CN107995007B - Customer charge configuration method and customer charge configure system - Google Patents
Customer charge configuration method and customer charge configure system Download PDFInfo
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- CN107995007B CN107995007B CN201711250959.0A CN201711250959A CN107995007B CN 107995007 B CN107995007 B CN 107995007B CN 201711250959 A CN201711250959 A CN 201711250959A CN 107995007 B CN107995007 B CN 107995007B
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- 238000000034 method Methods 0.000 title claims abstract description 21
- 235000012054 meals Nutrition 0.000 claims abstract description 31
- 238000003745 diagnosis Methods 0.000 claims abstract description 7
- 230000006641 stabilisation Effects 0.000 claims description 6
- 238000011105 stabilization Methods 0.000 claims description 6
- 238000005516 engineering process Methods 0.000 abstract description 2
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
- H04L41/0893—Assignment of logical groups to network elements
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/02—Details
- H04L12/14—Charging, metering or billing arrangements for data wireline or wireless communications
- H04L12/1442—Charging, metering or billing arrangements for data wireline or wireless communications at network operator level
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
- H04L41/0896—Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities
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Abstract
The invention belongs to information technology fields, and in particular to a kind of customer charge configuration method and customer charge configure system.The customer charge configuration method, comprising steps of step S1) acquisition user network data, and business diagnosis is carried out to the network data of user；Step S2) the corresponding traffic vector collection of user generated according to the type of service of the network data of user, and cluster is associated to the user with identical online preference, to customer service type progress preference categories；Step S3) according to the business type of preferences of user, calculate the corresponding service feature of the convergence group of different business type of preferences and convergence group in set period of time；Step S4) according to the service feature of convergence group, it is user configuration set meal mode.The customer charge configuration method and customer charge configure system, realize the charging mode of dynamic sensing customer service preference, can greatly improve the Experience Degree of user.
Description
Technical field
The invention belongs to information technology fields, and in particular to a kind of customer charge configuration method and customer charge configuration system
System.
Background technique
In recent years, as the high speed development of Internet, data service highlight the effect of operator, how to formulate
The charging mode for reasonably meeting customer consumption preference becomes the key of service competition between operator.
Currently, each common carrier both provides different tariff in addition to a small amount of in such a way that real consumption carries out charging
The set meal of grade is selected for user, under the conditions of identical total rate, wherein every is configured to different accountings, to give
User provides the multiple choices for being suitble to oneself data service.
However, current charging mode can only judge according to the service condition of the data service of user, then basis
Flow carries out charging, and there are the following problems:
Can not real-time perception user preference, cause the business of user preference and the business of non-preference to be equal to charging, thus
Know from experience that user less than preferential；
Can not to user business preference update dynamically assessed because the preference of user is likely to interconnection
The development and change of net, such as a user for liking seeing video, being likely under the recommendation of friend, which becomes one, likes playing new trip
The user of play.
As it can be seen that currently used charging mode can not perceive variation of the user in terms of network service in time, causing cannot
It is the charge mode that user's real-time recommendation meets their usage modes in first time, user experience is bad.
How dynamic, effective assessment is carried out to the network service preference of user, and carry out accordingly expense configuration and
Set meal is promoted, and important technical problem urgently to be resolved at present is become.
Summary of the invention
The technical problem to be solved by the present invention is to provide a kind of customer charge configuration for above-mentioned deficiency in the prior art
Method and customer charge configure system, realize the charging mode of dynamic sensing customer service preference, can greatly improve user's
Experience Degree.
Solving technical solution used by present invention problem is the customer charge configuration method, comprising steps of
Step S1) acquisition user network data, and business diagnosis is carried out to the network data of user；
Step S2) the corresponding traffic vector collection of user generated according to the type of service of the network data of user, and to having
The user of identical online preference is associated cluster, carries out preference categories to customer service type；
Step S3) according to the business type of preferences of user, calculate the convergence of different business type of preferences in set period of time
The corresponding service feature of group and convergence group；
Step S4) according to the service feature of convergence group, it is user configuration set meal mode.
Preferably, it in step S1), is carried out by the data packet to the interface for flowing through mobile network and internet
Analysis, and network layer protocol parsing is carried out, obtain different types of service.
Preferably, in step S2), customer service vector set are as follows:
M A { url1, x1, t1 } B { url2, x2, t2 } C { url3, x3, t3 } ... F { urli, xi, ti } ... N urln, xn,
tn}}
Wherein: A, B, C ... F ... G is service identification, and x1, x2, x3 ... xi ... xn are the corresponding flow of different business, t1,
T2, t3 ... ti ... tn, which are that different business is corresponding, uses the time, and i, n are natural number, i≤n.
Preferably, in step S3), calculate set period of time in different business type of preferences convergence group and
Converge the corresponding service feature of group comprising steps of
Step S31) multidimensional coordinate system is established, one-dimensional coordinate axis though is set by type of service, type of service is arranged original
Mass center；
Step S32) it carries out repeating to restrain calculating, user is sorted out according to the mass center of type of service；
Step S33) user group is converged by iteration, so that the same line of business of each convergence group is with identical
Feature；
Step S34) it counts in the set time period, the stabilization service features of difference convergence group's intersections.
Preferably, in step S4), demographic categories, and the service traffics type being concerned about are converged according to user, for not
The respective service feature of generic user, the charging set meal different to the user configuration of different classes of convergence group.
A kind of customer charge configuration system, including data acquisition module, business preference categories module, user's convergence group's mould
Block and expense configuration module, in which:
The data acquisition module carries out business diagnosis for acquiring user network data, and to the network data of user；
The business preference categories module, the type of service for the network data according to user generate the corresponding industry of user
Business vector set, and cluster is associated to the user with identical online preference, preference categories are carried out to customer service type；
The user converges group's module, for the business type of preferences according to user, calculates different in set period of time
The corresponding service feature of convergence group and convergence group of business type of preferences；
The expense configuration module is user configuration set meal mode for the service feature according to convergence group.
Preferably, in the data acquisition module, by the interface for flowing through mobile network and internet
Data packet is analyzed, and carries out network layer protocol parsing, obtains different types of service.
Preferably, in the business preference categories module, customer service vector set are as follows:
M A { url1, x1, t1 } B { url2, x2, t2 } C { url3, x3, t3 } ... F { urli, xi, ti } ... N urln, xn,
tn}}
Wherein: A, B, C ... F ... G is service identification, and x1, x2, x3 ... xi ... xn are the corresponding flow of different business, t1,
T2, t3 ... ti ... tn, which are that different business is corresponding, uses the time, and i, n are natural number, i≤n.
Preferably, it is converged in group's module in the user, including setting unit, convergence unit, convergence unit, judgement
Unit, in which:
The setting unit sets one-dimensional coordinate axis though for type of service, to type of service for establishing multidimensional coordinate system
Original mass center is set；
The convergence unit calculates for carrying out repeating to restrain, user is sorted out according to the mass center of type of service；
The convergence unit, for being converged by iteration to user group, so that the similar industry of each convergence group
Business has same characteristic features；
The judging unit, for counting in the set time period, the stabilization service feature of difference convergence group's intersection.
Preferably, in the expense configuration module, demographic categories, and the service traffics class being concerned about are converged according to user
Type, for the respective service feature of different classes of user, the charging set different to the user configuration of different classes of convergence group
Meal.
The beneficial effects of the present invention are: the customer charge configuration method and customer charge configure system, realizes dynamic and feel
Know the charging mode of customer service preference, the Experience Degree of user can be greatly improved.
Detailed description of the invention
Fig. 1 is the flow chart of customer charge configuration method in the embodiment of the present invention 1；
Fig. 2 is the schematic diagram that customer charge configures system in the embodiment of the present invention 2；
Fig. 3 is that customer charge configures systematic difference schematic diagram in the embodiment of the present invention 2；
In attached drawing mark:
1- data acquisition module；
2- business preference categories module；
3- user converges group's module；
4- expense configuration module.
Specific embodiment
Technical solution in order to enable those skilled in the art to better understand the present invention, with reference to the accompanying drawing and specific embodiment party
Formula is described in further detail customer charge configuration method of the present invention and customer charge configuration system.
Embodiment 1:
The present embodiment provides a kind of customer charge configuration methods, realize the charged party of dynamic sensing customer service preference
Formula can greatly improve the Experience Degree of user.
As shown in Figure 1, the customer charge configuration method includes:
Step S1) acquisition user network data, and business diagnosis is carried out to the network data of user.
In this step, acquisition user's internet log data in real time, by flowing through mobile network and internet connects
Data packet at mouthful is analyzed, and carries out the layer protocol parsing of network, obtains different types of service.Wherein, 7 are carried out here
Layer protocol parsing, according to the network protocol of heterogeneous networks layer, identifies corresponding network service.
Step S2) the corresponding traffic vector collection of user generated according to the type of service of the network data of user, and to having
The user of identical online preference is associated cluster, carries out preference categories to customer service type.
In this step, customer service vector set are as follows:
M A { url1, x1, t1 } B { url2, x2, t2 } C { url3, x3, t3 } ... F { urli, xi, ti } ... N urln, xn,
tn}}
Wherein: A, B, C ... F ... G is service identification, and x1, x2, x3 ... xi ... xn are the corresponding flow of different business, t1,
T2, t3 ... ti ... tn, which are that different business is corresponding, uses the time, and i, n are natural number, i≤n.
For example, may include such as video, amusement and news picture when generating the customer service vector set of corresponding business
Equal multiple business, and generate customer service vector set:
M { A { url1, x1, t1 } B { url2, x2, t2 } C { url3, x3, t3 } }
Wherein: A, B, C are the different service identifications such as video, amusement, news picture, and x1, x2, x3 are corresponding for different business
Flow, t1, t2, t3 be different business it is corresponding use the time.
Since there are diversity for the consumption habit of user, thus need to predict when based on preference charging user preference and
User's preference transfer that may be present.Such as a user for liking playing game also sees news, also sees picture, therefore for user
Social consumption feature just needs to carry out dynamic clustering, thus the user that potentially has similar tastes and interests of discovery, then according to marketing strategy,
Dynamic adjustment charge mode.
Step S3) according to the type of preferences of user, calculate the convergence group of different business type of preferences in set period of time,
And the corresponding service feature of convergence group.
In this step, substantially the consumer behavior of user is assessed.If the Cluster Evaluation period is T, i.e., at interval of T
Carry out consumer consumption behavior cluster, such as T=24 hours.
The merger of user's real-time perfoming is carried out according to the practical type of service being concerned about of operator or business, the specific method is as follows:
Step S31) multidimensional coordinate system is established, one-dimensional coordinate axis though is set by type of service, type of service is arranged original
Mass center.
Each reference axis of coordinate system is the business that operator is concerned about, such as establishes three-dimensional system of coordinate x, y, z, (x, y, z generation respectively
Table news, amusement, game flow), to the whole nation or some save range in user (M1, M2, M3 ... Mn), randomly select k (k <
N) original mass center of a user as merger is set as μ 1, μ 2 ... μ n.
Step S32) it carries out repeating to restrain calculating, user is sorted out according to the mass center of type of service.
Computation rule be to the validated user in all ranges, calculate each user in three-dimensional system of coordinate with choose mass center
The distance of each mass center in sequence, more each distance, the user belong to the class of that mass center nearest with its distance, such as user M
(x1, y1, z1), and each mass center distance l1, l2, l ... ln, for example, when wherein l1 minimum, this think M be it is similar with μ 1, together
Reason completes an iteration to all users point.
Step S33) user group is converged by iteration, so that the same line of business of each convergence group is with identical
Feature.
In this step, for n classification in step S32), all users have ownership, then in each classification
All coordinates of user average and generate (a1, b1, c1) respectively ... (an, bn, cn), then repeatedly step S32), it is again right
All users iterate.
Step S32 is repeated), step S33) operation, until stable or can be at one by mass center after successive ignition
When the threshold range fluctuation of receiving, it is believed that user group, which converges, to stablize, and at this moment produces n user group, each group has
The same characteristic features for the same line of business for thering is operator to be concerned about.
Wherein, the formula of distance is calculated are as follows:
L=argmin | | x1- μ 1 | |
Step S34) it counts in the set time period, the stabilization service features of difference convergence group's intersections.
In this step, according to marketing and the market demand, how long need to carry out perceptibility to user group to being greater than
Charging, if the period is t (t > T), then in the t period, the group for the n type that each T time generates carries out intersection, obtains steady
Fixed user's classification group, i.e. user group in intersection are the user within the t time with stable consumption feature.
Step S4) according to the service feature of convergence group, it is user configuration set meal mode.
Product customization is carried out according to set meal since network billing system is substantially, unification cannot be carried out for user and referred to
It is fixed, so needs select optimal as user in existing mode and most preferably recommend.Therefore, it is necessary to the business preferences according to user
Type calculates the match grade of the business type of preferences and the current expense set meal of charge mode by type, so that it is determined that with
The matched set meal in family is simultaneously configured.
In this step, demographic categories, and the service traffics type being concerned about are converged according to user, for different classes of use
Respectively service feature, the charging set meal different to the different classes of user configuration for converging group are user configuration charging at family.Example
Such as, for business such as news, video, amusement or game, type charging is combined according to the marketing strategy, generation meets difference
The user of classification respectively feature with predictive set meal, i.e., the preferential of real-time perception charge on traffic is carried out to these users,
To obtain apparent marketing effectiveness.
Embodiment 2:
Correspondingly, the present embodiment provides a kind of customer charges to configure system, dynamic sensing customer service preference is realized
Charging mode can greatly improve the Experience Degree of user.
As shown in Fig. 2, the customer charge configures system, including data acquisition module 1, business preference categories module 2, user
Converge group's module 3 and expense configuration module 4, in which:
Data acquisition module 1 carries out business diagnosis for acquiring user network data, and to the network data of user；
Business preference categories module 2, the type of service for the network data according to user generate the corresponding business of user
Vector set, and cluster is associated to the user with identical online preference, preference categories are carried out to customer service type；
User converges group's module 3, for the business type of preferences according to user, calculates different business in set period of time
The corresponding service feature of convergence group and convergence group of type of preferences；
Expense configuration module 4 is user configuration set meal mode for the service feature according to convergence group.
Interface deployment data acquisition module 1 in mobile network and internet passes through in data acquisition module 1
The data packet for the interface for flowing through mobile network and internet is analyzed, and carries out network layer protocol parsing, is obtained not
Same type of service.
In business preference categories module 2, customer service vector set are as follows:
M A { url1, x1, t1 } B { url2, x2, t2 } C { url3, x3, t3 } ... F { urli, xi, ti } ... N urln, xn,
tn}}
Wherein: A, B, C ... F ... G is service identification, and x1, x2, x3 ... xi ... xn are the corresponding flow of different business, t1,
T2, t3 ... ti ... tn, which are that different business is corresponding, uses the time, and i, n are natural number, i≤n.
For example, may include such as video, amusement and news picture when generating the customer service vector set of corresponding business
Equal multiple business, and generate customer service vector set:
M { A { url1, x1, t1 } B { url2, x2, t2 } C { url3, x3, t3 } }
Wherein: A, B, C are the different service identifications such as video, amusement, news picture, and x1, x2, x3 are corresponding for different business
Flow, t1, t2, t3 be different business it is corresponding use the time.
Since there are diversity for the consumption habit of user, thus need to predict when based on preference charging user preference and
User's preference transfer that may be present.Such as a user for liking playing game also sees news, also sees picture, therefore for user
Social consumption feature just needs to carry out dynamic clustering, thus the user that potentially has similar tastes and interests of discovery, then according to marketing strategy,
Dynamic adjustment charge mode.
It is converged in group's module 3 in user, including setting unit, convergence unit, convergence unit, judging unit, in which:
Setting unit sets one-dimensional coordinate axis though for type of service for establishing multidimensional coordinate system, and type of service is arranged
Original mass center.Each reference axis of coordinate system is the business that operator is concerned about, such as establishes three-dimensional system of coordinate x, y, z, (x, y, z difference
Represent the flow of news, amusement, game), to the user (M1, M2, M3 ... Mn) in the whole nation or some province's range, randomly select k
Original mass center of (k < n) a user as merger is set as μ 1, μ 2 ... μ n.
Unit is restrained, is calculated for carrying out repeating to restrain, user is sorted out according to the mass center of type of service.Calculate rule
Then for the validated user in all ranges, calculate each user in three-dimensional system of coordinate with choose each mass center in Centroid sequence
Distance, more each distance, the user belong to the class of that mass center nearest with its distance, such as user M (x1, y1, z1), and each
Distance l1, l2, l ... the ln of mass center, for example, this thinks M to be similar with μ 1, similarly to all users point when wherein l1 minimum
Complete an iteration.
Unit is converged, for converging by iteration to user group, so that the same line of business tool of each convergence group
There are same characteristic features.For n classification in convergence unit, all users have ownership, then to the user institute in each classification
There is coordinate to average respectively and generate (a1, b1, c1) ... (an, bn, cn), then iteration step, again to all users
It iterates.
By operating repeatedly in convergence unit and convergence unit, mass center is stable or at one after passing through successive ignition
When acceptable threshold range fluctuates, it is believed that user group, which converges, to stablize, and at this moment produces n user group, each group
The same characteristic features for the same line of business being all concerned about with operator.
Wherein, the formula of distance is calculated are as follows:
L=argmin | | x1- μ 1 | |
Judging unit, for counting in the set time period, the stabilization service feature of difference convergence group's intersection.According to battalion
How long pin and the market demand need to carry out perceptibility charging to user group to big decision, if the period is t (t > T), then
To in the t period, the group for the n type that each T time generates carries out intersection, obtains stable user's classification group, i.e. intersection
Interior user group is the user within the t time with stable consumption feature.
In expense configuration module 4, demographic categories, and the service traffics type being concerned about are converged according to user, for difference
The respective service feature of the user of classification, the charging set meal different to the user configuration of different classes of convergence group.
Product customization is carried out according to set meal since network billing system is substantially, unification cannot be carried out for user and referred to
It is fixed, so needs select optimal as user in existing mode and most preferably recommend.Therefore, it is necessary to the business preferences according to user
Type calculates the match grade of the business type of preferences and the current expense set meal of charge mode by type, so that it is determined that with
The matched set meal in family is simultaneously configured.
In expense configuration module 4, demographic categories, and the service traffics type being concerned about are converged according to user, for difference
The user of classification respectively match for user by service feature, the charging set meal different to the user configuration of different classes of convergence group
Set charging.For example, type charging is combined according to the marketing strategy for business such as news, video, amusement or game, it is raw
At meet different classes of user respectively feature with predictive set meal, i.e., real-time perception flowmeter is carried out to these users
What is taken is preferential, to obtain apparent marketing effectiveness.
As shown in figure 3, in practical applications, acquiring the Internet data of user terminal, user preference cluster is analyzed,
Based on the analysis results, it calculates and has immediate charge mode in the set meal of charge mode by type, so that it is determined that this set
Meal is user's optimal selection.Such as: originally user orders+180 minutes voice set meals of 500M flow, and present company and content provide
Activity is done in the cooperation of quotient Tencent, and new set meal activity can be released for the video of Tencent, and preferential activity includes that can exempt 200M to rise
The charge on traffic for interrogating video finds that user is user and the flow using Tencent's video when perceiving charging method by user
Greater than 200M, then can dynamic upgrade set meal for it and inform user, can allow the preferential activity of user's real-time perception in this way, be promoted
User experience and attention rate to company.
Customer charge configuration method of the invention and customer charge configure system, are based on domestic telecommunication operator mobile network
And the reality to customer consumption preference is realized in such a way that a kind of telescopic perception user set meal items are constituted in internet
When perceive；Meanwhile it being based on existing set meal charge mode, realize the perception of user group's consumer behavior to type of service, week
Phase property polymerize user behavior and carries out dynamic adjustment to the charging mode of the user of convergence group, promotes the experience of user.
It is understood that the principle that embodiment of above is intended to be merely illustrative of the present and the exemplary implementation that uses
Mode, however the present invention is not limited thereto.For those skilled in the art, essence of the invention is not being departed from
In the case where mind and essence, various changes and modifications can be made therein, these variations and modifications are also considered as protection scope of the present invention.
Claims (8)
1. a kind of customer charge configuration method, which is characterized in that comprising steps of
Step S1) acquisition user network data, and business diagnosis is carried out to the network data of user；
Step S2) the corresponding traffic vector collection of user generated according to the type of service of the network data of user, and to identical
The user of online preference is associated cluster, carries out preference categories to customer service type；
Step S3) according to the business type of preferences of user, calculate the convergence group of different business type of preferences in set period of time,
And the corresponding service feature of convergence group；The step includes:
Step S31) multidimensional coordinate system is established, one-dimensional coordinate axis though is set by type of service, original mass center is arranged to type of service；
Step S32) it carries out repeating to restrain calculating, user is sorted out according to the mass center of type of service；
Step S33) user group is converged by iteration, so that the same line of business of each convergence group has identical spy
Sign；
Step S34) it counts in the set time period, the stabilization service features of difference convergence group's intersections；
Step S4) according to the service feature of convergence group, it is user configuration set meal mode.
2. customer charge configuration method according to claim 1, which is characterized in that in step S1), by flow through move
The data packet of the interface of dynamic network and internet is analyzed, and carries out network layer protocol parsing, obtains different business
Type.
3. customer charge configuration method according to claim 2, which is characterized in that in step S2), customer service vector
Collection are as follows:
M { A { url1, x1, t1 } B { url2, x2, t2 } C { url3, x3, t3 } ... F { urli, xi, ti } ... N { urln, xn, tn } }
Wherein: A, B, C ... F ... G is service identification, and x1, x2, x3 ... xi ... xn are the corresponding flow of different business, t1, t2,
T3 ... ti ... tn, which is that different business is corresponding, uses the time, and i, n are natural number, i≤n.
4. customer charge configuration method according to claim 1, which is characterized in that in step S4), converged according to user
Demographic categories, and the service traffics type being concerned about, for the respective service feature of different classes of user, to different classes of convergence
The different charging set meal of the user configuration of group.
5. a kind of customer charge configures system, which is characterized in that including data acquisition module, business preference categories module, user
Converge group's module and expense configuration module, in which:
The data acquisition module carries out business diagnosis for acquiring user network data, and to the network data of user；
The business preference categories module, for the type of service according to the network data of user generate the corresponding business of user to
Quantity set, and cluster is associated to the user with identical online preference, preference categories are carried out to customer service type；
The user converges group's module, for the business type of preferences according to user, calculates different business in set period of time
The corresponding service feature of convergence group and convergence group of type of preferences；It includes that setting is single that the user, which converges group's module,
Member, convergence unit, convergence unit, judging unit, in which:
The setting unit sets one-dimensional coordinate axis though for type of service for establishing multidimensional coordinate system, and type of service is arranged
Original mass center；
The convergence unit calculates for carrying out repeating to restrain, user is sorted out according to the mass center of type of service；
The convergence unit, for being converged by iteration to user group, so that the same line of business tool of each convergence group
There are same characteristic features；
The judging unit, for counting in the set time period, the stabilization service feature of difference convergence group's intersection
The expense configuration module is user configuration set meal mode for the service feature according to convergence group.
6. customer charge according to claim 5 configures system, which is characterized in that in the data acquisition module, lead to
It crosses and the data packet for the interface for flowing through mobile network and internet is analyzed, and carry out network layer protocol parsing, obtain
Different types of service.
7. customer charge according to claim 6 configures system, which is characterized in that in the business preference categories module
In, customer service vector set are as follows:
M { A { url1, x1, t1 } B { url2, x2, t2 } C { url3, x3, t3 } ... F { urli, xi, ti } ... N { urln, xn, tn } }
Wherein: A, B, C ... F ... G is service identification, and x1, x2, x3 ... xi ... xn are the corresponding flow of different business, t1, t2,
T3 ... ti ... tn, which is that different business is corresponding, uses the time, and i, n are natural number, i≤n.
8. customer charge according to claim 5 configures system, which is characterized in that in the expense configuration module, root
Demographic categories, and the service traffics type being concerned about are converged according to user, for the respective service feature of different classes of user, to difference
The different charging set meal of the user configuration of the convergence group of classification.
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| CN112398663A (en) * | 2020-11-06 | 2021-02-23 | 浪潮云信息技术股份公司 | Elastic IP charging method and system based on deep neural network |
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| CN105389713A (en) * | 2015-10-15 | 2016-03-09 | 南京大学 | Mobile data traffic package recommendation algorithm based on user historical data |
| WO2017201379A1 (en) * | 2016-05-19 | 2017-11-23 | Vid Scale, Inc. | Client centric service quality control |
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| CN103607691A (en) * | 2013-11-26 | 2014-02-26 | 中国联合网络通信集团有限公司 | Flow package recommendation method and device |
| CN105389713A (en) * | 2015-10-15 | 2016-03-09 | 南京大学 | Mobile data traffic package recommendation algorithm based on user historical data |
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