User itinerary recognition method and apparatus, electronic device, and readable medium

Abstract

The application provides a user travel identification method and device, electronic equipment and readable medium. The method comprises: obtaining communication record data of a target user and engineering parameter data of a target base station, the communication record data comprising a communication time, and the engineering parameter data comprising base station scene and base station position information of the target base station, the base station scene representing a travel mode of the target user; performing data association on the communication record data and the engineering parameter data to obtain associated data of the target user; grouping the associated data according to the target position and the communication time, the base station scene and the base station position information in the associated data to obtain data groups, each data group corresponding to a base station scene; and determining a travel of the target user according to the base station scene corresponding to the data group to which the target user belongs. The method can reduce the input cost of travel identification and improve the statistical efficiency.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of computer, and particularly relates to a user travel identification method and device, electronic equipment and readable medium. BACKGROUND

[0002] With the development of economy at home and abroad, tourism has become an economic pillar industry, and a large number of tourists travel in various places in China every year. In order to manage tourists and plan and invest in related facilities, and to deal with emergency events with a large range of influence, tourism, transportation, entry and exit management departments and various related organizations need to have a clear understanding of the travel of tourists.

[0003] At present, the statistical method of the travel of tourists mainly includes the following modes: the registered tourist information is summarized and statistically, the tourists actively report, and the inspection points are set at key entrances and exits for manual inspection.

[0004] The above-mentioned mode needs a large amount of manual investment and active cooperation of tourists, has high investment cost, low statistical efficiency, and often has repeated data between multiple data sources, so that the final statistical result is inaccurate. SUMMARY

[0005] Based on the above technical problems, the present application provides a user travel identification method and device, electronic equipment and readable medium, so as to reduce the investment cost of travel identification, improve the statistical efficiency, and use the same data source to avoid the repeated data, and improve the statistical accuracy.

[0006] Other characteristics and advantages of the present application will become apparent from the following detailed description, or will be learned by practice of the present application.

[0007] According to one aspect of an embodiment of the present application, a user travel identification method is provided, comprising:

[0008] Obtaining communication record data of a target user and engineering parameter data of a target base station, the communication record data comprising communication time, and the engineering parameter data comprising base station scene and base station position information of the target base station, the base station scene representing a travel mode of the target user;

[0009] Data association is performed on the communication record data and the engineering parameter data to obtain associated data of the target user;

[0010] The associated data is grouped according to a target position and the communication time, the base station scene and the base station position information in the associated data, to obtain data groups, each data group corresponding to a base station scene;

[0011] Determine a travel of the target user according to a corresponding base station scenario in a data group to which the target user belongs.

[0012] In some embodiments of the present application, based on the above technical solution, the grouping of the associated data according to the target position, the communication time, the base station scenario and the base station position information in the associated data comprises:

[0013] According to the communication time, the base station position information and the target position in the associated data, data filtering is performed on the associated data to obtain filtered data of the target user.

[0014] According to the communication time and the base station scenario of the filtered data, the filtered data is grouped to obtain the data group.

[0015] In some embodiments of the present application, based on the above technical solution, the data filtering of the associated data according to the communication time, the base station position information and the target position in the associated data to obtain the filtered data of the target user comprises:

[0016] According to the communication time and the base station position information, a first passing position corresponding to a first preset time period and a second passing position corresponding to a second preset time period of the target user are determined, the first passing position and the second passing position both indicate positions reached by the target user, and the second preset time period is a time period before the first preset time period.

[0017] If the first passing position indicates that the target user has reached the target position and the second passing position indicates that the target user has not reached the target position, the filtered data of the target user is generated according to the associated data corresponding to the target user.

[0018] In some embodiments of the present application, based on the above technical solution, the grouping of the filtered data according to the communication time and the base station scenario of the filtered data to obtain the data group comprises:

[0019] According to the communication time and the base station scenario in the filtered data, a reaching scenario corresponding to the filtered data is determined, and the reaching scenario represents a base station scenario earliest passed by the target user.

[0020] According to the reaching scenario, the filtered data is grouped to generate the data group.

[0021] In some embodiments of the present application, based on the above technical solution, the communication record data comprises a cell identifier, and the engineering parameter data comprises a base station identifier; the data association of the communication record data and the engineering parameter data to obtain the association data of the target user comprises:

[0022] obtaining the cell identifier in the communication record data and the base station identifier in the engineering parameter data;

[0023] if the cell identifier matches the base station identifier, associating the communication record data with the engineering parameter data to generate association data.

[0024] In some embodiments of the present application, based on the above technical solution, after determining the travel of the target user according to the corresponding base station scene in the data group to which the target user belongs, the method further comprises:

[0025] obtaining the number of target users corresponding to each data group according to the data in each data group;

[0026] determining and displaying the user distribution result in the base station scene according to the number of target users corresponding to each data group.

[0027] In some embodiments of the present application, based on the above technical solution, after determining the travel of the target user according to the corresponding base station scene in the data group to which the target user belongs, the method further comprises:

[0028] if the travel of the target user matches the preset travel and the communication time of the target user is within the preset time range, sending an alarm prompt message to the target user according to the communication record data.

[0029] According to another aspect of the embodiments of the present application, a user travel identification device is provided, comprising:

[0030] a data acquisition module configured to acquire communication record data of a target user and engineering parameter data of a target base station, wherein the communication record data comprises a communication time, the engineering parameter data comprises a base station scene of the target base station and base station location information, and the base station scene represents a travel mode of the target user;

[0031] a data association module configured to associate the communication record data and the engineering parameter data to obtain association data of the target user;

[0032] a data grouping module configured to group the association data according to a target location, the communication time, the base station scene, and the base station location information in the association data to obtain data groups, each data group corresponding to a base station scene.

[0033] a travel determination module, configured to determine a travel of the target user according to a corresponding base station scenario in a data group to which the target user belongs.

[0034] According to an aspect of an embodiment of the present application, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute the user travel identification method as in the above technical solutions via executing the executable instructions.

[0035] According to an aspect of an embodiment of the present application, a computer readable storage medium is provided, having a computer program stored thereon, when the computer program is executed by a processor, the user travel identification method as in the above technical solutions is implemented.

[0036] In the embodiments of the present application, by associating and grouping the communication record data and the engineering parameter data, the travel of the target user is determined, without the active cooperation of the user and a large amount of manual visit statistics, so that the input cost of travel identification is reduced, the statistical efficiency is improved, the same data source is adopted, the situation of repeated data is avoided, and the statistical accuracy is improved.

[0037] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present application. BRIEF DESCRIPTION OF DRAWINGS

[0038] The drawings herein are incorporated into the description and form part of the description, show embodiments consistent with the present application, and together with the description serve to explain the principles of the present application. It is obvious that the drawings in the following description are only some embodiments of the present application, and those skilled in the art can obtain other drawings from these drawings without creative labor. In the drawings:

[0039] Figure 1 a schematic diagram of an exemplary physical architecture in an application scenario is schematically shown;

[0040] Figure 2 a schematic diagram of a system module structure in an embodiment of the present application is shown;

[0041] Figure 3 a flowchart of a user travel identification in an embodiment of the present application is shown;

[0042] Figure 4 a schematic diagram of an overall application flow in an embodiment of the present application is shown;

[0043] Figure 5 a block diagram of a user travel identification device in an embodiment of the present application is schematically shown;

[0044] Figure 6 A structural diagram of a computer system of an electronic device suitable for implementing embodiments of the present application is shown. DETAILED DESCRIPTION

[0045] Example implementations will now be described more fully with reference to the accompanying drawings. Example implementations may, however, be implemented in many different forms and should not be construed as limited to the examples set forth herein; rather, these implementations are provided so that this disclosure will be thorough and complete, and will fully convey the scope of example implementations to those skilled in the art.

[0046] Moreover, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the application. One skilled in the relevant art will recognize, however, that the

[0047] The block diagrams in the drawings show only the functionality of the features and can not imply a necessity of any particular physical or architectural arrangement. That is, the functionality of the features can be implemented in software, hardware, or a combination thereof, and can be implemented in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.

[0048] The flow diagrams shown in the drawings are merely examples of possible flow diagrams and are not necessarily meant to include all of the steps and operations, nor are the steps and operations necessarily meant to be performed in the order shown. For example, some steps and operations can be broken down further, while some steps and operations can be combined or partially combined, and thus the actual order of performance can vary from that shown.

[0049] It should be understood that the present application can be applied to scenarios such as passenger statistics, flow surveys, or epidemic prevention control, which need to count and master information such as the number and itinerary of passengers. Specifically, taking the scenario of epidemic prevention control as an example, for example, the personnel flow visiting a key area within a week is needed, then through the scheme of the present application, the communication record data of the user within a week can be collected, and the engineering parameter data of the base station of the traffic mode that can cover the way to the key area can be collected, for example, the base station near the bus station, the base station near the highway intersection, the base station near the train station, and the base station near the airport, etc. Subsequently, according to the communication record data and the engineering parameter data, the communication record data within a week is analyzed, so as to obtain the number of personnel corresponding to each different traffic mode, thereby obtaining the statistical data of the personnel flow visiting the key area.

[0050] The physical architecture of the system for user trip identification in the embodiments of the present application is introduced as follows. For the convenience of introduction, please refer to Figure 1 , Figure 1 The schematic diagram of the exemplary physical architecture in one application scenario is shown. As shown in Figure 1 It can be seen that the application scenario includes a server, a plurality of target base stations and a plurality of mobile terminals. The base station is usually a base station capable of covering a key area to be monitored. One key area can be covered by a plurality of base stations, and these base stations can all be considered as target base stations. When the user terminal moves to the key area with the user, the user terminal carried by the user will be connected to the target base station and communicate through the target base station. The server communicates with the target base station to collect the communication record data and the engineering parameter data of the base station. The communication record data can also be obtained through other channels, for example, through a data server to obtain the historically stored communication record data. In one embodiment, the communication record data and the engineering parameter data can be obtained from a dedicated data server without the need to communicate with the actual base station.

[0051] Figure 1 The server shown in can be a server, a server cluster including a plurality of servers or a cloud server. In one embodiment, no terminal device can be used in the system architecture, and the operations performed by the terminal device are run by the background service on the server or by a dedicated server.

[0052] It can be understood that Figure 1 The scenario shown in is only an example of the scenario to which the scheme of the present application is applied, and other suitable network structures can be used in the actual application scenario, for example, a proxy server and a multi-level network are added, and the present application does not limit this.

[0053] Figure 2 The schematic diagram of the system module structure in the embodiments of the present application is shown. The system module structure can be run in the physical architecture shown in and is usually run by the server in Figure 1 As shown in Figure 2 , the system module structure includes a database module, a data cleaning module and a data application module. The database module is responsible for the collection and storage of the deep packet inspection data and the collection and storage of the engineering parameter data of the base station. The data cleaning module is responsible for cleaning the data of the database according to the cleaning algorithm and maintaining the result data generated after cleaning. The data application module is used to form application data according to the generated cleaning data and different combination aggregation modes and is used in actual applications. Figure 2

[0054] The technical scheme provided by the present application is described in detail in combination with the specific embodiments.​

[0055] Referring to Figure 3 , Figure 3 A flowchart of a user travel identification method according to an embodiment of the present application is shown. The method can be applied to a user terminal as described above and executed by a server on the user terminal. The method can include the following steps S301-S304:

[0056] In step S301, communication record data of a target user and engineering parameter data of a target base station are obtained. The communication record data includes communication time, and the engineering parameter data includes base station scene and base station location information of the target base station, the base station scene representing a travel mode of the target user.

[0057] The target user generally refers to a user meeting a preset condition, which can be a specific particular user or a plurality of users meeting the condition. For example, the target user can be a user who has arrived in a city in the last month or a user who has visited a province in the first week of a month. The target base station is generally determined according to a range to be counted. For example, to count users visiting a city, the target base station can be determined as a base station covering various routes into the city. The communication record data refers to record information generated in the process of using a terminal. The communication record data can include data generated by a user actively communicating, and can also include data recorded when a terminal automatically reports a state, automatically operates a cell switching, etc. The communication record data includes communication time, and the engineering parameter data includes base station scene and base station location information of the target base station. It can be understood that the communication record data generally also includes other information, such as a terminal user identification code, a mobile device identification, a network access identification, a base station connected by communication, and a network address, etc. The engineering data of the base station also includes information for identifying the base station and information for identifying a cell of the base station. The base station scene represents a travel mode of the target user and is determined according to a location of the base station. For example, a base station near an airport has an airport as the base station scene, and a base station near a highway intersection has a highway as the base station scene. The base station scene can also represent a scene of an area covered by the base station, such as a hospital, a school, a station, a residence, etc.

[0058] In step S302, the communication record data and the engineering parameter data are associated to obtain associated data of the target user.

[0059] The user travel identification system data correlates the communication record data with the engineering parameter data. The purpose of the data correlation is to associate each piece of communication record data with the engineering parameter data of the base station on which the communication relies, so that the area in which the user terminal is located at the time of the communication record data communication can be determined, and thus the location of the user can be determined. It will be appreciated that the communication record data will include data for multiple users, and each user can correspond to multiple pieces of communication record data, and each piece of communication record data can find the corresponding base station and engineering parameter data.

[0060] In one embodiment, the target base stations can be selected according to the statistical range and purpose. When data correlation is performed, if a communication record cannot find corresponding information in the selected base stations, the communication record can be ignored, so as to preliminarily filter the communication record data.

[0061] Step S303, according to the target location and the communication time, the base station scene, and the base station location information in the association data, the association data is grouped to obtain data groups, and each data group corresponds to a base station scene.

[0062] Specifically, the target location refers to the location that needs to be counted, which can refer to a range, such as a province, a city, a residential area, etc. The grouping process mainly includes grouping the association data according to the grouping conditions. The association data can be filtered before grouping. The grouping conditions can be set according to the identification purpose, and are usually grouped according to different base station scenes, and on the basis of grouping according to the scenes, the grouping can be further performed according to different base station locations, according to the communication time, etc. Different data groups can correspond to the same base station scene, for example, in the case of grouping according to the time period, the grouping data of the first week of a month corresponds to the hospital and the school, and the grouping data of the second week still corresponds to the hospital and the school.

[0063] Step S304, according to the corresponding base station scene in the data group to which the target user belongs, the travel of the target user is determined.

[0064] Specifically, the identification of the itinerary of a specific user can be determined according to the data grouping. The communication record data corresponding to the target user is grouped into one or more data groupings, and the itinerary of the target user can be determined according to the corresponding base station scene in the data grouping. For example, the target location is Guangdong Province, the communication record data corresponding to the target user is grouped into three data groupings, and the corresponding scenes are airport, high-speed rail and highway, respectively. It can be determined that the user's travel mode in Guangdong Province is airplane, high-speed rail and vehicle. According to the communication time and the detailed information in the engineering parameter data of the base station, the detailed travel formation of the user can be further determined. For example, according to the time in the communication record data of a record, it is 15th, the base station area information in the engineering parameter data is Shenzhen City, and the base station scene is high-speed rail. It can be determined that the user arrives in or leaves Shenzhen by high-speed rail on 15th. Combined with the records of the user on other dates, the further travel trajectory of the user can be determined. For example, the base station area information in the data of the user after that changes to Guangzhou City, and it can be determined that the user leaves Shenzhen by high-speed rail on 15th and arrives in Guangzhou.

[0065] In the embodiments of the present application, by associating and grouping the communication record data and the engineering parameter data, the itinerary of the target user is determined, without the active cooperation of the user and a large amount of manual visit statistics, the input cost of itinerary identification is reduced, the statistical efficiency is improved, the same data source is used, the situation of repeated data is avoided, and the statistical accuracy is improved.

[0066] In an embodiment of the present application, based on the above technical solution, the step S303 of grouping the association data according to the target location, the communication time, the base station scene and the base station location information in the association data to obtain the data grouping can include the following steps:

[0067] According to the communication time, the base station location information and the target location in the association data, the association data is data filtered to obtain the filtered data of the target user;

[0068] According to the communication time and the base station scene of the filtered data, the filtered data is grouped to obtain the data grouping.

[0069] Specifically, a time range can be set for the communication time and the association data can be filtered according to matching of the target location and the base station location information. For example, the communication record data within the last month can be filtered according to the time condition. The target location and the base station location information are usually set in correspondence, for example, the base station location information can include information at various levels such as province, city, administrative district, etc., and the target location is also set at these levels in the base station location information. The filtered data can be obtained according to the matching result of the base station location information of the association data and the target location.

[0070] For the filtered data, data grouping can be obtained according to the communication time and the base station scene. Specifically, in the grouping, the filtered data corresponding to each base station scene in different time periods can be grouped. In an embodiment, the data of the same user can be merged or considered, and only the data corresponding to the target location with the earliest time is retained. For example, the target location is a certain residential area, a user enters and exits the residential area multiple times within a day, thereby generating multiple association data corresponding to the residential area, and only the association data with the earliest or latest time is retained to represent the travel situation of the user.

[0071] In the embodiments of the present application, for the association data, filtering is performed according to the communication time, the base station location information and the target location, and further data grouping is performed, which can effectively reduce the number of data grouping and improve the calculation efficiency.

[0072] In an embodiment of the present application, based on the above technical solution, the above step of filtering the association data according to the communication time, the base station location information and the target location to obtain the filtered data of the target user can include the following steps:

[0073] According to the communication time and the base station location information, a first passing location corresponding to the target user within a first preset time period and a second passing location corresponding to the target user within a second preset time period are determined, the first passing location and the second passing location both indicate a location reached by the target user, and the second preset time period is a time period before the first preset time period;

[0074] If the first passing location indicates that the target user has reached the target location and the second passing location indicates that the target user has not reached the target location, the filtered data of the target user is generated according to the association data corresponding to the target user.

[0075] The first preset time period is usually a time period of a statistical target, and the second preset time period is a time period before the preset time period. The first passing position of the target user in the first preset time period and the corresponding second passing position in the second preset time period are determined according to the communication time and the base station position information, so that whether the target user arrives at the target position in the first preset time period can be determined according to the first passing position and the second passing position. If the first passing position indicates that the target user has arrived at the target position and the second passing position indicates that the target user has not arrived at the target position, the filtering data of the target user is generated according to the associated data corresponding to the target user. For example, the target position is Shenzhen, the whole day of January 9 is set as the first preset time period, and the second preset time period is the previous 24 hours, i.e., January 8. According to the communication time and the base station position information, it is determined that the corresponding first passing position of the target user on January 9 indicates that the user has arrived at Shenzhen, and the second passing position corresponding to January 8 does not have Shenzhen, so it can be confirmed that the user arrives at Shenzhen on January 9, so that the associated data corresponding to the target user can be added to the filtering data. If the first passing position indicates that the target has not arrived at Shenzhen on January 9, or has arrived at Shenzhen on January 8, it indicates that the user is not arrived on January 9, so the associated information corresponding to the user is ignored and is not added to the filtering data.

[0076] Specifically, the filtering process can be performed by using the following filtering formula:

[0077]

[0078] wherein, the filtering data, which includes the associated data corresponding to user 1 to user n until the i-th hour; a represents the target position; user 1 passes through the target position in the first preset time period and does not pass through the target position in the second preset time period, the first preset time period is from the 0th hour to the i-th hour, and the second preset time period is the previous 24 hours; user n passes through the target position in the first preset time period and does not pass through the target position in the second preset time period. According to the above formula, it can be seen that the filtering data takes the union set of the associated data of user 1 to user n.

[0079] In the embodiments of the present application, the associated data is filtered by whether the user arrives at the target position in the preset time period, so that the user arriving at the new target position can be effectively identified and the interference data can be removed, thereby improving the accuracy of the data.

[0080] In an embodiment of the present application, based on the above technical solution, the step of grouping the filtering data according to the communication time and the base station scene of the filtering data can include the following steps:

[0081] According to the communication time and the base station scene in the filtered data, a reaching scene corresponding to the filtered data is determined, the reaching scene representing a base station scene where the target user passes through earliest;

[0082] According to the reaching scene, the filtered data is grouped to generate the data group.

[0083] According to the communication time and the base station scene in the filtered data, a reaching scene corresponding to the filtered data is determined. Specifically, for each user in the target user, there are usually multiple corresponding data in the filtered data, and the reaching scene is a base station scene where the target user passes through earliest. The filtered data can be understood as a collection of all communication record data of the user reaching the target position within a preset time period, and the target position can correspond to multiple base station scenes, and one target user can reach multiple base station scenes within the preset time period, for example, the target position is Shenzhen, and the user can reach Shenzhen by high-speed rail and leave Shenzhen by plane within a day. In this case, the user has two base station scenes of high-speed rail and airport in the filtered data, and the reaching scene is the earliest scene in time sequence, which is the high-speed rail scene in this example.

[0084] After determining the reaching scene of each user, the filtered data can be grouped according to the reaching scene of the target user. The filtered data of the same reaching scene is divided into the same data group, and the data of each user is usually divided into the same group. For example, user A has three communication record data, two corresponding to the airport and one corresponding to the high-speed rail, and the reaching scene of user A is determined as the high-speed rail. The three data can be divided into the high-speed rail group, or only the data corresponding to the high-speed rail is divided into the high-speed rail scene, and the data corresponding to the airport is ignored, so as to reduce the data amount.

[0085] Specifically, the data group can be grouped according to the following grouping formula:

[0086]

[0087] The data group is identified, which includes the associated data of user 1 to user n corresponding to the base station position information a of the target position a up to the ith hour, and E is the reaching scene of the data group. The reaching scenes of different data groups are usually different, for example, and can include high-speed rail, expressway and airport. It represents the associated data of user 1 appearing in scene E for the first time within k hours to i hours in the past. The association data represents that user n first appears in scene E within k hours to i hours in the past. According to the above formula, it can be seen that the data group takes the union of the association data of users 1 to n. The above formula divides the filtered data into different data groups by performing once for each scene E. It can be understood that the actual value of n representing the number of users will change as the grouping progresses.

[0088] In the embodiments of the present application, the arrival scene of the user is determined according to the communication time and the base station scene in the filtered data, and the data is further grouped according to the arrival scene, so that the scene corresponding to the arrival of the user at the target location can be accurately determined, and the interference of other base station scenes of the target location is excluded.

[0089] In an embodiment of the present application, based on the above technical solution, the communication record data includes a cell identifier, and the engineering parameter data includes a base station identifier; the step of associating the communication record data and the engineering parameter data to obtain the association data of the target user can include the following steps:

[0090] Obtaining the cell identifier in the communication record data and the base station identifier in the engineering parameter data;

[0091] If the cell identifier matches the base station identifier, the communication record data is associated with the engineering parameter data to generate association data.

[0092] The cell identifier is the identifier of the cell in which the user terminal is located when communicating. The identifier usually has a one-to-one correspondence with the base station, that is, each cell identifier is unique and uniquely corresponds to the base station providing the cell. The base station identifier is an identifier for uniquely identifying the base station device, and the cell identifier is usually directly used as the base station identifier. The travel identification system obtains the cell identifier in each communication record data and the base station identifier in the engineering parameter data of each base station. If the cell identifier matches the base station identifier, it indicates that the communication record data occurs in the cell of the base station, and then the communication record data can be associated with the engineering parameter data of the base station. The specific way of association can directly use the database table form. The communication record data can be in the form of deep packet inspection data, which is a series of detailed data records generated by the user during the use of the mobile communication network, and usually includes user signaling flow records, service access records, etc., wherein the service access record needs to include the user's mobile phone number, the user's international mobile subscriber identity, the Internet protocol address and other related association fields. The engineering parameter data is the information configured for the base station, which is usually fixed data and will not change. The engineering parameter data generally includes engineering parameters such as longitude and latitude, coverage scene, base station, and cell identifier.

[0093] In the embodiments of the present application, the communication record data is associated with the engineering parameter data through the cell identifier, so that the communication record of the user can be associated with the location covered by the cell, thereby providing a basis for determining the travel of the user and improving the operability of the scheme.

[0094] In an embodiment of the present application, based on the above technical scheme, after the step of determining the travel of the target user according to the corresponding base station scene of the data group to which the target user belongs, the method of the present application can further include the following steps:

[0095] According to the data in each data group, the number of target users corresponding to each data group is obtained.

[0096] According to the number of target users corresponding to each data group, the user distribution result in the base station scene is determined and displayed.

[0097] Specifically, the travel recognition system obtains the number of target users corresponding to each data group according to the data in each data group. Since each data group corresponds to a base station scene, in the case that the base station scene represents the arrival mode of the user, it can be considered that all users in the same data group adopt the same travel mode. Therefore, according to the target user data corresponding to each data group, the user distribution in each base station scene can be determined, and the distribution can be displayed. For example, the time period of collecting data is the past 3 hours, and the target location is Guangzhou, wherein the number of users corresponding to the high-speed rail group is 5000, it can be considered that the number of people who arrive in Guangzhou by high-speed rail in the past 3 hours is 5000. Based on the number of target users corresponding to each data group, a graphical display of the user distribution can also be generated, for example, a column chart or a curve chart can be generated to display the distribution of the user.

[0098] In an embodiment of the present application, based on the above technical scheme, after the step of determining the travel of the target user according to the corresponding base station scene of the data group to which the target user belongs, the method of the present application can further include the following steps:

[0099] If the travel of the target user matches the preset travel and the communication time of the target user is within the preset time range, an alarm prompt message is sent to the target user according to the communication record data.

[0100] Specifically, the preset travel and the preset time range are used to define the travel that needs to be warned. For example, in the scenario of epidemic prevention, the preset travel can be set as the province or city where the epidemic occurs, and the preset time range is set as the time when the epidemic-related personnel is in the preset travel, so that the users who can be affected can be determined, and the users are sent a notification for further prevention and control. Alternatively, the way in which the personnel in a certain region travel can be counted, for example, the distribution of passengers who travel in various ways in Guangzhou in the past month is counted, so that resources can be further allocated according to the distribution. The way of sending warning prompt information to the user can be through a short message or a telephone call.

[0101] Next, the overall flow of the scheme of the present application is described by taking the application of the scheme of the present application to epidemic prevention as an example. For ease of introduction, please refer to Figure 4 , Figure 4 is a schematic diagram of the overall application flow in the embodiments of the present application. The scheme of the present application can be applied to count the number of entries in a province, so as to allocate resources for epidemic prevention according to the statistical results. First, in step 401, the communication record data of users in a province in the past period of time and the engineering parameter data of the base stations corresponding to various channels that can enter the province need to be collected, mainly including covering airports, highways, railways, etc. For the obtained communication record data and engineering parameter data, in step 402, the two need to be associated to obtain associated data. In step 403, the obtained associated data is filtered by using the filtering formula introduced above, so as to remove garbage data that does not meet the conditions and obtain filtered data. Subsequently, in step 404, the filtered data is grouped by using the grouping formula described above, taking the airport as the target scene, so as to obtain the data grouping corresponding to the airport scene, in step 405, the filtered data is grouped by using the grouping formula described above, taking the high-speed rail as the scene, so as to obtain the data grouping corresponding to the high-speed rail scene, in step 406, the filtered data is grouped by using the grouping formula described above, taking the highway as the scene, so as to obtain the data grouping corresponding to the highway scene. It can be understood that steps 404, 405 and 406 can be executed in any order. Finally, in step 407, the last remaining data is determined as the passengers who enter by other means. The data grouping output in steps 404, 405 and 406 is counted and summarized to output the single-day entry number, 7-day cumulative entry number and average entry number corresponding to each entry mode. According to the proportion of the statistical results, the corresponding proportion of the epidemic prevention resources can be allocated, so that the distribution of the resources is more reasonable.

[0102] It should be noted that although the various steps of the methods of the present application are described in a particular order in the drawings, this is not required or implied that the steps must be performed in that particular order, or that all of the steps shown must be performed to achieve the desired result. Additionally or alternatively, certain steps can be omitted, multiple steps can be combined into a single step, and / or a single step can be broken up into multiple steps, etc.

[0103] The device implementation of the present application is introduced below, which can be used to perform the user travel identification method in the above embodiments of the present application. Figure 5 The constituent block diagram of the user travel identification device in the embodiments of the present application is schematically shown. As shown in Figure 5 The user travel identification device 500 can mainly include:

[0104] The data acquisition module 510 is configured to acquire the communication record data of the target user and the engineering parameter data of the target base station, the communication record data including the communication time, and the engineering parameter data including the base station scene and the base station position information of the target base station, the base station scene representing the travel mode of the target user.

[0105] The data association module 520 is configured to associate the communication record data and the engineering parameter data to obtain the associated data of the target user.

[0106] The data grouping module 530 is configured to group the associated data according to the target position and the communication time, the base station scene, and the base station position information in the associated data to obtain data groups, each data group corresponding to a base station scene.

[0107] The travel determination module 540 is configured to determine the travel of the target user according to the corresponding base station scene in the data group to which the target user belongs.

[0108] In some embodiments of the present application, based on the above technical solution, the data grouping module 530 includes:

[0109] The data filtering sub-module is configured to filter the associated data according to the communication time, the base station position information, and the target position in the associated data to obtain the filtered data of the target user.

[0110] The filtered data grouping sub-module is configured to group the filtered data according to the communication time and the base station scene of the filtered data to obtain the data groups.

[0111] In some embodiments of the present application, based on the above technical solution, the filtered data grouping sub-module includes:

[0112] A route position determining unit is configured to determine a first route position corresponding to the target user in a first preset time period and a second route position corresponding to the target user in a second preset time period according to the communication time and the base station position information, the first route position and the second route position both indicating positions passed by the target user, and the second preset time period being a time period before the first preset time period;

[0113] A filtered data generating unit is configured to generate filtered data of the target user according to the associated data corresponding to the target user if the first route position indicates that the target user has passed the target position and the second route position indicates that the target user has not passed the target position.

[0114] In some embodiments of the present application, based on the above technical solutions, the route position determining unit comprises:

[0115] A reaching scene determining sub-unit is configured to determine a reaching scene corresponding to the filtered data according to the communication time in the filtered data and the base station scene, the reaching scene representing a base station scene earliest passed by the target user.

[0116] A grouping sub-unit is configured to group the filtered data according to the reaching scene, and generate the data group.

[0117] In some embodiments of the present application, based on the above technical solutions, the communication record data comprises a cell identifier, and the engineering parameter data comprises a base station identifier; and the data association module 520 comprises:

[0118] An identifier obtaining sub-module is configured to obtain the cell identifier in the communication record data and the base station identifier in the engineering parameter data.

[0119] A data generating sub-module is configured to associate the communication record data with the engineering parameter data to generate associated data if the cell identifier matches the base station identifier.

[0120] In some embodiments of the present application, based on the above technical solutions, the user travel recognition device 500 further comprises:

[0121] A quantity obtaining module is configured to obtain a target user quantity corresponding to each data group according to data in each data group.

[0122] A distribution determining module is configured to determine and display a user distribution result in the base station scene according to the target user quantity corresponding to each data group.

[0123] In some embodiments of the present application, based on the above technical solutions, the user travel recognition device 500 method further comprises:

[0124] The alarm sending module is configured to send an alarm prompt message to the target user according to the communication record data if the travel of the target user matches the preset travel and the communication time of the target user is within the preset time range.

[0125] It should be noted that the apparatus provided by the above-described embodiments and the method provided by the above-described embodiments belong to the same concept, and the specific manner in which each module performs an operation has been described in detail in the method embodiments, which will not be described here.

[0126] Figure 6 A structural schematic diagram of a computer system of an electronic device suitable for implementing the embodiments of the present application is shown.

[0127] It should be noted that, Figure 6 The computer system 600 of the electronic device shown is only an example and should not impose any limitation on the functions and use range of the embodiments of the present application.

[0128] As Figure 6 shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 602 or loaded from a storage portion 608 into a random access memory (RAM) 603. Various programs and data required for system operation are also stored in the RAM 603. The CPU 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0129] The following components are connected to the I / O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a cathode ray tube (CRT), a liquid crystal display (LCD), and the like, and a speaker, and the like; a storage portion 608 including a hard disk, and the like; and a communication portion 609 including a network interface card such as a LAN (Local Area Network) card, a modem, and the like. The communication portion 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to the I / O interface 605 as necessary. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, and the like is mounted on the drive 610 as necessary, so that a computer program read therefrom is installed in the storage portion 608 as necessary.

[0130] In particular, according to embodiments of the present application, the processes described in the various method flowcharts can be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program carried on a computer readable medium, the computer program containing program code for executing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication section 609, and / or installed from the removable media 611. When the computer program is executed by the central processing unit (CPU) 601, various functions defined in the system of the present application are executed.

[0131] It should be noted that the computer readable medium shown in the embodiments of the present application can be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable storage medium may, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or apparatus, or any combination of the above. More specific examples of the computer readable storage medium can 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), a flash memory, an optical fiber, a portable compact disk read-only memory (Compact Disc Read-Only Memory, CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device or apparatus. In the present application, the computer readable signal medium can include a data signal carried in a baseband or as a part of a carrier wave, which carries computer readable program code. Such a propagated data signal can take many forms, including but not limited to an electromagnetic signal, an optical signal or any suitable combination of the above. The computer readable signal medium can also be any computer readable medium other than the computer readable storage medium that can transmit, propagate or transport a program for use by or in connection with an instruction execution system, device or apparatus. The program code contained on the computer readable medium can be transmitted by any suitable medium, including but not limited to wireless, wired, or the like, or any suitable combination of the above.

[0132] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0133] It should be noted that although several modules or units of the device for performing actions have been mentioned in the detailed description above, this grouping is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further grouped into multiple modules or units for embodiment.

[0134] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of this application.

[0135] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.

[0136] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A user journey recognition method, characterized in that, The method comprises: obtaining communication record data of a target user and engineering parameter data of a target base station, the communication record data comprising a communication time, and the engineering parameter data comprising a base station scenario of the target base station and base station position information, the base station scenario representing a travel mode of the target user; performing data association on the communication record data and the engineering parameter data to obtain associated data of the target user; performing data filtering on the associated data according to the communication time, the base station position information and a target position in the associated data to obtain filtered data of the target user, wherein the filtered data comprises data corresponding to a plurality of base station scenarios; determining a reaching scenario corresponding to the filtered data according to the communication time and the base station scenario in the filtered data, the reaching scenario representing a base station scenario that the target user has passed through earliest; grouping the filtered data according to the reaching scenario to generate data groups, each data group corresponding to a base station scenario; if the base station scenario of the filtered data corresponds to the reaching scenario, dividing the filtered data into the data groups; and if the base station scenario of the filtered data does not correspond to the reaching scenario, ignoring the filtered data; determining a travel of the target user according to a corresponding base station scenario in a data group to which the target user belongs.

2. The method of claim 1, wherein, The performing data filtering on the associated data according to the communication time, the base station position information and the target position in the associated data to obtain filtered data of the target user comprises: determining a first passing position corresponding to the target user in a first preset time period and a second passing position corresponding to the target user in a second preset time period according to the communication time and the base station position information, the first passing position and the second passing position both indicating positions reached by the target user, the second preset time period being a time period before the first preset time period; if the first passing position indicates that the target user has reached the target position and the second passing position indicates that the target user has not reached the target position, generating filtered data of the target user according to the associated data corresponding to the target user.

3. The method of claim 1, wherein, The communication record data comprises a cell identifier, and the engineering parameter data comprises a base station identifier; the performing data association on the communication record data and the engineering parameter data to obtain associated data of the target user comprises: obtaining the cell identifier in the communication record data and the base station identifier in the engineering parameter data; if the cell identifier matches the base station identifier, associating the communication record data with the engineering parameter data to generate associated data.

4. The method of claim 1, wherein, After the determining a travel of the target user according to a corresponding base station scenario in a data group to which the target user belongs, the method further comprises: obtaining a number of target users corresponding to each data group according to data in each data group; determining and displaying a user distribution result in the base station scenario according to the number of target users corresponding to each data group.

5. The method of claim 1, wherein, After determining the travel of the target user according to the corresponding base station scene of the data group to which the target user belongs, the method further comprises: If the travel of the target user matches a preset travel and the communication time of the target user is within a preset time range, an alarm prompt message is sent to the target user according to the communication record data.

6. A user trip identification apparatus characterized by comprising: Comprise: a data acquisition module configured to acquire communication record data of a target user and engineering parameter data of a target base station, the communication record data comprising a communication time, and the engineering parameter data comprising a base station scene and base station location information of the target base station, the base station scene representing a travel mode of the target user; a data association module configured to associate the communication record data and the engineering parameter data to obtain associated data of the target user; a data grouping module configured to filter the associated data according to the communication time, the base station location information and a target location in the associated data to obtain filtered data of the target user, wherein the filtered data comprises data corresponding to a plurality of base station scenes, a corresponding arrival scene is determined according to the communication time and the base station scene in the filtered data, the arrival scene representing an earliest base station scene passed by the target user, the filtered data is grouped according to the arrival scene, and each data group corresponds to a base station scene; if the base station scene of the filtered data corresponds to the arrival scene, the filtered data is divided into the data group, and if the base station scene of the filtered data does not correspond to the arrival scene, the filtered data is ignored; a travel determination module configured to determine the travel of the target user according to the corresponding base station scene of the data group to which the target user belongs.

7. An electronic device, comprising: Comprise: a processor; a memory configured to store executable instructions of the processor; wherein the processor is configured to cause the electronic device to perform the user travel identification method of any one of claims 1 to 5 by executing the executable instructions.

8. A computer readable medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the user travel identification method of any one of claims 1 to 5. The computer program is executed by the processor to realize the user travel identification method of any one of claims 1 to 5.

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