CN105405026A - Customized mobile phone determination method based on user behavior and apparatus thereof - Google Patents
Customized mobile phone determination method based on user behavior and apparatus thereof Download PDFInfo
- Publication number
- CN105405026A CN105405026A CN201510698175.9A CN201510698175A CN105405026A CN 105405026 A CN105405026 A CN 105405026A CN 201510698175 A CN201510698175 A CN 201510698175A CN 105405026 A CN105405026 A CN 105405026A
- Authority
- CN
- China
- Prior art keywords
- user
- mobile phone
- planes
- surfing flow
- changing
- 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.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0204—Market segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0207—Discounts or incentives, e.g. coupons or rebates
- G06Q30/0224—Discounts or incentives, e.g. coupons or rebates based on user history
Landscapes
- Business, Economics & Management (AREA)
- Strategic Management (AREA)
- Engineering & Computer Science (AREA)
- Accounting & Taxation (AREA)
- Development Economics (AREA)
- Finance (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- Game Theory and Decision Science (AREA)
- Economics (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Telephonic Communication Services (AREA)
Abstract
The invention provides a customized mobile phone determination method based on a user behavior. The method comprises the following steps of acquiring a user internet-surfing behavior information table; acquiring a potential mobile phone changing user, wherein the potential mobile phone changing user is the user whose current mobile phone usage time reaches a preset threshold of average usage time of the mobile phone with a same model; according to the user internet-surfing behavior information table, searching the user whose a mobile phone model before mobile phone changing is the same with the current mobile phone model of the potential machine changing user and determining the mobile phone model of the user who satisfies a preset condition after the mobile phone changing as a customized mobile phone recommended for the potential mobile phone changing user. By using the method, the potential mobile phone changing user who really has a mobile phone changing demand can be determined so that recommendation of the customized mobile phone is targeted and a success rate is high; simultaneously, the customized mobile phone determined through internet-surfing behavior analysis of the potential user is suitable for the demand of the potential mobile phone changing user.
Description
Technical field
The present invention relates to communication technical field, be specifically related to a kind of customization machine defining method based on user behavior and device.
Background technology
In recent years, Ge great operator terminal customization ratio improves constantly.For operator, terminal customization is conducive to it and promotes data service, develop new user and excavate high-end user, the popularization of various value-added service can be carried out to cultivate the custom that user uses new business simultaneously, improve ARPU value (i.e. AverageRevenuePerUser, for weighing the index of telecom operation commercial affairs income, be defined as the income that in the time period, operator obtains from each user).Meanwhile, for user, the custom terminal of operator has mobile phone in various degree or call charge allowance, and what reduce user purchases gate sill, can consider that the customization machine buying operator is to obtain subsidy when changing planes.
For the selection of custom terminal, the method for Ge great operator is different, mostly selects the mobile phone meeting self strategic planning standard, interval according to different prices, chooses some fast sales, the brand and model that quality is secure; Also some operators are had to carry out the deep layer custom-made mobile phone specified according to the configuration of self strategic adversary's machine.Above method is all the strategic angle from operator self, carries out the selection of customization machine, do not carry out custom terminal according to the actual demand of user in conjunction with the experience of the terminal sale data on some markets and accumulation and subjective Brand Preference.In addition, also lack data before operator intention and recommend suitable custom terminal based on the user that the method for data changes mobile phone to potential demand, Objective is indefinite, is difficult to realize doulbe-sides' victory.
How fundamentally solving the potential renewal user customized recommendation customization machine for really there being the demand of changing planes, is communications field problem demanding prompt solution.
Summary of the invention
Technical matters to be solved by this invention is for above-mentioned defect existing in prior art, a kind of customization machine defining method based on user behavior and device are provided, in order to solve exist in prior art can not customize according to user behavior the problem that machine determines targetedly, realize the determination to really there being the potential renewal user of the demand of changing planes to meet the customization machine of its user behavior.
For achieving the above object, the invention provides a kind of customization machine defining method based on user behavior, comprising:
Obtain user internet behavior information table, comprise mobile phone model before changing planes, change planes before internet behavior and mobile phone model after changing planes;
Obtain potential renewal user, described potential renewal user for its current phone use duration reached the user that same model mobile phone on average uses duration predetermined threshold value;
According to described user's internet behavior information table, search the user that before changing planes, mobile phone model is identical with described potential renewal user current use mobile phone model, mobile phone model after meeting the changing planes of pre-conditioned user is defined as the customization machine into described potential renewal user recommends.
For achieving the above object, the invention provides a kind of customization machine determining device based on user behavior, comprise internet behavior analysis module, potential user's analysis module and customization machine analysis module, wherein,
Internet behavior analysis module, for obtaining user's internet behavior information table, comprise mobile phone model before changing planes, change planes before internet behavior and mobile phone model after changing planes;
Potential user's analysis module, for obtaining potential renewal user, described potential renewal user for its current phone use duration reached the user that same model mobile phone on average uses duration predetermined threshold value;
Customization machine analysis module, for according to described user's internet behavior information table, search the user that before changing planes, mobile phone model is identical with described potential renewal user current use mobile phone model, mobile phone model after meeting the changing planes of pre-conditioned user is defined as the customization machine into described potential renewal user recommends.
A kind of customization machine defining method based on user behavior provided by the invention and device, by analyzing the original internet records data of user, search the potential renewal user really having the demand of changing planes, and by the internet behavior of user identical with the existing type of potential user for type before the changing planes of the internet behavior of potential renewal user and other renewal user, carry out the calculating of matching degree, thus find out the customization machine determined according to the internet behavior of potential user.
Based on the customization machine defining method of user behavior and device in the present invention, first the potential renewal user really having the demand of changing planes can be determined, make the recommendation of customization machine more targetedly and have higher success rate, secondly, by the customization machine that the internet behavior analysis of potential user is determined, draw to have the user of the internet behavior of matched to add up with potential renewal user, Objective is stronger, more be applicable to the demand of potential renewal user's individuality, realize the doulbe-sides' victory of telecom operators and user.
Accompanying drawing explanation
In order to the technical scheme in the clearer explanation embodiment of the present invention, below the accompanying drawing used required in describing embodiment is done and introduce simply, apparently, accompanying drawing in the following describes is some embodiments of the present invention, for those of ordinary skill in the art, under the prerequisite not paying creative work, other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 is a kind of customization machine defining method schematic flow sheet based on user behavior provided by the invention;
Fig. 2 is the schematic flow sheet of acquisition user internet behavior information table provided by the invention;
Fig. 3 is the schematic diagram of a kind of most preferred customization machine determining device based on user behavior provided by the invention.
Embodiment
For making those skilled in the art understand technical scheme of the present invention better, below in conjunction with drawings and Examples, the present invention is described in further detail.Obviously, described embodiment is the present invention's part embodiment, instead of whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art, not making the every other embodiment obtained under creative work prerequisite, belong to the scope of protection of the invention.
Reference Fig. 1, Fig. 1 are a kind of customization machine defining method schematic flow sheet based on user behavior provided by the invention.
A kind of customization machine defining method flow process based on user behavior provided by the invention comprises the steps:
Step 10, obtain user internet behavior information table, comprise mobile phone model before changing planes, change planes before internet behavior and mobile phone model after changing planes.
First, obtain the internet behavior information of all users, mainly comprise user change mobile phone before mobile phone model, changed the new cell-phone of which model and its change planes before internet behavior information data, utilize these data, the recommendation searching and customize machine of further potential renewal user can be carried out.Based on the different internet behaviors of different user, on the one hand mobile phone is used to the user of certain time length, the model of changing planes with the user of similar internet behavior can have been recommended as customization machine for it; On the other hand, the behavior of changing planes of himself, one of reference sample that the user that also can have as other demand of changing planes changes planes input database.
Described internet behavior data, are set as flow service condition, are the data groups comprising four data: [b
0, j
0, t
0, a
0]
Wherein:
B is a month flow;
J is a month record number;
T is month online hours;
A is application number.
Being set as the statistics duration of month, is the data deviation considering that the uncertain user behavior of filtering produces; Consider uninterrupted, online number of times, online hours, open the quantity of application, the behavioral data that user surfs the Net can be carried out the analysis of Comprehensive.Certainly, according to practical situations, also can be set as that other times section except one month is as statistics duration, does not limit here.
Step 20, obtains potential renewal user, described potential renewal user for its current phone use duration reached the user that same model mobile phone on average uses duration predetermined threshold value.
The object of suitable customization machine is recommended for being embodied as the real user with the demand of changing planes, potential renewal user is extremely important in accurate searching, the present invention proposes and used duration to reach the method for a preset duration threshold value according to the current phone of user, and specify that preset duration is the average use duration of the mobile phone identical with current phone model.
As, the mobile phone model that user uses is Samsung NOTE3, and the mobile phone of this kind of model on average uses duration to be 2 years, then arranges the threshold value of 80%, when user has used about 19 months, just this user can be classified as potential renewal user.
Step 30, according to described user's internet behavior information table, search the user that before changing planes, mobile phone model is identical with described potential renewal user current use mobile phone model, mobile phone model after meeting the changing planes of pre-conditioned user is defined as the customization machine into described potential renewal user recommends.
Wherein, described meeting is pre-conditioned, refers to the internet behavior information data of the user screened, and carrying out the calculating of matching degree, calculating as utilized Euclidean distance with the internet behavior information data of potential renewal user:
Choose the internet behavior data [b, j, t, a] of nearly month of potential renewal user;
Choose the internet behavior data [b', j', t', a'] of the previous moon of changing planes of the user filtered out;
Utilize Euclidean distance computing formula, calculate [b, j, t, a] and the distance owning [b', j', t', a']:
B is the monthly flow of user;
J is the monthly discharge record number of user;
T is the monthly online hours of user;
A on average applies number for user.
Distance is less, represents that similarity is higher, is sorted from small to large by Euclidean distance, and after spending changing planes of the highest or the highest several users similarly to potential user's recommendation, mobile phone model is the customization machine that potential user recommends the most.
A kind of customization machine defining method based on user behavior provided by the invention, by the analysis of the internet behavior to all users, find out the potential renewal user with demand of really changing planes, and find out the recommendation that the renewal user with its internet behavior with matched degree carries out customization machine machine type, really accomplish as potential renewal user is customized, improve the accuracy that customization machine is recommended.
With reference to the schematic flow sheet that Fig. 2, Fig. 2 are acquisition user internet behavior information table provided by the invention.
The flow process of acquisition user internet behavior information table provided by the invention, comprising:
Step 101, extracts the original internet records data of all users.
The original internet records data of user comprise all raw information, comprise the raw data such as user mobile phone IMSI number, IMEI, online start time, surfing flow, access service type.
Step 102, calculates mobile phone before changing planes and uses duration, surfing flow use value and surfing flow lifting values.
Wherein said change planes before mobile phone use duration to be that user changes mobile phone and the last mistiming changing mobile phone the last time; Described surfing flow use value comprises flow value, record number, online hours and application number; Described surfing flow lifting values deducts the difference of each several part numerical value corresponding to the surfing flow use value before changing planes by each several part numerical value of the surfing flow use value after changing planes, again with change planes before the corresponding part numerical value of surfing flow use value be divided by, finally business's addition calculation is drawn, is exemplified below:
Surfing flow lifting values=(b
1-b
0)/b
0+ (j
1-j
0)/j
0+ (t
1-t
0)/t
0+ (a
1-a
0)/a
0
The mobile phone model flow service condition of corresponding 1 month before changing planes: [b
0, j
0, t
0, a
0];
The mobile phone model flow service condition of corresponding 1 month after changing planes: [b
1, j
1, t
1, a
1];
B is a month flow;
J is a month record number;
T is month online hours;
A is application number.
Utilize surfing flow lifting values, can screen customization machine further, can by setting the mode of appropriate threshold value, after selection being changed planes, surfing flow lifting values does not meet the mobile phone model eliminating of predetermined threshold value, does not come for potential user recommends as customization machine.
Step 103, according to the internet behavior information of user described in preset duration record, described internet behavior information comprise change planes before mobile phone model, change planes before mobile phone use duration, mobile phone model, this time of changing planes after changing planes, change planes before surfing flow use value, change planes after surfing flow use value, change planes after surfing flow lifting values.
Wherein, mobile phone model and the mobile phone model after changing planes before changing planes, all drawn by the IMEI in raw readings, meanwhile, according to mobile phone model, the mobile phone of different model can segment by operator, as carried out the division of low terminal, middle terminal, high terminal, when carrying out the recommendation of customization machine, the user that replacing mobile phone is replaced by low terminal by high terminal is excluded, thus ensure the income that customization function is brought.
According to the internet behavior information table of this user, the replacing of certain mobile phone model person-time can also be added up, in conjunction with the surfing flow lifting values after changing planes, the integrated ordered determination carrying out customization machine, as, only will change person-time many and mobile phone model that the mean value of surfing flow lifting values is also high as the machine of customization.
Acquisition user internet behavior information table provided by the invention, as the potential renewal user of searching and the analysis foundation determining customization machine, can show that the type of potential renewal user and customization machine is used alone further; Wherein analyze the potential renewal user found out, have real demand of changing planes, the recommendation that can send customization machine for operator provides target accurately; And customize the determination of machine, consider the lifting values of the surfing flow of user, the income directly can brought for operator from customization machine determines customization machine, and while calculates according to user behavior again and to change planes person-time, and the customization machine determined is the mobile phone being really subject to customer's approval.
Reference Fig. 3, Fig. 3 are provided by the invention a kind of preferably based on the schematic diagram of the customization machine determining device of user behavior.
Fig. 3 is the most preferred customization machine determining device based on user behavior provided by the invention, comprising:
Internet behavior analysis module 30, for obtaining user's internet behavior information table, comprise mobile phone model before changing planes, change planes before internet behavior and mobile phone model after changing planes;
Potential user's analysis module 31, for obtaining potential renewal user, described potential renewal user for its current phone use duration reached the user that same model mobile phone on average uses duration predetermined threshold value;
Customization machine analysis module 32, for according to described user's internet behavior information table, search the user that before changing planes, mobile phone model is identical with described potential renewal user current use mobile phone model, mobile phone model after meeting the changing planes of pre-conditioned user is defined as the customization machine into described potential renewal user recommends.
Described internet behavior analysis module 30, comprises extraction unit 301, computing unit 302 and storage unit 303, wherein,
Extraction unit 301, for extracting the original internet records data of all users;
Computing unit 302, for calculate change planes before mobile phone use duration, surfing flow use value and surfing flow lifting values, wherein said change planes before mobile phone use duration to be that user changes mobile phone and the last mistiming changing mobile phone the last time; Described surfing flow use value comprises flow value, record number, online hours and application number; Described surfing flow lifting values deducts the difference of each several part numerical value corresponding to the surfing flow use value before changing planes by each several part numerical value of the surfing flow use value after changing planes, again with change planes before the corresponding part numerical value of surfing flow use value be divided by, finally business's addition calculation is drawn;
Storage unit 303, for the internet behavior information according to user described in preset duration record, described internet behavior information comprise change planes before mobile phone model, change planes before mobile phone use duration, mobile phone model, this time of changing planes after changing planes, change planes before surfing flow use value, change planes after surfing flow use value, change planes after surfing flow lifting values.
Described potential user's analysis module 31, also comprises,
Mobile phone on average uses duration analytic unit 311, on average uses duration for analyzing described same model mobile phone, is that mobile phone uses the mean value of duration to add up to draw before the replacing of same model mobile phone by mobile phone before changing in described user's internet behavior information table.
Described customization machine analysis module 32, comprises matching degree computing unit 321,
Described matching degree computing unit 321, for according to described user's internet behavior information table, search the surfing flow use value of the user that mobile phone model is identical with described potential renewal user current use mobile phone model before changing planes, calculate the matching degree of the surfing flow use value of itself and potential renewal user, by meet preset range matching degree corresponding to user, as meeting pre-conditioned user.
Described customization machine analysis module 32, also comprise candidate and customize machine analytic unit 322, described candidate customizes machine analytic unit 322, the screening that customization machine is carried out in machine list is customized for utilizing candidate, described candidate customizes machine list by having the user of mobile phone model after identical changing planes in the internet behavior information of searching described user, calculate its change planes after the average lifting values of surfing flow, calculate simultaneously described identical change planes after renewal user's summation of mobile phone model, average for surfing flow lifting values and renewal user's summation are sorted, the candidate that is defined as potential renewal user recommends of mobile phone model after changing planes at least partly after sequence is customized machine list.
Provided by the invention a kind of preferably based on the customization machine determining device of user behavior, can according to the original internet records of user, analyzing mobile phone uses duration to reach same model mobile phone and on average use a certain proportion of user of duration as potential renewal user, for the determination of customization machine, not only reference and potential renewal user have the candidate type of replacing type as the machine of customization of the user of the internet behavior of high matching degree, consider the overall replacing person-time of candidate's type and the surfing flow lifting values after changing simultaneously, find out and really can bring the customization machine type of income for operator, from the angle of individual subscriber and operator both sides, accomplish the doulbe-sides' victory that customization machine is recommended.
Finally, for the customization machine defining method that the present invention is based on user behavior is better described, illustrate according to analytical procedure with example:
The first step, extract the original internet records data of all users
Simply be expressed as follows table:
Second step, obtains user's internet behavior information table
With one month for statistical time range, the internet behavior information form of user is calculated and is added up, is listed below:
Wherein, surfing flow use value is: [b
0, j
0, t
0, a
0],
B is a month flow;
J is a month record number;
T is month online hours;
A is application number.
3rd step, finds potential renewal user
First, extract in user's internet behavior information table, this is changed planes the time, draws the duration of use of user's current phone, and as user 1, current phone is millet red rice 2, has used duration to be 1.6 years;
Secondly, extract a mobile phone model in user's internet behavior information table, as millet red rice 2, before calculating all changing planes, mobile phone model is the user of millet red rice 2, before changing planes, mobile phone uses duration to be averaged, and can show that the average use duration of the mobile phone of this model of millet red rice 2 is 2 years;
Again, further again according to user's internet information table, the screening scope of setting customization machine.Different mobile phone models is carried out the division of class, as the division of high terminal, middle and high end, low terminal and function machine, the statistics that the mobile phone simultaneously carrying out different model carries out changing person-time, when the mobile phone model after user changes compares the mobile phone model class step-down before changing, or change person-time lower mobile phone model, do not listed in the recommended range of customization machine, ensured the economic return that customization machine can bring for operator;
Be exemplified below:
| Brand | Model | Class | Average useful life | Replacing person-time | |
| 1 | Samsung | Note4 | Middle and high end | 1.5 year | 34532 |
| 2 | Samsung | S6 | High-end | 1.5 year | 232457 |
| 3 | Huawei | Mate7 | Middle and high end | 1.2 year | 2345 |
| 4 | Huawei | Mate7 | Middle and high end | 1.2 year | 983476 |
| 5 | Apple | Iphone6 | High-end | 2 years | 456234 |
| 6 | Apple | Iphone5s | High-end | 0.7 year | 34577 |
| 7 | Millet | Mi3 | Middle-end | 1.5 year | 12321 |
| 8 | Millet | Red rice 2 | Low and middle-end | 2 years | 37832 |
| 9 | Vertu | Vertu | Luxurious | 2.2 year | 2324 |
| 10 | Gionee | 4 | Low side | 1.8 year | 1245 |
| 11 | Nokia | M | Function machine | 1.9 year | 98347 |
| 12 | Millet | 2A | Low and middle-end | 1 year | 46234 |
Finally, the current phone setting potential renewal user uses duration on average to use 80% of duration as mobile phone, then user 1 reaches this thresholding system, and user 1 can as potential renewal user.
4th step, is defined as the customization machine that potential user recommends
First, extract in user's internet behavior information table, all change planes before mobile phone model be the user of millet red rice 2, before being changed planes, surfing flow use value and potential renewal user carry out the calculating of matching degree, if mobile phone model before filtering out user 2, user 3 user 2, user 4, user 5, user 6, the changing planes of user 7 is also millet red rice 2, Euclidean distance is adopted to calculate matching degree user 1 and user 2-7;
Secondly, calculate through Euclidean distance, as drawn, surfing flow use value and user 1 matching degree are the highest before user 2, the changing planes of user 3 and user 4, and the reason that user 5-7 matching degree is lower is: user 5 is comparatively large with the online duration difference of user 1, user 6 is comparatively large with the moon flow value difference of user 1, the online application number of user 7 and user 1 and the equal difference of online duration larger;
Again, search user 2 change planes after mobile phone model be Samsung NOTE4, after user 3 changes planes, mobile phone model is Samsung S6, and after user 4 changes planes, mobile phone model is millet 2A; Finally, because mobile phone model does not meet customization machine proposed standard after the changing planes of user 4, user 4 gets rid of, by mobile phone model Samsung NOTE4 after the changing planes of user 2, and user 3 change planes after mobile phone model Samsung S6, be the customization machine that user 1 recommends the most.
In several embodiment provided by the present invention, should be understood that, disclosed method, apparatus and system, can realize by another way.Such as, apparatus embodiments described above is only schematic, the division of described functional module, be only a kind of division of logic function, actual can have other dividing mode when realizing, such as multiple module can in conjunction with or another system can be integrated into, or some features can be ignored, or do not perform.
Last it is noted that above embodiment is only in order to illustrate technical scheme of the present invention, be not intended to limit; Although with reference to previous embodiment to invention has been detailed description, those of ordinary skill in the art is to be understood that: it still can be modified to the technical scheme described in foregoing embodiments, or carries out equivalent replacement to wherein portion of techniques feature; And these amendments or replacement, do not make the essence of appropriate technical solution depart from the spirit and scope of various embodiments of the present invention technical scheme.
Claims (10)
1., based on a customization machine defining method for user behavior, it is characterized in that, comprising:
Obtain user internet behavior information table, comprise mobile phone model before changing planes, change planes before internet behavior and mobile phone model after changing planes;
Obtain potential renewal user, described potential renewal user for its current phone use duration reached the user that same model mobile phone on average uses duration predetermined threshold value;
According to described user's internet behavior information table, search the user that before changing planes, mobile phone model is identical with described potential renewal user current use mobile phone model, mobile phone model after meeting the changing planes of pre-conditioned user is defined as the customization machine into described potential renewal user recommends.
2. method according to claim 1, described acquisition user internet behavior information table, is characterized in that: comprise,
Extract the original internet records data of all users;
Calculating change planes before mobile phone use duration, surfing flow use value and surfing flow lifting values, wherein said change planes before mobile phone use duration to be that user changes mobile phone and the last mistiming changing mobile phone the last time; Described surfing flow use value comprises flow value, record number, online hours and application number; Described surfing flow lifting values deducts the difference of each several part numerical value corresponding to the surfing flow use value before changing planes by each several part numerical value of the surfing flow use value after changing planes, again with change planes before the corresponding part numerical value of surfing flow use value be divided by, finally business's addition calculation is drawn;
According to the internet behavior information of user described in preset duration record, described internet behavior information comprise change planes before mobile phone model, change planes before mobile phone use duration, change planes after mobile phone model, this time of changing planes, change planes before surfing flow use value, change planes after surfing flow use value, change planes after surfing flow lifting values.
3. method according to claim 1, is characterized in that:
Described same model mobile phone on average uses duration to be, by searching the user identical with described potential renewal user's current phone model of mobile phone model before changing planes in described user's internet behavior information table, calculate described user change planes before mobile phone use the mean value of duration to draw.
4. method according to claim 1, it is characterized in that: describedly meet pre-conditioned user, comprise according to described user's internet behavior information table, search the surfing flow use value of the user that mobile phone model is identical with described potential renewal user current use mobile phone model before changing planes, calculate the matching degree of the surfing flow use value of itself and potential renewal user, by meet preset range matching degree corresponding to user, as meeting pre-conditioned user.
5. method according to claim 4, is characterized in that: before being defined as the customization machine into described potential renewal user's recommendation, also comprise further:
Utilize candidate to customize screening that customization machine is carried out in machine list, described candidate customizes machine list by having the user of mobile phone model after identical changing planes in the internet behavior information of searching described user, calculate its change planes after the average lifting values of surfing flow, calculate simultaneously described identical change planes after renewal user's summation of mobile phone model, average for surfing flow lifting values and renewal user's summation are sorted, the candidate that is defined as potential renewal user recommends of mobile phone model after changing planes at least partly after sequence is customized machine list.
6. based on a customization machine determining device for user behavior, it is characterized in that: comprise internet behavior analysis module, potential user's analysis module and customization machine analysis module, wherein,
Internet behavior analysis module, for obtaining user's internet behavior information table, comprise mobile phone model before changing planes, change planes before internet behavior and mobile phone model after changing planes;
Potential user's analysis module, for obtaining potential renewal user, described potential renewal user for its current phone use duration reached the user that same model mobile phone on average uses duration predetermined threshold value;
Customization machine analysis module, for according to described user's internet behavior information table, search the user that before changing planes, mobile phone model is identical with described potential renewal user current use mobile phone model, mobile phone model after meeting the changing planes of pre-conditioned user is defined as the customization machine into described potential renewal user recommends.
7. device according to claim 6, is characterized in that:
Described internet behavior analysis module, comprises extraction unit, computing unit and storage unit, wherein,
Extraction unit, for extracting the original internet records data of all users;
Computing unit, for calculate change planes before mobile phone use duration, surfing flow use value and surfing flow lifting values, wherein said change planes before mobile phone use duration to be that user changes mobile phone and the last mistiming changing mobile phone the last time; Described surfing flow use value comprises flow value, record number, online hours and application number; Described surfing flow lifting values deducts the difference of each several part numerical value corresponding to the surfing flow use value before changing planes by each several part numerical value of the surfing flow use value after changing planes, again with change planes before the corresponding part numerical value of surfing flow use value be divided by, finally business's addition calculation is drawn;
Storage unit, for the internet behavior information according to user described in preset duration record, described internet behavior information comprise change planes before mobile phone model, change planes before mobile phone use duration, mobile phone model, this time of changing planes after changing planes, change planes before surfing flow use value, change planes after surfing flow use value, change planes after surfing flow lifting values.
8. device according to claim 5, is characterized in that: described potential user's analysis module, also comprises,
Mobile phone on average uses duration analytic unit, on average uses duration for analyzing described same model mobile phone, is that mobile phone uses the mean value of duration to add up to draw before the replacing of same model mobile phone by mobile phone before changing in described user's internet behavior information table.
9. device according to claim 6, is characterized in that: described customization machine analysis module, comprises matching degree computing unit,
Described matching degree computing unit, for according to described user's internet behavior information table, search the surfing flow use value of the user that mobile phone model is identical with described potential renewal user current use mobile phone model before changing planes, calculate the matching degree of the surfing flow use value of itself and potential renewal user, by meet preset range matching degree corresponding to user, as meeting pre-conditioned user.
10. device according to claim 9, is characterized in that: described customization machine analysis module, also comprises candidate and customize machine analytic unit,
Described candidate customizes machine analytic unit, the screening that customization machine is carried out in machine list is customized for utilizing candidate, described candidate customizes machine list by having the user of mobile phone model after identical changing planes in the internet behavior information of searching described user, calculate its change planes after the average lifting values of surfing flow, calculate simultaneously described identical change planes after renewal user's summation of mobile phone model, average for surfing flow lifting values and renewal user's summation are sorted, the candidate that is defined as potential renewal user recommends of mobile phone model after changing planes at least partly after sequence is customized machine list.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510698175.9A CN105405026A (en) | 2015-10-23 | 2015-10-23 | Customized mobile phone determination method based on user behavior and apparatus thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510698175.9A CN105405026A (en) | 2015-10-23 | 2015-10-23 | Customized mobile phone determination method based on user behavior and apparatus thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105405026A true CN105405026A (en) | 2016-03-16 |
Family
ID=55470498
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510698175.9A Pending CN105405026A (en) | 2015-10-23 | 2015-10-23 | Customized mobile phone determination method based on user behavior and apparatus thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105405026A (en) |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108629609A (en) * | 2017-03-22 | 2018-10-09 | 中国移动通信集团河北有限公司 | The method and apparatus of reflexless terminal |
| CN110148057A (en) * | 2019-04-30 | 2019-08-20 | 德稻全球创新网络（北京）有限公司 | A kind of structural finance management system of enterprises |
| CN113316778A (en) * | 2019-06-24 | 2021-08-27 | 深圳市欢太科技有限公司 | Equipment recommendation method and related product |
| CN113841175A (en) * | 2019-07-05 | 2021-12-24 | 深圳市欢太科技有限公司 | Data analysis method and related product |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103944986A (en) * | 2014-04-18 | 2014-07-23 | 北京搜狗科技发展有限公司 | Method and device for integrating individual resources for users |
| CN103945430A (en) * | 2014-04-21 | 2014-07-23 | 中国联合网络通信集团有限公司 | Mobile terminal type recommending method and device |
-
2015
- 2015-10-23 CN CN201510698175.9A patent/CN105405026A/en active Pending
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103944986A (en) * | 2014-04-18 | 2014-07-23 | 北京搜狗科技发展有限公司 | Method and device for integrating individual resources for users |
| CN103945430A (en) * | 2014-04-21 | 2014-07-23 | 中国联合网络通信集团有限公司 | Mobile terminal type recommending method and device |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108629609A (en) * | 2017-03-22 | 2018-10-09 | 中国移动通信集团河北有限公司 | The method and apparatus of reflexless terminal |
| CN110148057A (en) * | 2019-04-30 | 2019-08-20 | 德稻全球创新网络（北京）有限公司 | A kind of structural finance management system of enterprises |
| CN110148057B (en) * | 2019-04-30 | 2021-09-14 | 德稻全球创新网络（北京）有限公司 | Enterprise internal structural financing management system |
| CN113316778A (en) * | 2019-06-24 | 2021-08-27 | 深圳市欢太科技有限公司 | Equipment recommendation method and related product |
| CN113841175A (en) * | 2019-07-05 | 2021-12-24 | 深圳市欢太科技有限公司 | Data analysis method and related product |
| CN113841175B (en) * | 2019-07-05 | 2024-07-02 | 深圳市欢太科技有限公司 | Data analysis method and related product |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107248082B (en) | Card maintenance identification method and device | |
| CN103164474B (en) | A kind of method that data service is analyzed | |
| CN103150696A (en) | Method and device for selecting potential customer of target value-added service | |
| CN109597974B (en) | Report generation method and device | |
| EP2546793A1 (en) | Method and apparatus for providing application list | |
| CN105405026A (en) | Customized mobile phone determination method based on user behavior and apparatus thereof | |
| CN105608592A (en) | Telecom user intelligent analyzing and pushing method and telecom user intelligent analyzing and pushing system | |
| CN107507016A (en) | A kind of information push method and system | |
| CN109345263A (en) | Predict the method and system of customer satisfaction | |
| CN104239338A (en) | Information recommendation method and information recommendation device | |
| AU2006236002A1 (en) | Identifying target customers for campaigns to increase average revenue per user | |
| Lee et al. | Forecasting mobile broadband traffic: Application of scenario analysis and Delphi method | |
| CN111666351A (en) | Fuzzy clustering system based on user behavior data | |
| CN109064265A (en) | Purchase vehicle recommended method and system based on the network platform | |
| CN103209422A (en) | Method for accurate spot selection of wireless local area network (WLAN) | |
| CN105975479A (en) | Tag library-based telecom user interest degree analysis method and system | |
| CN112149352A (en) | Prediction method for marketing activity clicking by combining GBDT automatic characteristic engineering | |
| CN111506755A (en) | Picture set classification method and device | |
| Choudhury et al. | Product attributes based on customer’s perception and their effect on customer satisfaction: the Kano analysis of mobile brands | |
| CN108154440A (en) | FoF assets industry analysis method, terminal and computer readable storage medium | |
| CN109858947B (en) | Retail user value analysis system and method | |
| CN106649323A (en) | Method and device for recommending keyword | |
| CN103617221A (en) | Software recommendation method and software recommendation system | |
| EP2621156B1 (en) | Subscriber portfolio management system | |
| US10565603B2 (en) | Segments of contacts |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20160316 |