A method, system, terminal and storage medium for evaluating the stay identification of mobile phone signaling data

Abstract

The present application relates to a method, system, terminal and storage medium for stop identification and evaluation of mobile phone signaling data. The method comprises: collecting mobile phone signaling data and corresponding GPS data of a travel target in a travel area; based on the mobile phone signaling data, using a stop identification algorithm to identify the stop activities of the travel target in the travel area; constructing a progressive stop identification and evaluation system based on the spatiotemporal sampling characteristics of the mobile phone signaling data, and evaluating the stop activity identification results of the travel target through the GPS data and the stop identification and evaluation system. The embodiments of the present application can fully consider the noise characteristics and interference sources of mobile phone signaling data during stop identification, provide a systematic verification and evaluation for the stop identification algorithm of mobile phone signaling data, and provide key technical support for many studies based on mobile phone signaling data.

Description

Technical Field

[0001] The present application belongs to the technical field of mobile phone signaling data processing, and in particular, relates to a method, system, terminal and storage medium for stop identification and evaluation of mobile phone signaling data. Background Art

[0002] Mobile phone signaling data is the communication data between mobile phone users and transmitting base stations or micro stations, and it has become the most mainstream big data source. At present, there are endless studies on mobile phone signaling data, but the mobile phone signaling data does not clearly indicate the user's activity start time, activity end time, activity location and other stop activity information. Therefore, it is necessary to process the activity information in the mobile phone signaling data through the stop recognition algorithm. Mobile phone signaling data is collected based on communication base station positioning technology. Due to the particularity of this sampling, data sampling is uneven and data noise occurs, which greatly increases the difficulty and error of stop activity recognition.

[0003] To verify the recognition effect of the stop recognition algorithm on the stop activities in the mobile phone signaling data, a set of targeted evaluation methods is needed. In the existing research on mobile phone signaling data, most of the evaluation methods for the recognition effect of stop activities are based only on subjective perception as a reference, and only a small number of studies use the work and residence data in the census to evaluate and verify the reliability of stop recognition of mobile phone signaling data. However, considering the diversity of human travel activities, it is not universal to use only work and residence data for stop recognition evaluation. At the same time, due to data collection restrictions and privacy protection restrictions, it is difficult for the above-mentioned studies to obtain the real verification data set corresponding to the mobile phone signaling data, and it is impossible to verify the reliability with the help of the correct stop points of individuals. However, the existing public data sets cannot serve as data support for the stop recognition algorithm of mobile phone signaling data. Therefore, it is necessary to provide an evaluation system for the characteristics of mobile phone signaling data to provide key technical support for many studies based on mobile phone signaling data. Summary of the invention

[0004] The present application provides a method, system, terminal and storage medium for dwell identification and evaluation of mobile phone signaling data, aiming to solve at least one of the above-mentioned technical problems in the prior art to a certain extent.

[0005] In order to solve the above problems, this application provides the following technical solutions:

[0006] A dwell identification and evaluation method for mobile phone signaling data, comprising:

[0007] Collect mobile phone signaling data and corresponding GPS data of the travel target within the travel area;

[0008] Based on the mobile phone signaling data, a stay recognition algorithm is used to identify the stay activities of the travel target in the travel area;

[0009] According to the spatiotemporal sampling characteristics of mobile phone signaling data, a progressive stop identification and evaluation system is constructed, and the stop activity identification results of the travel target are evaluated through the GPS data and the stop identification and evaluation system.

[0010] The technical solution adopted by the embodiment of the present application also includes: the collected mobile phone signaling data of the travel target in the travel area and the corresponding GPS data are specifically:

[0011] The GPS data of the travel target is obtained through a mobile phone positioning system or a GPS locator.

[0012] The technical solution adopted by the embodiment of the present application also includes: the collection of mobile phone signaling data of the travel target in the travel area and the corresponding GPS data also includes:

[0013] The stop activities in the GPS data are marked according to the travel log of the travel target, and the mobile phone signaling data is preprocessed in combination with the GPS data; the preprocessing includes interpolating or abandoning missing values, redundant values ​​and / or discrete points of the mobile phone signaling data.

[0014] The technical solution adopted by the embodiment of the present application also includes: the collection of mobile phone signaling data of the travel target in the travel area and the corresponding GPS data also includes:

[0015] Performing base station unit verification on the mobile phone signaling data and GPS data according to the base station distribution data in the travel area, deleting abnormal values ​​outside the travel area in the mobile phone signaling data and GPS data, and calculating the statistical characteristics of the GPS data at the time level and the space level;

[0016] The statistical characteristics at the time level include travel activity type distribution, travel activity time distribution and stay activity time distribution;

[0017] The statistical characteristics at the spatial level include the spatial distribution of stay locations and the spatial distribution of travel distances.

[0018] The technical solution adopted in the embodiment of the present application also includes: the stay identification algorithm includes SMoT, SMUoT or TwoStages&MAD.

[0019] The technical solution adopted by the embodiment of the present application also includes: constructing a progressive stay identification and evaluation system based on the spatiotemporal sampling characteristics of the mobile phone signaling data, and evaluating the stay activity identification result of the travel target through the GPS data and the stay identification and evaluation system. Specifically:

[0020] Select application scenarios, evaluation methods, evaluation indicators and evaluation parameters for the mobile phone signaling data stay identification to construct a stay identification evaluation system for the mobile phone signaling data stay identification algorithm, and evaluate the stay activity identification results from three perspectives: spatial discrimination, space-time state discrimination and space-time object discrimination;

[0021] The spatial discrimination is used to determine whether the spatial position of the travel target in the stop activity is correct; the evaluation method of the spatial discrimination is to determine whether the stop point identified by the stop recognition algorithm is adjacent to the spatial range of the correct stop point, and the evaluation index of the spatial discrimination is the proportion of the number of correct stop point samples within a given spatial range;

[0022] The space-time state discrimination is used to identify the spatial location of the travel target in the stop activity and the corresponding proportion of the stop duration; the evaluation method of the space-time state discrimination is to determine whether the stop point identified by the stop recognition algorithm is adjacent to the spatial range of the correct stop point, and the ratio of the stop duration of the identified stop point to the total duration of the day; the evaluation index of the space-time state discrimination is the proportion of the number of correct stop point samples within a given spatial range and the proportion of the cumulative duration of the stop activity at the correct stop point;

[0023] The space-time object discrimination is used to identify the spatial location and start and end time of the travel target in the stop activity; the evaluation method of the space-time object discrimination is to determine whether the spatial range and start and end time of the stop point identified by the stop recognition algorithm are adjacent to the correct stop point; the evaluation index of the space-time object discrimination is the proportion of the number of correct stop point samples within a given spatial range and time range.

[0024] Another technical solution adopted by the embodiment of the present application is: a stay identification and evaluation system for mobile phone signaling data, comprising:

[0025] Data collection module: used to collect mobile phone signaling data and corresponding GPS data of the travel target in the travel area;

[0026] A stay identification module: used to identify the stay activities of the travel target in the travel area by using a stay identification algorithm based on the mobile phone signaling data;

[0027] The stay evaluation module is used to construct a progressive stay identification and evaluation system according to the spatiotemporal sampling characteristics of mobile phone signaling data, and evaluate the stay activity identification results of the travel target through the GPS data and the stay identification and evaluation system.

[0028] Another technical solution adopted by the embodiment of the present application is: a terminal, the terminal includes a processor and a memory coupled to the processor, wherein:

[0029] The memory stores program instructions for implementing the dwell identification and evaluation method for mobile phone signaling data;

[0030] The processor is configured to execute the program instructions stored in the memory to control dwell identification evaluation for mobile phone signaling data.

[0031] Another technical solution adopted by the embodiment of the present application is: a storage medium storing program instructions executable by a processor, wherein the program instructions are used to execute the dwell identification and evaluation method for mobile phone signaling data.

[0032] Compared with the prior art, the beneficial effect of the embodiment of the present application is that the stop identification and evaluation method for mobile phone signaling data in the embodiment of the present application collects the mobile phone signaling data and the corresponding GPS data of the travel target, and uses the stop identification algorithm based on the mobile phone signaling data to identify the stop activities of the travel target in the travel area, and constructs a progressive stop identification and evaluation system based on the spatiotemporal sampling characteristics of the mobile phone signaling data, and evaluates the stop activity identification results from multiple angles such as spatial discrimination, space-time state discrimination, and space-time object discrimination based on the GPS data and the evaluation system. The embodiment of the present application can fully consider the noise characteristics and interference sources of mobile phone signaling data during stop identification, provide a systematic verification and evaluation for the mobile phone signaling data stop identification algorithm, and provide key technical support for many studies based on mobile phone signaling data. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 is a flow chart of a method for evaluating the stay identification of mobile phone signaling data according to an embodiment of the present application;

[0034] Figure 2 This is a schematic diagram of the structure of a dwell identification and evaluation system for mobile phone signaling data according to an embodiment of the present application;

[0035] Figure 3 This is a schematic diagram of the terminal structure of an embodiment of the present application;

[0036] Figure 4 A schematic diagram of the structure of a storage medium according to an embodiment of the present application. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0038] See also Figure 1, is a flow chart of a method for evaluating the stay of mobile phone signaling data in an embodiment of the present application. The method for evaluating the stay of mobile phone signaling data in an embodiment of the present application comprises the following steps:

[0039] S1: Collect the original mobile phone signaling data and corresponding GPS data of the travel target;

[0040] In this step, the GPS data of the travel target can be obtained through a mobile phone positioning system or a GPS locator.

[0041] S2: Mark the stop activities in the GPS data according to the travel log of the travel target, and pre-process the original mobile phone signaling data in combination with the GPS data to generate a mobile phone signaling data set and a GPS verification data set for the mobile phone signaling data;

[0042] In this step, the preprocessing of the original mobile phone signaling data includes interpolating or discarding missing values, redundant values ​​and / or discrete points of the original mobile phone signaling data.

[0043] S3: Perform base station unit verification on the mobile phone signaling dataset and the GPS verification dataset according to the base station distribution data of the travel area (i.e., delete the outliers outside the travel area in the dataset), and calculate the statistical characteristics of the GPS verification dataset at the temporal and spatial levels at the population mobility index level;

[0044] In this step, the statistical characteristics of the GPS verification data set at the time level are calculated, including the distribution of travel activity types, travel activity time distribution, and stay activity time distribution. The statistical characteristics of the GPS verification data set at the spatial level are calculated, including the spatial distribution of stay locations and the spatial distribution of travel distances. The statistical characteristics are used to provide a reference for the matching distance threshold and matching time threshold for evaluating the stay activity recognition results.

[0045] S4: Based on the mobile phone signaling dataset, a stay recognition algorithm is used to identify the stay activities of the travel target in the travel area;

[0046] In this step, the stay recognition algorithms include but are not limited to SMoT, SMUoT, TwoStages&MAD, etc. The recognized stay activities include the stay space location of the travel target, the start and end time of the stay, and the stay duration.

[0047] S5: Based on the spatiotemporal sampling characteristics of mobile phone signaling data, a progressive stop identification and evaluation system is constructed, and the stop activity identification results of travel targets are evaluated through the GPS verification data set and the stop identification and evaluation system;

[0048] In this step, in view of the collection characteristics and application scenarios of mobile phone signaling data, the embodiment of the present application selects application scenarios, evaluation methods, evaluation indicators, evaluation parameters (including a given spatial range and a given time range) for mobile phone signaling data stop identification, and constructs a mobile phone signaling data stop identification algorithm evaluation system based on GPS data to progressively evaluate the mobile phone signaling data stop activity identification results, and evaluates the stop activity identification results from three perspectives: spatial discrimination, space-time state discrimination, and space-time object discrimination. Among them:

[0049] Spatial discrimination is used to determine whether the spatial location of the travel target in the stop activity is correct; the evaluation method of spatial discrimination is to determine whether the spatial range of the identified stop point and the correct stop point are adjacent (whether the spatial distance between the identified stop point and the correct stop point is within the set distance range), and its evaluation index is the proportion of the number of correct stop point samples within a given spatial range.

[0050] Spatial-temporal state discrimination is used to identify the spatial location of the travel target in the stop activity and the corresponding proportion of the stop duration; the evaluation method of spatial-temporal state discrimination is to determine whether the spatial range of the identified stop point is adjacent to the correct stop point, and the ratio of the stop duration of the identified stop point to the whole day. The evaluation indicators are the proportion of the number of correct stop point samples within a given spatial range and the proportion of the cumulative duration of the stop activity at the correct stop point.

[0051] Spatial-temporal object discrimination is used to identify the spatial location and start and end time of the travel target during the stop activity; the evaluation method of spatial-temporal object discrimination is to determine whether the spatial range of the identified stop point and the correct stop point and the start and end time of the stop are adjacent, and its evaluation index is the proportion of the number of correct stop point samples within a given spatial range and within a given time range.

[0052] In order to verify the feasibility and effectiveness of the embodiments of the present application, the SMoT, SMUoT and TwoStages&MAD stay recognition algorithms were reproduced on the constructed mobile phone signaling data set to obtain the mobile phone signaling data stay recognition results; then the mobile phone signaling data stay recognition algorithm evaluation system constructed by the embodiments of the present application was used to evaluate the mobile phone signaling data stay recognition results from three perspectives: spatial discrimination, space-time discrimination, and space-time object discrimination. The evaluation results show the differences between the stay points identified by each stay recognition algorithm and the active stay points of the original mobile phone signaling data, thereby providing a systematic and accurate verification and evaluation for the mobile phone signaling data stay recognition algorithm.

[0053] The stop identification and evaluation method for mobile phone signaling data in the embodiment of the present application collects the mobile phone signaling data and the corresponding GPS data of the travel target, uses a stop identification algorithm based on the mobile phone signaling data to identify the stop activities of the travel target in the travel area, and constructs a progressive stop identification and evaluation system based on the spatiotemporal sampling characteristics of the mobile phone signaling data, and evaluates the stop activity identification results from multiple angles such as spatial discrimination, space-time state discrimination, and space-time object discrimination based on the GPS data and the evaluation system. The embodiment of the present application can fully consider the noise characteristics and interference sources of mobile phone signaling data during stop identification, provide a systematic verification and evaluation for the mobile phone signaling data stop identification algorithm, and provide key technical support for many studies based on mobile phone signaling data.

[0054] See also Figure 2 , is a schematic diagram of the structure of the stop identification and evaluation system for mobile phone signaling data in an embodiment of the present application. The stop identification and evaluation system 40 for mobile phone signaling data in an embodiment of the present application includes:

[0055] Data collection module 41: used to collect mobile phone signaling data and corresponding GPS data of the travel target in the travel area;

[0056] The stay identification module 42 is used to identify the stay activities of the travel target in the travel area by using a stay identification algorithm based on the mobile phone signaling data;

[0057] The stay evaluation module 43 is used to construct a progressive stay identification evaluation system according to the spatiotemporal sampling characteristics of the mobile phone signaling data, and evaluate the stay activity identification result of the travel target through the GPS data and the stay identification evaluation system.

[0058] See also Figure 3 , is a schematic diagram of the terminal structure of an embodiment of the present application. The terminal 50 includes a processor 51 and a memory 52 coupled to the processor 51.

[0059] The memory 52 stores program instructions for implementing the above-mentioned dwell identification and evaluation method for mobile phone signaling data.

[0060] The processor 51 is used to execute program instructions stored in the memory 52 to control the dwell identification evaluation for the mobile phone signaling data.

[0061] The processor 51 may also be referred to as a CPU (Central Processing Unit). The processor 51 may be an integrated circuit chip having the ability to process signals. The processor 51 may also be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0062] See also Figure 4 , which is a schematic diagram of the structure of the storage medium of the embodiment of the present application. The storage medium of the embodiment of the present application stores a program file 61 that can implement all the above methods, wherein the program file 61 can be stored in the above storage medium in the form of a software product, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) or a processor (processor) to execute all or part of the steps of each implementation method of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, or terminal devices such as a computer, a server, a mobile phone, and a tablet.

[0063] The above description of the disclosed embodiments enables professionals and technicians in the field to implement or use the present application. Various modifications to these embodiments will be apparent to professionals and technicians in the field, and the general principles defined in this application can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown in the present application, but will conform to the widest range consistent with the principles and novel features disclosed in the present application.

Claims

1. A dwell identification and evaluation method for mobile phone signaling data, characterized in that: include: Collect mobile phone signaling data and corresponding GPS data of the travel target within the travel area; Based on the mobile phone signaling data, a stay recognition algorithm is used to identify the stay activities of the travel target in the travel area; according to the spatiotemporal sampling characteristics of the mobile phone signaling data, a progressive stay recognition evaluation system is constructed, and the stay activity recognition results of the travel target are evaluated through the GPS data and the stay recognition evaluation system; wherein: The collection of mobile phone signaling data and corresponding GPS data of the travel target in the travel area also includes: Marking the stop activities in the GPS data according to the travel log of the travel target, and preprocessing the mobile phone signaling data in combination with the GPS data; the preprocessing includes interpolating or discarding missing values, redundant values ​​and / or discrete points of the mobile phone signaling data; The collection of mobile phone signaling data and corresponding GPS data of the travel target in the travel area also includes: Performing base station unit verification on the mobile phone signaling data and GPS data according to the base station distribution data in the travel area, deleting abnormal values ​​outside the travel area in the mobile phone signaling data and GPS data, and calculating the statistical characteristics of the GPS data at the time level and the space level; The statistical characteristics at the time level include travel activity type distribution, travel activity time distribution and stay activity time distribution; The statistical characteristics at the spatial level include the spatial distribution of the stay location and the spatial distribution of the travel distance; The progressive stop identification and evaluation system is constructed based on the spatiotemporal sampling characteristics of the mobile phone signaling data, and the stop activity identification result of the travel target is evaluated by the GPS data and the stop identification and evaluation system as follows: Select application scenarios, evaluation methods, evaluation indicators and evaluation parameters for the mobile phone signaling data stay identification to construct a stay identification evaluation system for the mobile phone signaling data stay identification algorithm, and evaluate the stay activity identification results from three perspectives: spatial discrimination, space-time state discrimination and space-time object discrimination; The spatial discrimination is used to determine whether the spatial position of the travel target in the stop activity is correct; the evaluation method of the spatial discrimination is to determine whether the stop point identified by the stop recognition algorithm is adjacent to the spatial range of the correct stop point, and the evaluation index of the spatial discrimination is the proportion of the number of correct stop point samples within a given spatial range; The space-time state discrimination is used to identify the spatial location of the travel target in the stop activity and the corresponding proportion of the stop duration; the evaluation method of the space-time state discrimination is to determine whether the stop point identified by the stop recognition algorithm is adjacent to the spatial range of the correct stop point, and the ratio of the stop duration of the identified stop point to the total duration of the day; the evaluation index of the space-time state discrimination is the proportion of the number of correct stop point samples within a given spatial range and the proportion of the cumulative duration of the stop activity at the correct stop point; The space-time object discrimination is used to identify the spatial location and start and end time of the travel target in the stop activity; the evaluation method of the space-time object discrimination is to determine whether the spatial range and start and end time of the stop point identified by the stop recognition algorithm are adjacent to the correct stop point; the evaluation index of the space-time object discrimination is the proportion of the number of correct stop point samples within a given spatial range and time range.

2. The method for evaluating the dwelling recognition of mobile phone signaling data according to claim 1, characterized in that: The collected mobile phone signaling data of the travel target in the travel area and the corresponding GPS data are as follows: The GPS data of the travel target is obtained through a mobile phone positioning system or a GPS locator.

3. The method for evaluating the dwell identification of mobile phone signaling data according to claim 1, characterized in that: The stay identification algorithm includes SMoT, SMUoT or TwoStages&MAD.

4. A system for identifying and evaluating the stay of mobile phone signaling data using the method for identifying and evaluating the stay of mobile phone signaling data according to claim 1, characterized in that: include: Data collection module: used to collect mobile phone signaling data and corresponding GPS data of the travel target in the travel area; A stay identification module: used to identify the stay activities of the travel target in the travel area by using a stay identification algorithm based on the mobile phone signaling data; The stop evaluation module is used to construct a progressive stop identification and evaluation system according to the spatiotemporal sampling characteristics of mobile phone signaling data, and evaluate the stop activity identification results of the travel target through the GPS data and the stop identification and evaluation system.

5. A terminal, characterized in that: The terminal includes a processor and a memory coupled to the processor, wherein: The memory stores program instructions for implementing the method for dwell identification and evaluation of mobile phone signaling data according to any one of claims 1 to 3; The processor is configured to execute the program instructions stored in the memory to control dwell identification evaluation for mobile phone signaling data.

6. A storage medium, characterized in that: The device stores program instructions executable by a processor, wherein the program instructions are used to execute the dwell identification and evaluation method for mobile phone signaling data as described in any one of claims 1 to 3.

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