CN109034983A - The recommended method and its system of online shopping mall's commodity - Google Patents
The recommended method and its system of online shopping mall's commodity Download PDFInfo
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- CN109034983A CN109034983A CN201811086630.XA CN201811086630A CN109034983A CN 109034983 A CN109034983 A CN 109034983A CN 201811086630 A CN201811086630 A CN 201811086630A CN 109034983 A CN109034983 A CN 109034983A
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- 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
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
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- 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
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0269—Targeted advertisements based on user profile or attribute
- G06Q30/0271—Personalized advertisement
Abstract
The invention discloses the recommended methods and its system of a kind of online shopping mall's commodity, its method specifically includes that then the consumption habit data of acquisition user and consumer record data establish database respectively, businessman's maintenance data analysis tool judges whether user has consumption wish, directly carries out advertisement pushing if having consumption wish；If not having wish, then other consumption wishes are excavated by recommending associated commodity to user or pushing Commdity advertisement to other users associated with the user, and database is updated and is extended in the process, it is ensured that the timeliness and accuracy of database.Its system includes that digital sampling and processing, customer data base establish module, consumption wish judgment module, consumption wish and excavate module and advertisement pushing module, cooperation between each module, avoid the limitation of existing advertisement pushing, the precision of advertisement pushing is enhanced, the recommendation of store commodity is more favorable for.
Description
Technical field
The present invention relates to data processing and advertisement pushing technical field, specially a kind of recommended method of online shopping mall's commodity
And its system.
Background technique
Shopping at network has become the preferred manner of consumer's shopping due to its convenience, and consumer can enjoy foot
The convenience that family commodity are visited is not gone out.But compared to traditional shopping way, how the Commdity advertisement of oneself to be pushed to and disappeared
Whether Fei Zhe is always a problem, because whether the user that businessman can not predict institute's advertisement needs the commodity, or has
Wish is consumed, once advertisement pushing link goes wrong, businessman will directly lose the consumer.So it is necessary to inventing one kind
Convenient for the scientific recommended method of online shopping mall's commodity, businessman is helped preferably to publicize its commodity.
The invention of the prior art such as Publication No. CN103345695A provides a kind of method and apparatus of commercial product recommending,
Middle method includes: to record user to the buying behavior data of commodity；When to user's Recommendations, judge that user is nearest
Commodity to be recommended whether were bought in setting period T1, if it is, not recommending the commodity to be recommended to user；Otherwise
Recommend the commodity to be recommended to user.Can be improved the accuracy of commercial product recommending through the invention, on the one hand avoid to
Family brings puzzlement to promote user experience, on the other hand also avoids to the temporary no longer interested commodity of user recommended user, from
And more effectively utilize Internet resources.But it is no wide well for the user for having bought commodity when carrying out advertisement pushing
Push mode is accused, and fails timely update database and the database for extending new user, leading to advertisement pushing, there are a foregone conclusions
It is sex-limited.
Summary of the invention
The purpose of the present invention is to provide the recommended methods and its system of a kind of online shopping mall's commodity, to solve above-mentioned background
The prior art proposed in technology does not have good advertisement pushing for the user for having bought commodity when carrying out advertisement pushing
Mode, and fail timely update database and the database for extending new user, leading to advertisement pushing, there are certain limitations
Problem.
To achieve the above object, the invention provides the following technical scheme:
A kind of recommended method of online shopping mall's commodity, method includes the following steps:
S1, the consumption habit data and consumer record data of user's end subscriber are acquired, and establish purchase note respectively
Record database and consumption preference database；
S2, the consumption wish that user is judged according to the purchaser record of user, if user is without consumption wish or consumption wish
It is not strong, then it carries out consumption wish and excavates；If user has consumption wish, direct advertisement；
S3, resurvey newest consumer spending habit data and consumer record data to the consumption preference database and
Purchaser record database is updated；
S4, the process for repeating S2 and S3, purchaser record database and consumption preference database to user are constantly updated simultaneously
Extend the purchaser record database and consumption preference database of new user.
Preferably, in the S1 to the consumption habit data of user and consumer record data be acquired include at least to
Family do shopping APP, user's wechat, user QQ and user's Alipay data acquisition modes in any one or a few.
Preferably, the consumption wish of user is judged in the S2 to go to judge user's based on the recent consumer record of user
Wish is consumed, if user has bought certain part commodity in the recent period, determines the user to this commodity or such commodity without consumption wish
Or consumption wish is not strong；If user does not buy this commodity or such commodity in the recent period, it is determined as that the user has consumption wish.
Preferably, the consumption wish of user is excavated to excavate the user quotient associated with purchased item in the S2
The purchase intention of product, or excavate the consumption wish of other users associated with the user.
The invention also discloses a kind of recommender systems of online shopping mall's commodity comprising:
Digital sampling and processing, for acquiring and handling the consumption habit data and consumer record data of user；User
Database module, the data for being acquired and being handled according to digital sampling and processing establish user's purchaser record number respectively
It is carried out in due course more according to library and consumption preference database, and to user's purchaser record database and consumption preference database
Newly comprising purchaser record Database Unit, consumption preference database unit and database updating unit；Consumption wish judges mould
Block, for judging whether user has consumption wish；It consumes wish and excavates module, for weak without consumption wish or consumption wish
User carry out consumption wish and excavate comprising association advertisement pushing unit and good friend's recommendation unit；And advertisement pushing module,
For carrying out advertisement pushing to the user for having consumption wish；
Wherein, the consumption habit data and consumer record data of digital sampling and processing acquisition and processing user, pass through
Customer data base establishes module and establishes user's purchaser record database and consumption preference database respectively, consumes wish judgment module
Judge whether user has consumption wish according to the purchaser record database of analysis user, it is direct if user has consumption wish
Advertisement pushing is carried out, wish is not consumed or consumption wish is weak, association advertisement is pushed to user or is pushed away to the association good friend of user
Advertisement is sent, or else data acquisition module breaks acquires user new consumption habit data and consumer record data or acquire new user's
Consumption habit data and consumer record data pass through the new database of database update unit more new database or enlarging.
Preferably, the digital sampling and processing include at least be integrated with user do shopping APP digital sampling and processing,
In user's wechat digital sampling and processing, user QQ digital sampling and processing and user's Alipay digital sampling and processing
Any one or a few.
Preferably, the consumption wish judgment module is the module for being integrated with data analysis and data processing software.
Preferably, it is server that the customer data base, which establishes module,.
Preferably, the digital sampling and processing, advertisement pushing module, association advertisement pushing unit and friend recommendation list
Member is all connected with user's end subscriber.
Compared with prior art, the beneficial effects of the present invention are: the recommended method of online shopping mall's commodity of the invention and its
System, the consumption hobby and consumer record data of acquisition user first are established database respectively, are then remembered according to the consumption of user
Record database judges the consumption wish of consumer, for there is the user of consumption wish directly to carry out advertisement pushing, for no consumption
The wish user weak with consumption wish can carry out the excavation of consumption wish；Additionally by database update unit timely replacement data
The database of library and the new user of enlarging, it is ensured that grasp the consumption habit variation of user in time and find new consumption user.This
Scheme is in user whether there is or not can carry out advertisement pushing in the case where consumption wish, and advertisement pushing precision is higher, and can be with
New user relevant to old user is found, the limitation of existing advertisement pushing is avoided, is more favorable for the recommendation of store commodity.
Detailed description of the invention
Fig. 1 is a kind of recommended method flow diagram of online shopping mall's commodity in the present invention；
Fig. 2 is a kind of recommender system structural schematic diagram of online shopping mall's commodity in the present invention.
Specific embodiment
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 description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on
Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other
Embodiment shall fall within the protection scope of the present invention.
As shown in Figure 1, for a kind of recommended method of online shopping mall's commodity of the present invention, method includes the following steps:
S1, the consumption habit data and consumer record data of user's end subscriber are acquired, and establish purchase note respectively
Record database and consumption preference database.
According to the consumption of user, the consumption habit data and consumer record data of user are comprehensively acquired as far as possible.
Such as the Taobao of user, only product meeting, spell the data acquisition of the shopping APP such as the more, the data acquisition of user's wechat, the number of user QQ
According to the acquisition of the data of acquisition and user's Alipay, user's bank card, the data acquisition of credit card purchase etc., and to collecting
Data be analyzed and processed, establish respectively purchaser record database and consumption preference database, buying according to actual needs
The record that user in nearest a period of time buys commodity is stored in database of record, in consumption preference database storage about with
The type of merchandise information that family is liked.
S2, the consumption wish that user is judged according to the purchaser record of user, if user is without consumption wish or consumption wish
It is not strong, then it carries out consumption wish and excavates；If user has consumption wish, direct advertisement.
For the user for needing advertisement, transfers the data that it is stored in purchaser record database and be compared
To judge whether the user has consumption wish.If the user does not buy this product or such product in the recent period, illustrate this
User is stronger for the purchase intention of this product or such product, can directly carry out the advertisement pushing of this product；If user is close
Phase has purchased this product or such product, illustrates that the user is not strong for the purchase intention of this product or such product, then
Need to excavate the consumption wish of the user.Customer consumption wish is excavated, on the one hand to excavate the user and purchased item phase
The purchase intention of associated commodity, still further aspect are to excavate the consumption wish of other users associated with the user.Example
If user has purchased pair of trainers, then commodity associated with sport footwear, such as movement socks, fortune can be promoted to the user
In addition dynamic suit, motion bracelet, sports earphones etc. can also be promoted directly to friend associated with the user, household and be used
The commodity that family was bought, or motivate user oneself to friends and family's Recommendations by way of recommending with lottery, it is dug convenient for businessman
Dig new user.
S3, resurvey newest consumer spending habit data and consumer record data to the consumption preference database and
Purchaser record database is updated.
With postponing for time, the consumption habit of user and consumption are liked being likely to occur some variations, so needing
Just the newest consumption information of user is acquired again every one end time, then it is comprehensive before data database is carried out more
Newly.
S4, the process for repeating S2 and S3, purchaser record database and consumption preference database to user are constantly updated simultaneously
Extend the purchaser record database and consumption preference database of new user.
Constantly repeat S2 and S3 in process, to matching user database be updated, while for user recommend or
The new user that other situations generate also uses same method to establish new database and accomplish and timely updates.
As shown in Fig. 2, for a kind of recommender system of online shopping mall's commodity of the present invention comprising:
Digital sampling and processing, for acquiring and handling the consumption habit data and consumer record data of user；User
Database module, the data for being acquired and being handled according to digital sampling and processing establish user's purchaser record number respectively
It is carried out in due course more according to library and consumption preference database, and to user's purchaser record database and consumption preference database
Newly comprising purchaser record Database Unit, consumption preference database unit and database updating unit；Consumption wish judges mould
Block, for judging whether user has consumption wish；It consumes wish and excavates module, for weak without consumption wish or consumption wish
User carry out consumption wish and excavate comprising association advertisement pushing unit and good friend's recommendation unit；And advertisement pushing module,
For carrying out advertisement pushing to the user for having consumption wish；
Wherein, the consumption habit data and consumer record data of digital sampling and processing acquisition and processing user, pass through
Customer data base establishes module and establishes user's purchaser record database and consumption preference database respectively, consumes wish judgment module
Judge whether user has consumption wish according to the purchaser record database of analysis user, it is direct if user has consumption wish
Advertisement pushing is carried out, wish is not consumed or consumption wish is weak, association advertisement is pushed to user or is pushed away to the association good friend of user
Advertisement is sent, or else data acquisition module breaks acquires user new consumption habit data and consumer record data or acquire new user's
Consumption habit data and consumer record data pass through the new database of database update unit more new database or enlarging.
Digital sampling and processing, for acquiring and handling the consumption habit data and consumer record data of user.Data
Acquisition processing module, which includes at least, is integrated with the various shopping APP digital sampling and processings of user, at user's wechat data acquisition
Any one or a few in module, user QQ digital sampling and processing and user's Alipay digital sampling and processing is managed,
Businessman can comprehensively acquire the related data of user as far as possible as needed, and be analyzed and processed to these data.
Customer data base establishes module, and the data for being acquired and being handled according to digital sampling and processing establish use respectively
Family purchaser record database and consumption preference database, and to user's purchaser record database and consumption preference database
Carry out timely replacement comprising purchaser record Database Unit, consumption preference database unit and database updating unit.User
Database module particularly for Data Analysis Services central server, when collected user related data is through excessive
After analysis processing, user's purchaser record database and consumption preference database are established respectively, is convenient for later period other module calls numbers
According to.In addition, database update unit is used to like user's purchaser record database and consumption after collecting new data
The amendment and update of database, it is ensured that the timeliness and accuracy of purchaser record database and consumption preference database.
Wish judgment module is consumed, for judging whether user has consumption wish.Specially be integrated with data analysis and
One standard and judgment of the module of data processing software, judgement is: the recent consumer record of comparison user goes to judge user
Consumption wish determine that the user anticipates to this commodity or such commodity without consumption if user has bought certain part commodity in the recent period
It is willing to or consumption wish is not strong；If user does not buy this commodity or such commodity in the recent period, it is determined as that the user has consumption wish.
In addition the consumption wish of user can also be judged according to other relatively scientific methods.
Consumption wish excavates module, for carrying out consumption wish excavation to without the weak user of consumption wish or consumption wish,
It includes association advertisement pushing unit and good friend's recommendation unit.Consuming wish and excavating module is actually also an advertisement pushing mould
Block specially excavates the purchase intention of user commodity associated with purchased item, and pushes the wide of associated commodity
It accuses, or excavates the consumption wish of other users associated with the user, and push Commdity advertisement to other users.
Advertisement pushing module, for user's progress advertisement pushing to being judged to having consumption wish.
It although an embodiment of the present invention has been shown and described, for the ordinary skill in the art, can be with
A variety of variations, modification, replacement can be carried out to these embodiments without departing from the principles and spirit of the present invention by understanding
And modification, the scope of the present invention is defined by the appended.
Claims (9)
1. a kind of recommended method of online shopping mall's commodity, which is characterized in that method includes the following steps:
S1, the consumption habit data and consumer record data of user's end subscriber are acquired, and establish purchaser record number respectively
According to library and consumption preference database；
S2, the consumption wish that user is judged according to the purchaser record of user, if user is not strong without consumption wish or consumption wish,
Consumption wish is then carried out to excavate；If user has consumption wish, direct advertisement；
S3, newest consumer spending habit data and consumer record data are resurveyed to the consumption preference database and purchase
Database of record is updated；
S4, the process for repeating S2 and S3, purchaser record database and consumption preference database to user are constantly updated and are extended
The purchaser record database and consumption preference database of new user.
2. a kind of recommended method of online shopping mall's commodity according to claim 1, which is characterized in that user in the S1
Consumption habit data and consumer record data be acquired to include at least and do shopping APP, user's wechat, user QQ and use to user
Any one or a few in the data acquisition modes of family Alipay.
3. a kind of recommended method of online shopping mall's commodity according to claim 1, which is characterized in that judge to use in the S2
The consumption wish at family is to go to judge the consumption wish of user based on the recent consumer record of user, if user has bought certain in the recent period
Part commodity then determine that the user is not strong without consumption wish or consumption wish to this commodity or such commodity；If user is in the recent period not
This commodity or such commodity are bought, then are determined as that the user has consumption wish.
4. a kind of recommended method of online shopping mall's commodity according to claim 1, which is characterized in that user in the S2
It consumes wish to excavate to excavate the purchase intention of user's commodity associated with purchased item, or excavates and the user
The consumption wish of associated other users.
5. a kind of recommender system of online shopping mall's commodity characterized by comprising
Digital sampling and processing, for acquiring and handling the consumption habit data and consumer record data of user；
Customer data base establishes module, and the data for being acquired and being handled according to digital sampling and processing establish user's purchase respectively
Database of record and consumption preference database are bought, and user's purchaser record database and consumption preference database are carried out
Timely replacement comprising purchaser record Database Unit, consumption preference database unit and database updating unit；
Wish judgment module is consumed, for judging whether user has consumption wish；
Consumption wish excavates module, for carrying out consumption wish excavation, packet to without the weak user of consumption wish or consumption wish
Include association advertisement pushing unit and good friend's recommendation unit；And
Advertisement pushing module, for carrying out advertisement pushing to the user for having consumption wish；
Wherein, the consumption habit data and consumer record data of the digital sampling and processing acquisition and processing user, pass through
The customer data base establishes module and establishes user's purchaser record database and consumption preference database, the consumption wish respectively
Judgment module judges whether user has consumption wish according to the purchaser record database of analysis user, if user has consumption to anticipate
It is willing to then directly carry out advertisement pushing, does not consume wish or consumption wish is weak is then associated with advertisement to user's push or to the pass of user
Join good friend's advertisement, the data acquisition module or else break the new consumption habit data and consumer record data of acquisition user or
The consumption habit data and consumer record data for acquiring new user pass through the database update unit more new database or enlarging
New database.
6. a kind of recommender system of online shopping mall's commodity according to claim 5, which is characterized in that at the data acquisition
Reason module, which includes at least, is integrated with user shopping APP digital sampling and processing, user's wechat digital sampling and processing, user
Any one or a few in QQ digital sampling and processing and user's Alipay digital sampling and processing.
7. a kind of recommender system of online shopping mall's commodity according to claim 5, which is characterized in that the consumption wish is sentenced
Disconnected module is to be integrated with the module of data analysis and data processing software.
8. a kind of recommender system of online shopping mall's commodity according to claim 5, which is characterized in that the customer data base
Establishing module is server.
9. a kind of recommender system of online shopping mall's commodity according to claim 5, which is characterized in that at the data acquisition
Reason module, advertisement pushing module, association advertisement pushing unit and good friend's recommendation unit are all connected with user's end subscriber.
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| Application Number | Priority Date | Filing Date | Title |
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| CN201811086630.XA CN109034983A (en) | 2018-09-18 | 2018-09-18 | The recommended method and its system of online shopping mall's commodity |
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| CN201811086630.XA CN109034983A (en) | 2018-09-18 | 2018-09-18 | The recommended method and its system of online shopping mall's commodity |
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| CN109872220A (en) * | 2019-01-24 | 2019-06-11 | 上海朝朝晤网络科技有限公司 | A kind of commercial product recommending list method for pushing and commercial product recommending list supplying system |
| CN111507486A (en) * | 2019-01-29 | 2020-08-07 | 买风格科技股份有限公司 | Environment-friendly intelligent circulation retail method and system for supplying and selling various life single products in series |
| CN112232888A (en) * | 2020-11-06 | 2021-01-15 | 深圳市护家科技有限公司 | Intelligent analysis system and method for consumer behaviors |
| CN112632149A (en) * | 2020-12-24 | 2021-04-09 | 深圳市高德信通信股份有限公司 | Potential user mining method based on network data analysis |
| CN112950304A (en) * | 2019-12-11 | 2021-06-11 | 北京沃东天骏信息技术有限公司 | Information pushing method, device, equipment and storage medium |
| CN113592523A (en) * | 2021-06-03 | 2021-11-02 | 山东大学 | Financial data processing system and method |
| CN114722278A (en) * | 2022-03-31 | 2022-07-08 | 北京金堤科技有限公司 | Method and device for pushing information, storage medium and electronic equipment |
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| CN109872220A (en) * | 2019-01-24 | 2019-06-11 | 上海朝朝晤网络科技有限公司 | A kind of commercial product recommending list method for pushing and commercial product recommending list supplying system |
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| CN114722278B (en) * | 2022-03-31 | 2024-03-08 | 北京金堤科技有限公司 | Information pushing method and device, storage medium and electronic equipment |
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Application publication date: 20181218 |