CN113076316B - Information relation mapping analysis method, device, equipment and storage medium - Google Patents
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Abstract
The embodiment of the invention discloses an analysis method, a device, equipment and a storage medium for information relation mapping, wherein the method comprises the following steps: extracting UA keywords in a user agent UA from DPI data to generate a terminal UA keyword temporary table; screening the acquired terminal data according to a preset supporting network to obtain a terminal data table; using a terminal UA keyword temporary table and a terminal data table to update the increment of the current terminal annotation table; screening out screening UA keywords corresponding to TACs through the occurrence times of UA keywords corresponding to each TAC in a terminal UA keyword temporary table, and generating a terminal UA keyword filtering table; and carrying out preset association aggregation operation on the terminal UA keyword filtering table and the terminal annotation table to obtain a terminal TAC matching table. The embodiment of the invention can obtain the mapping relation of the TAC and the terminal information by extracting the keyword information in the UA in the DPI and carrying out association analysis on the terminal information.
Description
Technical Field
The embodiment of the invention relates to an information association technology, in particular to an analysis method, an analysis device, an analysis equipment and a storage medium for information relation mapping.
Background
With the continuous development of the informatization technology level, more and more intelligent terminal devices emerge in the market, and with the continuous maturity of the 5G technology, the 5G terminal devices are also continuously popularized to more users, and how to associate the relation mapping of the users and the 5G terminal devices becomes a problem to be broken through, such as machine changing duration analysis of the users, using time length analysis of the 5G terminals, number analysis of 5G package users using the 5G terminals, geographical distribution information and other data analysis indexes for scene marketing. In order to expand the analysis possibility of more index dimensions, the relation mapping processing of the user information and the 5G terminal information is needed, so that the expansion of points and planes is performed.
At present, the existing network generally analyzes DPI (Deep Packet Inspection ) data received by a big data platform, but the information in the DPI data is complex and lacks formatting, and the data source is single, the information of the user cannot contain terminal related information, and data index analysis of the terminal direction cannot be performed, so that the mapping relation between the type allocation codes (Type Allocation Code, TAC) and the terminal needs to be analyzed through associating terminal information.
Disclosure of Invention
The embodiment of the invention provides an analysis method, an analysis device, analysis equipment and a storage medium for information relation mapping, so as to obtain the mapping relation between TAC and terminal information.
In a first aspect, an embodiment of the present invention provides a method for analyzing an information relationship map, including:
extracting UA keywords in User Agents (UAs) from deep packet inspection DPI data to generate a terminal UA keyword temporary table; the terminal UA keyword temporary table comprises equipment names, type allocation codes TAC and UA keywords of each piece of DPI data;
screening the acquired terminal data according to a preset supporting network to obtain a terminal data table; the terminal data table comprises the equipment name of the terminal and a supporting network;
using the terminal UA keyword temporary table and the terminal data table to update the increment of the current terminal annotation table;
screening out the screening UA keywords corresponding to the TAC through the occurrence times of the UA keywords corresponding to each TAC in the terminal UA keyword temporary table, and generating a terminal UA keyword filtering table;
and carrying out preset association aggregation operation on the terminal UA keyword filtering table and the terminal annotation table to obtain a terminal TAC matching table.
In a second aspect, an embodiment of the present invention further provides an apparatus for analyzing information relationship mapping, including:
the key word temporary table generation module is used for extracting UA key words in the user agent UA from the deep packet inspection DPI data to generate a terminal UA key word temporary table; the terminal UA keyword temporary table comprises equipment names, type allocation codes TAC and UA keywords of each piece of DPI data;
the terminal data table generation module is used for screening the acquired terminal data according to a preset supporting network to obtain a terminal data table; the terminal data table comprises the equipment name of the terminal and a supporting network;
the terminal registry updating module is used for carrying out incremental updating on the current terminal annotation table by using the terminal UA keyword temporary table and the terminal data table;
the keyword filtering table generating module is used for screening out screening UA keywords corresponding to the TACs through the occurrence times of the UA keywords corresponding to each TAC in the terminal UA keyword temporary table to generate a terminal UA keyword filtering table;
and the terminal TAC matching table generation module is used for carrying out preset association aggregation operation on the terminal UA keyword filtering table and the terminal annotation table to obtain a terminal TAC matching table.
In a third aspect, an embodiment of the present invention further provides an information relationship mapping analysis apparatus, where the information relationship mapping analysis apparatus includes:
one or more processors;
a memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement a method of analysis of information-relation maps as provided by any of the embodiments of the present invention.
In a fourth aspect, embodiments of the present invention also provide a storage medium containing computer-executable instructions which, when executed by a computer processor, are used to perform a method of analysis of an information relationship map as provided by any of the embodiments of the present invention.
According to the embodiment of the invention, the mapping relation between the TAC and the terminal information is obtained by extracting the keyword information in the UA in the DPI and carrying out the association analysis on the terminal information, so that the problem that the data index analysis of the terminal direction cannot be carried out by only analyzing the DPI data is solved, and the effect of obtaining the mapping relation between the TAC and the terminal information by analysis is realized.
Drawings
FIG. 1 is a flow chart of a method for analyzing information relationship mapping in accordance with a first embodiment of the present invention;
FIG. 2 is a flow chart of a method for analyzing an information relationship map in a second embodiment of the present invention;
FIG. 3 is a flow chart of a method for analyzing information relationship mapping in a third embodiment of the present invention;
FIG. 4 is a schematic structural diagram of an analysis device for information relationship mapping in a fourth embodiment of the present invention;
fig. 5 is a schematic structural diagram of an analysis device for information relationship mapping in the fifth embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
Example 1
Fig. 1 is a flowchart of an analysis method for information relationship mapping according to an embodiment of the present invention, where the embodiment is applicable to a case of analyzing relationship mapping between terminal information and DPI data, the method may be performed by an analysis device for information relationship mapping, and the device may be implemented by hardware and/or software, and the method specifically includes the following steps:
step 110, extracting UA keywords in a user agent UA from deep packet inspection DPI data to generate a terminal UA keyword temporary table;
the temporary list of the terminal UA keywords comprises the equipment name, the type allocation code TAC and the UA keywords of each piece of DPI data. The ticket data of the DPI data can be processed, UA keywords of UA in the ticket are extracted through a user-defined ETL (Extract-Transform-Load) program, and the UA keywords are put into a pre-established database, for example, a database established through Clickhouse. The temporary list of the terminal UA key words may include the end time of each ticket data, an international mobile equipment identification (International Mobile Equipment Identity, IMEI), TAC and UA, and may further include a device alias, a brand name, a device formatting model name, a date, and the like.
Step 120, screening the acquired terminal data according to a preset supporting network, and obtaining a terminal data table;
the terminal data table comprises the device name of the terminal and the supporting network. The terminal information can be crawled through a crawler program and is stored in a database in an arrangement mode. The fields of the original crawler data, such as medium brands, models, terminal support network, formatted model names, terminal aliases and the like, need to be subjected to data screening according to the terminal support network fields, for example, the user using a 5G terminal is subjected to model name formatting operation, the formatting mode is to remove contents in all brackets in the terminal information, including version, memory, storage size and the like, according to the model names, and only preset information, such as Iphone12, mate40 and the like, is reserved. Optionally, the screening of the obtained terminal data according to a preset supporting network, to obtain a terminal data table, includes: and comparing the support network in each piece of terminal data with a preset support network, reserving the terminal data of which the support network is the same as the preset support network, and recording the terminal data in a terminal data table. The preset support network may be 5G, 4G, etc.
130, using a terminal UA keyword temporary table and a terminal data table to update the increment of the current terminal annotation table;
wherein the existing prepared tag data may be imported into a terminal registry and the terminal registry stored in a database. When the temporary list of the UA keywords of the terminal is obtained, the data of the temporary list of the UA keywords of the terminal can be imported into the registry of the terminal, so that the incremental update of the data is realized, and the situation that repeated UA keywords are put in storage is ensured.
Step 140, screening out the screening UA keywords corresponding to the TACs through the occurrence times of the UA keywords corresponding to each TAC in the terminal UA keyword temporary table, and generating a terminal UA keyword filtering table;
the aggregation analysis may be performed on the TAC and the UA keywords in the temporary UA keyword table of the terminal, which may be that the number of occurrences of each UA keyword corresponding to each TAC is calculated, the UA keyword with the highest number of occurrences is used as the UA keyword to be filtered, and the final association operation result is written into the UA keyword filtering table of the terminal. Optionally, screening out a screening UA keyword corresponding to the TAC through the occurrence number of UA keywords corresponding to each TAC in the terminal UA keyword temporary table, and generating a terminal UA keyword filtering table, including: calculating the occurrence times of UA keywords corresponding to each TAC; using the UA keywords with the largest occurrence number as screening keywords of the corresponding TAC; and recording the screening keywords in a terminal UA keyword filtering table.
And 150, carrying out preset association aggregation operation on the terminal UA keyword filtering table and the terminal annotation table to obtain a terminal TAC matching table.
And performing association operations such as grouping, aggregation operation, topN algorithm and the like on the terminal UA keyword filtering table and the terminal annotation table, and finally aggregating a data terminal table and a terminal TAC matching table. The terminal TAC matching table may include field information such as TAC, brand name, device name, and date.
According to the technical scheme, the mapping relation between the TAC and the terminal information is obtained by extracting the keyword information in the UA in the DPI and carrying out the association analysis on the terminal information, the problem that the data index analysis of the terminal direction cannot be carried out by only analyzing the DPI data is solved, and the effect of obtaining the mapping relation between the TAC and the terminal information by analysis is achieved.
Example two
Fig. 2 is a flowchart of an analysis method of information relation mapping according to a second embodiment of the present invention, where the method is further refined based on the above technical solution, and the method includes:
step 210, screening DPI data, and filtering null value and invalid data;
wherein, invalid data is DPI data except a preset terminal system. And carrying out data screening once aiming at the UA, filtering out { null value and invalid data }, wherein the invalid data is completed by carrying out regular matching on terminal operating system information in the UA, and finally reserving DPI data which is a preset terminal system in the UA, wherein the preset terminal system can be an IOS (Internet of things) and an Android system.
Step 220, extracting UA keywords in the user agent UA from deep packet inspection DPI data to generate a terminal UA keyword temporary table;
step 230, screening the acquired terminal data according to a preset supporting network, and obtaining a terminal data table;
step 240, using the terminal UA keyword temporary table and the terminal data table to update the increment of the current terminal annotation table;
step 250, screening out the screening UA keywords corresponding to the TACs through the occurrence times of the UA keywords corresponding to each TAC in the terminal UA keyword temporary table, and generating a terminal UA keyword filtering table;
and 260, carrying out preset association aggregation operation on the terminal UA keyword filtering table and the terminal annotation table to obtain a terminal TAC matching table.
Optionally, performing preset association aggregation operation on the terminal UA keyword filtering table and the terminal annotation table to obtain a terminal TAC matching table, including:
aggregating the terminal UA keyword filtering table and the terminal annotation table to obtain an incremented terminal annotation table;
calculating UA keywords uniquely corresponding to the TAC in the terminal annotation table after increment based on the TopN algorithm;
and carrying out tandem updating through a preset terminal information field to obtain a relation mapping of the TAC and the terminal information, and recording the relation mapping into a terminal TAC matching table.
The method comprises the steps of integrating a terminal UA keyword filtering table and a terminal annotation table together, performing TopN operation and series updating, and finally realizing the mapping relation between TAC and terminal information. And aggregating the terminal UA keyword filtering list and the terminal annotation list. Filtering TAC data, and calculating the unique value of the UA keyword corresponding to the TAC according to the TopN algorithm. Finally, the relation mapping between the TAC and the terminal is obtained by carrying out series updating through a preset equipment information field, so that the relation mapping between the TAC and the terminal information is realized. The preset terminal information field may be a terminal name field, etc.
Example III
Fig. 3 is a flowchart of an analysis method for information relation mapping according to a third embodiment of the present invention, where the embodiment is a specific implementation manner based on the above technical solution, but is not limited to the following implementation manner, and the method specifically includes:
step 301, extracting DPI data, where data required in the process is exemplified as follows:
wherein the data amount of one day of the current network is selected as a demonstration sample, and IMEI (International Mobile Equipment Identity ).
Step 302, performing data screening on DPI data aiming at userAgents, filtering { null values and invalid data }, wherein the invalid data is completed through regular matching of terminal operating system information in userAgents, and finally reserving IOS and Android systems.
Step 303, generating a temporary table (device_ua_keyword_all) of a terminal UA keyword from the DPI data obtained in the two steps, which is exemplified as follows:
the device_alias is a terminal alias, the vendor_name is a brand, and the device_format is a formatted model name.
Step 304, performing aggregation analysis on the TAC and the UA keywords in the temporary table of the UA keywords of the terminal generated in step 303, and generating a filtering table of the UA keywords of the terminal, that is, calculating the most accurate UA keywords of each TAC, and keeping the best solution by calculating the number of occurrences of each keyword of each TAC, taking the highest data as the reference, and continuously updating the data, where the process result is as follows:
| device_alias | tac | pv | day |
| X20A | 01353400 | 11 | 20201103 |
| IPHONE6,1 | 01398700 | 11 | 20201103 |
| _VSIMLL | 15708549 | 11 | 20201103 |
step 311, the terminal information is collected and put in storage, and the implementation process is as follows: * *
date；ls crawler_original.csv|xargs-i-t cat{}|clickhouse-client--database＝hdfs--format_csv_delimiter'|'--query＝"INSERT INTO hdfs.device_crawler_original FORMAT CSV"；date
Step 312, inputting the terminal crawler data into a crawler data original table (crawler_original);
step 313, screening original crawler data, screening fields such as brands, models, terminal support network, format model names, terminal aliases and the like, wherein data screening is required according to the terminal support network fields, the user using the 5G terminal is carrying out model name formatting operation, the formatting mode is to remove contents in all brackets according to model names, including information such as version, memory, storage size and the like, and only essence, for example Iphone12 and mate40 is reserved.
Step 314, inputting the screened data into a terminal crawler data format table (device_crawler_format), and warehousing, which is exemplified as follows:
step 315, importing the existing prepared tag data (terminal UA keyword temporary table) into a terminal annotation table device_tag; the method mainly aims to realize incremental update of data and ensure that no repeated UA keywords are put in storage; and frequency calculation is carried out on each UA keyword (namely, the occurrence frequency of each keyword is calculated);
step 316, as a result of step 315, the step 316 process is to aggregate and update the terminal crawler formatting table device_crawler_format and the terminal labeling table device_tag, and update the two data sources to the latest state, namely, the synchronization data, which is exemplified as follows:
step 305, integrating multi-table aggregation, topN operation and serial updating together, and finally realizing the mapping relation between TAC and terminal information;
the keyword filtering table device_ua_keyword_filter and the terminal annotation table device_tag are aggregated; filtering TAC data, and calculating a unique value of the TAC again according to a TopN algorithm; finally, serial updating is carried out through the Alias field to obtain the relation mapping between the TAC and the terminal, and the flow is ended.
The result set is as follows:
| Tac | Vendor_name | Device_name | day |
| 00000008 | Huawei | hua is nova6SE | 20201103 |
| 00100115 | OPPO | OPPOR9 | 20201103 |
Example IV
Fig. 4 is a schematic structural diagram of an information relationship mapping analysis device according to a fourth embodiment of the present invention, where the device may be disposed in an information relationship mapping analysis apparatus, and the information relationship mapping analysis apparatus may be a computer device such as a server, and the device specifically includes:
the keyword temporary table generating module 410 is configured to extract UA keywords in the user agent UA from deep packet inspection DPI data, and generate a terminal UA keyword temporary table; the temporary list of the terminal UA keywords comprises equipment names, type allocation codes TAC and UA keywords of each piece of DPI data;
the terminal data table generating module 420 is configured to screen the acquired terminal data according to a preset supporting network, so as to obtain a terminal data table; the terminal data table comprises the equipment name of the terminal and a supporting network;
the terminal registry updating module 430 is configured to use the temporary table of the UA keyword of the terminal and the terminal data table to perform incremental updating on the current terminal annotation table;
the keyword filtering table generating module 440 is configured to screen out a screening UA keyword corresponding to a TAC according to the occurrence number of UA keywords corresponding to each TAC in the terminal UA keyword temporary table, and generate a terminal UA keyword filtering table;
the terminal TAC matching table generating module 450 is configured to perform a preset association aggregation operation on the terminal UA keyword filtering table and the terminal annotation table, so as to obtain a terminal TAC matching table.
According to the technical scheme, the mapping relation between the TAC and the terminal information is obtained by extracting the keyword information in the UA in the DPI and carrying out the association analysis on the terminal information, the problem that the data index analysis of the terminal direction cannot be carried out by only analyzing the DPI data is solved, and the effect of obtaining the mapping relation between the TAC and the terminal information by analysis is achieved.
Optionally, the analysis device of the information relation map further includes:
the DPI data screening module is used for screening the DPI data before extracting UA keywords in the user agent UA from the deep packet detection DPI data and generating a terminal UA keyword temporary table, and filtering null values and invalid data; wherein, invalid data is DPI data except a preset terminal system.
Optionally, the keyword filtering table generating module is specifically configured to:
calculating the occurrence times of UA keywords corresponding to each TAC;
using the UA keywords with the largest occurrence number as screening keywords of the corresponding TAC;
and recording the screening keywords in a terminal UA keyword filtering table.
Optionally, the terminal data table generating module 420 is specifically configured to:
and comparing the support network in each piece of terminal data with a preset support network, reserving the terminal data of which the support network is the same as the preset support network, and recording the terminal data in a terminal data table.
Optionally, the terminal TAC matching table generating module 450 is specifically configured to:
aggregating the terminal UA keyword filtering table and the terminal annotation table to obtain an incremented terminal annotation table;
calculating UA keywords uniquely corresponding to the TAC in the terminal annotation table after increment based on the TopN algorithm;
and carrying out tandem updating through a preset terminal information field to obtain a relation mapping of the TAC and the terminal information, and recording the relation mapping into a terminal TAC matching table.
The analysis device for the information relation mapping provided by the embodiment of the invention can execute the analysis method for the information relation mapping provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example five
Fig. 5 is a schematic structural diagram of an information relationship mapping analysis device according to a fifth embodiment of the present invention, where, as shown in fig. 5, the information relationship mapping analysis device includes a processor 510, a memory 520, an input device 530, and an output device 540; the number of processors 510 in the analysis device of the information-relation map may be one or more, and one processor 510 is taken as an example in fig. 5; the processor 510, memory 520, input means 530 and output means 540 in the analysis device of the information relation map may be connected by a bus or other means, for example by a bus connection in fig. 5.
The memory 520 serves as a computer-readable storage medium, and may be used to store software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the analysis method of the information relationship map in the embodiment of the present invention (e.g., the keyword temporary table generation module 410, the terminal data table generation module 420, the terminal registry update module 430, the keyword filtering table generation module 440, and the terminal TAC matching table generation module 450 in the analysis apparatus of the information relationship map). The processor 510 performs various functional applications and data processing of the information-relation-mapping analysis apparatus, that is, implements the above-described information-relation-mapping analysis method, by running software programs, instructions, and modules stored in the memory 520.
Memory 520 may include primarily a program storage area and a data storage area, wherein the program storage area may store an operating system, at least one application program required for functionality; the storage data area may store data created according to the use of the terminal, etc. In addition, memory 520 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some examples, memory 520 may further include memory located remotely from processor 510, which may be connected to the information relationship mapping analysis device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input means 530 may be used to receive input numeric or character information and to generate key signal inputs related to user settings and function control of the analysis device for information relationship mapping. The output 540 may include a display device such as a display screen.
Example six
A sixth embodiment of the present invention also provides a storage medium containing computer-executable instructions for performing an analysis method of information-relation mapping when executed by a computer processor, comprising:
extracting UA keywords in a user agent UA from deep packet inspection DPI data to generate a terminal UA keyword temporary table; the terminal UA keyword temporary table comprises equipment names, type allocation codes TAC and UA keywords of each piece of DPI data;
screening the acquired terminal data according to a preset supporting network to obtain a terminal data table; the terminal data table comprises the equipment name of the terminal and a supporting network;
using the terminal UA keyword temporary table and the terminal data table to update the increment of the current terminal annotation table;
screening out the screening UA keywords corresponding to the TAC through the occurrence times of the UA keywords corresponding to each TAC in the terminal UA keyword temporary table, and generating a terminal UA keyword filtering table;
and carrying out preset association aggregation operation on the terminal UA keyword filtering table and the terminal annotation table to obtain a terminal TAC matching table.
Of course, the storage medium containing the computer executable instructions provided in the embodiments of the present invention is not limited to the method operations described above, and may also perform the related operations in the information relationship mapping analysis method provided in any embodiment of the present invention.
From the above description of embodiments, it will be clear to a person skilled in the art that the present invention may be implemented by means of software and necessary general purpose hardware, but of course also by means of hardware, although in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, etc., and include several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments of the present invention.
It should be noted that, in the embodiment of the information relation mapping analysis apparatus, each unit and module included are only divided according to the functional logic, but not limited to the above-mentioned division, so long as the corresponding functions can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (10)
1. An analysis method of information relation mapping, characterized by comprising:
extracting UA keywords in a user agent UA from deep packet inspection DPI data to generate a terminal UA keyword temporary table; the terminal UA keyword temporary table comprises equipment names, type allocation codes TAC and UA keywords of each piece of DPI data;
screening the acquired terminal data according to a preset supporting network to obtain a terminal data table; the terminal data table comprises the equipment name of the terminal and a supporting network;
using the terminal UA keyword temporary table and the terminal data table to update the increment of the current terminal annotation table;
screening out the screening UA keywords corresponding to the TAC through the occurrence times of the UA keywords corresponding to each TAC in the terminal UA keyword temporary table, and generating a terminal UA keyword filtering table;
and carrying out preset association aggregation operation on the terminal UA keyword filtering table and the terminal annotation table to obtain a terminal TAC matching table.
2. The method of claim 1, further comprising, prior to said extracting UA keywords in the user agent UA from deep packet inspection, DPI data, generating a terminal UA keyword temporary table:
screening the DPI data, and filtering null value and invalid data; wherein, the invalid data is DPI data except a preset terminal system.
3. The method of claim 1, wherein the step of screening out the screening UA keywords corresponding to the TAC by the occurrence number of the UA keywords corresponding to each TAC in the temporary table of terminal UA keywords, and generating a terminal UA keyword filtering table includes:
calculating the occurrence times of the UA keywords corresponding to each TAC;
using the UA keywords with the largest occurrence frequency as the screening keywords of the corresponding TAC;
and recording the screening keywords in the terminal UA keyword filtering table.
4. The method of claim 1, wherein the screening the acquired terminal data according to the preset supporting network to obtain the terminal data table includes:
comparing the support network in each piece of terminal data with the preset support network, reserving the terminal data with the same support network as the preset support network, and recording the terminal data in the terminal data table.
5. The method of claim 1, wherein the performing a preset association aggregation operation on the terminal UA keyword filtering table and the terminal annotation table to obtain a terminal TAC matching table includes:
the terminal UA keyword filtering table and the terminal annotation table are aggregated to obtain the terminal annotation table after increment;
calculating UA keywords uniquely corresponding to the TAC in the terminal annotation table after increment based on a TopN algorithm;
and carrying out series update through a preset terminal information field to obtain the relation mapping of the TAC and the terminal information, and recording the relation mapping into the terminal TAC matching table.
6. An information relation map analysis apparatus, comprising:
the key word temporary table generation module is used for extracting UA key words in the user agent UA from the deep packet inspection DPI data to generate a terminal UA key word temporary table; the terminal UA keyword temporary table comprises equipment names, type allocation codes TAC and UA keywords of each piece of DPI data;
the terminal data table generation module is used for screening the acquired terminal data according to a preset supporting network to obtain a terminal data table; the terminal data table comprises the equipment name of the terminal and a supporting network;
the terminal registry updating module is used for carrying out incremental updating on the current terminal annotation table by using the terminal UA keyword temporary table and the terminal data table;
the keyword filtering table generating module is used for screening out screening UA keywords corresponding to the TACs through the occurrence times of the UA keywords corresponding to each TAC in the terminal UA keyword temporary table to generate a terminal UA keyword filtering table;
and the terminal TAC matching table generation module is used for carrying out preset association aggregation operation on the terminal UA keyword filtering table and the terminal annotation table to obtain a terminal TAC matching table.
7. The apparatus as recited in claim 6, further comprising:
the DPI data screening module is used for screening the DPI data before the UA keywords in the user agent UA are extracted from the deep packet inspection DPI data and the terminal UA keyword temporary table is generated, and filtering null values and invalid data; wherein, the invalid data is DPI data except a preset terminal system.
8. The apparatus of claim 6, wherein the keyword filtering table generation module is specifically configured to:
calculating the occurrence times of the UA keywords corresponding to each TAC;
using the UA keywords with the largest occurrence frequency as the screening keywords of the corresponding TAC;
and recording the screening keywords in the terminal UA keyword filtering table.
9. An analysis device of an information relation map, characterized in that the analysis device of an information relation map comprises:
one or more processors;
a memory for storing one or more programs;
the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of analysis of information-relation maps of any of claims 1-5.
10. A storage medium containing computer executable instructions which, when executed by a computer processor, are for performing the method of analysis of information relationship mapping of any of claims 1-5.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102013004795A1 (en) * | 2012-03-21 | 2013-09-26 | Gabriele Trinkel | Method for generating noise for noise generator for generating random numbers, passwords in computer technology, cloud computing, involves generating true random number for processing or transporting electric binary data |
| CN103747002A (en) * | 2014-01-16 | 2014-04-23 | 电信科学技术第一研究所 | Communication terminal capacity management system and terminal capacity management method |
| DE102012022894A1 (en) * | 2012-11-23 | 2014-05-28 | Gabriele Lisa Trinkel | System for identification, verification and/or authentication of projectile e.g. railgun projectile, has sensor, communication unit, processing unit and power supply or power generation unit which are arranged in housing of projectile |
| CN105260365A (en) * | 2014-06-04 | 2016-01-20 | 中国移动通信集团宁夏有限公司 | Terminal information processing method and device |
| CN107105428A (en) * | 2016-02-23 | 2017-08-29 | 中国移动通信集团内蒙古有限公司 | The method and device in quick completion end message storehouse |
| CN107301192A (en) * | 2016-04-14 | 2017-10-27 | 中国移动通信集团河北有限公司 | A kind of terminal identification method and identification server |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3963917A4 (en) * | 2019-05-02 | 2023-01-18 | Nokia Technologies Oy | Method and apparatus for support of migration and co-existence of public land mobile network and user equipment capability identifications |
-
2021
- 2021-04-07 CN CN202110374166.XA patent/CN113076316B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102013004795A1 (en) * | 2012-03-21 | 2013-09-26 | Gabriele Trinkel | Method for generating noise for noise generator for generating random numbers, passwords in computer technology, cloud computing, involves generating true random number for processing or transporting electric binary data |
| DE102012022894A1 (en) * | 2012-11-23 | 2014-05-28 | Gabriele Lisa Trinkel | System for identification, verification and/or authentication of projectile e.g. railgun projectile, has sensor, communication unit, processing unit and power supply or power generation unit which are arranged in housing of projectile |
| CN103747002A (en) * | 2014-01-16 | 2014-04-23 | 电信科学技术第一研究所 | Communication terminal capacity management system and terminal capacity management method |
| CN105260365A (en) * | 2014-06-04 | 2016-01-20 | 中国移动通信集团宁夏有限公司 | Terminal information processing method and device |
| CN107105428A (en) * | 2016-02-23 | 2017-08-29 | 中国移动通信集团内蒙古有限公司 | The method and device in quick completion end message storehouse |
| CN107301192A (en) * | 2016-04-14 | 2017-10-27 | 中国移动通信集团河北有限公司 | A kind of terminal identification method and identification server |
Non-Patent Citations (1)
| Title |
|---|
| 基于信令数据的移动物联网终端识别特征研究;全俊斌 等;物联网技术;101-103 * |
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