CN112333040B - Flow separation method and device, storage medium and computer equipment - Google Patents
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Abstract
In the technical scheme of the flow separation method, the flow separation device, the storage medium and the computer equipment provided by the embodiment of the invention, a plurality of flow logs are acquired, the flow logs comprise access type identifiers and flow data, application types corresponding to the access type identifiers are inquired according to the access type identifiers, a plurality of flow data used by application programs of each application type are counted according to the application types and the flow data corresponding to the plurality of flow logs, the plurality of flow data are separated according to access addresses corresponding to the acquired plurality of flow types for the application program of each application type, the flow type of each flow data is determined, the use habit and preference of a user can be analyzed by determining the flow types of the flow data, and the experience of the user in using vehicle-mounted application is facilitated to be improved.
Description
[ field of technology ]
The present invention relates to the field of communications technologies, and in particular, to a flow separation method, a flow separation device, a storage medium, and a computer device.
[ background Art ]
At present, the networking function of the vehicle is a development trend of the networking of the vehicle in the future. The vehicle networking components can be installed on the vehicle, and new requirements are set for the whole design, experiment, production, test and sales links of the automobile, and meanwhile, new requirements are set for mobile network operators. The main expression is as follows: firstly, the influence of the newly added components on the design, experiment, purchase and production of the automobile is mainly that the mature automobile manufacturing system of the automobile factory is incompatible with the virtual and subsequent cost components; and secondly, the flow management mechanism of the operator is incompatible with the flow requirements in the vehicle life flow.
In order to solve the basic contradiction between the two points, a unified internet of vehicles flow management platform is urgently required to be built so as to meet urgent requirements of a vehicle factory. At present, the prior art does not have a flow separation technology specially aiming at the internet of vehicles, and particularly has no corresponding solution to the technical problems of how to rapidly position the source of vehicle-mounted flow data used by a user, accurately count and analyze the vehicle-mounted flow data and the like.
[ invention ]
In view of the above, the present invention provides a traffic separation method, apparatus, storage medium and computer device, which can analyze the usage habit and preference of a user by determining the traffic type of traffic data, so as to facilitate improving the experience of the user in using vehicle applications.
In one aspect, an embodiment of the present invention provides a flow separation method, including:
acquiring a plurality of flow logs, wherein the flow logs comprise access type identifiers and flow data;
inquiring an application type corresponding to the access type identifier according to the access type identifier;
counting a plurality of flow data used by application programs of each application type according to the application types corresponding to the plurality of flow logs and the flow data;
and separating a plurality of flow data according to access addresses corresponding to the acquired flow types aiming at the application program of each application type, and determining the flow type of each flow data, wherein the type comprises a directional flow or a general flow.
Optionally, the traffic data includes address information;
the step of separating the plurality of flow data according to the access addresses corresponding to the acquired plurality of flow types to determine the flow type of each flow data comprises the following steps:
and determining the same access address as each address information according to the address information of each flow data and the access addresses corresponding to the acquired multiple flow types, and determining the flow type corresponding to the access address as the flow type of each flow data.
Optionally, the traffic log includes an access point name;
before the statistics of the plurality of traffic data used by the application program of each application type according to the application type corresponding to the plurality of traffic logs and the traffic data, the method further comprises:
and screening out the traffic logs with the same access point name from the traffic logs.
Optionally, after the separating the plurality of traffic data according to the access addresses corresponding to the acquired plurality of traffic types and determining the traffic type of each traffic data, the method further includes:
and determining the application preference degree corresponding to the application programs of each application type according to the flow data used by the application programs of each application type.
Optionally, the traffic data includes a number of times each application type of application program is accessed;
the determining the application preference degree corresponding to the application program of each application type according to the flow data used by the application program of each application type comprises the following steps:
counting the times of a plurality of users accessing the application program of each application type in a preset time period according to the flow data;
and sequencing the times by adopting an H index algorithm, and determining the times preference degree of the plurality of users in the application program of each application type.
Optionally, the traffic data includes access traffic;
the determining the application preference degree corresponding to the application program of each application type according to the flow data used by the application program of each application type comprises the following steps:
according to the flow data, counting access flow of a plurality of users for accessing application programs of each application type in a preset time period;
and sequencing the access flow by adopting an H index algorithm, and determining the flow preference degree of the plurality of users in the application program of each application type.
Optionally, the traffic data includes an application type;
the determining the application preference degree corresponding to the application program of each application type according to the flow data used by the application program of each application type comprises the following steps:
according to the flow data, counting the application types accessed by a plurality of users for the first time every day and the total days accessed by each user for the first time every day in a preset time period;
and sequencing the total days by adopting an H index algorithm, and determining the browsing preference of the user in the application program of each application type.
In another aspect, an embodiment of the present invention provides a flow separation device, including:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring a plurality of flow logs, and the flow logs comprise access type identifiers and flow data;
the query module is used for querying out the application type corresponding to the access type identifier according to the access type identifier;
the first determining module is used for counting a plurality of flow data used by the application program of each application type according to the application types corresponding to the plurality of flow logs and the flow data; and separating a plurality of flow data according to access addresses corresponding to the acquired flow types aiming at the application program of each application type, and determining the flow type of each flow data, wherein the type comprises a directional flow or a general flow.
On the other hand, the embodiment of the invention provides a storage medium, which comprises a stored program, wherein the device where the storage medium is located is controlled to execute the flow separation method when the program runs.
In another aspect, an embodiment of the present invention provides a computer device, including a memory for storing information including program instructions, and a processor for controlling execution of the program instructions, where the program instructions are loaded by the processor and execute the steps of the flow separation method described above.
In the technical scheme provided by the embodiment of the invention, a plurality of flow logs are acquired, the flow logs comprise access type identifiers and flow data, application types corresponding to the access type identifiers are inquired according to the access type identifiers, a plurality of flow data used by application programs of each application type are counted according to the application types and the flow data corresponding to the plurality of flow logs, the plurality of flow data are separated according to access addresses corresponding to the acquired plurality of flow types for the application programs of each application type, the flow type of each flow data is determined, and the use habit and preference of a user can be analyzed by determining the flow type of the flow data, so that the experience of the user using the vehicle-mounted application is facilitated to be improved.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a block diagram of a flow separation system according to an embodiment of the present invention;
FIG. 2 is a flow chart of a flow separation method according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a flow separation device according to an embodiment of the present invention;
fig. 4 is a schematic diagram of a computer device according to an embodiment of the invention.
[ detailed description ] of the invention
For a better understanding of the technical solution of the present invention, the following detailed description of the embodiments of the present invention refers to the accompanying drawings.
It should be understood that the described embodiments are merely some, but not all, embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The terminology used in the embodiments of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in this application and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be understood that the term "and/or" as used herein is merely one way of describing an association of associated objects, meaning that there may be three relationships, e.g., a and/or b, which may represent: the first and second cases exist separately, and the first and second cases exist separately. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship.
Fig. 1 is a schematic diagram of a flow separation system according to an embodiment of the present invention, and as shown in fig. 1, the system 100 includes: a flow analysis module 01 and a flow separation module 02.
In the embodiment of the present invention, the flow analysis module 01 is configured to obtain a plurality of flow logs, where the flow logs include an access type identifier and flow data.
The flow analysis module 01 is also used for inquiring the application type corresponding to the access type identifier according to the access type identifier; and counting a plurality of flow data used by the application program of each application type according to the application types and the flow data corresponding to the plurality of flow logs. It should be noted that, the traffic data includes an upstream traffic and a downstream traffic, and the traffic data is used to indicate traffic data used by one application program, so when traffic data used by an application program of the same application type is counted, a plurality of traffic data are counted.
In the embodiment of the present invention, the flow separation module 02 is configured to separate, for each application program of each application type, multiple flow data according to access addresses corresponding to the multiple acquired flow types, and determine a flow type of each flow data, where the type includes a directional flow or a general flow.
Based on the above flow separation system, the flow type of each flow data can be described in detail by steps 101 to 105, which are described in detail below, according to one embodiment of the present invention:
fig. 2 is a flow chart of a flow separation method according to an embodiment of the present invention, as shown in fig. 2, the method includes:
In the embodiment of the invention, the steps are executed by terminal equipment, wherein the terminal equipment comprises a car machine, a computer, a tablet personal computer, a mobile phone or a wearable device. When the terminal equipment comprises a vehicle machine, the flow separation method provided by the embodiment of the invention is applied to the field of the Internet of vehicles, and is particularly used for flow separation of the Internet of vehicles.
In the embodiment of the invention, the flow log comprises an access type identifier and flow data.
In the embodiment of the present invention, before executing step 101, the method further includes: and recording flow logs generated by the tasks, and storing the flow logs into a database. The process of obtaining multiple flow logs of step 101 may therefore be performed by obtaining multiple flow logs from a database.
In the embodiment of the invention, the application types can comprise navigation types, music types, video types and the like.
In the embodiment of the present invention, before executing step 102, the method further includes: and pre-establishing a corresponding relation list of the access type identifier and the application type. Therefore, when executing step 102, the application type corresponding to the access type identifier may be queried through the correspondence list, for example, when the access type identifier is "1", the application type of the access type identifier is a navigation class.
In the embodiment of the invention, the flow log also comprises an access point name.
In the embodiment of the invention, the flow logs with the same access point name are screened out, so that the flow data used by application programs with different application types can be counted in the subsequent steps, and the flow type corresponding to each flow data can be determined.
In the embodiment of the invention, the flow data comprises an uplink flow and a downlink flow, and the flow data is used for indicating the flow data used by one application program, so that when the flow data used by the application program of the same application type is counted, a plurality of flow data are counted. For example, the plurality of traffic logs includes the traffic data of video a, the traffic data of video B, the traffic data of video C, the traffic data of music a, and the traffic data of music B, so in the process of executing step 103, the traffic data of the application program of the video class are combined together to generate a plurality of traffic data used by the application programs of the video class (video a, video B, and video C), and the plurality of traffic data includes the traffic data of video a, the traffic data of video B, and the traffic data of video C.
Similarly, the flow data of the application program of the music class are combined together, and a plurality of flow data used by the application programs of the music class (music a and music b) including the flow data of music a and the flow data of music b are generated.
In the embodiment of the invention, the traffic data comprises address information, wherein the address information can comprise URL or IP. Specifically, the process of executing the "separating the plurality of traffic data according to the access addresses corresponding to the plurality of acquired traffic types" in step 105, and determining the traffic type of each traffic data may include: according to the address information of each flow data and the access addresses corresponding to the acquired flow types, determining the access address identical to each address information, and determining the flow type corresponding to the access address as the flow type of each flow data.
That is, before executing step 104, the system defines access addresses corresponding to each flow type in advance, and if it is determined that the address information of the quantity data is the same as the access address corresponding to a certain flow type, the flow type corresponding to the access address is determined as the flow type of each flow data. Wherein the address information includes URL or IP. In addition, the traffic data may include information such as uplink traffic, downlink traffic, and time, in addition to address information (URL or IP), which is not limited in the embodiment of the present invention.
In the embodiment of the invention, the flow data is separated by determining the flow type of each flow data, so that the use habit and preference of a user can be analyzed through the separated data flow, and the experience of the user in using the vehicle-mounted application is improved conveniently.
Further, after step 105, the method further includes:
and 106, determining the application preference degree corresponding to the application programs of each application type according to the flow data used by the application programs of each application type.
In the embodiment of the present invention, as an alternative, the traffic data includes the number of times of accessing the application program of each application type. Specifically, step 106 may specifically include: counting the times of a plurality of users accessing the application program of each application type in a preset time period according to the flow data; and sequencing the times by adopting an H index algorithm, and determining the times preference degree of a plurality of users in the application program of each application type.
For example, taking an example that the application type includes music and video, the preset time period includes one week, the number of browsing times of application programs of a plurality of users accessing the music in one week is counted as 10 times, and the number of browsing times of application programs of a plurality of users accessing the video in one week is counted as 20 times. Further, the times are ranked by adopting an H index algorithm, and the times preference degree of a plurality of users in the application program of each application type is determined. For example, the ranking is performed from large to small, and the browsing times corresponding to the plurality of types of applications are ranked from large to small, so as to generate the times preference degree. For example: and sequencing the browsing times corresponding to the application programs of the music class from large to small for 10 times and the browsing times corresponding to the application programs of the video class for 20 times, and generating the times preference degree. The number of browsing times corresponding to the video application program is large, so that the frequency preference of the video application program is large.
As another alternative, the traffic data includes access traffic. Specifically, step 106 may specifically include: according to the flow data, counting the access flow of a plurality of users for accessing the application program of each application type in a preset time period; and sequencing the access flow by adopting an H index algorithm, and determining the flow preference degree of a plurality of users in the application program of each application type.
For example, taking an example that the application type includes music and video, the preset time period includes one week, the access flow of the application program of the plurality of users accessing the music in one week is counted as 100M, and the access flow of the application program of the plurality of users accessing the video in one week is counted as 200M. Further, the flow is ranked by adopting an H index algorithm, and the flow preference degree of a plurality of users in the application program of each application type is determined. For example, the ranking is performed from large to small, and the access traffic corresponding to the plurality of types of applications is ranked from large to small, so as to generate the traffic preference. For example: and ordering the access flow 100M corresponding to the application program of the music class and the access flow 200M corresponding to the application program of the video class from large to small to generate flow preference. Because the access flow corresponding to the video-type application program is larger, the flow preference of the video-type application program is larger.
As another alternative, the traffic data includes an application type. Specifically, step 106 may specifically include: according to the flow data, counting the application types of a plurality of users which are accessed for the first time every day and the total days of the application types which are accessed for the first time every day by each user in a preset time period; and sequencing the total days by adopting an H index algorithm, and determining the browsing preference of the user in the application program of each application type.
For example, taking an application type including music and video, and taking a preset period including one week as an example, counting the total days of the first access of the user to the music every day in one week as 3 days; the total number of days that the user first accessed the video class daily during a week was counted as 5 days. Further, the total days are ranked by adopting an H index algorithm, and browsing preference of the user in the application program of each application type is determined. For example, the ranking is performed from large to small, and the total number of days corresponding to the plurality of types of applications is ranked from large to small, thereby generating the browsing preference. For example: and sequencing the total days corresponding to the music class from big to small, wherein the total days corresponding to the music class are 3 days, and the total days corresponding to the video class are 5 days, so as to generate the browsing preference. Since the total number of days corresponding to the video class is large, the browsing preference of the video class is large.
It should be noted that, besides the above-mentioned frequency preference, flow preference and browsing preference, other types of preference may be determined, which is not limited by the embodiment of the present invention.
In the embodiment of the invention, the application preference degree corresponding to each application program of each application type is determined through step 106, so that the application program with the user preference can be recommended to the user according to the generated application preference degree, and the convenience of using the application program by the user is improved.
In the technical scheme provided by the embodiment of the invention, a plurality of flow logs are acquired, the flow logs comprise access type identifiers and flow data, application types corresponding to the access type identifiers are inquired according to the access type identifiers, a plurality of flow data used by application programs of each application type are counted according to the application types and the flow data corresponding to the plurality of flow logs, the plurality of flow data are separated according to access addresses corresponding to the acquired plurality of flow types for the application programs of each application type, the flow type of each flow data is determined, and the use habit and preference of a user can be analyzed by determining the flow type of the flow data, so that the experience of the user using the vehicle-mounted application is facilitated to be improved.
Fig. 3 is a schematic structural diagram of a flow separation device according to an embodiment of the present invention, as shown in fig. 3, the flow separation device includes: the device comprises an acquisition module 11, a query module 12 and a first determination module 13.
The obtaining module 11 is configured to obtain a plurality of flow logs, where the flow logs include an access type identifier and flow data;
the query module 12 is configured to query, according to the access type identifier, an application type corresponding to the access type identifier;
the first determining module 13 is configured to count a plurality of traffic data used by an application program of each application type according to application types corresponding to the plurality of traffic logs and the traffic data; and separating a plurality of flow data according to access addresses corresponding to the acquired flow types aiming at the application program of each application type, and determining the flow type of each flow data, wherein the type comprises a directional flow or a general flow.
In the embodiment of the invention, the flow data comprises address information; the first determining module 13 of the device is specifically configured to determine, according to address information of each flow data and access addresses corresponding to the acquired multiple flow types, an access address identical to each address information, and determine a flow type corresponding to the access address as a flow type of each flow data.
In the embodiment of the invention, the flow log comprises an access point name; the apparatus further comprises: a screening module 14.
The screening module 14 is configured to screen out traffic logs with the same access point name from the plurality of traffic logs.
In the embodiment of the invention, the device further comprises: a second determination module 15.
The second determining module 15 is configured to determine, according to the traffic data used by the application program of each application type, an application preference corresponding to the application program of each application type.
In the embodiment of the invention, the flow data comprises the number of times of accessing the application program of each application type; the second determining module 15 of the device is specifically configured to count, according to the flow data, the number of times that the plurality of users access the application program of each application type in a preset time period; and sequencing the times by adopting an H index algorithm, and determining the times preference degree of the plurality of users in the application program of each application type.
In the embodiment of the invention, the flow data comprises access flow; the second determining module 15 of the device is specifically configured to calculate, according to the flow data, access flows of a plurality of users for accessing application programs of each application type in a preset time period; and sequencing the access flow by adopting an H index algorithm, and determining the flow preference degree of the plurality of users in the application program of each application type.
In the embodiment of the invention, the flow data comprises an application type; the second determining module 15 of the device is specifically configured to count, according to the flow data, an application type of a plurality of users accessing the application type for the first time every day and a total number of days in a preset time period, where each user accesses the application type for the first time every day; and sequencing the total days by adopting an H index algorithm, and determining the browsing preference of the user in the application program of each application type.
In the technical scheme provided by the embodiment of the invention, a plurality of flow logs are acquired, the flow logs comprise access type identifiers and flow data, application types corresponding to the access type identifiers are inquired according to the access type identifiers, a plurality of flow data used by application programs of each application type are counted according to the application types and the flow data corresponding to the plurality of flow logs, the plurality of flow data are separated according to access addresses corresponding to the acquired plurality of flow types for the application programs of each application type, the flow type of each flow data is determined, and the use habit and preference of a user can be analyzed by determining the flow type of the flow data, so that the experience of the user using the vehicle-mounted application is facilitated to be improved.
The embodiment of the invention provides a storage medium, which comprises a stored program, wherein the program is used for controlling equipment where the storage medium is positioned to execute the steps of the embodiment of the flow separation method, and the specific description can be seen from the embodiment of the flow separation method.
The embodiment of the invention provides a computer device, which comprises a memory and a processor, wherein the memory is used for storing information comprising program instructions, the processor is used for controlling the execution of the program instructions, and the program instructions realize the steps of the flow separation method when being loaded and executed by the processor. For a specific description, reference is made to the embodiments of the flow separation method described above.
Fig. 4 is a schematic diagram of a computer device according to an embodiment of the present invention. As shown in fig. 4, the computer device 4 of this embodiment includes: the processor 41, the memory 42, and the computer program 43 stored in the memory 42 and capable of running on the processor 41, where the computer program 43 is executed by the processor 41 to implement the flow separation method according to the embodiment, and is not repeated herein. Alternatively, the computer program when executed by the processor 41 implements the functions of the embodiments applied to each model/unit in the flow separation device, and is not described herein in detail for avoiding repetition.
The computer device 4 includes, but is not limited to, a processor 41, a memory 42. It will be appreciated by those skilled in the art that fig. 4 is merely an example of computer device 4 and is not intended to limit computer device 4, and may include more or fewer components than shown, or may combine certain components, or different components, e.g., computer device 4 may also include input and output devices, network access devices, buses, etc.
The processor 41 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 42 may be an internal storage unit of the computer device 4, such as a hard disk or a memory of the computer device 4. The memory 42 may also be an external storage device of the computer device 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the computer device 4. Further, the memory 42 may also include both internal storage units and external storage devices of the computer device 4. The memory 42 is used to store computer programs and other programs and data required by the computer device 4. The memory 42 may also be used to temporarily store data that has been output or is to be output.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
In the several embodiments provided in the present invention, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of elements is merely a logical function division, and there may be additional divisions of actual implementation, e.g., multiple elements or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in hardware plus software functional units.
The integrated units implemented in the form of software functional units described above may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium, and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) or a Processor (Processor) to perform part of the steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather to enable any modification, equivalent replacement, improvement or the like to be made within the spirit and principles of the invention.
Claims (10)
1. A flow separation method, comprising:
acquiring a plurality of flow logs, wherein the flow logs comprise access type identifiers and flow data;
inquiring an application type corresponding to the access type identifier according to the access type identifier;
counting a plurality of flow data used by application programs of each application type according to the application types corresponding to the plurality of flow logs and the flow data;
and separating a plurality of flow data according to access addresses corresponding to the acquired flow types aiming at the application program of each application type, and determining the flow type of each flow data, wherein the flow type comprises a directional flow or a general flow.
2. The method of claim 1, wherein the traffic data includes address information;
the step of separating the plurality of flow data according to the access addresses corresponding to the acquired plurality of flow types to determine the flow type of each flow data comprises the following steps:
and determining the same access address as each address information according to the address information of each flow data and the access addresses corresponding to the acquired multiple flow types, and determining the flow type corresponding to the access address as the flow type of each flow data.
3. The method of claim 1, wherein the traffic log comprises an access point name;
before the statistics of the plurality of traffic data used by the application program of each application type according to the application type corresponding to the plurality of traffic logs and the traffic data, the method further comprises:
and screening out the traffic logs with the same access point name from the traffic logs.
4. The method according to claim 1, wherein after separating the plurality of traffic data according to the access addresses corresponding to the acquired plurality of traffic types to determine the traffic type of each traffic data, further comprising:
and determining the application preference degree corresponding to the application programs of each application type according to the flow data used by the application programs of each application type.
5. The method of claim 4, wherein the traffic data includes a number of times an application program of each application type is accessed;
the determining the application preference degree corresponding to the application program of each application type according to the flow data used by the application program of each application type comprises the following steps:
counting the times of a plurality of users accessing the application program of each application type in a preset time period according to the flow data;
and sequencing the times by adopting an H index algorithm, and determining the times preference degree of the plurality of users in the application program of each application type.
6. The method of claim 4, wherein the traffic data comprises access traffic;
the determining the application preference degree corresponding to the application program of each application type according to the flow data used by the application program of each application type comprises the following steps:
according to the flow data, counting access flow of a plurality of users for accessing application programs of each application type in a preset time period;
and sequencing the access flow by adopting an H index algorithm, and determining the flow preference degree of the plurality of users in the application program of each application type.
7. The method of claim 4, wherein the traffic data comprises an application type;
the determining the application preference degree corresponding to the application program of each application type according to the flow data used by the application program of each application type comprises the following steps:
according to the flow data, counting the application types accessed by a plurality of users for the first time every day and the total days accessed by each user for the first time every day in a preset time period;
and sequencing the total days by adopting an H index algorithm, and determining the browsing preference of the user in the application program of each application type.
8. A flow separation device, comprising:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring a plurality of flow logs, and the flow logs comprise access type identifiers and flow data;
the query module is used for querying out the application type corresponding to the access type identifier according to the access type identifier;
the first determining module is used for counting a plurality of flow data used by the application program of each application type according to the application types corresponding to the plurality of flow logs and the flow data; and separating a plurality of flow data according to access addresses corresponding to the acquired flow types aiming at the application program of each application type, and determining the flow type of each flow data, wherein the flow type comprises a directional flow or a general flow.
9. A storage medium comprising a stored program, wherein the program, when run, controls a device in which the storage medium is located to perform the flow separation method of any one of claims 1 to 7.
10. A computer device comprising a memory for storing information including program instructions and a processor for controlling the execution of the program instructions, characterized in that the program instructions, when loaded and executed by the processor, implement the steps of the flow separation method of any one of claims 1 to 7.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102547786A (en) * | 2010-12-31 | 2012-07-04 | 上海博泰悦臻电子设备制造有限公司 | 3G (the 3rd Generation Telecommunication) flow analysis method and device of vehicle-mounted device |
| CN104125596A (en) * | 2014-07-07 | 2014-10-29 | 北京奇虎科技有限公司 | Data traffic statistics method and data traffic statistics device |
| CN105022729A (en) * | 2014-04-15 | 2015-11-04 | 中国移动通信集团河北有限公司 | User preference determination method and device |
| CN105101270A (en) * | 2014-05-12 | 2015-11-25 | 宇龙计算机通信科技(深圳)有限公司 | Traffic managing device and traffic managing method for terminal |
| CN106303751A (en) * | 2015-05-18 | 2017-01-04 | 中兴通讯股份有限公司 | A kind of realization method and system orienting flow bag |
| CN108234141A (en) * | 2016-12-22 | 2018-06-29 | 中移（杭州）信息技术有限公司 | A kind of orientation flow processing method and server |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106650760A (en) * | 2015-10-28 | 2017-05-10 | 华为技术有限公司 | Method and device for recognizing user behavioral object based on flow analysis |
-
2020
- 2020-10-12 CN CN202011085869.2A patent/CN112333040B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102547786A (en) * | 2010-12-31 | 2012-07-04 | 上海博泰悦臻电子设备制造有限公司 | 3G (the 3rd Generation Telecommunication) flow analysis method and device of vehicle-mounted device |
| CN105022729A (en) * | 2014-04-15 | 2015-11-04 | 中国移动通信集团河北有限公司 | User preference determination method and device |
| CN105101270A (en) * | 2014-05-12 | 2015-11-25 | 宇龙计算机通信科技(深圳)有限公司 | Traffic managing device and traffic managing method for terminal |
| CN104125596A (en) * | 2014-07-07 | 2014-10-29 | 北京奇虎科技有限公司 | Data traffic statistics method and data traffic statistics device |
| CN106303751A (en) * | 2015-05-18 | 2017-01-04 | 中兴通讯股份有限公司 | A kind of realization method and system orienting flow bag |
| CN108234141A (en) * | 2016-12-22 | 2018-06-29 | 中移（杭州）信息技术有限公司 | A kind of orientation flow processing method and server |
Non-Patent Citations (1)
| Title |
|---|
| 许闻秋 ; 雒江涛 ; 杨军超 ; .基于Hadoop的校园网视频流量访问偏好分析.重庆邮电大学学报(自然科学版).2016,(06),全文. * |
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