CN106572126A - Method for calculating number of active devices, and server - Google Patents
Method for calculating number of active devices, and server Download PDFInfo
- Publication number
- CN106572126A CN106572126A CN201510646068.1A CN201510646068A CN106572126A CN 106572126 A CN106572126 A CN 106572126A CN 201510646068 A CN201510646068 A CN 201510646068A CN 106572126 A CN106572126 A CN 106572126A
- Authority
- CN
- China
- Prior art keywords
- data
- active device
- identification code
- obtaining
- interaction data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title abstract description 13
- 230000003993 interaction Effects 0.000 claims abstract description 140
- 238000001914 filtration Methods 0.000 claims abstract description 84
- 238000000205 computational method Methods 0.000 claims description 31
- 238000004364 calculation method Methods 0.000 claims description 30
- 238000004321 preservation Methods 0.000 claims description 21
- 238000007689 inspection Methods 0.000 claims description 19
- 238000000605 extraction Methods 0.000 claims description 16
- 238000004458 analytical method Methods 0.000 claims description 9
- 238000012217 deletion Methods 0.000 claims description 5
- 230000037430 deletion Effects 0.000 claims description 5
- 238000012216 screening Methods 0.000 claims description 3
- 238000007405 data analysis Methods 0.000 abstract description 13
- 230000009286 beneficial effect Effects 0.000 abstract description 7
- 238000012795 verification Methods 0.000 abstract 1
- 230000009471 action Effects 0.000 description 5
- 238000010586 diagram Methods 0.000 description 5
- 238000012360 testing method Methods 0.000 description 4
- 238000005516 engineering process Methods 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 238000012517 data analytics Methods 0.000 description 2
- 230000002452 interceptive effect Effects 0.000 description 2
- 230000004899 motility Effects 0.000 description 2
- 239000000047 product Substances 0.000 description 2
- 241001269238 Data Species 0.000 description 1
- 230000008901 benefit Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 239000007795 chemical reaction product Substances 0.000 description 1
- 238000013461 design Methods 0.000 description 1
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/535—Tracking the activity of the user
Landscapes
- Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- General Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Debugging And Monitoring (AREA)
Abstract
The invention discloses a method for calculating the number of active devices, and a server. The method comprises the steps: obtaining user equipment interaction data from data source equipment, filtering the obtained user equipment interaction data according to a preset filtering rule, and obtaining the filtered transaction data; extracting a preset type of log information from the filtered interaction data; verifying the filtered transaction data according to a preset APP verification rule, and obtaining first device recognition codes corresponding to currently active devices of each APP; carrying out the repeat removing operation of the obtained currently active devices of each APP based on the obtained first device recognition codes, and obtaining the first device reference data corresponding to the active device number of the APP after repeat removing; and calculating the number of real-time active devices of each AP based on the APP ID in the log information based on the obtained first device reference data. The invention has the beneficial effects that the method counts the number of active devices in the APP dimension conveniently and quickly through big data analysis.
Description
Technical field
The present invention relates to Internet technical field, more particularly to a kind of computational methods and clothes of active device number
Business device.
Background technology
With Internet technology make constant progress and end product is intelligentized increasingly advances in the whole world, people
IED used in routine work and life it is more and more, such as it is smart mobile phone, flat
Plate computer (Pure Audio Design, Pad), controlling intelligent household appliances etc..At the same time, terminal is operated in
The value volume and range of product of the application program (Application, APP) on equipment is also more and more, its exploitation week
Phase is also shorter and shorter, also more and more lower using threshold.
But the active number of devices of APP how is obtained from each terminal unit and then is provided necessarily for follow-up service
Data support, not yet provide a kind of effective technical scheme for the problem at present；Meanwhile, mesh
It is front also not yet to provide based on big data analysis (such as different relatively accurately to count other dimensions in the industry
Region, different plug-in unit) under active device number.
The content of the invention
In view of the foregoing, it is necessary to which the computational methods and server of a kind of active device number are provided, to
The active device number gone out under APP this dimension using big data analytic statisticss.
The invention discloses a kind of computational methods of active device number, comprise the following steps：
User equipment interaction data is obtained from data-source device, and according to default filtering rule, to obtaining
The user equipment interaction data filtered, the interaction data after being filtered；
The log information of preset kind is extracted in interaction data from after filtration；Wherein, the log information
Including：Application program identification code；
According to default application program inspection rule, the interaction data after filtration is tested, respectively should be obtained
Corresponding first EIC equipment identification code of active device currently enlivened with program；
Based on the work that first EIC equipment identification code for obtaining, each application program to obtaining currently are enlivened
Jump equipment carries out deduplication operation, obtains the first equipment base corresponding to application program active device number after duplicate removal
Quasi- data；
The application program identification code in the log information, based on first equipment for obtaining
Benchmark data, calculates the real-time active device number of each application program.
Preferably, the log information of the preset kind of the extraction also includes：Plug-in unit identification code；
The computational methods of the active device number " are extracted pre- in the step in the interaction data from after filtration
If after the log information of type ", can also carry out following steps：
According to preset plug-in inspection rule, the interaction data after filtration is tested, obtain each plug-in unit and work as
Corresponding second EIC equipment identification code of front enlivened active device；
Based on second EIC equipment identification code for obtaining, what each plug-in unit to obtaining currently was enlivened active sets
It is standby to carry out deduplication operation, obtain the second equipment benchmark data corresponding to plug-in unit active device number after duplicate removal；
The plug-in unit identification code in the log information, based on the second equipment benchmark for obtaining
Data, calculate the real-time active device number of each plug-in unit.
Preferably, the log information of the preset kind of the extraction also includes：Latitude and longitude information；
The computational methods of the active device number also include step：
The latitude and longitude information in the log information, obtains corresponding to the interaction data after filtering
Regional information；
According to the regional information for obtaining, each application program is calculated in the application program corresponding to each region
Active device number.
Preferably, it is described that user equipment interaction data is obtained from data-source device, and according to default filtration
Rule, the user equipment interaction data to obtaining is filtered, the interaction data after being filtered,
Including：
In real time or according to predetermined period, from each service server or the application server of each application program
In, obtain the user equipment interaction data of batch；
Pre-set Data Identification to be filtered and its respective value；
The user equipment interaction data to obtaining is retrieved one by one, is recognized whether：It is to be filtered
The user equipment interaction data of Data Identification and its respective value；
The Data Identification described to be filtered that will identify that and its user equipment interaction data of respective value are filtered out
Come, the interaction data after being filtered.
Preferably, described based on first EIC equipment identification code for obtaining, each application program to obtaining is worked as
Front enlivened active device carries out deduplication operation, obtains after duplicate removal corresponding to application program active device number
The first equipment benchmark data, including：
From the EIC equipment identification code of each application program active device for having preserved and enliven in date data storehouse, sieve
Select the preservation EIC equipment identification code for preserving active device for enlivening that the date is the analysis same day；
First EIC equipment identification code for obtaining and the preservation EIC equipment identification code for filtering out are carried out
Match somebody with somebody, the preservation EIC equipment identification code of matching is deleted from first EIC equipment identification code；
Using corresponding to remaining first EIC equipment identification code as the application program active device number after deletion
The first equipment benchmark data.
Corresponding to a kind of computational methods of active device number disclosed above, the invention also discloses a kind of
The calculation server of active device number, including：
Filtering module, for obtaining user equipment interaction data from data-source device, and according to presetting
Filter rule, the user equipment interaction data to obtaining is filtered, the interaction data after being filtered；
Extraction module, for the log information for extracting preset kind in the interaction data from after filtration；Wherein,
The log information includes：Application program identification code；
Inspection module, for according to default application program inspection rule, carrying out to the interaction data after filtration
Inspection, obtains corresponding first EIC equipment identification code of active device that each application program is currently enlivened；
Deduplication module, for based on first EIC equipment identification code for obtaining, to each application program for obtaining
The current active device enlivened carries out deduplication operation, obtains application program active device number institute after duplicate removal right
The the first equipment benchmark data answered；
Computing module, for the application program identification code in the log information, based on acquisition
The first equipment benchmark data, calculate the real-time active device number of each application program.
Preferably, the log information of the preset kind that the extraction module is extracted also includes：Plug-in unit identification code；
The inspection module is additionally operable to：According to preset plug-in inspection rule, the interaction data after filtration is entered
Performing check, obtains corresponding second EIC equipment identification code of active device that each plug-in unit is currently enlivened；
The deduplication module is additionally operable to：It is each slotting to what is obtained based on second EIC equipment identification code for obtaining
The active device that part is currently enlivened carries out deduplication operation, obtains after duplicate removal corresponding to plug-in unit active device number
The second equipment benchmark data；
The computing module is additionally operable to：The plug-in unit identification code in the log information, based on obtaining
The the second equipment benchmark data for taking, calculates the real-time active device number of each plug-in unit.
Preferably, the log information of the preset kind that the extraction module is extracted also includes：Latitude and longitude information；
The calculation server of the active device number also includes：
Region acquisition module, for the latitude and longitude information in the log information, obtains and filters
The regional information corresponding to interaction data afterwards；
The computing module is additionally operable to：According to the regional information for obtaining, each application program is calculated each
Application program active device number corresponding to region.
Preferably, the filtering module includes：
Acquiring unit, in real time or according to predetermined period, from each service server or respectively using journey
In the application server of sequence, the user equipment interaction data of batch is obtained；
Setting unit, for pre-setting Data Identification to be filtered and its respective value；
Retrieval unit, for being retrieved one by one to the user equipment interaction data for obtaining, identification is
No presence：The user equipment interaction data of Data Identification to be filtered and its respective value；
Filter element, for the Data Identification described to be filtered that will identify that and its user equipment of respective value
Interaction data is filtered out, the interaction data after being filtered.
Preferably, the deduplication module includes：
Screening unit, for from the EIC equipment identification code of each application program active device for having preserved and active day
In phase data base, the preservation equipment identification for preserving active device for enlivening that the date is the analysis same day is filtered out
Code；
Delete unit, for will obtain first EIC equipment identification code and the preservation equipment for filtering out
Identification code is matched, and the preservation EIC equipment identification code of matching is deleted from first EIC equipment identification code
Remove；
Counting unit, for remaining first EIC equipment identification code after deletion to be enlivened as the application program
The first equipment benchmark data corresponding to number of devices.
A kind of computational methods and server of active device number of the present invention can reach following beneficial effect：
It is right by obtaining user equipment interaction data from data-source device, and according to default filtering rule
The user equipment interaction data for obtaining is filtered, the interaction data after being filtered；From after filtration
Interaction data in extract preset kind log information；Wherein, the log information includes：Using journey
Sequence identification code；According to default application program inspection rule, the interaction data after filtration is tested, obtained
Take corresponding first EIC equipment identification code of active device that each application program is currently enlivened；Based on the institute for obtaining
The first EIC equipment identification code is stated, the active device that each application program to obtaining currently is enlivened carries out duplicate removal behaviour
Make, obtain the first equipment benchmark data corresponding to application program active device number after duplicate removal；According to described
The application program identification code in log information, based on the first equipment benchmark data for obtaining, meter
Calculate the real-time active device number of each application program；Easily count in APP with being analyzed using big data
The beneficial effect of the active device number under this dimension, for follow-up further data analysiss provide it is important according to
According to；In addition, different types of information in by extracting log information, can obtain the work under different dimensions
Jump number of devices, improves versatility, convenience and the motility of the analysis of active device number.
Description of the drawings
Fig. 1 is a kind of schematic flow sheet of embodiment of the computational methods of active device number of the present invention；
Fig. 2 is the schematic flow sheet of the another embodiment of the computational methods of active device number of the present invention；
Fig. 3 is the schematic flow sheet of another embodiment of the computational methods of active device number of the present invention；
Fig. 4 be active device number of the present invention computational methods in step in embodiment described in Fig. 1, Fig. 2, Fig. 3
A kind of schematic flow sheet of the embodiment of S10；
Fig. 5 be active device number of the present invention computational methods in embodiment described in Fig. 1 step S13 one kind
The schematic flow sheet of embodiment；
Fig. 6 is a kind of block diagram of embodiment of the calculation server of active device number of the present invention；
Fig. 7 is the block diagram of the another embodiment of the calculation server of active device number of the present invention；
Fig. 8 be active device number of the present invention calculation server in filtering module in embodiment described in Fig. 6, Fig. 7
A kind of block diagram of 60 embodiment；
Fig. 9 be active device number of the present invention calculation server in deduplication module 63 in embodiment described in Fig. 6
A kind of block diagram of embodiment；
Figure 10 is the block diagram of another embodiment of the calculation server of active device number of the present invention.
The realization of embodiment of the present invention purpose, functional characteristics and advantage will be done referring to the drawings in conjunction with the embodiments
Further illustrate.
Specific embodiment
Technical scheme is further illustrated below in conjunction with Figure of description and specific embodiment.Should
Understand, specific embodiment described herein only to explain the present invention, is not intended to limit the present invention.
A kind of computational methods and server of active device number of the present invention, can apply and count any obtaining
In the application scenarios of the active device number for taking each dimension of respective dimensions information correspondence, for example, by obtaining not
Distinguish the log information of corresponding preset kind with dimension, you can according to above-mentioned log information, analyze
Go out the corresponding active device number of each dimension；The computational methods of active device number of the present invention and server it is following
In embodiment, counting for active device number of the present invention is described by taking APP, region and plug-in unit this several dimension as an example
The keynote idea of calculation method and server, but cannot function as the computational methods to active device number of the present invention and
Limited explanation done by the protection domain of server.
The invention provides a kind of computational methods of active device number, to be gone out using big data analytic statisticss
Active device number under APP this dimension.As shown in figure 1, the computational methods of active device number of the present invention
May be embodied as step S10-S14 described by Fig. 1：
Step S10, from data-source device user equipment interaction data is obtained, and according to default filtering rule,
The user equipment interaction data to obtaining is filtered, the interaction data after being filtered；
In the embodiment of the present invention, calculation server obtains large batch of user equipment from data-source device and hands over
Mutual data；Its acquisition modes includes：Obtain in real time, or obtain according to the default acquisition cycle.It is described
Data-source device include but is not limited to：Each APP application server, each service server, for example：
Insurance server, security server, bank server etc..
After the user equipment interaction data of batch is got, calculation server is according to filtration set in advance
Rule presets filtering rule, and the above-mentioned user equipment interaction data to obtaining is filtered, so as to obtain
Interaction data after filtration；Wherein, default filtering rule is included but is not limited to：The user of preset kind sets
The user equipment interaction data of standby interaction data, preset data mark and respective value.
The log information of preset kind is extracted in step S11, the interaction data from after filtration；Wherein, it is described
Log information includes：Application program identification code；
For the interaction data after filtration, the log information of preset kind is therefrom extracted；Wherein, carried
Dimension of the log information of the preset kind for taking according to corresponding to active device to be analyzed determining, for example,
In embodiment described in Fig. 1, be for this dimension of APP analyzing active device number, then it is extracted here
The log information of preset kind then includes：APP identification codes required for APP this dimension, i.e. APP ID
(Identity)。
Step S12, according to default application program inspection rule, the interaction data after filtration is tested,
Obtain corresponding first EIC equipment identification code of active device that each application program is currently enlivened；
For the interaction data after filtration, according to default application program detected rule, that is, APP test gauges are preset
Then, the interaction data to filtering out is detected one by one.In the embodiment of the present invention, described default APP
Inspection rule includes：Judge that whether " action type " in the user equipment interaction data filtered out per bar be
" initialization times "；If its " action type " is " initialization times ", the user equipment after filtering is illustrated
Equipment corresponding to interaction data is inactive in APP；If its " action type " is not " initialization times ",
Illustrate that the equipment corresponding to the user equipment interaction data after filtering is active in APP.Examined according to above-mentioned APP
Rule is tested, the first EIC equipment identification code corresponding to the active device that each APP is currently enlivened, i.e. APP is obtained
Active device ID.
Step S13, first EIC equipment identification code based on acquisition, to the current institute of each application program for obtaining
Active active device carries out deduplication operation, obtains after duplicate removal corresponding to application program active device number
One equipment benchmark data；
After above-mentioned first EIC equipment identification code i.e. APP active devices ID are got, to avoid repeating to obtain, meter
Calculating each APP current active device enlivened of the server to obtaining carries out deduplication operation；For example, will be current
Above-mentioned APP active devices ID for obtaining and its stored above-mentioned APP for enlivening the date and currently obtaining
Active device ID date identical active device ID is matched, and the above-mentioned APP that the match is successful is enlivened and is set
Standby ID is deleted from current APP active devices ID of above-mentioned acquisition, that is, remaining being is gone after being deleted
The first equipment benchmark data after weight corresponding to APP active devices number, i.e. APP active devices benchmark data.
Step S14, the application program identification code in the log information, described in obtaining
First equipment benchmark data, calculates the real-time active device number of each application program.
Application program identification code in the log information extracted in above-mentioned steps S11 is APP ID, and root
It is APP active device benchmark datas according to the above-mentioned first equipment benchmark data for obtaining, you can calculate and obtain each
The real-time active device number of APP.
Preferably, in an embodiment of the present invention, when calculating gets the real-time active device number of each APP,
Preserve simultaneously the device id of each APP active devices and it is corresponding enliven the date, be easy to subsequently be based on above-mentioned number
According to carrying out further data separate and data analysiss.
A kind of computational methods of active device number of the present invention are handed over by obtaining user equipment from data-source device
Mutual data, and according to default filtering rule, the user equipment interaction data to obtaining is filtered,
Interaction data after being filtered；The log information of preset kind is extracted in interaction data from after filtration；
Wherein, the log information includes：Application program identification code；According to default application program inspection rule,
Interaction data after filtration is tested, the active device correspondence that each application program is currently enlivened is obtained
The first EIC equipment identification code；Based on first EIC equipment identification code for obtaining, to each application program for obtaining
The current active device enlivened carries out deduplication operation, obtains application program active device number institute after duplicate removal right
The the first equipment benchmark data answered；The application program identification code in the log information, is based on
The the first equipment benchmark data for obtaining, calculates the real-time active device number of each application program；With profit
The beneficial effect of the active device number under APP this dimension is easily counted with big data analysis, after being
Continuous further data analysiss provide important evidence.
Based on the description of embodiment described in Fig. 1, in the embodiment of the present invention, the log information for extracting can be passed through
In plug-in unit dimension obtaining the active device number corresponding to plug-in unit this dimension.As shown in Fig. 2
The computational methods of active device number of the present invention can also be embodied as steps as described below S10-S23：
Step S10, from data-source device user equipment interaction data is obtained, and according to default filtering rule,
The user equipment interaction data to obtaining is filtered, the interaction data after being filtered；
In the embodiment of the present invention, calculation server obtains large batch of user equipment from data-source device and hands over
Mutual data；Its acquisition modes includes：Obtain in real time, or obtain according to the default acquisition cycle.It is described
Data-source device include but is not limited to：Each APP application server, each service server, for example：
Insurance server, security server, bank server etc..
After the user equipment interaction data of batch is got, calculation server is according to filtration set in advance
Rule presets filtering rule, and the above-mentioned user equipment interaction data to obtaining is filtered, so as to obtain
Interaction data after filtration；Wherein, default filtering rule is included but is not limited to：The user of preset kind sets
The user equipment interaction data of standby interaction data, preset data mark and respective value.
The log information of preset kind is extracted in step S11, the interaction data from after filtration；Wherein, it is described
Log information includes：Plug-in unit identification code；
For the interaction data after filtration, the log information of preset kind is therefrom extracted；Wherein, carried
Dimension of the log information of the preset kind for taking according to corresponding to active device to be analyzed determining, for example,
In embodiment described in Fig. 2, be for this dimension of plug-in unit analyzing active device number, then it is extracted here
The log information of preset kind then includes：Plug-in unit identification code required for plug-in unit this dimension, i.e. plug-in unit ID
(Identity)。
Step S21, according to preset plug-in inspection rule, the interaction data after filtration is tested, obtain
Corresponding second EIC equipment identification code of active device that each plug-in unit is currently enlivened；
For the interaction data after filtration, according to preset plug-in detected rule, to the interaction data for filtering out
Detected one by one.In the embodiment of the present invention, described preset plug-in inspection rule includes：Judge every
Whether " action type " in the user equipment interaction data that bar is filtered out is " plug-in unit click "；If its " operation
Type " is " plug-in unit click ", then the equipment corresponding to the user equipment interaction data after explanation is filtered is being inserted
Part is enlivened；The user equipment interaction number if its " action type " is not " plug-in unit click ", after illustrating to filter
It is inactive in plug-in unit according to corresponding equipment.According to above-mentioned preset plug-in inspection rule, obtain each plug-in unit and work as
The second EIC equipment identification code corresponding to front enlivened active device, i.e. plug-in unit active device ID.
Step S22, second EIC equipment identification code based on acquisition, each plug-in unit to obtaining currently is enlivened
Active device carry out deduplication operation, obtain the second equipment base corresponding to plug-in unit active device number after duplicate removal
Quasi- data；
After above-mentioned second EIC equipment identification code i.e. plug-in unit active device ID is got, to avoid repeating to obtain,
Calculation server carries out deduplication operation to the active device that each plug-in unit for obtaining currently is enlivened；For example, will
It is above-mentioned with current acquisition that current above-mentioned plug-in unit active device ID for obtaining enlivens the date with stored its
Plug-in unit active device ID date identical active device ID is matched, and the above-mentioned plug-in unit that the match is successful is lived
Jump device id from above-mentioned acquisition when in anterior plug-in active device ID delete, that is, after being deleted it is remaining i.e.
The second equipment benchmark data corresponding to plug-in unit active device number after duplicate removal, i.e. plug-in component equipment benchmark data.
Step S23, the plug-in unit identification code in the log information, based on described second for obtaining
Equipment benchmark data, calculates the real-time active device number of each plug-in unit.
Plug-in unit identification code in the log information extracted in above-mentioned steps S11 is plug-in unit ID, and according to obtaining
The above-mentioned second equipment benchmark data i.e. plug-in component equipment benchmark data for taking, you can calculate the reality for obtaining each plug-in unit
When active device number.
Preferably, in an embodiment of the present invention, the real-time active device number of each plug-in unit is got in calculating
When, at the same preserve the device id of each plug-in unit active device and it is corresponding enliven the date, be easy to subsequently be based on
Above-mentioned data carry out further data separate and data analysiss.
A kind of computational methods of active device number of the present invention are handed over by obtaining user equipment from data-source device
Mutual data, and according to default filtering rule, the user equipment interaction data to obtaining is filtered,
Interaction data after being filtered；The log information of preset kind is extracted in interaction data from after filtration；
Wherein, the log information includes：Plug-in unit identification code；According to preset plug-in inspection rule, after filtration
Interaction data test, obtain the corresponding second equipment knowledge of active device that each plug-in unit currently enliven
Other code；Based on second EIC equipment identification code for obtaining, it is active that each plug-in unit to obtaining currently is enlivened
Equipment carries out deduplication operation, obtains the second equipment benchmark data corresponding to plug-in unit active device number after duplicate removal；
The plug-in unit identification code in the log information, based on the second equipment benchmark data for obtaining,
Calculate the real-time active device number of each plug-in unit；With using big data analysis easily count plug-in unit this
The beneficial effect of the active device number under dimension, for follow-up further data analysiss important evidence is provided.
Based on the description of embodiment described in Fig. 1, Fig. 2, in the embodiment of the present invention, the day extracted can be passed through
Latitude and longitude information in will information is obtaining for APP in the active device number corresponding to different geographical.Such as
Shown in Fig. 3, on the basis of embodiment described in Fig. 1, the computational methods of active device number of the present invention are in Fig. 1 institutes
State " step S14, the application program identification code in the log information, based on obtaining of embodiment
The the first equipment benchmark data for taking, calculates the real-time active device number of each application program " after, also wrap
Include step S31-S32：
Step S31, the latitude and longitude information in the log information, obtain the interactive number after filtering
According to corresponding regional information；
In the embodiment of the present invention, the preset kind that interaction data of the calculation server from after filtration is extracted
In log information, due to the log information of preset kind for being extracted it is right according to active device institute to be analyzed
The dimension answered determining, therefore, in the embodiment of the present invention described in Fig. 3, the day of the preset kind for being extracted
Will information also includes：Latitude and longitude information required for this dimension of region.
According to the latitude and longitude information in the above-mentioned log information for extracting, above-mentioned latitude and longitude information institute is searched in analysis
Corresponding area；It will be appreciated by those skilled in the art that by above-mentioned longitude and dimensional information, you can really
Recognize the area corresponding to above-mentioned latitude and longitude information；Therefore, the longitude and latitude by extracting in above-mentioned log information
Degree information, you can easily search and obtain the region letter corresponding to the user equipment interaction data after filtering
Breath.
Step S32, according to the regional information for obtaining, calculate each application program corresponding to each region
Application program active device number.
According to the regional information of above-mentioned acquisition, you can easily calculate each APP right respectively in different geographical institute
The APP active device numbers answered.
The computational methods of active device number of the present invention are by the longitude and latitude letter in extraction preset kind log information
Breath, according to the latitude and longitude information for obtaining, calculates each application program in the application journey corresponding to each region
Sequence active device number, with using big data analysis work of the APP under this dimension of region is easily counted
The beneficial effect of jump number of devices, for follow-up further data analysiss important evidence is provided.
Based on the description of embodiment described in figure 1 above, Fig. 2 and Fig. 3, calculation server is obtaining user equipment
Interaction data and to obtain user equipment interaction data filter when, can pass through Fig. 4 described in technology
Means are realized；As shown in figure 4, in embodiment described in Fig. 1, Fig. 2, Fig. 3, " step S10, from data source
User equipment interaction data is obtained in equipment, and according to default filtering rule, the user to obtaining sets
Standby interaction data is filtered, the interaction data after being filtered " may be implemented as the step of describing
S101-S104：
Step S101, in real time or according to predetermined period, from each service server or each application program
In application server, the user equipment interaction data of batch is obtained；
In the embodiment of the present invention, calculation server obtains large batch of user equipment from data-source device and hands over
Mutual data；Its acquisition modes includes：Obtain in real time, or obtain according to the default acquisition cycle.It is described
Data-source device include but is not limited to：Each APP application server, each service server, for example：
Insurance server, security server, bank server etc..
Step S102, pre-set Data Identification to be filtered and its respective value；
Step S103, the user equipment interaction data to obtaining are retrieved one by one, identify whether to deposit
：The user equipment interaction data of Data Identification to be filtered and its respective value；
The user equipment interaction of step S104, the Data Identification described to be filtered that will identify that and its respective value
Data filtering out, the interaction data after being filtered.
After the user equipment interaction data of batch is got, calculation server is according to filtration set in advance
Rule presets filtering rule, and the above-mentioned user equipment interaction data to obtaining is filtered, so as to obtain
Interaction data after filtration.
In the embodiment of the present invention, calculation server pre-sets Data Identification to be filtered and its respective value,
When the user equipment interaction data to obtaining is filtered, by the way of retrieving one by one, i.e., to obtaining
The user equipment interaction data retrieved one by one, recognize whether：Data Identification to be filtered and
The user equipment interaction data of its respective value；If existing, the Data Identification described to be filtered that will identify that
And its user equipment interaction data of respective value is filtered out, the interaction data after being filtered.
By way of the embodiment of the present invention is adopting the Data Identification and its respective value that pre-set, to obtaining
User equipment interaction data filtered, improve the efficiency and accuracy of data filtering.
Based on the description of embodiment described in Fig. 1, Fig. 2, Fig. 3 and Fig. 4, the calculating of active device number of the present invention
In method, to avoid repeating to obtain corresponding active device number under each dimension, need to carry out duplicate removal behaviour to it
Make；In the embodiment of the present invention, as shown in figure 5, describing deduplication operation only by taking APP this dimension as an example
Thought；Other dimensions such as plug-in unit dimension can also be realized by the keynote idea described in Fig. 5, in invention
In embodiment, it is not repeated one by one and exhaustive.
As shown in figure 5, in the computational methods of active device number of the present invention, in embodiment described in Fig. 1, " step
S13, the work currently enlivened based on first EIC equipment identification code for obtaining, each application program to obtaining
Jump equipment carries out deduplication operation, obtains the first equipment base corresponding to application program active device number after duplicate removal
The step of quasi- data " may be implemented as description S131-S133：
Step S131, from the EIC equipment identification code and active day issue of each application program active device for having preserved
According to storehouse, the preservation EIC equipment identification code for preserving active device for enlivening that the date is the analysis same day is filtered out；
In the embodiment of the present invention, due to while the device id of each APP active devices is preserved, also saving
It is corresponding to enliven the date, therefore, it can the device id by each APP active devices and enliven the data on date
In storehouse, it is that the preservation for preserving active device of saved mistake for analyzing the same day sets to filter out and enliven the date
Standby ID.
Step S132, by obtain first EIC equipment identification code and filter out the preservation equipment identification
Code is matched, and the preservation EIC equipment identification code of matching is deleted from first EIC equipment identification code；
Step S133, will delete after remaining first EIC equipment identification code as the application program active device
Corresponding the first equipment benchmark data of number.
It is APP active devices ID by above-mentioned first EIC equipment identification code for obtaining, sets with the above-mentioned preservation for filtering out
Standby ID is matched, and the above-mentioned preservation device id for matching consistent completely is deleted from APP active devices ID,
So as to, it is to avoid the double counting of same APP active devices ID.Delete APP active devices ID for repeating
Afterwards, after deletion it is remaining first identification identification code be APP active devices ID be APP active devices number institute it is right
The the first equipment benchmark data answered, i.e. APP active devices benchmark data.
The embodiment of the present invention is to APP active devices ID by carrying out deduplication operation, it is to avoid be directed to same APP
The repeat count of active device ID, improves the accuracy of active device number calculating.
For in a kind of meter of active device number of embodiment description described in Fig. 1, Fig. 2, Fig. 3, Fig. 4 and Fig. 5
A kind of calculation method, present invention also offers calculation server of active device number；As shown in fig. 6, of the invention
A kind of calculation server of active device number includes：Filtering module 60, extraction module 61, inspection module 62,
Deduplication module 63 and computing module 64；Wherein：
The filtering module 60, for the acquisition user equipment interaction data from data-source device, and according to
Default filtering rule, the user equipment interaction data to obtaining is filtered, the friendship after being filtered
Mutual data；
The extraction module 61, for the log information for extracting preset kind in the interaction data from after filtration；
Wherein, the log information includes：Application program identification code；
The inspection module 62, for according to default application program inspection rule, to filtration after interactive number
According to testing, corresponding first EIC equipment identification code of active device that each application program is currently enlivened is obtained；
The deduplication module 63, for based on first EIC equipment identification code for obtaining, respectively should to what is obtained
The active device currently enlivened with program carries out deduplication operation, obtains application program active device after duplicate removal
The first corresponding equipment benchmark data of number；
The computing module 64, for the application program identification code in the log information, base
In the first equipment benchmark data for obtaining, the real-time active device number of each application program is calculated.
Preferably, as shown in fig. 6, the log information of the preset kind of the extraction of the extraction module 61 also includes：
Plug-in unit identification code；
The inspection module 62 is additionally operable to：According to preset plug-in inspection rule, to the interaction data after filtration
Test, obtain corresponding second EIC equipment identification code of active device that each plug-in unit is currently enlivened；
The deduplication module 63 is additionally operable to：It is each to what is obtained based on second EIC equipment identification code for obtaining
The active device that plug-in unit is currently enlivened carries out deduplication operation, obtains plug-in unit active device number institute after duplicate removal right
The the second equipment benchmark data answered；
The computing module 64 is additionally operable to：The plug-in unit identification code in the log information, is based on
The the second equipment benchmark data for obtaining, calculates the real-time active device number of each plug-in unit.
Preferably, the log information of the preset kind that the extraction module 61 is extracted also includes：Longitude and latitude is believed
Breath；
As shown in fig. 7, the calculation server of the active device number also includes：
Region acquisition module 65, for the latitude and longitude information in the log information, obtained
The regional information corresponding to interaction data after filter；
The computing module 64 is additionally operable to：According to the regional information for obtaining, calculate each application program and exist
Application program active device number corresponding to each region.
Preferably, as shown in figure 8, the filtering module 60 includes：
Acquiring unit 601, in real time or according to predetermined period, from each service server or each application
In the application server of program, the user equipment interaction data of batch is obtained；
Setting unit 602, for pre-setting Data Identification to be filtered and its respective value；
Retrieval unit 603, for being retrieved one by one to the user equipment interaction data for obtaining, recognizes
Whether there is：The user equipment interaction data of Data Identification to be filtered and its respective value；
Filter element 604, the user for the Data Identification described to be filtered that will identify that and its respective value sets
Standby interaction data is filtered out, the interaction data after being filtered.
Preferably, as shown in figure 9, the deduplication module 63 includes：
Screening unit 631, for from the EIC equipment identification code of each application program active device for having preserved and active
In date data storehouse, the preservation equipment knowledge for preserving active device for enlivening that the date is the analysis same day is filtered out
Other code；
Unit 632 is deleted, for first EIC equipment identification code for obtaining to be set with the preservation for filtering out
Standby identification code is matched, by the preservation EIC equipment identification code of matching from first EIC equipment identification code
Delete；
Counting unit 633, lives for remaining first EIC equipment identification code after deleting as the application program
The first equipment benchmark data corresponding to jump number of devices.
Preferably, as shown in Figure 10, the calculation server of the active device number also includes：
Preserving module 66, calculates the active device number of each application program and/or each inserts for the computing module
While the active device number of part, EIC equipment identification code corresponding to each active device and corresponding active is preserved
Date.
The calculation server of active device number of the present invention from data-source device by obtaining user equipment interaction
Data, and according to default filtering rule, the user equipment interaction data to obtaining is filtered, obtained
Interaction data to after filtration；The log information of preset kind is extracted in interaction data from after filtration；Press
According to default application program inspection rule, the interaction data after filtration is tested, obtain each application program
Current corresponding first EIC equipment identification code of active device enlivened；Known based on first equipment for obtaining
Other code, the active device that each application program to obtaining currently is enlivened carries out deduplication operation, obtains duplicate removal
The first equipment benchmark data corresponding to application program active device number afterwards；According in the log information
The application program identification code, based on the first equipment benchmark data for obtaining, calculates each application program
Real-time active device number；With easily counting the work under APP this dimension using big data analysis
The beneficial effect of jump number of devices, for follow-up further data analysiss important evidence is provided；In addition, passing through
Different types of information in log information is extracted, the active device number under different dimensions can be obtained, improved
The versatility of active device number analysis, convenience and motility.
It should be noted that herein, term " including ", "comprising" or its any other variant are intended to
Cover including for nonexcludability, so that a series of process, method, article or dress including key elements
Put and not only include those key elements, but also including other key elements being not expressly set out, or also include
The key element intrinsic for this process, method, article or device.In the absence of more restrictions,
The key element limited by sentence "including a ...", it is not excluded that in process, method, thing including the key element
Also there is other identical element in product or device.
The embodiments of the present invention are for illustration only, do not represent the quality of embodiment.
Through the above description of the embodiments, those skilled in the art can be understood that above-mentioned
Embodiment method can add the mode of required general hardware platform to realize by software, naturally it is also possible to logical
Cross hardware, but in many cases the former is more preferably embodiment.It is of the invention based on such understanding
The part that technical scheme substantially contributes in other words to prior art can in the form of software product body
Reveal and, the computer software product is stored in a storage medium (such as ROM/RAM, magnetic disc, CD)
In, including some instructions use so that a station terminal equipment (can be mobile phone, computer, server,
Or the network equipment etc.) perform method described in each embodiment of the invention.
The preferred embodiments of the present invention are the foregoing is only, its scope of the claims, every profit is not thereby limited
The equivalent structure made with description of the invention and accompanying drawing content or equivalent flow conversion, directly or indirectly transport
Used in other related technical fields, it is included within the scope of the present invention.
Claims (10)
1. a kind of computational methods of active device number, it is characterised in that comprise the following steps：
User equipment interaction data is obtained from data-source device, and according to default filtering rule, to obtaining
The user equipment interaction data filtered, the interaction data after being filtered；
The log information of preset kind is extracted in interaction data from after filtration；Wherein, the log information
Including：Application program identification code；
According to default application program inspection rule, the interaction data after filtration is tested, respectively should be obtained
Corresponding first EIC equipment identification code of active device currently enlivened with program；
Based on the work that first EIC equipment identification code for obtaining, each application program to obtaining currently are enlivened
Jump equipment carries out deduplication operation, obtains the first equipment base corresponding to application program active device number after duplicate removal
Quasi- data；
The application program identification code in the log information, based on first equipment for obtaining
Benchmark data, calculates the real-time active device number of each application program.
2. computational methods as claimed in claim 1, it is characterised in that the preset kind of the extraction
Log information also includes：Plug-in unit identification code；
The computational methods of the active device number " are extracted pre- in the step in the interaction data from after filtration
If after the log information of type ", can also carry out following steps：
According to preset plug-in inspection rule, the interaction data after filtration is tested, obtain each plug-in unit and work as
Corresponding second EIC equipment identification code of front enlivened active device；
Based on second EIC equipment identification code for obtaining, what each plug-in unit to obtaining currently was enlivened active sets
It is standby to carry out deduplication operation, obtain the second equipment benchmark data corresponding to plug-in unit active device number after duplicate removal；
The plug-in unit identification code in the log information, based on the second equipment benchmark for obtaining
Data, calculate the real-time active device number of each plug-in unit.
3. computational methods as claimed in claim 1, it is characterised in that the preset kind of the extraction
Log information also includes：Latitude and longitude information；
The computational methods of the active device number also include step：
The latitude and longitude information in the log information, obtains corresponding to the interaction data after filtering
Regional information；
According to the regional information for obtaining, each application program is calculated in the application program corresponding to each region
Active device number.
4. computational methods as described in claim 1 or 2 or 3, it is characterised in that described to set from data source
Standby middle acquisition user equipment interaction data, and according to default filtering rule, to the user equipment for obtaining
Interaction data is filtered, the interaction data after being filtered, including：
In real time or according to predetermined period, from each service server or the application server of each application program
In, obtain the user equipment interaction data of batch；
Pre-set Data Identification to be filtered and its respective value；
The user equipment interaction data to obtaining is retrieved one by one, is recognized whether：It is to be filtered
The user equipment interaction data of Data Identification and its respective value；
The Data Identification described to be filtered that will identify that and its user equipment interaction data of respective value are filtered out
Come, the interaction data after being filtered.
5. computational methods as described in claim 1 or 2 or 3, it is characterised in that described based on obtaining
First EIC equipment identification code, the active device that each application program to obtaining currently is enlivened carries out duplicate removal
Operation, obtains the first equipment benchmark data corresponding to application program active device number after duplicate removal, including：
From the EIC equipment identification code of each application program active device for having preserved and enliven in date data storehouse, sieve
Select the preservation EIC equipment identification code for preserving active device for enlivening that the date is the analysis same day；
First EIC equipment identification code for obtaining and the preservation EIC equipment identification code for filtering out are carried out
Match somebody with somebody, the preservation EIC equipment identification code of matching is deleted from first EIC equipment identification code；
Using corresponding to remaining first EIC equipment identification code as the application program active device number after deletion
The first equipment benchmark data.
6. a kind of calculation server of active device number, it is characterised in that include：
Filtering module, for obtaining user equipment interaction data from data-source device, and according to presetting
Filter rule, the user equipment interaction data to obtaining is filtered, the interaction data after being filtered；
Extraction module, for the log information for extracting preset kind in the interaction data from after filtration；Wherein,
The log information includes：Application program identification code；
Inspection module, for according to default application program inspection rule, carrying out to the interaction data after filtration
Inspection, obtains corresponding first EIC equipment identification code of active device that each application program is currently enlivened；
Deduplication module, for based on first EIC equipment identification code for obtaining, to each application program for obtaining
The current active device enlivened carries out deduplication operation, obtains application program active device number institute after duplicate removal right
The the first equipment benchmark data answered；
Computing module, for the application program identification code in the log information, based on acquisition
The first equipment benchmark data, calculate the real-time active device number of each application program.
7. calculation server as claimed in claim 6, it is characterised in that what the extraction module was extracted
The log information of preset kind also includes：Plug-in unit identification code；
The inspection module is additionally operable to：According to preset plug-in inspection rule, the interaction data after filtration is entered
Performing check, obtains corresponding second EIC equipment identification code of active device that each plug-in unit is currently enlivened；
The deduplication module is additionally operable to：It is each slotting to what is obtained based on second EIC equipment identification code for obtaining
The active device that part is currently enlivened carries out deduplication operation, obtains after duplicate removal corresponding to plug-in unit active device number
The second equipment benchmark data；
The computing module is additionally operable to：The plug-in unit identification code in the log information, based on obtaining
The the second equipment benchmark data for taking, calculates the real-time active device number of each plug-in unit.
8. calculation server as claimed in claim 6, it is characterised in that what the extraction module was extracted
The log information of preset kind also includes：Latitude and longitude information；
The calculation server of the active device number also includes：
Region acquisition module, for the latitude and longitude information in the log information, obtains and filters
The regional information corresponding to interaction data afterwards；
The computing module is additionally operable to：According to the regional information for obtaining, each application program is calculated each
Application program active device number corresponding to region.
9. the calculation server as described in claim 6 or 7 or 8, it is characterised in that the filtering module
Including：
Acquiring unit, in real time or according to predetermined period, from each service server or respectively using journey
In the application server of sequence, the user equipment interaction data of batch is obtained；
Setting unit, for pre-setting Data Identification to be filtered and its respective value；
Retrieval unit, for being retrieved one by one to the user equipment interaction data for obtaining, identification is
No presence：The user equipment interaction data of Data Identification to be filtered and its respective value；
Filter element, for the Data Identification described to be filtered that will identify that and its user equipment of respective value
Interaction data is filtered out, the interaction data after being filtered.
10. the calculation server as described in claim 6 or 7 or 8, it is characterised in that the deduplication module
Including：
Screening unit, for from the EIC equipment identification code of each application program active device for having preserved and active day
In phase data base, the preservation equipment identification for preserving active device for enlivening that the date is the analysis same day is filtered out
Code；
Delete unit, for will obtain first EIC equipment identification code and the preservation equipment for filtering out
Identification code is matched, and the preservation EIC equipment identification code of matching is deleted from first EIC equipment identification code
Remove；
Counting unit, for remaining first EIC equipment identification code after deletion to be enlivened as the application program
The first equipment benchmark data corresponding to number of devices.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510646068.1A CN106572126B (en) | 2015-10-08 | 2015-10-08 | Active equipment number calculation method and server |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510646068.1A CN106572126B (en) | 2015-10-08 | 2015-10-08 | Active equipment number calculation method and server |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106572126A true CN106572126A (en) | 2017-04-19 |
| CN106572126B CN106572126B (en) | 2020-06-30 |
Family
ID=58506541
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510646068.1A Active CN106572126B (en) | 2015-10-08 | 2015-10-08 | Active equipment number calculation method and server |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106572126B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107562815A (en) * | 2017-08-16 | 2018-01-09 | 上海斐讯数据通信技术有限公司 | A kind of statistical method and device of client application platform |
| CN115037489A (en) * | 2021-02-24 | 2022-09-09 | 北京国双千里科技有限公司 | Method and device for determining number of equipment identifications, storage medium and electronic equipment |
Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101557304A (en) * | 2008-04-09 | 2009-10-14 | 北京闻言科技有限公司 | Method for counting online user number of distributed application servers |
| CN101729571A (en) * | 2009-12-28 | 2010-06-09 | 广州游家信息技术有限公司 | Method, server and system for counting network on-line user number |
| CN101753566A (en) * | 2009-12-25 | 2010-06-23 | 北京畅游天下网络技术有限公司 | Multi-application inter-system data application method and system |
| US20110083127A1 (en) * | 2009-10-07 | 2011-04-07 | Sony Corporation | System and method for effectively providing software to client devices in an electronic network |
| CN102902775A (en) * | 2012-09-27 | 2013-01-30 | 新浪网技术(中国)有限公司 | Internet real-time computing method and internet real-time computing system |
| CN103530796A (en) * | 2013-10-10 | 2014-01-22 | 北京智谷睿拓技术服务有限公司 | Active period detection method and active period detection system of application program |
| CN103686821A (en) * | 2012-08-27 | 2014-03-26 | 上海亿动信息技术有限公司 | Control method for application program traffic statistics according to unique identification of mobile terminal |
| CN103823665A (en) * | 2012-11-19 | 2014-05-28 | 中国移动通信集团公司 | SDK (software development kit) activeness analyzing method, network server and system |
| CN103841172A (en) * | 2012-11-27 | 2014-06-04 | 上海亿动信息技术有限公司 | Application download operation statistic method and device based on user terminal identification comparison |
| CN104239519A (en) * | 2014-09-17 | 2014-12-24 | 广州华多网络科技有限公司 | Information recommendation method and related equipment and system |
| WO2015006617A1 (en) * | 2013-07-11 | 2015-01-15 | Al-Nasser Khalid | Smart watch |
| CN104391968A (en) * | 2014-12-03 | 2015-03-04 | 北京奇虎科技有限公司 | Application characteristic parameter estimating method and device |
| CN104462500A (en) * | 2014-12-19 | 2015-03-25 | 北京奇虎科技有限公司 | Method for determining activeness of controls and control processing method and device |
| CN104462277A (en) * | 2014-11-25 | 2015-03-25 | 广州酷狗计算机科技有限公司 | Application program installation data statistical method, server and terminal |
| CN104462177A (en) * | 2013-09-20 | 2015-03-25 | 纽昂斯通信有限公司 | Mobile application daily user engagement scores and user profiles |
| CN104603753A (en) * | 2014-03-19 | 2015-05-06 | 华为技术有限公司 | Method, system and server for recommending application |
| CN104699710A (en) * | 2013-12-09 | 2015-06-10 | 腾讯科技（深圳）有限公司 | User structure judgment method and device as well as account state recording method and device |
| CN104899325A (en) * | 2015-06-19 | 2015-09-09 | 上海卓悠网络科技有限公司 | APP (application) acquired data collection method, terminal, server and system |
-
2015
- 2015-10-08 CN CN201510646068.1A patent/CN106572126B/en active Active
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101557304A (en) * | 2008-04-09 | 2009-10-14 | 北京闻言科技有限公司 | Method for counting online user number of distributed application servers |
| US20110083127A1 (en) * | 2009-10-07 | 2011-04-07 | Sony Corporation | System and method for effectively providing software to client devices in an electronic network |
| CN101753566A (en) * | 2009-12-25 | 2010-06-23 | 北京畅游天下网络技术有限公司 | Multi-application inter-system data application method and system |
| CN101729571A (en) * | 2009-12-28 | 2010-06-09 | 广州游家信息技术有限公司 | Method, server and system for counting network on-line user number |
| CN103686821A (en) * | 2012-08-27 | 2014-03-26 | 上海亿动信息技术有限公司 | Control method for application program traffic statistics according to unique identification of mobile terminal |
| CN102902775A (en) * | 2012-09-27 | 2013-01-30 | 新浪网技术(中国)有限公司 | Internet real-time computing method and internet real-time computing system |
| CN103823665A (en) * | 2012-11-19 | 2014-05-28 | 中国移动通信集团公司 | SDK (software development kit) activeness analyzing method, network server and system |
| CN103841172A (en) * | 2012-11-27 | 2014-06-04 | 上海亿动信息技术有限公司 | Application download operation statistic method and device based on user terminal identification comparison |
| WO2015006617A1 (en) * | 2013-07-11 | 2015-01-15 | Al-Nasser Khalid | Smart watch |
| CN104462177A (en) * | 2013-09-20 | 2015-03-25 | 纽昂斯通信有限公司 | Mobile application daily user engagement scores and user profiles |
| CN103530796A (en) * | 2013-10-10 | 2014-01-22 | 北京智谷睿拓技术服务有限公司 | Active period detection method and active period detection system of application program |
| CN104699710A (en) * | 2013-12-09 | 2015-06-10 | 腾讯科技（深圳）有限公司 | User structure judgment method and device as well as account state recording method and device |
| CN104603753A (en) * | 2014-03-19 | 2015-05-06 | 华为技术有限公司 | Method, system and server for recommending application |
| CN104239519A (en) * | 2014-09-17 | 2014-12-24 | 广州华多网络科技有限公司 | Information recommendation method and related equipment and system |
| CN104462277A (en) * | 2014-11-25 | 2015-03-25 | 广州酷狗计算机科技有限公司 | Application program installation data statistical method, server and terminal |
| CN104391968A (en) * | 2014-12-03 | 2015-03-04 | 北京奇虎科技有限公司 | Application characteristic parameter estimating method and device |
| CN104462500A (en) * | 2014-12-19 | 2015-03-25 | 北京奇虎科技有限公司 | Method for determining activeness of controls and control processing method and device |
| CN104899325A (en) * | 2015-06-19 | 2015-09-09 | 上海卓悠网络科技有限公司 | APP (application) acquired data collection method, terminal, server and system |
Non-Patent Citations (4)
| Title |
|---|
| NONE: "友盟：活跃用户详解", 《HTTPS://WWW.GUOKR.COM/BLOG/797754/》 * |
| XIANGZILV1987: "MobclickAgent——友盟用户分析工具", 《HTTPS://BLOG.CSDN.NET/XIANGZILV1987/ARTICLE/DETAILS/7840582》 * |
| YANGXI_001: "MobclickAgent友盟统计分析工具", 《HTTPS://BLOG.CSDN.NET/YANGXI_PEKIN/ARTICLE/DETAILS/8940578》 * |
| 飞翔的熊猫: "关于友盟的用户行为分析笔记一", 《HTTPS://CNBLOGS.COM/HESIMING/ARCHIVE/2012/06/20/2556100.HTML》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107562815A (en) * | 2017-08-16 | 2018-01-09 | 上海斐讯数据通信技术有限公司 | A kind of statistical method and device of client application platform |
| CN115037489A (en) * | 2021-02-24 | 2022-09-09 | 北京国双千里科技有限公司 | Method and device for determining number of equipment identifications, storage medium and electronic equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106572126B (en) | 2020-06-30 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106980573B (en) | Method, device and system for constructing test case request object | |
| CN102279786B (en) | A kind of method of monitoring and measuring application program effective access amount and device | |
| US11481698B2 (en) | Data-driven method and apparatus for handling user inquiries using collected data | |
| WO2010058949A3 (en) | Method and apparatus for information recovery using snapshot database | |
| CN107832216A (en) | One kind buries a method of testing and device | |
| CN103116638B (en) | Webpage screening method and device thereof | |
| CN108399565A (en) | Financial product recommendation apparatus, method and computer readable storage medium | |
| SA521430068B1 (en) | System and Method for File Artifact Metadata Collection and Analysis | |
| CN106934705A (en) | A kind of special ticket doubtful point taxpayer's monitoring method of value-added tax based on SVMs | |
| CN108734306A (en) | A kind of data processing method, device, road upkeep system and storage medium | |
| CN111949702A (en) | Abnormal transaction data identification method, device and equipment | |
| CN110347931A (en) | The detection method and device of the new chapters and sections of article | |
| CN106997350B (en) | Data processing method and device | |
| CN106572126A (en) | Method for calculating number of active devices, and server | |
| CN102984162B (en) | The recognition methods of credible website and gathering system | |
| CN107862599B (en) | Bank risk data processing method and device, computer equipment and storage medium | |
| CN110301892A (en) | A kind of detection method and Related product based on hand vein recognition | |
| CN105374131A (en) | Method and device for automatic testing | |
| CN108921433B (en) | Risk quantitative analysis system based on business continuity | |
| CN103853933A (en) | Android digital forensics-oriented user behavior analysis method and system | |
| CN110493368B (en) | Matching method and device of equipment identifiers | |
| CN109885417B (en) | Anomaly analysis method, electronic device and readable storage medium | |
| Bano et al. | Addressing the challenges of alignment of requirements and services: a vision for user-centered method | |
| CN107767066A (en) | Wisdom site user behavior analysis method and device, storage medium and terminal | |
| CN112540919A (en) | Test equipment determination method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |