A CN201911200827 A CN 201911200827A CN 110909262 B CN110909262 B CN 110909262B
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- G06F16/90—Details of database functions independent of the retrieved data types
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Abstract
The application provides a method and a device for determining an accompanying relation of identity information, which are used for acquiring space-time trajectory information of a plurality of identity information; carrying out fragmentation processing on time information and position information in the time-space track information; generating index information of each identity information under different time slices and space slices according to the slicing processing result; for every two pieces of identity information, determining the co-occurrence rate of the two pieces of identity information under the combination of all time slices and all space slices based on the index information of the two pieces of identity information; and determining the adjoint relation of every two identity information based on the co-occurrence rate. Compared with the prior art, the method and the device have the advantages that the co-occurrence rate of the two identity information under the combination of all the time slices and the space slices can be achieved, the accompanying relation of the two identity information is determined based on the co-occurrence rate, the calculation amount required for determining the accompanying relation can be greatly reduced, the waste of resources is avoided, the processing efficiency is improved, the limitation of preset rules is avoided, and the accuracy is high.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to a method and an apparatus for determining an accompanying relationship of identity information.
Background
The space-time accompanying analysis problem is an accompanying relation analysis problem about a relation person or an account. In which, based on the analysis of the association relationship between people or things using the spatiotemporal trajectory, the association between people or things can be learned and applied to various scenes, such as traffic management, tracking of people or things, and determination of related targets.
At present, the conventional method for determining the adjoint relationship generally directly uses the collected original spatiotemporal trajectory data, and determines the adjoint relationship between different devices or people according to preset rules. However, in practical applications, the trace data is usually extremely large in size, so that the calculation amount of the trace data is far larger than the receivable range, a large amount of resources are wasted, the preset rule cannot flexibly meet various application scenarios, and the accuracy of the obtained accompanying relationship is low.
Disclosure of Invention
In view of this, an object of the present application is to provide a method and an apparatus for determining an accompanying relationship of identity information, which are capable of determining the accompanying relationship of two identity information based on a co-occurrence rate of the two identity information under all combinations of time slices and space slices, and greatly reducing a calculation amount required for determining the accompanying relationship, avoiding waste of resources, improving processing efficiency, and having higher accuracy without being limited by a preset rule.
The embodiment of the application provides a method for determining an accompanying relationship of identity information, which comprises the following steps:
acquiring space-time track information of a plurality of identity information, wherein the space-time track information comprises time information and position information when the identity information is monitored each time in a preset time period;
carrying out fragmentation processing on time information and position information in the space-time trajectory information;
generating index information of each identity information under different time slices and space slices according to the slicing processing result;
for every two pieces of identity information, determining the co-occurrence rate of the two pieces of identity information under all combinations of time slices and space slices based on index information of the two pieces of identity information, wherein the co-occurrence rate indicates that the frequency of the two pieces of identity information is monitored under all combinations of time slices and space slices;
and determining the adjoint relation of every two identity information based on the co-occurrence rate.
Further, the determining, for every two identity information, a co-occurrence rate of the two identity information under each combination of the time slice and the space slice based on index information of the two identity information includes:
weighting the index information of each identity information under different time slices and space slices according to the importance degrees of different time slices and position slices;
and calculating the co-occurrence rate of the two identity information under the combination of all the time slices and the control slices according to the index information weighted by every two identity information.
Further, the plurality of identity information includes at least two kinds of identity information.
Further, the at least two kinds of identity information include:
a medium access control MAC address, and/or an international mobile subscriber identity.
Further, the determining the accompanying relationship between every two identity information based on the co-occurrence rate includes:
determining that the two identity information with the co-occurrence rate larger than or equal to a preset threshold value have an accompanying relationship.
The embodiment of the present application further provides an apparatus for determining an accompanying relationship of identity information, where the apparatus includes:
the system comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring space-time track information of a plurality of identity information, and the space-time track information comprises time information and position information when the identity information is monitored each time in a preset time period;
the fragmentation module is used for carrying out fragmentation processing on the time information and the position information in the space-time trajectory information;
the generating module is used for generating index information of each identity information under different time slices and space slices according to the slice processing result;
the device comprises a first determining module, a second determining module and a third determining module, wherein the first determining module is used for determining the co-occurrence rate of every two pieces of identity information under the combination of all time slices and all space slices based on the index information of the two pieces of identity information, and the co-occurrence rate indicates that the frequency of the two pieces of identity information is monitored under the combination of all time slices and all space slices;
and the second determining module is used for determining the accompanying relationship of every two identity information based on the co-occurrence rate.
Further, the first determining module is specifically configured to:
weighting the index information of each identity information under different time slices and space slices according to the importance degrees of different time slices and position slices;
and calculating the co-occurrence rate of the two identity information under the combination of all the time slices and the control slices according to the index information weighted by every two identity information.
Further, the second determining module is specifically configured to:
determining that the two identity information with the co-occurrence rate larger than or equal to a preset threshold value have an accompanying relationship.
Further, the plurality of identity information includes at least two kinds of identity information.
Further, the at least two kinds of identity information include:
a medium access control MAC address, and/or an international mobile subscriber identity.
An embodiment of the present application further provides an electronic device, including: a processor, a memory and a bus, the memory storing machine readable instructions executable by the processor, the processor and the memory communicating via the bus when the electronic device is running, the machine readable instructions when executed by the processor performing the steps of the method for determining an accompanying relationship of identity information as described above.
Embodiments of the present application further provide a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the method for determining an accompanying relationship of identity information as described above are performed.
The method and the device for determining the accompanying relationship of the identity information, provided by the embodiment of the application, are used for acquiring the space-time trajectory information of a plurality of identity information, wherein the space-time trajectory information comprises time information and position information when the identity information is monitored each time in a preset time period; carrying out fragmentation processing on time information and position information in the space-time trajectory information; generating index information of each identity information under different time slices and space slices according to the slicing processing result; for every two pieces of identity information, determining the co-occurrence rate of the two pieces of identity information under all combinations of time slices and space slices based on index information of the two pieces of identity information, wherein the co-occurrence rate indicates that the frequency of the two pieces of identity information is monitored under all combinations of time slices and space slices; and determining the accompanying relation of every two identity information based on the co-occurrence rate. Compared with the prior art, the method and the device have the advantages that the co-occurrence rate of the two identity information under the combination of all the time slices and the space slices can be achieved, the accompanying relation of the two identity information is determined based on the co-occurrence rate, the calculation amount required for determining the accompanying relation can be greatly reduced, the waste of resources is avoided, the processing efficiency is improved, the limitation of preset rules is avoided, and the accuracy is high.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a flowchart illustrating a method for determining an accompanying relationship of identity information according to an embodiment of the present application;
fig. 2 is a flowchart illustrating another method for determining an accompanying relationship of identity information according to an embodiment of the present application;
fig. 3 is a schematic structural diagram illustrating an apparatus for determining an accompanying relationship of identity information according to an embodiment of the present application;
fig. 4 shows a schematic structural diagram of an electronic device provided in an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, as generally described and illustrated in the figures herein, could be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. Every other embodiment that can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present application falls within the protection scope of the present application.
According to research, the conventional accompanying relation determining method generally determines an accompanying relation between different devices or people by directly using acquired original spatiotemporal trajectory data according to preset rules. However, in practical applications, the trace data is usually extremely large in size, so that the calculation amount of the trace data is far larger than the receivable range, a large amount of resources are wasted, the preset rule cannot flexibly meet various application scenarios, and the accuracy of the obtained accompanying relationship is low.
Based on this, the embodiment of the application provides a method for determining an accompanying relationship of identity information, which can determine the accompanying relationship of two identity information based on a co-occurrence rate of the two identity information under the combination of all time slices and all space slices, can greatly reduce the amount of calculation required for determining the accompanying relationship, avoid the waste of resources, improve the processing efficiency, is not limited by a preset rule, and has higher accuracy.
Referring to fig. 1, fig. 1 is a flowchart of an association relationship determining method for identity information according to an embodiment of the present disclosure. As shown in fig. 1, a method for determining an accompanying relationship of identity information provided in an embodiment of the present application includes:
s101, space-time trajectory information of a plurality of identity information is obtained.
The space-time trajectory information comprises time information and position information when the identity information is monitored each time in a preset time period.
Here, the identity may be an entity ID, such as a human face feature, a MAC number of the mobile device, an international mobile subscriber identity, a license plate number of the vehicle, a virtual account number, and the like. Each monitoring terminal can monitor the identity, when the identity is monitored by the monitoring terminal, the monitoring terminal records the monitored identity and records the time and the place for monitoring the identity, namely the time information and the position information are combined, and the space-time trajectory information is formed.
The spatiotemporal trajectory information may include a portrait gate trajectory, a vehicle gate trajectory, an electronic fence trajectory, a WIFI fence trajectory, a human evidence checking and recording trajectory, and the like. The space-time trajectory information can be obtained by processing monitoring data of different types of monitoring terminals, each type of monitoring terminal can monitor one or more types of space-time trajectory information, and the monitoring data can be collected and processed by a server.
It is worth noting that through analyzing the accompanying relation between the identity information, the two identity information can be related, and the method can play a vital role in a public security scene, a traffic planning scene and an advertisement tracking scene.
For example, in a public security scenario, the relationship between users corresponding to identity information can be determined through the accompanying relationship between different identity information, so that the relationship network of the users can be conveniently determined; in a traffic planning scene, the time of traffic lights and the like can be reasonably planned according to the accompanying relations of different car owners; in the advertisement tracking scene, whether the equipment terminals to which the two pieces of identity information belong are the same equipment terminal can be determined, and then an advertisement scheme and the like aiming at the equipment terminal are designed.
And S102, carrying out fragmentation processing on the time information and the position information in the space-time trajectory information.
In the step, the space-time trajectory information can be standardized, then the fragmentation processing is carried out, and the index is established, so that the subsequent use is facilitated.
Specifically, the normalized data may be data in the form of the following tables 1 and 2. Referring to tables 1 and 2, table 1 shows standardized Wifi fence data, and table 2 shows standardized electronic fence data.
| MAC | STARTTIME | LOCATION |
| DA:A1:19:17:AC:12 | 2019-08-06 16:20:13 | Location ID1 |
| DA:A5:11:19:AC:10 | 2019-08-05 16:20:12 | Location ID2 |
TABLE 1
| IMSI | STARTTIME | LOCATION |
| 460003111370161 | 2019-08-06 16:20:10 | Location ID1 |
| 460001211370160 | 2019-08-05 16:19:11 | Location ID2 |
TABLE 2
Table 1, including the detected MAC address, the time when the MAC address was detected, and the location where the MAC address was detected; table 2 includes the detected IMSI address, the time when the IMSI address was detected, and the location where the IMSI address was detected.
In the step, after the spatiotemporal trajectory information of a plurality of identity identifiers is acquired, the spatiotemporal trajectory data can be stored in a partitioned manner according to space and time, each space is defined as a space site ID, the site ID is used as a first-level directory, and then the spatiotemporal trajectory information is subjected to fragmentation processing according to a preset time period.
Specifically, the data can be equally divided according to 24 hours per day, and the data of each hour is stored in a directory, wherein repeated data are removed from the data of each hour, so that the quantity of the stored data can be greatly reduced.
Further, the hourly storage may be adjusted, for example, to the minute storage. Through this conversion, specific data can be found through the fragmented path. The effect of the specific slicing can be shown in table 3 and table 4 below.
Referring to tables 3 and 4, table 3 shows normalized data before slicing, and table 4 shows data after slicing.
| ID | Time of acquisition | Location ID |
| 001 | 2019-08-06 16:20:13 | 100 |
| 001 | 2019-08-05 16:20:12 | 101 |
TABLE 3
| ID | Location ID | Time of acquisition | Place/time slicing |
| 001 | 100 | 2019-08-06 16:20:13 | 100/2019080616 |
| 001 | 101 | 2019-08-05 16:20:12 | 101/2019080516 |
TABLE 4
As shown in table 3 and table 4, the ID is a number corresponding to the authentication identifier, the location ID is a number corresponding to a location where the authentication identifier is detected, and the location/time slice is a character string generated according to the location ID and the acquisition time.
And S103, generating index information of each identity information under different time slices and space slices according to the slice processing result.
In the step, after the fragmentation operation is carried out, a spatiotemporal index corresponding to spatiotemporal trajectory information can be established, spatiotemporal positions corresponding to each identity can be converted into spatiotemporal trajectory storage fragments, and then the information is compressed and stored in a file, so that spatiotemporal position points of specific identities can be quickly retrieved. The form of the index may be as shown in table 5 below.
Referring to table 5, table 5 is an index list generated in this step, and as shown in table 5, the corresponding sorting and arrangement are performed on each identity according to the location fragment and the time fragment.
Table 5S104, for every two identity information, determining a co-occurrence rate of the two identity information under all combinations of time slices and space slices based on index information of the two identity information.
Wherein the co-occurrence rate indicates a frequency of monitoring the two identity information simultaneously under all combinations of time slicing and space slicing.
Specifically, the co-occurrence rate may be the number of times that two pieces of identity information are monitored at the same time, and the co-occurrence rate can represent the frequency of the two pieces of identity information appearing at the same time, and when the co-occurrence rate is greater than a preset threshold, it can be considered that an association relationship exists between the two pieces of identity information.
Furthermore, the co-occurrence rate can also be the ratio of the number of times that the two pieces of identity information are monitored simultaneously to the sum of the locations where the two pieces of identity information are detected, so that the association between the two pieces of identity information can be reflected on the whole.
In the step, the trajectory data can be stored according to a certain space-time range through a space-time interval index, and the identity information stored in an index file is defined to be space-time co-occurrence in a certain space-time range. The current space-time can be divided into a plurality of indexes, and different weights can be selected in different index intervals during calculation.
Specifically, for example, the weight of the night co-occurrence is high, and the weight of the commute to work and off work is low; the co-occurrence weight of suburbs is high, and the co-occurrence weight of places with large urban pedestrian traffic is low. The total co-occurrence rate is obtained by weighting the calculated co-occurrence rates of the plurality of spatio-temporal interval indexes. By comparing the total co-occurrence rate to determine the two identity information with high co-occurrence rate, it can be determined that the two entities have the accompanying relationship.
Therefore, the required data can be quickly positioned through the index information of each identity information under different time slices and space slices, the complex positioning process is omitted, the efficiency of determining the accompanying relation is improved, and the determining of the accompanying relation is more accurate by setting the weights of different time periods.
And S105, determining the accompanying relation between every two identity information based on the co-occurrence rate.
Specifically, when the co-occurrence rate is greater than or equal to a preset threshold, the two identity information may be determined that the association relationship exists.
The preset threshold value may be determined according to actual situations such as the arrangement of the monitoring terminals.
In some possible embodiments, the determining, for every two identity information, a co-occurrence rate of the two identity information under each combination of time slicing and space slicing based on index information of the two identity information includes:
weighting the index information of each identity information under different time slices and space slices according to the importance degrees of different time slices and position slices;
and calculating the co-occurrence rate of the two identity information under the combination of all the time slices and the control slices according to the index information weighted by every two identity information.
Specifically, the value corresponding to each index information may be 1, and the weights may be different under different time slices and position slices, for example, time slices with small flow rate such as late-night time slices, for example, from 2 am to 4 am, and the weight may be a higher weight such as 1.5, 3, or 4; the time slice with large people flow such as off-duty time, for example, 18 to 19 points, may have a smaller weight such as 0.7, and the position slice also has a smaller weight for the places with large people flow such as subways, intersections, and shopping malls, and the remote places have a larger weight.
In some possible embodiments, the plurality of identity information includes at least two kinds of identity information.
In some possible embodiments, the at least two types of identity information include:
a medium access control MAC address, and/or an international mobile subscriber identity.
Further, the identity information may further include information such as a face feature, an MAC number of the mobile device, an international mobile subscriber identity, a license plate number of the vehicle, and a virtual account.
In some possible embodiments, the determining, based on the co-occurrence rate, a companion relationship between every two identity information includes:
determining that the two identity information with the co-occurrence rate larger than or equal to a preset threshold value have an accompanying relationship.
Referring to fig. 2, fig. 2 is a flowchart of an association relationship determining method for identity information according to another embodiment of the present application. As shown in fig. 2, the method for determining an accompanying relationship of identity information provided in the embodiment of the present application includes:
1. track data normalization
Through standardized processing of data accessed by different sensing devices, the data are processed into a uniform format, and here, places with close positions can be regarded as the same place.
2. Constructing spatio-temporal interval indices
And standard spatiotemporal data is processed into a spatiotemporal index format to be stored by setting a spatiotemporal interval index.
3. Performing spatio-temporal adjoint analysis calculations
And quickly calling space-time trajectory information through space-time interval indexes, determining space-time co-occurrence rate, and calculating based on the space-time co-occurrence rate to complete space-time adjoint analysis.
4. Result output
And outputting a space-time accompanying analysis result.
The method for determining the accompanying relationship of the identity information, provided by the embodiment of the application, acquires the space-time trajectory information of a plurality of identity information, wherein the space-time trajectory information comprises time information and position information when the identity information is monitored each time within a preset time period; carrying out fragmentation processing on time information and position information in the space-time trajectory information; generating index information of each identity information under different time slices and space slices according to the slicing processing result; for every two pieces of identity information, determining the co-occurrence rate of the two pieces of identity information under all combinations of time slices and space slices based on index information of the two pieces of identity information, wherein the co-occurrence rate indicates that the frequency of the two pieces of identity information is monitored under all combinations of time slices and space slices; and determining the adjoint relation of every two identity information based on the co-occurrence rate. Compared with the prior art, the method and the device have the advantages that the co-occurrence rate of the two identity information under the combination of all the time slices and the space slices can be achieved, the accompanying relation of the two identity information is determined based on the co-occurrence rate, the calculation amount required for determining the accompanying relation can be greatly reduced, the waste of resources is avoided, the processing efficiency is improved, the limitation of preset rules is avoided, and the accuracy is high.
Referring to fig. 3, fig. 3 is a schematic structural diagram of an apparatus for determining an association relationship between identity information according to an embodiment of the present disclosure. As shown in fig. 3, the accompanying relation determination apparatus 300 for identity information includes:
an obtaining module 310, configured to obtain spatio-temporal trajectory information of a plurality of identity information, where the spatio-temporal trajectory information includes time information and position information when the identity information is monitored each time within a preset time period;
a slicing module 320, configured to perform slicing processing on the time information and the position information in the spatio-temporal trajectory information;
a generating module 330, configured to generate, according to the result of the fragmentation processing, index information of each identity information in different time fragments and space fragments;
a first determining module 340, configured to determine, for every two identity information, a co-occurrence rate of the two identity information under all combinations of time slices and space slices based on index information of the two identity information, where the co-occurrence rate indicates that frequencies of the two identity information are monitored simultaneously under all combinations of time slices and space slices;
a second determining module 350, configured to determine an accompanying relationship between every two identity information based on the co-occurrence rate.
Further, the first determining module 340 is specifically configured to:
weighting the index information of each identity information under different time slices and space slices according to the importance degrees of different time slices and position slices;
and calculating the co-occurrence rate of the two identity information under the combination of all the time slices and the control slices according to the index information weighted by every two identity information.
Further, the second determining module 350 is specifically configured to:
determining that the two identity information with the co-occurrence rate larger than or equal to a preset threshold value have an accompanying relationship.
Further, the plurality of identity information includes at least two kinds of identity information.
Further, the at least two kinds of identity information include:
a medium access control MAC address, and/or an international mobile subscriber identity.
The device for determining the accompanying relationship of the identity information, provided by the embodiment of the application, is used for acquiring the space-time trajectory information of a plurality of identity information, wherein the space-time trajectory information comprises time information and position information when the identity information is monitored each time in a preset time period; carrying out fragmentation processing on time information and position information in the space-time trajectory information; generating index information of each identity information under different time slices and space slices according to the slicing processing result; for every two pieces of identity information, determining the co-occurrence rate of the two pieces of identity information under all combinations of time slices and space slices based on index information of the two pieces of identity information, wherein the co-occurrence rate indicates that the frequency of the two pieces of identity information is monitored under all combinations of time slices and space slices; and determining the adjoint relation of every two identity information based on the co-occurrence rate. Compared with the prior art, the method and the device have the advantages that the co-occurrence rate of the two identity information under the combination of all the time slices and the space slices can be utilized, the accompanying relation of the two identity information can be determined based on the co-occurrence rate, the calculation amount required for determining the accompanying relation can be greatly reduced, the waste of resources is avoided, the processing efficiency is improved, the limitation of preset rules is avoided, and the accuracy is high.
Please refer to fig. 4, fig. 4 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 4, the electronic device 400 includes a processor 410, a memory 420, and a bus 430.
The memory 420 stores machine-readable instructions executable by the processor 410, when the electronic device 400 runs, the processor 410 communicates with the memory 420 through the bus 430, and when the machine-readable instructions are executed by the processor 410, the steps of the method for determining an accompanying relationship of identity information in the method embodiments shown in fig. 1 and fig. 2 may be performed.
An embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the step of the method for determining an association relationship between identity information in the method embodiments shown in fig. 1 and fig. 2 may be executed.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other ways. The above-described apparatus embodiments are merely illustrative, and for example, the division of the units into only one type of logical function may be implemented in other ways, and for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not implemented. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some communication interfaces, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solutions of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the methods described in the embodiments of the present application. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the exemplary embodiments of the present application, and are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (8)
1. A method for determining an accompanying relationship of identity information, the method comprising:
acquiring space-time track information of a plurality of identity information, wherein the space-time track information comprises time information and position information when the identity information is monitored each time in a preset time period;
carrying out fragmentation processing on time information and position information in the space-time trajectory information;
generating index information of each identity information under different time slices and space slices according to the slicing processing result;
for every two pieces of identity information, determining the co-occurrence rate of the two pieces of identity information under all combinations of time slices and space slices based on index information of the two pieces of identity information, wherein the co-occurrence rate represents the frequency of monitoring the two pieces of identity information simultaneously under all combinations of time slices and space slices, or the co-occurrence rate represents the ratio of the number of times of monitoring the two pieces of identity information simultaneously to the sum of the places where the two pieces of identity information are detected;
the spatiotemporal trajectory data are stored into the same index file according to a spatiotemporal range through the index information, and the identity information stored in one same index file is defined to be spatiotemporal co-occurrence in one spatiotemporal range;
determining an accompanying relation of every two identity information based on the co-occurrence rate;
wherein, for every two identity information, determining the co-occurrence rate of the two identity information under the combination of each time slice and each space slice based on the index information of the two identity information includes:
weighting the index information of each identity information under different time slices and space slices according to the importance degrees of different time slices and position slices;
and calculating the co-occurrence rate of the two identity information under the combination of all time slices and all space slices according to the index information after weighting every two identity information.
2. The method of claim 1, wherein the plurality of identity information comprises at least two identity information.
3. The method of claim 2, wherein the at least two types of identity information comprise:
a medium access control MAC address, and/or an international mobile subscriber identity.
4. The method of claim 1, wherein determining the companion relationship between every two identity information based on the co-occurrence rate comprises:
determining that the two identity information with the co-occurrence rate larger than or equal to a preset threshold value have an accompanying relationship.
5. An apparatus for accompanying relationship determination of identity information, the apparatus comprising:
the system comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring space-time track information of a plurality of identity information, and the space-time track information comprises time information and position information when the identity information is monitored each time in a preset time period;
the fragmentation module is used for carrying out fragmentation processing on the time information and the position information in the space-time trajectory information;
the generating module is used for generating index information of each identity information under different time slices and space slices according to the slice processing result;
a first determining module, configured to determine, for every two identity information, a co-occurrence rate of the two identity information under all combinations of time slices and space slices based on index information of the two identity information, where the co-occurrence rate indicates a frequency of monitoring the two identity information simultaneously under all combinations of time slices and space slices, or the co-occurrence rate indicates a ratio of a number of times that the two identity information is monitored simultaneously to a sum of locations where the two identity information is detected;
the spatiotemporal trajectory data are stored into the same index file according to a spatiotemporal range through the index information, and the identity information stored in one same index file is defined to be spatiotemporal co-occurrence in one spatiotemporal range;
the second determining module is used for determining the adjoint relationship of every two identity information based on the co-occurrence rate;
wherein the first determining module is specifically configured to:
weighting the index information of each identity information under different time slices and space slices according to the importance degrees of different time slices and position slices;
and calculating the co-occurrence rate of the two identity information under all time slices and combinations of the slices according to the index information weighted by every two identity information.
6. The apparatus of claim 5, wherein the second determining module is specifically configured to:
determining that the two identity information with the co-occurrence rate larger than or equal to a preset threshold value have an accompanying relationship.
7. An electronic device, comprising: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating via the bus when the electronic device is running, the processor executing the machine-readable instructions to perform the steps of the method for determining an accompanying relationship of identity information according to any one of claims 1 to 4.
8. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when being executed by a processor, performs the steps of the method for determining an accompanying relationship of identity information according to any one of claims 1 to 4.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104796468A (en) * | 2015-04-14 | 2015-07-22 | 蔡宏铭 | Method and system for realizing instant messaging of people travelling together and travel-together information sharing |
| CN107609107A (en) * | 2017-09-13 | 2018-01-19 | 大连理工大学 | A kind of trip co-occurrence phenomenon visual analysis method based on multi-source Urban Data |
| CN108170834A (en) * | 2018-01-12 | 2018-06-15 | 南京理工大学 | A kind of determining method of mobile target association co-occurrence pattern |
| CN108984561A (en) * | 2017-06-01 | 2018-12-11 | 华为技术有限公司 | Site selecting method and equipment |
| CN109918395A (en) * | 2019-02-19 | 2019-06-21 | 北京明略软件系统有限公司 | One kind of groups method for digging and device |
| CN109947793A (en) * | 2019-03-20 | 2019-06-28 | 深圳市北斗智能科技有限公司 | Analysis method, device and the storage medium of accompanying relationship |
| CN110489400A (en) * | 2019-08-23 | 2019-11-22 | 武汉白虹软件科技有限公司 | A kind of realization people's vehicle acquisition data quasi real time associated algorithm model |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10754913B2 (en) * | 2011-11-15 | 2020-08-25 | Tapad, Inc. | System and method for analyzing user device information |
-
2019
- 2019-11-29 CN CN201911200827.6A patent/CN110909262B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104796468A (en) * | 2015-04-14 | 2015-07-22 | 蔡宏铭 | Method and system for realizing instant messaging of people travelling together and travel-together information sharing |
| CN108984561A (en) * | 2017-06-01 | 2018-12-11 | 华为技术有限公司 | Site selecting method and equipment |
| CN107609107A (en) * | 2017-09-13 | 2018-01-19 | 大连理工大学 | A kind of trip co-occurrence phenomenon visual analysis method based on multi-source Urban Data |
| CN108170834A (en) * | 2018-01-12 | 2018-06-15 | 南京理工大学 | A kind of determining method of mobile target association co-occurrence pattern |
| CN109918395A (en) * | 2019-02-19 | 2019-06-21 | 北京明略软件系统有限公司 | One kind of groups method for digging and device |
| CN109947793A (en) * | 2019-03-20 | 2019-06-28 | 深圳市北斗智能科技有限公司 | Analysis method, device and the storage medium of accompanying relationship |
| CN110489400A (en) * | 2019-08-23 | 2019-11-22 | 武汉白虹软件科技有限公司 | A kind of realization people's vehicle acquisition data quasi real time associated algorithm model |
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