CN113727274A - User mobility determination method, device, equipment and storage medium - Google Patents
User mobility determination method, device, equipment and storage medium Download PDFInfo
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- H04W4/02—Services making use of location information
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Abstract
The embodiment of the disclosure provides a user mobility determination method, a user mobility determination device, user mobility determination equipment and a storage medium, relates to the technical field of big data application, and aims to solve the problem that the mobility of a user cannot be comprehensively evaluated in the prior art. The method specifically comprises the following steps: acquiring network data and work parameter data in a preset time period of a user; inquiring the longitude and latitude of a base station corresponding to each piece of data in the network data in the working parameter data; determining the distance span and the rasterization number corresponding to each duration in a preset time period; and determining the mobility index of the user according to the distance span and the rasterization number corresponding to each time length.
Description
Technical Field
The present disclosure relates to the field of big data application technologies, and in particular, to a method, an apparatus, a device, and a storage medium for determining user mobility.
Background
The mobility data of the user may reflect a life trajectory of the user over a period of time. By analyzing the mobility data of the user, the user behavior that may occur in a future period of time can be predicted. According to the user behaviors which possibly occur, the travel tool recommendation service system intelligently provides various services such as travel tool recommendation and path navigation for the user, so that the user can travel more conveniently, and the national happiness is further improved. Therefore, how to get accurate user mobility data is crucial.
In the prior art, user mobility is determined by a cell handover signaling procedure of a core network. However, the calculation process of the method is complex, and the mobility of the user cannot be comprehensively evaluated.
Disclosure of Invention
The disclosure provides a user mobility determination method, a user mobility determination device, user mobility determination equipment and a storage medium, which are used for solving the problem that the mobility of a user cannot be comprehensively evaluated in the prior art.
In order to achieve the purpose, the technical scheme adopted by the disclosure is as follows:
in a first aspect, the present disclosure provides a user mobility determining method, including the following steps: the user mobility determining device acquires network data and work parameter data in a user preset time period; inquiring the longitude and latitude of a base station corresponding to each piece of data in the network data in the working parameter data; determining the distance span and the rasterization number corresponding to each duration in a preset time period; and determining the mobility index of the user according to the distance span and the rasterization number corresponding to each time length.
Based on the technical scheme provided by the disclosure, the user mobility determination device determines the longitude and latitude, the distance span and the rasterization number of the base station corresponding to the network data according to the acquired network data and the acquired work parameter data within the preset time period of the user, and determines the mobility index of the user by combining the distance span and the rasterization number. Compared with the prior art, the calculation method is simpler and has higher efficiency; and the present disclosure includes cleansing of network data such that the accuracy of the resulting user mobility index is higher.
In a second aspect, the present disclosure provides an apparatus for determining user mobility, the apparatus including an obtaining module and a processing module; the acquisition module is configured to acquire network data and work parameter data in a preset time period of a user; the processing module is configured to inquire the longitude and latitude of the base station corresponding to each piece of data in the network data in the working parameter data; the processing module is also configured to determine the distance span and the rasterization number corresponding to each duration in a preset time period; and the processing module is also configured to determine the mobility index of the user according to the distance span and the rasterization number corresponding to each time length.
In a third aspect, a user mobility determination device is provided, including: a processor; a memory for storing the processor-executable instructions; wherein the processor is configured to execute the instructions to implement the user mobility determination method as provided in the first aspect above.
In a fourth aspect, the invention provides a computer-readable storage medium comprising instructions. The instructions, when executed on the computer, cause the computer to perform the user mobility determination method as provided above in the first aspect.
In a fifth aspect, the present invention provides a computer program product for causing a computer to perform the user mobility determination method as provided in the first aspect when the computer program product is run on the computer.
It should be noted that all or part of the above computer instructions may be stored on the first computer readable storage medium. The first computer readable storage medium may be packaged with the processor of the access network device or may be packaged separately from the processor of the access network device, which is not limited in the present invention.
Reference may be made to the detailed description of the first aspect for the description of the second to fifth aspects of the invention; in addition, for the beneficial effects described in the second aspect to the fifth aspect, reference may be made to the beneficial effect analysis of the first aspect, and details are not described here.
In the present invention, the above names do not limit the devices or the functional modules themselves, and in actual implementation, the devices or the functional modules may appear by other names. Insofar as the functions of the respective devices or functional blocks are similar to those of the present invention, they are within the scope of the claims of the present invention and their equivalents.
These and other aspects of the invention will be more readily apparent from the following description.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present disclosure, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present disclosure, and it is obvious for those skilled in the art to obtain other drawings based on the drawings without creative efforts.
Fig. 1 is a schematic diagram of a communication system in accordance with an embodiment of the present disclosure;
fig. 2 is a flowchart illustrating a user mobility determination method according to an embodiment of the disclosure;
fig. 3 is a second flowchart illustrating a user mobility determination method according to an embodiment of the disclosure;
fig. 4 is a third flowchart illustrating a user mobility determination method according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of a user mobility determination apparatus according to an embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of a user mobility determination device according to an embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of a computer program product of a user mobility determination method according to an embodiment of the present disclosure.
Detailed Description
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
It should be noted that in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described herein as "exemplary" or "e.g.," is not necessarily to be construed as preferred or advantageous over other embodiments or designs. Rather, use of the word "exemplary" or "such as" is intended to present concepts related in a concrete fashion.
For the convenience of clearly describing the technical solutions of the embodiments of the present application, in the embodiments of the present application, the terms "first" and "second" are used to distinguish the same items or similar items with basically the same functions and actions, and those skilled in the art can understand that the terms "first" and "second" are not limited in number or execution order.
Based on the background technology, the embodiment of the application provides a user mobility determination method. The method comprises the steps of obtaining network data of a target user, determining corresponding longitude and latitude, distance span and rasterization number of a base station according to the network data of the user, and finally determining the mobility index of the user according to the distance span and the rasterization number. Compared with the prior art, the method and the device are simple in calculation, and meanwhile, the abnormal data are cleaned, so that the obtained user mobility index result is more accurate.
Next, a brief description will be given of an implementation environment related to the present disclosure.
Referring to fig. 1, fig. 1 is a schematic diagram illustrating a communication system according to an example embodiment. The system comprises an access network device 10 and a user terminal 20. Wherein the access network device 10 and the user terminal 20 may be interconnected and communicate through a network.
In some embodiments, the access network device 10 may be configured to obtain network data of a target user, determine a mobility index of the user, and so on. Specifically, the Access network device 10 may be an Access Point (AP), an evolved Node Base Station (eNB), or a Base Station in the 5Generation Mobile communication Technology (5G) network, which is not limited in this embodiment of the present invention.
The user terminal 20 may be a mobile phone, a tablet computer, a notebook computer, a desktop computer, a portable computer, etc., which is not limited in this disclosure. The user terminal 20 is shown in fig. 1 as a mobile phone.
Those skilled in the art will appreciate that the communication system is by way of example only and that other existing or future communication systems, as may be suitable for use with the present disclosure, are intended to be within the scope of the present disclosure and are hereby incorporated by reference.
The technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments, which can be derived by one of ordinary skill in the art from the embodiments disclosed herein without making any creative effort, shall fall within the scope of protection of the present disclosure.
Fig. 2 is a flowchart illustrating a user mobility determination method according to an example embodiment. The method can be applied to the system shown in fig. 1, and as shown in fig. 2, the method comprises steps 21-24.
And step 21, the user mobility determining device acquires network data and work parameter data in a preset time period of a user.
The user mobility determination device may be the terminal 10 in the communication system, or may be the base station 20 in the communication system.
The network data is obtained by collecting an Object Storage Service (OSS) domain data XDR ticket. The XDR ticket comprises a single interface ticket and a special ticket, wherein the single interface ticket is generated by analyzing data in a certain specific interface, and the special ticket is generated by performing multi-interface association or secondary processing according to specific requirements. And for the single interface ticket, dividing the single interface ticket into each interface ticket according to the difference of the interfaces.
The parameters commonly used in the network include: base station longitude, base station latitude, base station name, local cell identifier, downlink frequency point, downlink bandwidth, cell identifier, PCI (physical cell identifier), cell activation state, PRACH (physical random access channel), cell transmission and reception mode, cell instance state, base station identifier, PA value (decibel) when PDSCH employs uniform power allocation, reference signal power (0.1 milliwatt decibel), TAC (tracking area code), and the like. Optionally, the job parameter data is job parameter data associated with network data.
Specifically, the network data in the present disclosure may be call data, internet data, or a full-scale user table and a position track.
The call data may be obtained by collecting data of the IUCS interface. In the IUCS interface, SpecFlag 1 indicates data called by the user, and CallDropFlag 1 indicates data called successfully by the user. The present disclosure keeps a record of CallDropFlag ═ 1, and deletes the data for SpecFlag ═ 1.
The internet data can be obtained by collecting data of the S1UHTTP interface. The S1UHTTP interface comprises the internet access behavior of the user.
The total user list and the location trajectory may be obtained by collecting data of 4 interfaces, an Interface (IUCS) for transmitting a circuit domain between the radio network controller and the core network, an Interface (IUPS) for transmitting a packet domain between the radio network controller and the core network, an interface (S1MME) for transmitting session management and mobility management information, and an interface (S1UHTTP) for transmitting user data traffic. Specifically, all tables corresponding to three interfaces of IUCS, IUPS and S1MME are obtained, then 8 general fields are extracted from all tables, and finally the 8 extracted general fields are connected completely to obtain a full-user table. After obtaining the full user table, adding a column of proctype description interface names, such as: s1MME, IUCS, IUPS, etc. For an exemplary, 8 general fields extracted are shown in table 1.
TABLE 1
| Name of field | Are collectively named as |
| sdrtype/proctype/specflag | sdrtype |
| Imei | Imei |
| msisdn/phone | msisdn |
| imsi | imsi |
| StartTime | StartTime |
| EndTime | EndTime |
| tac/lac_tac/lai | lac_tac |
| eci/ci/ci_eci/CGI | eci |
Wherein tac/lac _ tac/lai in table 1 is uniformly named lac _ tac; eci/ci/ci _ eci/CGI are collectively named eci.
The result of the eci field is determined in a different manner depending on the type of network.
The eci field calculation method of the 4G ticket comprises the following steps: firstly, performing 10-to-16-system conversion on the ENODEB _ ID and the CELL _ ID, wherein eNodeB identification _ HEX is Dec2Hex (base station identification), and CELL identification _ HEX is Dec2Hex (CELL identification); secondly, directly performing and merging on the 16-system eNodeB identifier and the 16-system cell identifier to obtain the 16-system ECI, wherein ECI _ HEX is eNodeB identifier _ HEX and cell identifier _ HEX, and if the cell identifier is 1 bit, ECI _ HEX is eNodeB identifier _ HEX & '0' & cell identifier _ HEX; finally, the 16-ary ECI is inverted into 10-ary ECI, and ECI _ DEC is Hex2DEC (ECI _ Hex), and the ECI _ DEC can be cell matched with the detail list.
Illustratively, the FHBCI0001 bananlai home _1 CELL corresponds to an ENODEB _ ID of 685277 and a CELL _ ID of 1. Converting the base station identifier into a 16-system de 2Hex (685277) ═ a74DD, and converting the cell identifier into a 16-system de 2Hex (1) ═ 1; combining to obtain 16-system ECI, wherein ECI _ HEX is equal to A74DD '&' 0 '&' 1 '&' A74DD 01; finally, 16-system ECI is inverted into 10-system ECI _ DEC (HEX 2DEC (A74DD01) ═ 175430913
The 3Geci field calculation method is as follows: ECI ═ 46001 "&" 5-bit LAC "&" 5-bit CI ".
Illustratively, a cell has a LAC of 4104 and a CI of 34625, and eci is 460010410434625.
And step 22, the user mobility determination device inquires the longitude and latitude of the base station corresponding to each piece of data in the network data in the working parameter data.
In the embodiment of the present disclosure, in combination with table 1, according to the ci _ eci associated work parameter data in table 1, the work parameter data queries the base station location information (base station longitude, base station latitude) corresponding to ci _ eci, and adds the base station location information to table 1.
And step 23, the user mobility determining device determines the distance span and the rasterization number of the base station in a preset time period.
In the embodiment of the present disclosure, the distance span is used to characterize the moving range of the user, and the rasterized number is used to characterize the moving frequency of the user.
The base stations connected with the user in the preset time period may include a plurality of base stations, and the distance span in the preset time period is calculated according to the longitude and latitude of the base stations. And performing rasterization representation on the longitude and latitude coordinates of all base stations connected by the user to obtain a plurality of rasterization results, and performing statistics on all the rasterization results in a preset time period to obtain the number of rasterization.
In conjunction with fig. 2, as shown in fig. 3, the step 23 may include:
step 231, the user mobility determination device determines the longitude and latitude of the multiple base stations in each time period.
Illustratively, after the latitude and longitude data of the base station are obtained according to the working parameters, the latitude and longitude data of the base station are classified according to each time length in a preset time period, so as to obtain a plurality of groups of latitude and longitude of the base station corresponding to each time length.
Step 232, the user mobility determination device performs ranking processing on the longitude and latitude of the multiple groups of base stations in each time length to obtain a ranking result of each time length.
Illustratively, the longitude and latitude of the base station appearing in each time (such as every day) are sorted, and the maximum longitude lon is obtained according to the sorting resultmaxMaximum latitude latmaxMinimum longitude lonminMinimum latitude latmin。
Step 233, the user mobility determining device performs data processing on the sequencing result of each duration to obtain the distance span corresponding to each duration.
In the embodiment of the present disclosure, the sorting result of each duration is calculated to obtain the distance span corresponding to each duration.
Illustratively, the calculation of the distance span satisfies the following expression:
d＝(d12+d22)1/2
d1＝|LonA-LonB|
d2＝|LatA-LatB|
wherein LonA is the latitude and longitude of the base station A, and LatA is the latitude of the base station A; LonB is the latitude and longitude of the base station B, and LatB is the latitude of the base station B.
In conjunction with fig. 2, as shown in fig. 3, the step 22 may include:
step 234, the user mobility determination device performs rasterization processing on the longitude and latitude of the multiple groups of base stations in each time length to obtain a rasterization result corresponding to each time length.
In the embodiment of the disclosure, the longitude and latitude of the base station included in each time within the preset time period are converted into the rasterization result according to the rasterization rule and the reserved decimal requirement.
For example, regarding the longitude and latitude of the base station a included in the first duration, since the base station a connected by the user is located in the central urban area, the longitude and latitude of the base station in the central urban area need to reserve 3 decimal places. The longitude and latitude (113.42535, 36.7683) of the base station a is reserved with 3-bit decimal, converted to (113.425, 36.768), and then the rasterization result of the base station a is obtained 113.425_36.768 according to the rasterization rule.
Step 235, the user mobility determining device counts the rasterization result corresponding to each duration to obtain the rasterization number corresponding to each duration.
In the embodiment of the disclosure, after the rasterization result included in each duration in the preset time period is calculated, the number of the rasterization results in each duration is counted one by one to obtain the corresponding rasterization number of each duration.
Illustratively, after obtaining the rasterization results of each day within 30 days of the user, the number of the rasterization results of each day is counted, so as to obtain the corresponding rasterization number m of each day within 30 days.
And step 24, the user mobility determining device determines the mobility index of the user according to the distance span and the rasterization number corresponding to each time length.
In the embodiment of the disclosure, after the distance span and the rasterization number are obtained, the mobility index of the user is calculated by introducing a time decay function.
Illustratively, the time decay function satisfies the following expression:
wherein μ is an attenuation factor, 0< μ < 1; t is the number of days apart from the day; if the current day is the current day, t is 0; if the previous day is the same, t is 1, and so on; t is the time span, illustratively, T-10.
The mobility index of the user satisfies the following expression:
wherein, mu and v are attenuation factors, 0<μ<1,0<v<1; a1 and a2 are weight coefficients of the two factors respectively; dtA range span of base stations from the day of the day at t; m istThe number of grids passed by the user on the day t away from the day.
In conjunction with fig. 2, as shown in fig. 4, step 24 may further include:
step 236, the user mobility determining device performs a first operation on the distance span of each duration, and determines the data type corresponding to each duration.
The first operation is to determine the variance of the distance span corresponding to the first time length; and if the distance span corresponding to the first time length is larger than a first threshold, determining that the data type corresponding to the first time length is a first type.
The first time length is any time length in a preset time period; the first threshold is determined based on the variance.
Illustratively, the distance span of each day in 30 days of all users is calculated, and the variance δ of the distance span is calculated according to the distance span of each day1. And if the distance span corresponding to the first day is larger than the first threshold, the data type corresponding to the first day is considered to be long distance travel. The data type corresponding to each day of 30 days is calculated according to the method. Furthermore, by combining the method, the long distance travel days of each user in 30 days of the city can be obtained, and then, the length of each user in 30 days is determinedThe number of days of trip, the variance delta of the number of days of trip n is calculated2. Wherein the first threshold is 10 δ1。
Step 237, the user mobility determining means counts the number of target durations within a preset time period.
The target duration is any duration in a preset time period, and the corresponding data type is duration of the first type.
And step 238, if the number of the target time lengths is smaller than the second threshold, the user mobility determining device deletes the data corresponding to the target time lengths.
Illustratively, the number of the determined target time lengths is niAnd then, if the number of the target time lengths is smaller than a second threshold value, the user is considered to be only occasionally going for a long distance, and therefore the data corresponding to the target time lengths are deleted. If the number of the target duration is larger than the second threshold, the user is considered to be frequently long-distance travel, and therefore data corresponding to the target duration are reserved. Wherein the second threshold value ═ avg (n) -2 δ2。
The technical scheme provided by the steps at least has the following beneficial effects: according to the acquired network data and the acquired work parameter data in the preset time period of the user, determining the longitude and latitude, the distance span and the rasterization number of the base station corresponding to the network data, and determining the mobility index of the user by combining the distance span and the rasterization number. Compared with the prior art, the calculation method is simpler and has higher efficiency; and the present disclosure includes cleansing of network data, resulting in a higher accuracy of the resulting user mobility index.
The foregoing describes the scheme provided by the embodiments of the present disclosure, primarily from a methodological perspective. To implement the above functions, it includes hardware structures and/or software modules for performing the respective functions. Those of skill in the art will readily appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as hardware or combinations of hardware and computer software. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present disclosure.
Fig. 5 is a schematic structural diagram illustrating a user mobility determination apparatus according to an exemplary embodiment, which may be used to execute the user mobility determination method illustrated in fig. 2. As an implementation manner, the apparatus may include an acquisition module 51 and a processing module 52.
The obtaining module 51 is configured to obtain network data and work parameter data within a preset time period of a user. For example, in conjunction with fig. 2, the obtaining module 51 may be used to perform step 21.
A processing module 52 configured to query the longitude and latitude of the base station corresponding to each piece of data in the network data in the working parameter data; for example, in conjunction with fig. 2, processing module 52 may be used to perform step 22.
The processing module 52 is further configured to determine a distance span and a rasterization number corresponding to each duration within a preset time period; for example, in conjunction with fig. 2, processing module 52 may be used to perform step 23.
And the processing module is also configured to determine the mobility index of the user according to the distance span and the rasterization number corresponding to each time length. For example, in conjunction with fig. 2, processing module 52 may be used to perform step 24.
Optionally, the processing module is further configured to determine a plurality of sets of base station longitudes and latitudes in each time duration; for example, in conjunction with fig. 2, processing module 52 may be configured to perform step 231.
The processing module is also configured to perform sequencing processing on the longitude and latitude of the multiple groups of base stations in each time length to obtain a sequencing result of each time length; for example, in conjunction with fig. 2, processing module 52 may be configured to perform step 232.
And the processing module is also configured to perform data processing on the sequencing result of each time length to obtain the distance span corresponding to each time length. For example, in conjunction with fig. 2, processing module 52 may be configured to perform step 233.
Optionally, the processing module 52 is further configured to perform rasterization processing on the multiple groups of base station longitudes and latitudes in each time duration to obtain a rasterization result corresponding to each time duration; for example, in conjunction with fig. 2, processing module 52 may be configured to perform step 234.
The processing module 52 is further configured to count the rasterization result corresponding to each duration to obtain the number of rasterization corresponding to each duration. For example, in conjunction with fig. 2, processing module 52 may be configured to perform step 235.
Optionally, the processing module 52 is further configured to perform a first operation on the distance span of each duration, and determine a data type corresponding to each duration; the first operation is to determine the variance of the distance span corresponding to the first time length; if the distance span corresponding to the first time length is larger than a first threshold, determining that the data type corresponding to the first time length is a first type; the first time length is any time length in a preset time period; the first threshold is determined according to the variance; for example, in conjunction with fig. 2, the processing module 52 may be configured to perform step 236.
The processing module 52 is further configured to count the number of the target durations in the preset time period; the target duration is any duration in a preset time period, and the corresponding data type is duration of a first type; for example, in conjunction with fig. 2, the processing module 52 may be configured to perform step 237.
The processing module 52 is further configured to delete the data corresponding to the target duration if the number of the target durations is smaller than the second threshold. For example, in conjunction with fig. 2, the processing module 52 may be configured to perform step 238.
Of course, the user mobility determining apparatus provided in the embodiment of the present invention includes, but is not limited to, the above modules, for example, the user mobility determining apparatus may further include the storage module 53. The storage module 53 may be configured to store the program code of the write user mobility determining apparatus, and may also be configured to store data generated by the write user mobility determining apparatus during operation, such as data in a write request.
Fig. 6 is a schematic structural diagram of a user mobility determining device according to an embodiment of the present invention, and as shown in fig. 6, the user mobility determining device may include: at least one processor 61, a memory 62, a communication interface 63, and a communication bus 64.
The following specifically describes the components of the user mobility determining apparatus with reference to fig. 6:
the processor 61 is a control center of the user mobility determining apparatus, and may be a single processor or a collective term for a plurality of processing elements. For example, the processor 61 is a Central Processing Unit (CPU), or may be an Application Specific Integrated Circuit (ASIC), or may be one or more Integrated circuits configured to implement embodiments of the present invention, such as: one or more DSPs, or one or more Field Programmable Gate Arrays (FPGAs).
In particular implementations, processor 61 may include one or more CPUs such as CPU0 and CPU1 shown in fig. 6 as one example. Also, as an embodiment, the user mobility determining means may include a plurality of processors, such as the processor 61 and the processor 65 shown in fig. 6. Each of these processors may be a Single-core processor (Single-CPU) or a Multi-core processor (Multi-CPU). A processor herein may refer to one or more devices, circuits, and/or processing cores for processing data (e.g., computer program instructions).
The Memory 62 may be a Read-Only Memory (ROM) or other type of static storage device that can store static information and instructions, a Random Access Memory (RAM) or other type of dynamic storage device that can store information and instructions, an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc Read-Only Memory (CD-ROM) or other optical Disc storage, optical Disc storage (including Compact Disc, laser Disc, optical Disc, digital versatile Disc, blu-ray Disc, etc.), a magnetic Disc storage medium or other magnetic storage device, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory 62 may be self-contained and coupled to the processor 61 via a communication bus 64. The memory 62 may also be integrated with the processor 61.
In a particular implementation, the memory 62 is used to store data and software programs that implement the present invention. The processor 61 may perform various functions of the air conditioner by running or executing software programs stored in the memory 62 and calling data stored in the memory 62.
The communication interface 63 is a device such as any transceiver, and is used for communicating with other devices or communication Networks, such as a Radio Access Network (RAN), a Wireless Local Area Network (WLAN), a user terminal, and a cloud. The communication interface 63 may include an acquisition unit implementing the acquisition function and a transmission unit implementing the transmission function.
The communication bus 64 may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, an Extended ISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 6, but this is not intended to represent only one bus or type of bus.
As an example, in connection with fig. 6, the processing module 52 in the user mobility determination device implements the same functions as the processor 61 in fig. 6, and the storage module 53 implements the same functions as the memory 62 in fig. 6.
Another embodiment of the present invention further provides a computer-readable storage medium, which stores instructions that, when executed on a computer, cause the computer to perform the method shown in the above method embodiment.
In some embodiments, the disclosed methods may be implemented as computer program instructions encoded on a computer-readable storage medium in a machine-readable format or encoded on other non-transitory media or articles of manufacture.
Fig. 7 schematically illustrates a conceptual partial view of a computer program product comprising a computer program for executing a computer process on a computing device provided by an embodiment of the invention.
In one embodiment, the computer program product is provided using a signal bearing medium 710. The signal bearing medium 710 may include one or more program instructions that, when executed by one or more processors, may provide the functions or portions of the functions described above with respect to fig. 2. Thus, for example, referring to the embodiment shown in FIG. 2, one or more features of steps 21-24 may be undertaken by one or more instructions associated with the signal bearing medium 710. Further, the program instructions in FIG. 7 also describe example instructions.
In some examples, signal bearing medium 710 may include a computer readable medium 711 such as, but not limited to, a hard disk drive, a Compact Disc (CD), a Digital Video Disc (DVD), a digital tape, a memory, a read-only memory (ROM), a Random Access Memory (RAM), or the like.
In some implementations, the signal bearing medium 710 may include a computer recordable medium 712 such as, but not limited to, a memory, a read/write (R/W) CD, a R/W DVD, and so forth.
In some implementations, the signal bearing medium 710 may include a communication medium 713, such as, but not limited to, a digital and/or analog communication medium (e.g., a fiber optic cable, a waveguide, a wired communications link, a wireless communication link, etc.).
The signal bearing medium 710 may be conveyed by a wireless form of communication medium 713, such as a wireless communication medium conforming to the IEEE 802.71 standard or other transmission protocol. The one or more program instructions may be, for example, computer-executable instructions or logic-implementing instructions.
In some examples, a data writing device, such as that described with respect to fig. 2, may be configured to provide various operations, functions, or actions in response to one or more program instructions through computer-readable medium 711, computer-recordable medium 712, and/or communication medium 713.
Through the above description of the embodiments, it is clear to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be completed by different functional modules according to needs, that is, the internal structure of the device may be divided into different functional modules to complete the above-described full-classification part or part of the functions.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, a module or a unit may be divided into only one logic function, and may be implemented in other ways, for example, a plurality of units or components may be combined or integrated into another apparatus, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may be one physical unit or a plurality of physical units, may be located in one place, or may be distributed to a plurality of different places. The purpose of the scheme of the embodiment can be realized by selecting a part of or a whole classification part unit according to actual needs.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a readable storage medium. Based on such understanding, the technical solutions of the embodiments of the present invention may be substantially implemented as a part contributing to the prior art, or a whole classification part or a part of the technical solutions may be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a device (which may be a single chip, a chip, etc.) or a processor (processor) to execute the whole classification part or a part of the steps of the methods of the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a U disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk.
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions within the technical scope of the present invention are intended to be covered by the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A method for user mobility determination, comprising:
acquiring network data and work parameter data in a preset time period of a user;
inquiring the longitude and latitude of a base station corresponding to each piece of data in the network data in the working parameter data;
determining the distance span and the rasterization number corresponding to each duration in a preset time period;
and determining the mobility index of the user according to the distance span and the rasterization number corresponding to each time length.
2. The method of claim 1, wherein the determining the distance span corresponding to each duration in the preset time period comprises:
determining the longitude and latitude of a plurality of groups of base stations in each time length;
sequencing the longitude and latitude of the multiple groups of base stations in each time length to obtain a sequencing result of each time length;
and carrying out data processing on the sequencing result of each time length to obtain the distance span corresponding to each time length.
3. The method according to claim 2, wherein the determining the number of rasterized bits corresponding to each duration within the preset time period comprises:
rasterizing the longitude and latitude of the multiple groups of base stations in each time length to obtain a rasterization result corresponding to each time length;
and counting the rasterization result corresponding to each time length to obtain the rasterization number corresponding to each time length.
4. The method of claim 3, wherein before the data processing the distance span and the rasterized number to determine a mobility index of the user, further comprising:
executing a first operation on the distance span of each time length, and determining a data type corresponding to each time length; the first operation is to determine a variance of the distance span corresponding to the first duration; if the distance span corresponding to the first time length is larger than a first threshold, determining that the data type corresponding to the first time length is a first type; the first time length is any time length in the preset time period; the first threshold is determined according to the variance;
counting the number of target durations in the preset time period; the target duration is any duration in the preset time period, and the corresponding data type is the duration of the first type;
and if the number of the target time lengths is smaller than a second threshold value, deleting the data corresponding to the target time lengths.
5. An apparatus for user mobility determination, comprising:
the acquisition module is configured to acquire network data and work parameter data in a preset time period of a user;
the processing module is configured to inquire the longitude and latitude of the base station corresponding to each piece of data in the network data in the working parameter data;
the processing module is further configured to determine a distance span and a rasterization number corresponding to each duration within a preset time period;
the processing module is further configured to determine a mobility index of the user according to the distance span and the rasterization number corresponding to each duration.
6. The apparatus of claim 5,
the processing module is further configured to determine a plurality of sets of base station latitudes and longitudes in each time period;
the processing module is further configured to perform sorting processing on the multiple groups of base station longitudes and latitudes in each time length to obtain a sorting result of each time length;
the processing module is further configured to perform data processing on the sequencing result of each duration to obtain a distance span corresponding to each duration.
7. The apparatus of claim 6,
the processing module is further configured to perform rasterization processing on the multiple groups of base station longitudes and latitudes in each time length to obtain a rasterization result corresponding to each time length;
the processing module is further configured to count the rasterization result corresponding to each duration to obtain the rasterization number corresponding to each duration.
8. The apparatus of claim 7,
the processing module is further configured to perform a first operation on the distance span of each duration, and determine a data type corresponding to each duration; the first operation is to determine a variance of the distance span corresponding to the first duration; if the distance span corresponding to the first time length is larger than a first threshold, determining that the data type corresponding to the first time length is a first type; the first time length is any time length in the preset time period; the first threshold is determined according to the variance;
the processing module is further configured to count the number of the target durations in the preset time period; the target duration is any duration in the preset time period, and the corresponding data type is the duration of the first type;
the processing module is further configured to delete the data corresponding to the target duration if the number of the target durations is smaller than a second threshold.
9. A user mobility determination device, characterized in that the user mobility determination device comprises:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the method of user mobility determination as claimed in any one of claims 1 to 4.
10. A computer-readable storage medium having instructions stored thereon, wherein the instructions in the computer-readable storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the method of user mobility determination as claimed in any of claims 1-4.
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