CN108805614A - A kind of e-commerce system based on consumer budget analysis - Google Patents
A kind of e-commerce system based on consumer budget analysis Download PDFInfo
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- CN108805614A CN108805614A CN201810519932.5A CN201810519932A CN108805614A CN 108805614 A CN108805614 A CN 108805614A CN 201810519932 A CN201810519932 A CN 201810519932A CN 108805614 A CN108805614 A CN 108805614A
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- 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
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Abstract
The present invention relates to a kind of e-commerce systems based on consumer budget analysis,Including first information module,Second information module,Third information module,First acquisition module,First processing module,Second processing module,Third processing module,First acquisition module is for acquiring consumption information,First information module is for storing the single month propensity to consume and data,Second information module is for storing the commodity classification propensity to consume and data,Third information module is for storing the monthly propensity to consume and data,First processing module is used to generate the single month propensity to consume according to consumption information,Second processing module is used to generate the commodity classification propensity to consume according to consumption information,Third processing module is used to generate the monthly propensity to consume according to consumption information,E-commerce system further includes analysis module,Analysis module is used for according to the single month propensity to consume,The commodity classification propensity to consume and the monthly propensity to consume carry out commercial product recommending.
Description
Technical field
The present invention relates to e-commerce field more particularly to a kind of e-commerce systems based on consumer budget analysis.
Background technology
The electric business platform Taobao of largest domestic accesses user up to 60,000,000 daily, and daily online commodity number alreadys exceed
800,000,000.In face of burgeoning data scale, user is faced with " information overload problem ", if drawn without the help of search
Hold up, commending system or information classification etc. ancillary techniques, user found from the Internet resources of magnanimity oneself really it is interested
Information be a very difficult thing so that the effective rate of utilization of information reduces instead.Search engine and personalization push away
The system of recommending is to solve the problems, such as two kinds of means of " information overload ".Search engine feeds back to user according to keyword input by user and looks into
Ask as a result, due to search engine according to proprietary Behavior law return search result, can not be carried according to each user
For personalized service so that possible user really by the search result of magnanimity covered by interested content.Personalized recommendation exists
The deficiency of search engine is compensated in this problem, i.e., assesses its all product that do not seen instead of user, and by analyzing user
Hobby and historical behavior, actively recommend to meet the projects of user preferences.
Commending system under the big data epoch is met the training scale of the amount of bordering on the sea, the commending system under conventional individual environment
Cannot meet the needs of big data epoch recommendation.Therefore in a distributed manner computing platform as model computing platform commending system gradually
Secondary birth.Into after the Web2.0 epoch, the demand of real-time recommendation is more and more, and conventional recommendation systems, is all periodically to data
It is analyzed, then model is updated, and then personalized recommendation is carried out using new model, training effectiveness is low, simultaneously
Because imperfect mechanism cooperation makes feedback to active user, therefore there is recommend satisfaction and transaction conversion ratio low
Under problem.Therefore structure is based on new distribution type stream parallel processing technique, can analyze active user behavior and make reality
When recommend feedback system be to have very much research significance.
Invention content
Goal of the invention：
For conventional recommendation systems, all it is that periodically data are analyzed, then model is updated, and then uses new mould
Type carries out personalized recommendation, and training effectiveness is low, simultaneously as imperfect mechanism cooperation makes feedback to active user, because
This has that recommendation satisfaction and transaction conversion ratio are low, and the present invention provides a kind of electricity based on consumer budget analysis
Sub- business system.
Technical solution：
A kind of e-commerce system based on consumer budget analysis, including first information module, the second information module, third information
Module, the first acquisition module, first processing module, Second processing module, third processing module, the first acquisition module difference
Connect the first information module, the second information module, third information module, first processing module, Second processing module, third
Processing module, the first information module connect the first processing module, and second information module connects at described second
Module is managed, the third information module connects the third processing module, and first acquisition module has consumed letter for acquiring
Breath, the first information module is for storing the single month propensity to consume and data, and second information module is for storing commodity
Classify the propensity to consume and data, the third information module is for storing the monthly propensity to consume and data, at described first
Reason module is used to generate the single month propensity to consume according to consumption information, and the Second processing module is used to be given birth to according to consumption information
At the commodity classification propensity to consume, the third processing module is used to generate the monthly propensity to consume, the electricity according to consumption information
Sub- business system further includes analysis module, the analysis module respectively with the first information module, the second information module and
Third information module connects, and the analysis module is used for according to the single month propensity to consume, the commodity classification propensity to consume and monthly disappears
Take trend and carries out commercial product recommending.
Further include budget module as a kind of preferred embodiment of the present invention, the budget module connects the analysis module,
The analysis module is additionally operable to provide of that month consumer budget feedback to the budget module, and the budget module was consumed according to this month
Budget, which is fed back to the analysis module, provides available budget feedback.
As a kind of preferred embodiment of the present invention, the analysis module disappears according to single month propensity to consume, the commodity classification
Take trend and the monthly propensity to consume carries out budget trend analysis, the analysis module carries out budget mould according to budget trend analysis
Block master budget is fed back, and the budget module is according to master budget feedback adjustment master budget.
As a kind of preferred embodiment of the present invention, the analysis module is consumed according to the master budget after the adjustment
The adjustment of trend.
As the present invention a kind of preferred embodiment, further include the second acquisition module, second acquisition module with described point
Module connection is analysed, second acquisition module is used to analyze the single month propensity to consume according to the analysis module, commodity classification is consumed
The commercial product recommending that trend and the monthly propensity to consume obtain carries out the acquisition of commodity data.
As a kind of preferred embodiment of the present invention, second acquisition module is additionally operable to carry out commodity based on commodity keyword
Search acquisition, commercial articles searching acquisition and single month propensity to consume, commodity classification of the analysis module by second acquisition module
The propensity to consume and the comparison of the monthly propensity to consume, and according to the single month propensity to consume, the commodity classification propensity to consume and monthly consumption
Trend carries out the screening of the commodity of the second acquisition module acquisition.
As a kind of preferred embodiment of the present invention, the analysis module is additionally operable to the second acquisition module described in analysis of control
Commodity data acquires and the commodity of the analysis module screen.
As the present invention a kind of preferred embodiment, second acquisition module respectively with the first processing module, second
Processing module and the connection of third processing module, the first processing module, Second processing module and third processing module point
The commodity not acquired according to second acquisition module are carried out the single month propensity to consume, the commodity classification propensity to consume and are become with monthly consumption
Gesture preanalysis.
Further include data-pushing module as a kind of preferred embodiment of the present invention, described in the data-pushing module connection
Analysis module, the data-pushing module carry out data-pushing according to the analysis of control of the analysis module.
The present invention realizes following advantageous effect：
Using e-commerce system provided by the invention, periodically data are analyzed, then model is updated, and then are made
Personalized recommendation is carried out with new model, perfect mechanism cooperation is provided, feedback is made to active user, improve recommendation satisfaction
Degree and transaction conversion ratio.
Description of the drawings
The drawings herein are incorporated into the specification and forms part of this specification, and shows the implementation for meeting the disclosure
Example, and consistent with the instructions for explaining the principles of this disclosure.
Fig. 1 is system framework figure.
Specific implementation mode
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation describes, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.
Embodiment one：
Reference chart is Fig. 1.A kind of e-commerce system based on consumer budget analysis, including first information module 1, the second information
Module 2, third information module 3, the first acquisition module 4, first processing module 5, Second processing module 6, third processing module 7,
First acquisition module 4 is separately connected the first information module 1, the second information module 2, at third information module 3, first
Module 5, Second processing module 6, third processing module 7 are managed, the first information module 1 connects the first processing module 5, institute
It states the second information module 2 and connects the Second processing module 6, the third information module 3 connects the third processing module 7,
First acquisition module 4 for acquiring consumption information, the first information module 1 for store the single month propensity to consume and
Data, for storing the commodity classification propensity to consume and data, the third information module 3 is used for second information module 2
The monthly propensity to consume and data are stored, the first processing module 5 is used to generate the single month propensity to consume according to consumption information,
The Second processing module 6 is used to generate the commodity classification propensity to consume according to consumption information, and the third processing module 7 is used for
The monthly propensity to consume is generated according to consumption information, the e-commerce system further includes analysis module 8, the analysis module 8
It is connect respectively with the first information module 1, the second information module 2 and third information module 3, the analysis module 8 is used for
Commercial product recommending is carried out according to the single month propensity to consume, the commodity classification propensity to consume and the monthly propensity to consume.
Further include budget module 9, the budget module 9 connects the analysis mould as a kind of preferred embodiment of the present invention
Block 8, the analysis module 8 are additionally operable to provide of that month consumer budget feedback, 9 basis of the budget module to the budget module 9
Of that month consumer budget, which is fed back to the analysis module 8, provides available budget feedback.
As a kind of preferred embodiment of the present invention, the analysis module 8 disappears according to single month propensity to consume, the commodity classification
Take trend and the monthly propensity to consume carries out budget trend analysis, the analysis module 8 carries out budget according to budget trend analysis
9 master budget of module is fed back, and the budget module 9 is according to master budget feedback adjustment master budget.
As a kind of preferred embodiment of the present invention, the analysis module 8 disappears according to the master budget after the adjustment
Take the adjustment of trend.
In specific implementation process, the concrete condition of commodity when the first acquisition module 4 acquires previous consumption, including commodity close
Key word, commodity classification, goods amount etc..For the single month propensity to consume, first processing module 5 carried out the consumption of previous each moon
The calculating of the propensity to consume, and it is integrated into according to the previous trimestral propensity to consume average consumption trend of previous each moon, this is average
The propensity to consume and the single month propensity to consume.For the commodity classification propensity to consume, Second processing module 6 in previous 1 year for each
The commodity of classification are counted, and calculate the commodity classification propensity to consume.For the monthly propensity to consume, 7 basis of third processing module
On the basis of the consumption summation of previous each moon, the calculating of the monthly propensity to consume of each moon consumption summation is carried out.All trend calculate all
It is calculated using spending amount ratio.
Remaining budget carries out analysis module 8 in the single month propensity to consume and budget module 9 in module 1 according to the first information
When the judgement of secondary consumer budget, i.e.,：Of that month consumer budget is subtracted of that month spending amount and calculates of that month remain by analysis module 8
Remaining consumer budget, analysis module 8 calculates of that month spending amount and accounts for the ratio of of that month consumer budget, and determines the ratio in list
Position in month propensity to consume, and determine position of consumption next time in the single month propensity to consume, the consumption next time position on tendency chart
It sets i.e. user and extracts the ratio of the position, and pre- according to the ratio and of that month remaining consumption when time consumer budget proportional positions
Calculate the calculating for carrying out user's current consumption budget.Analysis module 8 obtains the keyword of current commodity, and obtains the second information module
The corresponding commodity classification propensity to consume of keyword in 2, analysis module 8 is according to the commodity classification propensity to consume in the second information module 2
And in budget module 9 remaining budget into the trade time consumer budget judgement, i.e.,：Analysis module 8 had consumed gold according to this month
Volume accounts for the position in the ratio-dependent commodity classification propensity to consume of of that month consumer budget, and determines consumption next time in this kind of commodity
Position in the commodity classification propensity to consume, on tendency chart next time consumption position, that is, user when time consumer budget proportional positions, carry
The ratio of the position is taken, and carries out the calculating of user's current consumption budget according to the ratio and of that month remaining consumer budget.Point
It is pre- into the trade time consumption according to remaining budget in the monthly propensity to consume in third information module 3 and budget module 9 to analyse module 8
The judgement of calculation, i.e.,：Analysis module 8 is accounted for according to of that month spending amount in the monthly propensity to consume of ratio-dependent of of that month consumer budget
Position, and determine position of consumption next time in the monthly propensity to consume, on tendency chart next time consumption position, that is, user when time
Consumer budget proportional positions extract the ratio of the position, and carry out user according to the ratio and of that month remaining consumer budget and work as
The calculating of preceding consumer budget.Analysis module 8 calculates the average value when time consumer budget, the consumer budget according to when time consumer budget
Average value be the secondary consumption consumer budget consequently recommended value.
When user determines when the commodity of secondary consumption, keyword, commodity of the first acquisition module 4 acquisition when time consumer lines
The information such as classification, goods amount, first processing module 5, Second processing module 6, third processing module 7 are according to the first acquisition module
The merchandise news of 4 acquisitions extracts corresponding information in first information module 1, the second information module 2, third information module 3 and carries out list
Month propensity to consume, the supplement of the commodity classification propensity to consume, the monthly propensity to consume.
For budget module 9, analysis module 8 is according to the single month propensity to consume, the commodity classification propensity to consume and monthly consumption
The trend for moving towards the consumer budget in previous 1 year of user of analysis of trend, and according to the trend of consumer budget to master budget into
The adjustment of row budget.
Embodiment two：
Reference chart is Fig. 1.For embodiment one, the difference of the present embodiment is：
Further include the second acquisition module 10 as a kind of preferred embodiment of the present invention, second acquisition module 10 with described point
It analyses module 8 to connect, second acquisition module 10 is used to analyze single month propensity to consume, commodity classification according to the analysis module 8
The commercial product recommending that the propensity to consume and the monthly propensity to consume obtain carries out the acquisition of commodity data.
As a kind of preferred embodiment of the present invention, second acquisition module 10 is additionally operable to based on commodity keyword into doing business
Product search acquisition, commercial articles searching acquisition and single month propensity to consume, commodity of the analysis module 8 by second acquisition module 10
The propensity to consume of classifying and the comparison of the monthly propensity to consume, and according to the single month propensity to consume, the commodity classification propensity to consume and monthly
The propensity to consume carries out the screening of the commodity of the second acquisition module 10 acquisition.
As a kind of preferred embodiment of the present invention, the analysis module 8 is additionally operable to the second acquisition module described in analysis of control
10 commodity data acquisition and the commodity of the analysis module 8 screen.
As a kind of preferred embodiment of the present invention, second acquisition module 10 respectively with the first processing module 5, the
Two processing modules 6 and third processing module 7 connect, the first processing module 5, Second processing module 6 and third processing
Module 7 respectively according to second acquisition module 10 acquire commodity carry out the single month propensity to consume, the commodity classification propensity to consume with
Monthly propensity to consume preanalysis.
Further include data-pushing module 11 as a kind of preferred embodiment of the present invention, the data-pushing module 11 connects
The analysis module 8, the data-pushing module 11 carry out data-pushing according to the analysis of control of the analysis module 8.
In specific implementation process, when analysis module 8 is calculated when secondary consumer budget, the second acquisition module 10 is according to working as
Secondary consumer budget and the corresponding commodity of current keyword carry out the acquisition of commodity, and analysis module 8 is according to the second acquisition module 10
The amount of money of the commodity of acquisition is with the single month propensity to consume, the commodity classification propensity to consume and the monthly propensity to consume for when time consumption
Budget is compared, if analysis module 8 judges the amount of money and single month propensity to consume, commodity of the commodity of the second acquisition module 10 acquisition
The comparing result of any one tendency chart is that deviation tendency chart is excessive in the propensity to consume of classifying and the monthly propensity to consume, then analyzes
Module 8 filters the commodity；If judging, the amount of money of the commodity of the second acquisition module 10 acquisition disappeared with single month propensity to consume, commodity classification
The tendency chart comparing result for taking trend and the monthly propensity to consume is that deviation tendency chart is little, then analysis module 8 chooses the commodity.
Analysis module 8 carries out the sequence of commodity according to the size of total departure, and analysis module 8 is synchronized to data according to the sequence of commodity and pushes away
Module 11, data-pushing module 11 is sent to carry out the push of commodity.
The above embodiments merely illustrate the technical concept and features of the present invention, and the purpose is to allow the skill for being familiar with the technical field
Art personnel can understand the content of the present invention and implement it accordingly, and can not be limited the scope of the invention with this.All bases
Equivalent changes or modifications made by spirit of the invention, should be covered by the protection scope of the present invention.
Claims (9)
1. a kind of e-commerce system based on consumer budget analysis, including first information module, the second information module, third letter
Cease module, the first acquisition module, first processing module, Second processing module, third processing module, first acquisition module point
The first information module, the second information module, third information module, first processing module, Second processing module, are not connected
Three processing modules, the first information module connect the first processing module, the second information module connection described second
Processing module, the third information module connect the third processing module, it is characterised in that：First acquisition module is used for
Consumption information, the first information module are used to store the single month propensity to consume and data, second information module for acquisition
For storing the commodity classification propensity to consume and data, the third information module is for storing the monthly propensity to consume and number
According to the first processing module is used to generate the single month propensity to consume according to consumption information, and the Second processing module is used for root
The commodity classification propensity to consume is generated according to consumption information, the third processing module is used to generate monthly disappear according to consumption information
Take trend, the e-commerce system further includes analysis module, the analysis module respectively with the first information module, second
Information module and the connection of third information module, the analysis module are used to be become according to the single month propensity to consume, commodity classification consumption
Gesture and the monthly propensity to consume carry out commercial product recommending.
2. a kind of e-commerce system based on consumer budget analysis according to claim 1, it is characterised in that：Further include
Budget module, the budget module connect the analysis module, and the analysis module is additionally operable to work as to budget module offer
The moon, consumer budget was fed back, and the budget module feeds back anti-to analysis module offer available budget according to of that month consumer budget
Feedback.
3. a kind of e-commerce system based on consumer budget analysis according to claim 2, it is characterised in that：Described point
It analyses module and budget trend analysis is carried out according to the single month propensity to consume, the commodity classification propensity to consume and the monthly propensity to consume,
The analysis module carries out budget module master budget feedback according to budget trend analysis, and the budget module is fed back according to master budget
Adjust master budget.
4. a kind of e-commerce system based on consumer budget analysis according to claim 3, it is characterised in that：Described point
Analyse the adjustment that module carries out the propensity to consume according to the master budget after the adjustment.
5. a kind of e-commerce system based on consumer budget analysis according to claim 4, it is characterised in that：Further include
Second acquisition module, second acquisition module are connect with the analysis module, and second acquisition module is used for according to
Analysis module analyzes commercial product recommending that the single month propensity to consume, the commodity classification propensity to consume and the monthly propensity to consume obtain into doing business
The acquisition of product data.
6. a kind of e-commerce system based on consumer budget analysis according to claim 5, it is characterised in that：Described
Two acquisition modules are additionally operable to carry out commercial articles searching acquisition based on commodity keyword, and the analysis module is by second acquisition module
Commercial articles searching acquisition compared with the single month propensity to consume, the commodity classification propensity to consume and the monthly propensity to consume, and according to Dan Yue
The propensity to consume, the commodity classification propensity to consume and the monthly propensity to consume carry out the screening of the commodity of the second acquisition module acquisition.
7. a kind of e-commerce system based on consumer budget analysis according to claim 6, it is characterised in that：Described point
Analysis module is additionally operable to the commodity data acquisition of the second acquisition module described in analysis of control and the commodity of the analysis module screen.
8. a kind of e-commerce system based on consumer budget analysis according to claim 7, it is characterised in that：Described
Two acquisition modules are connect with the first processing module, Second processing module and third processing module respectively, at described first
It manages module, Second processing module and third processing module and carries out Dan Yue according to the commodity of second acquisition module acquisition respectively
The propensity to consume, the commodity classification propensity to consume are with monthly propensity to consume preanalysis.
9. a kind of e-commerce system based on consumer budget analysis according to claims 1 to 8, it is characterised in that：Also
Including data-pushing module, the data-pushing module connects the analysis module, and the data-pushing module is according to described point
The analysis of control for analysing module carries out data-pushing.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007041971A (en) * | 2005-08-04 | 2007-02-15 | Albert:Kk | Recommendation system, recommendation method and recommendation program |
| CN103325052A (en) * | 2013-07-03 | 2013-09-25 | 姚明东 | Commodity recommendation method based on multidimensional user consumption propensity modeling |
| CN104463637A (en) * | 2014-12-23 | 2015-03-25 | 北京石油化工学院 | Commodity recommendation method and device based on electronic business platform and server |
| CN105631706A (en) * | 2015-12-22 | 2016-06-01 | 高旭磊 | Method and device for processing recommended information |
| CN106021379A (en) * | 2016-05-12 | 2016-10-12 | 深圳大学 | Personalized recommendation method and system based on user preference |
| CN107424030A (en) * | 2016-05-23 | 2017-12-01 | 富士施乐株式会社 | Products Show method and Products Show system |
-
2018
- 2018-05-28 CN CN201810519932.5A patent/CN108805614A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2007041971A (en) * | 2005-08-04 | 2007-02-15 | Albert:Kk | Recommendation system, recommendation method and recommendation program |
| CN103325052A (en) * | 2013-07-03 | 2013-09-25 | 姚明东 | Commodity recommendation method based on multidimensional user consumption propensity modeling |
| CN104463637A (en) * | 2014-12-23 | 2015-03-25 | 北京石油化工学院 | Commodity recommendation method and device based on electronic business platform and server |
| CN105631706A (en) * | 2015-12-22 | 2016-06-01 | 高旭磊 | Method and device for processing recommended information |
| CN106021379A (en) * | 2016-05-12 | 2016-10-12 | 深圳大学 | Personalized recommendation method and system based on user preference |
| CN107424030A (en) * | 2016-05-23 | 2017-12-01 | 富士施乐株式会社 | Products Show method and Products Show system |
Non-Patent Citations (1)
| Title |
|---|
| 王茜 等: "基于价格消费习惯的商品多样化推荐", 《***工程》 * |
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