CN106709756A - User demand information acquisition method and apparatus thereof - Google Patents
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- CN106709756A CN106709756A CN201611122913.6A CN201611122913A CN106709756A CN 106709756 A CN106709756 A CN 106709756A CN 201611122913 A CN201611122913 A CN 201611122913A CN 106709756 A CN106709756 A CN 106709756A
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- G06Q30/02—Marketing; Price estimation or determination; Fundraising
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- G06Q30/0224—Discounts or incentives, e.g. coupons or rebates based on user history
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Abstract
The invention provides a user demand information acquisition method and an apparatus thereof. According to a historical record of webpage browsing of a user, an attention degree of all the subsets of at least one type of characteristics in a second-hand car is acquired. According to the attention degree of all the subsets of the at least one type of characteristics, user demand information is determined. The user browses webpage of one subset or some subsets containing one type of characteristics, which means that the user pays attention to the subset or the subsets of the type of characteristics. Based on an attention degree of the user to all the subsets of each characteristic, the user demand information is determined, which is reasonable. Therefore, accuracy of user demand information prediction is increased.
Description
Technical field
The present invention relates to computer technology, more particularly to a kind of user's request information acquisition method and device.
Background technology
Used car purchases the first-selection of car as many low-income groups because of the advantage of its low cost, and used car businessman is purchasing
Valency purchases used car, then is sold with the price higher than procurement price, so as to backspread, to obtain profit.
Due to the limitation of warehouse capacity and fund etc., in the prior art, used car businessman when used car is purchased, according to warp
The demand of user is tested and is predicted for the understanding of some vehicle car systems, so that, it is determined whether purchase certain used car.
However, using the method for prior art, the forecasting accuracy to user's request information is not high.
The content of the invention
The present invention provides a kind of user's request information acquisition method and device, to improve the standard to user's request information prediction
True property.
In a first aspect, the present invention provides a kind of user's request information acquisition method, including：
The historical record of webpage is browsed according to user, the concern of all subsets of an at least category feature of used car is obtained
Degree, wherein, multiple subsets are included per category feature；
The attention rate of all subsets according to an at least category feature, determines the demand information of user.
Alternatively, an at least category feature includes the combination of following classes or multiclass：
Brand；
Vehicle；
Price；
Mileage；
Car age.
Alternatively, the historical record of webpage is browsed according to user, all subsets of an at least category feature of used car are obtained
Attention rate, including：
The historical record of webpage is browsed according to user, the number of clicks of all subsets per category feature is obtained；
Obtain the number of clicks of the first subset and all subsets of the first subset generic number of clicks it is total
Ratio, determines the attention rate of the first subset；
Wherein, the first subset is any one subset in a category feature.
Alternatively, when an at least category feature is a category feature；
The attention rate of all subsets according to an at least category feature, determines the demand information of user, including：
Determine the N number of subset of attention rate highest, be the subset of user's request, wherein, N is the integer more than or equal to 1.
Alternatively, when at least a category feature is at least two class；
The attention rate of all subsets according to an at least category feature, determines the demand information of user, including：
Obtain the weight coefficient of the characteristic value of every kind of classification；
All subsets at least two classifications are combined, according to weight coefficient and the attention rate of each subset,
Calculate the attention rate of each combination；
Determine the M combination of attention rate highest, be the combination of user's request, M is the integer more than or equal to 1.
Alternatively, the method also includes：For every category feature, the attention rate of all subsets of graphic software platform.
Second aspect, the present invention provides a kind of user's request information acquisition device, including：
Acquisition module, the historical record for browsing webpage according to user obtains the institute of an at least category feature of used car
There is the attention rate of subset, wherein, multiple subsets are included per category feature；
Processing module, for the attention rate of all subsets according to an at least category feature, determines the demand information of user.
Alternatively, acquisition module obtains all per category feature specifically for browsing the historical record of webpage according to user
The number of clicks of subset；Obtain the number of clicks of the number of clicks of the first subset and all subsets of the first subset generic
The ratio of sum, determines the attention rate of the first subset；
Wherein, the first subset is any one subset in a category feature.
Alternatively, when an at least category feature is a category feature；
Processing module specifically for determine the N number of subset of attention rate highest, be the subset of user's request, wherein, N be more than
Integer equal to 1.
Alternatively, when at least a category feature is at least two class；
Weight coefficient of the processing module specifically for the characteristic value of the every kind of classification of acquisition；To all sons of at least two classifications
Collection is combined, and according to weight coefficient and the attention rate of each subset, calculates the attention rate of each combination；Determine attention rate
M combination of highest, is the combination of user's request, and M is the integer more than or equal to 1.
Alternatively, processing module is additionally operable to for every category feature, the attention rate of all subsets of graphic software platform.
User's request information acquisition method and device that the present invention is provided, are remembered by the history that webpage is browsed according to user
Record, obtains the attention rate of all subsets of an at least category feature of used car, the pass of all subsets according to an at least category feature
Note degree, determines the demand information of user, and user browses certain subset comprising certain category feature or a few webpages of subset, says
Bright user pays close attention to certain or some subset of this feature, based on user to the attention rate of all subsets of each feature, it is determined that with
The demand information at family, more rationally, so that, improve the accuracy to user's request information prediction.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
The accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments of invention, for those of ordinary skill in the art, without having to pay creative labor, may be used also
Other accompanying drawings are obtained with according to these accompanying drawings.
Fig. 1 is the schematic flow sheet of demand information acquisition methods embodiment one of the present invention；
Fig. 2 is the schematic flow sheet of demand information acquisition methods embodiment two of the present invention；
Fig. 3 is the schematic flow sheet of demand information acquisition methods embodiment three of the present invention；
Fig. 4 is the schematic diagram of the attention rate of brand of the present invention；
Fig. 5 is the structural representation of user's request information acquisition device embodiment of the present invention.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Site preparation is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.It is based on
Embodiment in the present invention, it is every other that those of ordinary skill in the art are obtained under the premise of creative work is not made
Embodiment, belongs to the scope of protection of the invention.
Term " first ", " second ", " the 3rd " " in description and claims of this specification and above-mentioned accompanying drawing
Four " etc. (if present) is for distinguishing similar object, without for describing specific order or precedence.Should manage
Solution so data for using can be exchanged in the appropriate case, so that embodiments of the invention described herein for example can be removing
Order beyond those for illustrating herein or describing is implemented.Additionally, term " comprising " and " having " and theirs is any
Deformation, it is intended that covering is non-exclusive to be included, for example, containing process, method, system, the product of series of steps or unit
Product or equipment are not necessarily limited to those steps clearly listed or unit, but may include not list clearly or for this
A little processes, method, product or other intrinsic steps of equipment or unit.
In Internet era, when user is generally intended to buy certain class product, for example：Purchase used car, it will usually by browsing
Webpage understands the information of the product to be bought, and the present invention exactly utilizes this feature, going through for webpage is browsed by according to user
The Records of the Historian is recorded, the attention rate of all subsets of each category feature of acquisition used car, the attention rate of all subsets according to each category feature,
Determine the demand information of user, user browses certain subset comprising certain category feature or a few webpages of subset, illustrate to use
Certain or some subset of this feature is paid close attention at family, based on user to the attention rate of all subsets of each feature, determines user's
Demand information, more rationally, so that, improve the accuracy to user's request information prediction.
In various embodiments of the present invention, can be by obtaining the historical record that user browses webpage, root from traffic log
According to the infoID of the model in webpage, RPC service is called, obtain the essential information of the subset of each category feature.
Technical scheme is described in detail with specifically embodiment below.These specific implementations below
Example can be combined with each other, and may be repeated no more in some embodiments for same or analogous concept or process.
Fig. 1 is the schematic flow sheet of demand information acquisition methods embodiment one of the present invention, as shown in figure 1, the present embodiment
Method is as follows：
S101：The historical record of webpage is browsed according to user, all subsets of an at least category feature of used car are obtained
Attention rate.
Wherein, multiple subsets are included per category feature.
Wherein, at least a category feature includes but is not limited to the combination of following one or more features：
Brand；Vehicle；Price；Mileage；Car age.
For example, the subset of brand includes：Buick, masses, BYD, Ford, modern times etc.；
The subset of vehicle includes：Compact car, micro- vehicle, compact vehicle, medium vehicle, senior vehicle, deluxe carmodel, three railway carriage or compartments
Vehicle etc.；
The subset of price includes：Less than 50000；50000-8 ten thousand；80000-10 ten thousand；100000-15 ten thousand；150000-20 ten thousand；200000-30
Ten thousand；300000 with first-class；
The subset of mileage includes：Less than 10000 kilometers；10000 kilometer -2 ten thousand kilometers；20000 kilometer -3 ten thousand kilometers；30000 kilometers with
It is first-class；
Car age：Less than 1 year；- 2 years 1 year；- 3 years 2 years；- 4 years 3 years；4 years with first-class；
Wherein, a kind of possible implementation of attention rate of all subsets of an at least category feature of used car is obtained such as
Under：
The historical record of webpage is browsed according to user, the number of clicks of all subsets per category feature is obtained；
Obtain the number of clicks of the first subset and all subsets of the first subset generic number of clicks it is total
Ratio, determines the attention rate of the first subset；
Wherein, the first subset is any one subset in a category feature.
May be comprising multiple subsets, then when user browses the webpage once, its all subset for including in each webpage
Number of clicks increase by 1 time；Based on this, the historical record of webpage can be browsed according to user, get the institute of every category feature
There is the number of clicks of subset
By taking brand as an example, the number of clicks of all kinds of subsets of brand is respectively：Buick 150, popular 100, BYD 200,
Ford 250, modern 200, other 100 times；
Then the attention rate of Buick is 150/1000, i.e.,：15%；Popular attention rate is 150/1000, i.e.,：15%；Than Asia
The attention rate of enlightening is 150/1000, i.e.,：15%；The attention rate of Ford is 250/1000, i.e.,：25%；Modern attention rate is
200/1000, i.e.,：20%；Other attention rates are 100/1000, i.e.,：10%.
The acquisition methods of the attention rate of the subset of other features are identical, no longer repeat one by one.
S102：The attention rate of all subsets according to an at least category feature, determines the demand information of user.
User is higher to the attention rate of certain subset, and user is stronger to the demand of the corresponding product of the subset.
The present embodiment, by browsing the historical record of webpage according to user, obtains the institute of an at least category feature of used car
There is the attention rate of subset, the attention rate of all subsets according to an at least category feature determines the demand information of user, and user browses
Certain subset comprising certain category feature or a few webpages of subset, illustrate user pay close attention to this feature certain or certain it is a little
Collection, based on user to the attention rate of all subsets of each feature, determines the demand information of user, more rationally, so that, it is right to improve
The accuracy of user's request information prediction.
Fig. 2 is the schematic flow sheet of demand information acquisition methods embodiment two of the present invention, and Fig. 2 is in embodiment illustrated in fig. 1
On the basis of, when only a category feature is, a kind of possible implementation of S102：
S102’：Determine the N number of subset of attention rate highest, be the subset of user's request.
Wherein, N is the integer more than or equal to 1.
By taking the brand in S101 as an example, the attention rate of Buick is 15%；Popular attention rate is 15%；The concern of BYD
Spend is 15%；The attention rate of Ford is 25%；Modern attention rate is 20%；Other attention rates are 10%.
Wherein, if N takes 1, the attention rate highest of Ford, it is determined that Ford is the brand of user's request；
If N takes 2, it is determined that Ford and modern times are the brand of user's request.
The present embodiment, by higher to the attention rate of certain subset according to user, user is to the corresponding product of the subset
The characteristics of demand, determine the N number of subset of attention rate highest, be the subset of user's request, acquired user's request information is more
It is rationally accurate.
Fig. 3 is the schematic flow sheet of demand information acquisition methods embodiment three of the present invention, and Fig. 3 is in embodiment illustrated in fig. 1
On the basis of, when used car includes the feature of more than two classes or this two class, a kind of possible implementation of S102：
S102a：Obtain the weight coefficient of the characteristic value of every kind of classification.
Wherein, weight coefficient is configured according to actual conditions, and the feature weight value that usual user more takes notice of is bigger.
For example：Assuming that the weight coefficient of brand is 0.6, the weight coefficient in car age is 0.4.
The method being similar to using S101, it less than 1 year is 20% to determine that the attention rate of vehicle is respectively；It is within -2 years 1 year 30%；
It is within -3 years 2 years 15%；It is within -4 years 3 years 10%；It is within more than 4 years 10%
S102b：All subsets at least two classifications are combined, according to weight coefficient and the pass of each subset
Note degree, calculates the attention rate of each combination.
As shown in table 1：
Table 1
| Less than 1 year | - 2 years 1 year | - 3 years 2 years | - 4 years 3 years | More than 4 years | |
| Buick | 0.17 | 0.21 | 0.15 | 0.13 | 0.13 |
| It is popular | 0.17 | 0.21 | 0.15 | 0.13 | 0.13 |
| BYD | 0.17 | 0.21 | 0.15 | 0.13 | 0.13 |
| Ford | 0.23 | 0.27 | 0.21 | 0.19 | 0.19 |
| It is modern | 0.2 | 0.24 | 0.18 | 0.16 | 0.16 |
| Other | 0.14 | 0.18 | 0.12 | 0.1 | 0.1 |
S102c：Determine the M combination of attention rate highest, be the combination of user's request.
From table 1 it follows that when M takes 1, the attention rate highest of Ford and the combination of -2 years 1 year；
When M takes 2, the modern attention rate highest with the combination of -2 years 1 year；
Others are similar, do not repeat one by one herein.
The present embodiment, different weighted values are distributed by different features, and multiple features are combined, and determine user
Demand information, more rationally, accuracy it is higher.
In the above-described embodiments, further, can also by the attention rate of all subsets of graphic software platform, specifically,
Can be by calling commercial product picture library table (Enterprise Charts, abbreviation：ECHARTS) graphical plug-in unit carries out figure
Change display, as shown in figure 4, by taking brand as an example, Fig. 4 is the schematic diagram of the attention rate of brand of the present invention.By figure, can be more
Intuitively know the attention rate of user.
The attention rate information of each subset of the various embodiments described above of the present invention, can store in database, just according to the date
Checked in user.
The various embodiments described above of the present invention, get after user's request information, and used car businessman can be according to user's request
Information reasonably chooses used car, it is to avoid the problems such as stock.
Fig. 5 is the structural representation of user's request information acquisition device embodiment of the present invention, and the device of the present embodiment includes：
Acquisition module 501 and processing module 502；
Wherein, acquisition module 501 is used to be browsed according to user the historical record of webpage, and at least class for obtaining used car is special
The attention rate of all subsets levied, wherein, multiple subsets are included per category feature；
Processing module 502 is used for the attention rate of all subsets according to an at least category feature, determines the demand information of user.
Further, acquisition module obtains the institute per category feature specifically for browsing the historical record of webpage according to user
There is the number of clicks of subset；Obtain the number of clicks of the number of clicks of the first subset and all subsets of the first subset generic
Total ratio, determine the attention rate of the first subset；
Wherein, the first subset is any one subset in a category feature.
The corresponding technical scheme that can be used to perform embodiment of the method shown in Fig. 1 of the device of the present embodiment, its realization principle
Similar with technique effect, here is omitted.
In the above-described embodiments, when an at least category feature is a category feature；
Processing module 502, specifically for determining the N number of subset of attention rate highest, is the subset of user's request, wherein, N is
Integer more than or equal to 1.
The corresponding technical scheme that can be used to perform embodiment of the method shown in Fig. 2 of the device of the present embodiment, its realization principle
Similar with technique effect, here is omitted.
In the above-described embodiments, when at least a category feature is at least two class；
Weight coefficient of the processing module 502 specifically for the characteristic value of the every kind of classification of acquisition；To the institute of at least two classifications
There is subset to be combined, according to weight coefficient and the attention rate of each subset, calculate the attention rate of each combination；It is determined that closing
The M combination of note degree highest, is the combination of user's request.
The corresponding technical scheme that can be used to perform embodiment of the method shown in Fig. 2 of the device of the present embodiment, its realization principle
Similar with technique effect, here is omitted.
In the above-described embodiments, processing module 502 is additionally operable to for every category feature, the concern of all subsets of graphic software platform
Degree.
The present embodiment, by processing the attention rate by all subsets with graphic software platform, can more intuitively know use
The attention rate at family.
One of ordinary skill in the art will appreciate that：Realizing all or part of step of above-mentioned each method embodiment can lead to
The related hardware of programmed instruction is crossed to complete.Foregoing program can be stored in a computer read/write memory medium.The journey
Sequence upon execution, performs the step of including above-mentioned each method embodiment；And foregoing storage medium includes：ROM, RAM, magnetic disc or
Person's CD etc. is various can be with the medium of store program codes.
Finally it should be noted that：Various embodiments above is merely illustrative of the technical solution of the present invention, rather than its limitations；To the greatest extent
Pipe has been described in detail with reference to foregoing embodiments to the present invention, it will be understood by those within the art that：Its according to
The technical scheme described in foregoing embodiments can so be modified, or which part or all technical characteristic are entered
Row equivalent；And these modifications or replacement, the essence of appropriate technical solution is departed from various embodiments of the present invention technology
The scope of scheme.
Claims (11)
1. a kind of user's request information acquisition method, it is characterised in that including：
The historical record of webpage is browsed according to user, the attention rate of all subsets of an at least category feature of used car is obtained, its
In, multiple subsets are included per category feature；
The attention rate of all subsets according to an at least category feature, determines the demand information of the user.
2. method according to claim 1, it is characterised in that an at least category feature includes following classes or multiclass
Combination：
Brand；
Vehicle；
Price；
Mileage；
Car age.
3. method according to claim 2, it is characterised in that the historical record that webpage is browsed according to user, obtains
The attention rate of all subsets of an at least category feature of used car, including：
The historical record of webpage is browsed according to user, the number of clicks of all subsets per category feature is obtained；
The number of clicks for obtaining the first subset is total with the number of clicks of all subsets of the first subset generic
Ratio, determines the attention rate of first subset；
Wherein, first subset is any one subset in a category feature.
4. method according to claim 3, it is characterised in that when an at least category feature is a category feature；
The attention rate of all subsets of an at least category feature described in the basis, determines the demand information of the user, including：
Determine the N number of subset of attention rate highest, be the subset of user's request, wherein, the N is the integer more than or equal to 1.
5. method according to claim 3, it is characterised in that when it is described at least a category feature is at least two class when；
The attention rate of all subsets of an at least category feature described in the basis, determines the demand information of the user, including：
Obtain the weight coefficient of the characteristic value of every kind of classification；
All subsets at least two classification are combined, according to the concern of the weight coefficient and each subset
Degree, calculates the attention rate of each combination；
Determine the attention rate highest M combination for being combined as user's request, the M is the integer more than or equal to 1.
6. the method according to claim any one of 1-5, it is characterised in that also include：It is graphical aobvious for every category feature
Show the attention rate of all subsets.
7. a kind of user's request information acquisition device, it is characterised in that including：
Acquisition module, the historical record for browsing webpage according to user obtains all sons of an at least category feature of used car
The attention rate of collection, wherein, multiple subsets are included per category feature；
Processing module, for the attention rate of all subsets of an at least category feature according to, determines the demand letter of the user
Breath.
8. device according to claim 7, it is characterised in that the acquisition module according to user specifically for browsing webpage
Historical record, obtain per category feature all subsets number of clicks；Obtain the number of clicks and described first of the first subset
The total ratio of the number of clicks of all subsets of subset generic, determines the attention rate of first subset；
Wherein, first subset is any one subset in a category feature.
9. device according to claim 8, it is characterised in that when an at least category feature is a category feature；
The processing module, specifically for determining the N number of subset of attention rate highest, is the subset of user's request, wherein, the N is
Integer more than or equal to 1.
10. device according to claim 8, it is characterised in that when it is described at least a category feature is at least two class when；
Weight coefficient of the processing module specifically for the characteristic value of the every kind of classification of acquisition；To the institute of at least two classification
There is subset to be combined, according to the weight coefficient and the attention rate of each subset, calculate the attention rate of each combination；Really
Determine the attention rate highest M combination for being combined as user's request, the M is the integer more than or equal to 1.
11. device according to claim any one of 7-10, it is characterised in that the processing module is additionally operable to for per class
Feature, the attention rate of all subsets of graphic software platform.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108198037A (en) * | 2018-01-12 | 2018-06-22 | 金瓜子科技发展（北京）有限公司 | Account management method and device |
| CN108460651A (en) * | 2018-01-04 | 2018-08-28 | 金瓜子科技发展（北京）有限公司 | Vehicle recommends method and device |
| CN108932644A (en) * | 2017-05-26 | 2018-12-04 | 车伯乐（北京）信息科技有限公司 | A kind of user selects vehicle method, apparatus, equipment and computer-readable medium |
| CN110517064A (en) * | 2017-11-16 | 2019-11-29 | 北京新意互动数字技术有限公司 | A kind of competing product model analysis method and system of core |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103106259A (en) * | 2013-01-25 | 2013-05-15 | 西北工业大学 | Mobile webpage content recommending method based on situation |
| CN103235824A (en) * | 2013-05-06 | 2013-08-07 | 上海河广信息科技有限公司 | Method and system for determining web page texts users interested in according to browsed web pages |
| US20140057974A1 (en) * | 1998-04-15 | 2014-02-27 | The Regents Of The University Of California | Methods for therapy of neurodegenerative disease of the brain |
| CN105260913A (en) * | 2015-10-16 | 2016-01-20 | 上海晶赞科技发展有限公司 | CTR estimation method and system, and DSP server used for Internet advertisement putting |
| CN105426536A (en) * | 2015-12-21 | 2016-03-23 | 北京奇虎科技有限公司 | Presentation method and device for automobile category search result page |
| CN105430073A (en) * | 2015-11-12 | 2016-03-23 | 北京易车互联信息技术有限公司 | Message pushing method and system based on user behaviors |
| CN105930507A (en) * | 2016-05-10 | 2016-09-07 | 腾讯科技（深圳）有限公司 | Method and apparatus for obtaining Web browsing interest of user |
| CN105956161A (en) * | 2016-05-17 | 2016-09-21 | 北京奇虎科技有限公司 | Information recommendation method and apparatus |
-
2016
- 2016-12-08 CN CN201611122913.6A patent/CN106709756A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20140057974A1 (en) * | 1998-04-15 | 2014-02-27 | The Regents Of The University Of California | Methods for therapy of neurodegenerative disease of the brain |
| CN103106259A (en) * | 2013-01-25 | 2013-05-15 | 西北工业大学 | Mobile webpage content recommending method based on situation |
| CN103235824A (en) * | 2013-05-06 | 2013-08-07 | 上海河广信息科技有限公司 | Method and system for determining web page texts users interested in according to browsed web pages |
| CN105260913A (en) * | 2015-10-16 | 2016-01-20 | 上海晶赞科技发展有限公司 | CTR estimation method and system, and DSP server used for Internet advertisement putting |
| CN105430073A (en) * | 2015-11-12 | 2016-03-23 | 北京易车互联信息技术有限公司 | Message pushing method and system based on user behaviors |
| CN105426536A (en) * | 2015-12-21 | 2016-03-23 | 北京奇虎科技有限公司 | Presentation method and device for automobile category search result page |
| CN105930507A (en) * | 2016-05-10 | 2016-09-07 | 腾讯科技（深圳）有限公司 | Method and apparatus for obtaining Web browsing interest of user |
| CN105956161A (en) * | 2016-05-17 | 2016-09-21 | 北京奇虎科技有限公司 | Information recommendation method and apparatus |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108932644A (en) * | 2017-05-26 | 2018-12-04 | 车伯乐（北京）信息科技有限公司 | A kind of user selects vehicle method, apparatus, equipment and computer-readable medium |
| CN110517064A (en) * | 2017-11-16 | 2019-11-29 | 北京新意互动数字技术有限公司 | A kind of competing product model analysis method and system of core |
| CN108460651A (en) * | 2018-01-04 | 2018-08-28 | 金瓜子科技发展（北京）有限公司 | Vehicle recommends method and device |
| CN108198037A (en) * | 2018-01-12 | 2018-06-22 | 金瓜子科技发展（北京）有限公司 | Account management method and device |
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