CN105931066A - Transaction data processing method and device - Google Patents

Transaction data processing method and device Download PDF

Info

Publication number
CN105931066A
CN105931066A CN201510617766.9A CN201510617766A CN105931066A CN 105931066 A CN105931066 A CN 105931066A CN 201510617766 A CN201510617766 A CN 201510617766A CN 105931066 A CN105931066 A CN 105931066A
Authority
CN
China
Prior art keywords
user
described user
tradable commodity
commodity type
database node
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN201510617766.9A
Other languages
Chinese (zh)
Inventor
王文柏
冯哲
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
China Unionpay Co Ltd
Original Assignee
China Unionpay Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by China Unionpay Co Ltd filed Critical China Unionpay Co Ltd
Priority to CN201510617766.9A priority Critical patent/CN105931066A/en
Publication of CN105931066A publication Critical patent/CN105931066A/en
Priority to PCT/CN2016/099224 priority patent/WO2017050188A1/en
Pending legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Accounting & Taxation (AREA)
  • Development Economics (AREA)
  • Strategic Management (AREA)
  • Finance (AREA)
  • Game Theory and Decision Science (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Economics (AREA)
  • Marketing (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The invention discloses a transaction data processing method and device. The method includes that the history transaction information including transaction sum and transaction goods types of a user is acquired; the transaction sum average value of the user is determined based on the transaction sum, the weight transaction sum average value of the user is determined based on the transaction sum average value of the user and the transaction goods types, and the consumption level of the user is determined based on the weight transaction sum average value; the characteristic transaction goods type of the user is determined from the transaction goods types of the user, the characteristic transaction goods type is determined based on the condition that the transaction times of the transaction goods type is greater than the threshold value corresponding to the transaction goods type, and the transaction goods type is the preset transaction goods type in the consumption stage; the consumption stage of the user is determined based on the characteristic transaction goods type of the user; and the goods information matched with the user is determined based on the consumption level and the consumption stage of the user.

Description

A kind of transaction data processing method and device
Technical field
The present invention relates to technical field of data processing, particularly relate to a kind of transaction data processing method and dress thereof Put.
Background technology
Along with the safety of network payment business is more and more higher, increasing consuming behavior is complete by network Become.Some electricity business's platforms are just according to web search and the consuming behavior consumer foundation consumption row of consumer For model, and push corresponding merchandise news for consumer.
But, due to the limitation of network environment, some commodity consumption person can't buy in a network, example As, automobile, meanwhile, the consumption account of consumer can be used by many individuals simultaneously.Therefore, based on consumption The consuming behavior model that person's consumption row in a network is set up is the real consumption that can not embody consumer Behavior.
Therefore, according to consumer in a network consumption row set up consumption model go push merchandise news effect Fruit is not fine.
Summary of the invention
The embodiment of the present invention provides a kind of transaction data processing method and device thereof, sets up accurately in order to realizing Consuming behavior model.
The embodiment of the present invention provides a kind of transaction data processing method, including:
Obtaining the historical transactional information of user, described historical transactional information includes dealing money, trader's category Type；
The dealing money meansigma methods of described user is determined according to described dealing money, and according to the friendship of described user Easily amount of money meansigma methods and tradable commodity type determine the weighting dealing money meansigma methods of described user, and according to Described weighting dealing money meansigma methods determines the consumption grade of described user；
The feature tradable commodity type of described user, described spy is determined from the tradable commodity type of described user Levying tradable commodity type is that transaction count corresponding to this tradable commodity type is corresponding more than this tradable commodity type Threshold value and this tradable commodity type belong in consumer phase preset tradable commodity type；
Feature tradable commodity type according to described user determines the consumer phase residing for described user；
Consumer phase residing for consumption grade according to described user and described user, determines and described user's phase The merchandise news of coupling.
Preferably, the described historical transactional information obtaining user, including:
The database node of the historical transactional information storing described user is determined in distributed memory system；
Status indicator according to database node determines the number of the historical transactional information of the described user of described storage According to the database node being in active state in the node of storehouse；
The historical transactional information of described user is obtained by the described database node being in active state.
Preferably, the status indicator of database node is determined in the following manner:
Detection messages is sent, if not receiving described database node in preset time period to database node Response message, it is determined that described database node is in failure state, and by the shape of described database node State mark is defined as failure state, otherwise the status indicator of described database node is defined as active state.
Preferably, after the described status indicator by described database node is defined as failure state, also include:
Determine and in the described database node being in failure state, the data of storage are identical and be in and enliven shape The database node of state；
To in the described and described database node being in failure state, the data of storage are identical and are in active The data backup stored in the database node of state is in the database node of active state to other.
Preferably, the described dealing money meansigma methods determining described user according to described dealing money, and according to The dealing money meansigma methods of described user and tradable commodity type determine the weighting dealing money of described user Meansigma methods, and the consumption grade of described user is determined according to described weighting dealing money meansigma methods, including:
The weighting dealing money meansigma methods of user is determined according to below equation:
M = Σ e = 1 N C e × D / N
Wherein, M represents the weighting dealing money meansigma methods of user, and D represents the dealing money meansigma methods of user, CeRepresenting the weighted value of the tradable commodity type concluded the business the e time, e is more than or equal to 1 and less than or equal to N, N Represent transaction count；
Grade corresponding for the weighting dealing money meansigma methods of described user is determined the consumption grade of described user.
Preferably, the consumer phase residing for the described consumption grade according to described user and described user, determine The merchandise news matched with described user, including:
Determine other users consistent with the consumption grade of described user；
Determine the tradable commodity type in the historical transactional information of other users described；
In tradable commodity type in the historical transactional information of other users described, determine and described user institute The tradable commodity type that the consumer phase at place matches, and will match with the consumer phase residing for described user Tradable commodity information corresponding to tradable commodity type be defined as the merchandise news that matches with described user.
Preferably, the consumer phase residing for the described consumption grade according to described user and described user, determine The merchandise news matched with described user, including:
Obtain businessman's attribute information and the historical transactional information of businessman of businessman, in described businessman attribute information Including tradable commodity type, the historical transactional information of described businessman includes dealing money；
By the business that the dealing money meansigma methods of businessman is in same scope and the tradable commodity type of businessman is identical Family is divided into businessman's cluster；
The consumption grade of the dealing money meansigma methods of businessman Yu described user is matched and the trader of businessman Category type belongs to businessman's cluster of the consumer phase residing for described user, is defined as matching with described user Businessman clusters；
The businessman described and described user matched clusters corresponding merchandise news and is defined as and described user The merchandise news matched.
Preferably, the method also includes:
Obtain the real-time deal information of user；
In the tradable commodity type that the merchandise news that matches described user is corresponding, determine and described real-time friendship The tradable commodity type of easy tradable commodity type matching, and by the trader's category with described real-time deal Tradable commodity information pushing corresponding to tradable commodity type that type matches gives described user.
The embodiment of the present invention provides a kind of transaction data processing means, and this device includes:
Acquiring unit, for obtaining the historical transactional information of user, described historical transactional information includes trade gold Volume, tradable commodity type；
Determine unit, for determining the dealing money meansigma methods of described user according to described dealing money, and root The weighting trade gold of described user is determined according to the dealing money meansigma methods of described user and tradable commodity type Volume meansigma methods, and the consumption grade of described user is determined according to described weighting dealing money meansigma methods；From described The tradable commodity type of user determines the feature tradable commodity type of described user, described feature tradable commodity Type is threshold value that transaction count corresponding to this tradable commodity type is corresponding more than this tradable commodity type and should Tradable commodity type belongs to the tradable commodity type preset in consumer phase；Feature transaction according to described user The type of merchandise determines the consumer phase residing for described user；
Matching unit, for the consumer phase residing for the consumption grade according to described user and described user, really The fixed merchandise news matched with described user.
Preferably, described acquiring unit specifically for:
The database node of the historical transactional information storing described user is determined in distributed memory system；
Status indicator according to database node determines the number of the historical transactional information of the described user of described storage According to the database node being in active state in the node of storehouse；
The historical transactional information of described user is obtained by the described database node being in active state.
Preferably, this device also includes that detector unit, described detector unit determine data base in the following manner The status indicator of node:
Detection messages is sent, if not receiving described database node in preset time period to database node Response message, it is determined that described database node is in failure state, and by the shape of described database node State mark is defined as failure state, otherwise the status indicator of described database node is defined as active state.
Preferably, this device also includes that backup units, described backup units are used for:
Determine and in the described database node being in failure state, the data of storage are identical and be in and enliven shape The database node of state；
To in the described and described database node being in failure state, the data of storage are identical and are in active The data backup stored in the database node of state is in the database node of active state to other.
Preferably, described determine unit specifically for:
The weighting dealing money meansigma methods of user is determined according to below equation:
M = Σ e = 1 N C e × D / N
Wherein, M represents the weighting dealing money meansigma methods of user, and D represents the dealing money meansigma methods of user, CeRepresenting the weighted value of the tradable commodity type concluded the business the e time, e is more than or equal to 1 and less than or equal to N, N Represent transaction count；
Grade corresponding for the weighting dealing money meansigma methods of described user is determined the consumption grade of described user.
Preferably, described matching unit specifically for:
Determine other users consistent with the consumption grade of described user；
Determine the tradable commodity type in the historical transactional information of other users described；
In tradable commodity type in the historical transactional information of other users described, determine and described user institute The tradable commodity type that the consumer phase at place matches, and will match with the consumer phase residing for described user Tradable commodity information corresponding to tradable commodity type be defined as the merchandise news that matches with described user.
Preferably, described matching unit specifically for:
Obtain businessman's attribute information and the historical transactional information of businessman of businessman, in described businessman attribute information Including tradable commodity type, the historical transactional information of described businessman includes dealing money；
By the business that the dealing money meansigma methods of businessman is in same scope and the tradable commodity type of businessman is identical Family is divided into businessman's cluster；
The consumption grade of the dealing money meansigma methods of businessman Yu described user is matched and the trader of businessman Category type belongs to businessman's cluster of the consumer phase residing for described user, is defined as matching with described user Businessman clusters；
The businessman described and described user matched clusters corresponding merchandise news and is defined as and described user The merchandise news matched.
Preferably, this device also includes push unit；Described push unit specifically for:
Obtain the real-time deal information of user；
In the tradable commodity type that the merchandise news that matches described user is corresponding, determine and described real-time friendship The tradable commodity type of easy tradable commodity type matching, and by the trader's category with described real-time deal Tradable commodity information pushing corresponding to tradable commodity type that type matches gives described user.
The embodiment of the present invention has the advantages that
In the embodiment of the present invention, it it is the dealing money meansigma methods that determines user of the off-line transaction record by user And tradable commodity type, so that it is determined that the consumption grade of user and consumer phase, finally determine user's Consuming behavior model.More can reflect the real behavior of consumer due to off-line transaction record, therefore obtain disappears Take behavior model more accurate.
Accompanying drawing explanation
For the technical scheme being illustrated more clearly that in the embodiment of the present invention, institute in embodiment being described below The accompanying drawing used is needed to briefly introduce, it should be apparent that, the accompanying drawing in describing below is only the present invention's Some embodiments, from the point of view of those of ordinary skill in the art, in the premise not paying creative work Under, it is also possible to other accompanying drawing is obtained according to these accompanying drawings.
A kind of transaction data processing method schematic flow sheet that Fig. 1 provides for the embodiment of the present invention；
A kind of transaction data processing means structural representation that Fig. 2 provides for the embodiment of the present invention.
Detailed description of the invention
In order to make the object, technical solutions and advantages of the present invention clearer, below in conjunction with accompanying drawing to this Bright it is described in further detail, it is clear that described embodiment is only some embodiments of the present invention, Rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art are not doing Go out all other embodiments obtained under creative work premise, broadly fall into the scope of protection of the invention.
As it is shown in figure 1, a kind of transaction data processing method schematic flow sheet that the embodiment of the present invention provides, should Method includes:
Step 101: obtain user historical transactional information, described historical transactional information include dealing money, Tradable commodity type；
Step 102: determine the dealing money meansigma methods of described user according to described dealing money, and according to institute Dealing money meansigma methods and the tradable commodity type of stating user determine that the weighting dealing money of described user is put down Average, and the consumption grade of described user is determined according to described weighting dealing money meansigma methods；
Step 103: determine feature trader's category of described user from the tradable commodity type of described user Type, described feature tradable commodity type is that transaction count corresponding to this tradable commodity type is more than this tradable commodity Threshold value and this tradable commodity type that type is corresponding belong to the tradable commodity type preset in consumer phase；
Step 104: determine the consumption rank residing for described user according to the feature tradable commodity type of described user Section；
Step 105: according to the consumer phase residing for the consumption grade of described user and described user, determine with The merchandise news that described user matches.
In step 101, the tradable commodity type in historical transactional information is specifically as follows food and drink, dress ornament, family Electricity, consumer electronics etc., indicate the type of the commodity of transaction, or indicate type of transaction.
In the embodiment of the present invention, the historical transactional information of user can be stored in distributed memory system.Point Cloth storage system, is data dispersion to be stored on the database node of many platform independent.Traditional network is deposited Storage system uses the database node concentrated to deposit all data, and distributed network storage system uses expansible System structure, utilize multiple stage database node to share storage load, it not only increase system reliability, Availability and access efficiency, be also easy to extension.
In the embodiment of the present invention, distributed data-storage system has the following characteristics that
Data have the redundancy of more than 2 parts, can be configured to many points of redundancies；
When database node lost efficacy, the database node of failure state can be in automatism isolation；
When database node actual effect, can with automated back-up be in failure state database node data extremely Other active database nodes；
Database node can be increased with dynamic realtime；
Database node can be reduced with dynamic realtime.
In order to quickly indicate the status indicator of database node, in the embodiment of the present invention, to described The database node being in failure state is marked, and determines and the described data base's joint being in failure state In point, the data of storage are identical and are in the database node of active state；It is in inefficacy to described and described In the database node of state, the data of storage are identical and are in storage in the database node of active state Data backup is in the database node of active state to other.
In sum, in the embodiment of the present invention, database node mainly comprises two class key messages: position is believed Breath and status indicator.Positional information can by IP (between network interconnection agreement, Internet Protocol) Location and port (port) number are constituted, and indicate position when accessing this database node.Status indicator represents Going out database node is active state or failure state.
For example, when needs read data, it is determined that the IP address of database node and port numbers are just May determine that the position of database node, and from the database node determined, read data.
When obtaining the historical transactional information of user, need first to determine the status indicator of database node, and lead to Cross the database node that status indicator in distributed memory system is active state and obtain the historical trading of user Information.Concrete, distributed memory system determines the data of the historical transactional information storing described user Storehouse node；Status indicator according to database node determines the historical transactional information of the described user of described storage Database node is in the database node of active state；Saved by the described data base being in active state Point obtains the historical transactional information of described user.
Wherein it is possible to determine the status indicator of database node in the following manner:
Detection messages is sent, if not receiving described database node in preset time period to database node Response message, it is determined that described database node is in failure state, and by the shape of described database node State mark is defined as failure state, otherwise the status indicator of described database node is defined as active state.
It is, of course, also possible to determined the status indicator of database node by other detection methods, the most superfluous at this State.
After determining that database node is failure state, it is also possible to need the data base to this failure state to save Data in point back up.Concrete, first determine and deposit in the described database node being in failure state The data of storage are identical and are in the database node of active state；To the described and described failure state of being in In database node, the data of storage are identical and to be in the data of storage in the database node of active state standby Part is in the database node of active state to other.
In step 102, after obtaining the historical transactional information of described user, can hand over according to the history of user Easily the dealing money in information determines the dealing money meansigma methods of described user, and according to the transaction of described user Amount of money meansigma methods and tradable commodity type determine the consumption grade of described user.
The dealing money meansigma methods of described user is determined according to described dealing money, and according to the friendship of described user Easily amount of money meansigma methods and tradable commodity type determine the weighting dealing money meansigma methods of described user, and according to Described weighting dealing money meansigma methods determines the consumption grade of described user
Concrete, the weighting dealing money meansigma methods of user can be determined according to below equation:
M = Σ e = 1 N C e × D / N ... ( 1 )
Wherein, M represents the weighting dealing money meansigma methods of user, and D represents the dealing money meansigma methods of user, CeRepresenting the weighted value of the tradable commodity type concluded the business the e time, e is more than or equal to 1 and less than or equal to N, N Represent transaction count.
It should be noted that the weighted value of tradable commodity type can go to arrange according to practical situation.Trader The weighted value of category type is the number more than 0.The value of the dealing money that type of transaction is corresponding is the biggest, this transaction class The weighted value of type can be the biggest.
Then grade corresponding for the weighting dealing money meansigma methods of described user is determined the consumption of described user Grade.
Concrete, determine the historical transaction record of all users got, and determine all use got The weighting dealing money meansigma methods at family；
For a user, determine that the weighting dealing money average bits of this user all gets in described Ranking in the weighting dealing money meansigma methods of user, according to the row of the weighting dealing money meansigma methods of this user Name and the mapping relations of consumption grade, determine the consumption grade of described user.
For example, can will be located in the weighting dealing money meansigma methods of described all users got is arranged The consumption grade of all users of name front 1% determines the first estate；Will be located in described all users got Weighting dealing money meansigma methods in before ranking the consumption grade of all users of 1% determine the first estate；Will In the weighting dealing money meansigma methods of described all users got before ranking between 3% to 1% The consumption grade of all users determines the second grade；Will be located in the weighting transaction of described all users got In amount of money meansigma methods, before ranking, the consumption grade of all users between 15% to 3% determines the tertiary gradient；Will In the weighting dealing money meansigma methods of described all users got before ranking between 47% to 15% The consumption grade of all users determine the fourth estate；The weighting that will be located in described all users got is handed over Easily in amount of money meansigma methods, before ranking, the consumption grade of all users between 85% to 47% determines the 5th grade； Will be located in the weighting dealing money meansigma methods of described all users got before ranking 94% to 85% it Between the consumption grade of all users determine the 6th grade；Will be located in the weighting of described all users got In dealing money meansigma methods, the consumption grade of all users of the last 6% determines the 7th grade.Certainly, The ranking of weighting dealing money meansigma methods that can also have the user of other forms is closed with the mapping of consumption grade System, does not repeats them here.
When after the weighting dealing money meansigma methods ranking determining a user, it is possible to close according to mapping above System determines the consumption grade of user.
The consumption grade of user may indicate that the consuming capacity of user, or shows the social class of user.
Meanwhile, in step 103, the consumer phase of user can be determined by the historical transaction record of user. The tradable commodity type preset in consumer phase can have multiple.
For example, the consumer phase of user can be divided into following several stages: unmarried stage, standby wedding Stage, newly-married stage, the stage of nursing a baby, child-bearing stage, (refer to the most stage by stage: the child fostered the most stage by stage Son has been grown up, but does not also marry), the empty-nest stage, the few stage.
Wherein, during the unmarried stage, default tradable commodity type is mainly the amusements such as food, books, film Project；During the standby wedding stage, default tradable commodity type is mainly the project such as high fashion, marriage articles for use； During the newly-married stage, default tradable commodity type is mainly the projects such as amusement, tourism；Nurse a baby the stage time, in advance If tradable commodity type be mainly the project such as milk powder, diaper；During the child-bearing stage, default tradable commodity Type is mainly the projects such as spending for education；Time the most stage by stage, the predominantly social activity of default tradable commodity type is used The projects such as product；During the empty-nest stage, default tradable commodity type is mainly the projects such as health product；The few stage Time, the projects such as default tradable commodity type is the most medical.
In step 104, can determine that user can be in different people according to the different feature of life different phase There is the tradable commodity type of difference preference in the raw stage.
For example, if user often buys the articles for babies such as milk powder and diaper, it may be determined that user's Feature tradable commodity type is child-bearing product, so that it is determined that the consumer phase residing for described user is rank of nursing a baby Section.
The most in step 105, consumption grade and consumer phase according to user determine the business that user is mated Product information, and push these merchandise news for user when needed.
A kind of possible implementation determining the merchandise news that user mates is:
Determine other users consistent with the consumption grade of described user；
Determine the tradable commodity type in the historical transactional information of other users described；
In tradable commodity type in the historical transactional information of other users described, determine and described user institute The tradable commodity type that the consumer phase at place matches, and will match with the consumer phase residing for described user Tradable commodity information corresponding to tradable commodity type be defined as the merchandise news that matches with described user.
For example, user A and user B belongs to same consumption grade, and user A likes the first product The Sichuan cuisine shop consumption of board, user B likes the Sichuan cuisine shop of the second brand to consume.At this point it is possible to by user B The merchandise news in the Sichuan cuisine shop of the second brand liked is mated with user A.Accordingly, it is also possible to will use The merchandise news in the Sichuan cuisine shop of the second brand that family A likes is mated with user B.When user A is When the Sichuan cuisine shop of one brand is consumed, the merchandise news in the Sichuan cuisine shop of the second brand can be pushed to user A, Thus realize precision marketing.
The alternatively possible implementation determining the merchandise news that user mates is:
Obtain businessman's attribute information and the historical transactional information of businessman of businessman, in described businessman attribute information Including tradable commodity type, the historical transactional information of described businessman includes dealing money；
By the business that the dealing money meansigma methods of businessman is in same scope and the tradable commodity type of businessman is identical Family is divided into businessman's cluster；
The consumption grade of the dealing money meansigma methods of businessman Yu described user is matched and the trader of businessman Category type belongs to businessman's cluster of the consumer phase residing for described user, is defined as matching with described user Businessman clusters；
The businessman described and described user matched clusters corresponding merchandise news and is defined as and described user The merchandise news matched.
For example, user A belongs to the 3rd consumption grade, and user A is in the unmarried stage, now may be used With by the businessman cluster corresponding with user A coupling.When user A buys certain high-grade mobile phone, can be to use Family A pushes and belongs to, with this top grade mobile phone, the high-grade digital camera that same businessman clusters, thus realizes precisely battalion Pin.
Finally, when user's real-time deal, can be that user pushes and trader's category of user's real-time deal The merchandise news that type matches.
Concrete, obtain the real-time deal information of user；
In the tradable commodity type that the merchandise news that matches described user is corresponding, determine and described real-time friendship The tradable commodity type of easy tradable commodity type matching, and by the trader's category with described real-time deal Tradable commodity information pushing corresponding to tradable commodity type that type matches gives described user.
When customer transaction, the tradable commodity information being pushed to described user can be printed upon described user's In bill, or in electronic bill, thus obtain the concern of user.
The commodity that the consumer phase with user matches can also be pushed to user.
Concrete, obtain the real-time deal information of user；
Determine real-time tradable commodity type according to described real-time deal information, and push and institute to described user State the tradable commodity information that the consumer phase of user matches.
In the tradable commodity type that the merchandise news that matches described user is corresponding, determine and described real-time friendship The tradable commodity type of easy tradable commodity type matching, and by the trader's category with described real-time deal Tradable commodity information pushing corresponding to tradable commodity type that type matches gives described user.
Based on identical technology design, the embodiment of the present invention also provides for a kind of transaction data processing means, this dress Put and can perform said method embodiment.The device that the embodiment of the present invention provides is as shown in Figure 2.
As in figure 2 it is shown, a kind of transaction data processing means provided for the embodiment of the present invention, this device includes:
Acquiring unit 201, for obtaining the historical transactional information of user, described historical transactional information includes handing over The easily amount of money, tradable commodity type；
Determine unit 202, for determining the dealing money meansigma methods of described user according to described dealing money, And the dealing money meansigma methods and tradable commodity type according to described user determines that the weighting of described user is handed over Easily amount of money meansigma methods, and the consumption grade of described user is determined according to described weighting dealing money meansigma methods；From Determining the feature tradable commodity type of described user in the tradable commodity type of described user, described feature is concluded the business The type of merchandise be threshold value that transaction count corresponding to this tradable commodity type is corresponding more than this tradable commodity type, And this tradable commodity type belongs to the tradable commodity type preset in consumer phase；Feature according to described user Tradable commodity type determines the consumer phase residing for described user；
Matching unit 203, for the consumer phase residing for the consumption grade according to described user and described user, Determine the merchandise news matched with described user.
Preferably, described acquiring unit 201 specifically for:
The database node of the historical transactional information storing described user is determined in distributed memory system；
Status indicator according to database node determines the number of the historical transactional information of the described user of described storage According to the database node being in active state in the node of storehouse；
The historical transactional information of described user is obtained by the described database node being in active state.
Preferably, this device also includes detector unit 204, and described detector unit 204 is the most true The status indicator of given data storehouse node:
Detection messages is sent, if not receiving described database node in preset time period to database node Response message, it is determined that described database node is in failure state, and by the shape of described database node State mark is defined as failure state, otherwise the status indicator of described database node is defined as active state.
Preferably, this device also includes that backup units 205, described backup units 205 are used for:
Determine and in the described database node being in failure state, the data of storage are identical and be in and enliven shape The database node of state；
To in the described and described database node being in failure state, the data of storage are identical and are in active The data backup stored in the database node of state is in the database node of active state to other.
Preferably, described determine unit 202 specifically for:
The weighting dealing money meansigma methods of user is determined according to below equation:
M = Σ e = 1 N C e × D / N
Wherein, M represents the weighting dealing money meansigma methods of user, and D represents the dealing money meansigma methods of user, CeRepresenting the weighted value of the tradable commodity type concluded the business the e time, e is more than or equal to 1 and less than or equal to N, N Represent transaction count；
Grade corresponding for the weighting dealing money meansigma methods of described user is determined the consumption grade of described user.
Preferably, described matching unit 203 specifically for:
Determine other users consistent with the consumption grade of described user；
Determine the tradable commodity type in the historical transactional information of other users described；
In tradable commodity type in the historical transactional information of other users described, determine and described user institute The tradable commodity type that the consumer phase at place matches, and will match with the consumer phase residing for described user Tradable commodity information corresponding to tradable commodity type be defined as the merchandise news that matches with described user.
Preferably, described matching unit 203 specifically for:
Obtain businessman's attribute information and the historical transactional information of businessman of businessman, in described businessman attribute information Including tradable commodity type, the historical transactional information of described businessman includes dealing money；
By the business that the dealing money meansigma methods of businessman is in same scope and the tradable commodity type of businessman is identical Family is divided into businessman's cluster；
The consumption grade of the dealing money meansigma methods of businessman Yu described user is matched and the trader of businessman Category type belongs to businessman's cluster of the consumer phase residing for described user, is defined as matching with described user Businessman clusters；
The businessman described and described user matched clusters corresponding merchandise news and is defined as and described user The merchandise news matched.
Preferably, this device also includes push unit；Described push unit 206 specifically for:
Obtain the real-time deal information of user；
In the tradable commodity type that the merchandise news that matches described user is corresponding, determine and described real-time friendship The tradable commodity type of easy tradable commodity type matching, and by the trader's category with described real-time deal Tradable commodity information pushing corresponding to tradable commodity type that type matches gives described user.
In the embodiment of the present invention, it it is the dealing money meansigma methods that determines user of the off-line transaction record by user And tradable commodity type, so that it is determined that the consumption grade of user and consumer phase, finally determine user's Consuming behavior model.More can reflect the real behavior of consumer due to off-line transaction record, therefore obtain disappears Take behavior model more accurate.
The present invention is with reference to method, equipment (system) and computer program product according to embodiments of the present invention The flow chart of product and/or block diagram describe.It should be understood that can by computer program instructions flowchart and / or block diagram in each flow process and/or flow process in square frame and flow chart and/or block diagram and/ Or the combination of square frame.These computer program instructions can be provided to general purpose computer, special-purpose computer, embedding The processor of formula datatron or other programmable data processing device is to produce a machine instruction so that pass through The instruction that the processor of computer or other programmable data processing device performs produces for realizing in flow process The dress of the function specified in one flow process of figure or multiple flow process and/or one square frame of block diagram or multiple square frame Put.
These computer program instructions may be alternatively stored in and computer or the process of other programmable datas can be guided to set In the standby computer-readable memory worked in a specific way so that be stored in this computer-readable memory Instruction produce and include the manufacture of command device, this command device realizes in one flow process or multiple of flow chart The function specified in flow process and/or one square frame of block diagram or multiple square frame.
These computer program instructions also can be loaded in computer or other programmable data processing device, makes Sequence of operations step must be performed to produce computer implemented place on computer or other programmable devices Reason, thus the instruction performed on computer or other programmable devices provides for realizing flow chart one The step of the function specified in flow process or multiple flow process and/or one square frame of block diagram or multiple square frame.
Although preferred embodiments of the present invention have been described, but those skilled in the art once know base This creativeness concept, then can make other change and amendment to these embodiments.So, appended right is wanted Ask and be intended to be construed to include preferred embodiment and fall into all changes and the amendment of the scope of the invention.
Obviously, those skilled in the art can carry out various change and modification without deviating from this to the present invention Bright scope.So, if the present invention these amendment and modification belong to the claims in the present invention scope it In, then the present invention is also intended to comprise these change and modification.

Claims (16)

1. a transaction data processing method, it is characterised in that the method includes:
Obtaining the historical transactional information of user, described historical transactional information includes dealing money, trader's category Type；
The dealing money meansigma methods of described user is determined according to described dealing money, and according to the friendship of described user Easily amount of money meansigma methods and tradable commodity type determine the weighting dealing money meansigma methods of described user, and according to Described weighting dealing money meansigma methods determines the consumption grade of described user；
The feature tradable commodity type of described user, described spy is determined from the tradable commodity type of described user Levying tradable commodity type is that transaction count corresponding to this tradable commodity type is corresponding more than this tradable commodity type Threshold value and this tradable commodity type belong in consumer phase preset tradable commodity type；
Feature tradable commodity type according to described user determines the consumer phase residing for described user；
Consumer phase residing for consumption grade according to described user and described user, determines and described user's phase The merchandise news of coupling.
2. the method for claim 1, it is characterised in that the historical trading letter of described acquisition user Breath, including:
The database node of the historical transactional information storing described user is determined in distributed memory system；
Status indicator according to database node determines the number of the historical transactional information of the described user of described storage According to the database node being in active state in the node of storehouse；
The historical transactional information of described user is obtained by the described database node being in active state.
3. method as claimed in claim 2, it is characterised in that determine that data base saves in the following manner The status indicator of point:
Detection messages is sent, if not receiving described database node in preset time period to database node Response message, it is determined that described database node is in failure state, and by the shape of described database node State mark is defined as failure state, otherwise the status indicator of described database node is defined as active state.
4. method as claimed in claim 3, it is characterised in that the described shape by described database node After state mark is defined as failure state, also include:
Determine and in the described database node being in failure state, the data of storage are identical and be in and enliven shape The database node of state；
To in the described and described database node being in failure state, the data of storage are identical and are in active The data backup stored in the database node of state is in the database node of active state to other.
5. the method as described in any one of Claims 1-4, it is characterised in that described according to described friendship Easily the amount of money determines the dealing money meansigma methods of described user, and according to the dealing money meansigma methods of described user with And tradable commodity type determines the weighting dealing money meansigma methods of described user, and according to described weighting trade gold Volume meansigma methods determines the consumption grade of described user, including:
The weighting dealing money meansigma methods of user is determined according to below equation:
M = Σ e = 1 N C e × D / N
Wherein, M represents the weighting dealing money meansigma methods of user, and D represents the dealing money meansigma methods of user, CeRepresenting the weighted value of the tradable commodity type concluded the business the e time, e is more than or equal to 1 and less than or equal to N, N Represent transaction count；
Grade corresponding for the weighting dealing money meansigma methods of described user is determined the consumption grade of described user.
6. the method for claim 1, it is characterised in that the described consumption etc. according to described user Level and the consumer phase residing for described user, determine the merchandise news matched with described user, including:
Determine other users consistent with the consumption grade of described user；
Determine the tradable commodity type in the historical transactional information of other users described；
In tradable commodity type in the historical transactional information of other users described, determine and described user institute The tradable commodity type that the consumer phase at place matches, and will match with the consumer phase residing for described user Tradable commodity information corresponding to tradable commodity type be defined as the merchandise news that matches with described user.
7. the method for claim 1, it is characterised in that the described consumption etc. according to described user Level and the consumer phase residing for described user, determine the merchandise news matched with described user, including:
Obtain businessman's attribute information and the historical transactional information of businessman of businessman, in described businessman attribute information Including tradable commodity type, the historical transactional information of described businessman includes dealing money；
By the business that the dealing money meansigma methods of businessman is in same scope and the tradable commodity type of businessman is identical Family is divided into businessman's cluster；
The consumption grade of the dealing money meansigma methods of businessman Yu described user is matched and the trader of businessman Category type belongs to businessman's cluster of the consumer phase residing for described user, is defined as matching with described user Businessman clusters；
The businessman described and described user matched clusters corresponding merchandise news and is defined as and described user The merchandise news matched.
Method the most as claimed in claims 6 or 7, it is characterised in that the method also includes:
Obtain the real-time deal information of user；
In the tradable commodity type that the merchandise news that matches described user is corresponding, determine and described real-time friendship The tradable commodity type of easy tradable commodity type matching, and by the trader's category with described real-time deal Tradable commodity information pushing corresponding to tradable commodity type that type matches gives described user.
9. a transaction data processing means, it is characterised in that this device includes:
Acquiring unit, for obtaining the historical transactional information of user, described historical transactional information includes trade gold Volume, tradable commodity type；
Determine unit, for determining the dealing money meansigma methods of described user according to described dealing money, and root The weighting trade gold of described user is determined according to the dealing money meansigma methods of described user and tradable commodity type Volume meansigma methods, and the consumption grade of described user is determined according to described weighting dealing money meansigma methods；From described The tradable commodity type of user determines the feature tradable commodity type of described user, described feature tradable commodity Type is threshold value that transaction count corresponding to this tradable commodity type is corresponding more than this tradable commodity type and should Tradable commodity type belongs to the tradable commodity type preset in consumer phase；Feature transaction according to described user The type of merchandise determines the consumer phase residing for described user；
Matching unit, for the consumer phase residing for the consumption grade according to described user and described user, really The fixed merchandise news matched with described user.
10. device as claimed in claim 9, it is characterised in that described acquiring unit specifically for:
The database node of the historical transactional information storing described user is determined in distributed memory system；
Status indicator according to database node determines the number of the historical transactional information of the described user of described storage According to the database node being in active state in the node of storehouse；
The historical transactional information of described user is obtained by the described database node being in active state.
11. devices as claimed in claim 10, it is characterised in that this device also includes detector unit, Described detector unit determines the status indicator of database node in the following manner:
Detection messages is sent, if not receiving described database node in preset time period to database node Response message, it is determined that described database node is in failure state, and by the shape of described database node State mark is defined as failure state, otherwise the status indicator of described database node is defined as active state.
12. devices as claimed in claim 11, it is characterised in that this device also includes backup units, Described backup units is used for:
Determine and in the described database node being in failure state, the data of storage are identical and be in and enliven shape The database node of state；
To in the described and described database node being in failure state, the data of storage are identical and are in active The data backup stored in the database node of state is in the database node of active state to other.
13. devices as described in any one of claim 9 to 12, it is characterised in that described determine unit Specifically for:
The weighting dealing money meansigma methods of user is determined according to below equation:
M = Σ e = 1 N C e × D / N
Wherein, M represents the weighting dealing money meansigma methods of user, and D represents the dealing money meansigma methods of user, CeRepresenting the weighted value of the tradable commodity type concluded the business the e time, e is more than or equal to 1 and less than or equal to N, N Represent transaction count；
Grade corresponding for the weighting dealing money meansigma methods of described user is determined the consumption grade of described user.
14. devices as claimed in claim 9, it is characterised in that described matching unit specifically for:
Determine other users consistent with the consumption grade of described user；
Determine the tradable commodity type in the historical transactional information of other users described；
In tradable commodity type in the historical transactional information of other users described, determine and described user institute The tradable commodity type that the consumer phase at place matches, and will match with the consumer phase residing for described user Tradable commodity information corresponding to tradable commodity type be defined as the merchandise news that matches with described user.
15. devices as claimed in claim 9, it is characterised in that described matching unit specifically for:
Obtain businessman's attribute information and the historical transactional information of businessman of businessman, in described businessman attribute information Including tradable commodity type, the historical transactional information of described businessman includes dealing money；
By the business that the dealing money meansigma methods of businessman is in same scope and the tradable commodity type of businessman is identical Family is divided into businessman's cluster；
The consumption grade of the dealing money meansigma methods of businessman Yu described user is matched and the trader of businessman Category type belongs to businessman's cluster of the consumer phase residing for described user, is defined as matching with described user Businessman clusters；
The businessman described and described user matched clusters corresponding merchandise news and is defined as and described user The merchandise news matched.
16. devices as described in claims 14 or 15, it is characterised in that this device also includes pushing list Unit；Described push unit specifically for:
Obtain the real-time deal information of user；
In the tradable commodity type that the merchandise news that matches described user is corresponding, determine and described real-time friendship The tradable commodity type of easy tradable commodity type matching, and by the trader's category with described real-time deal Tradable commodity information pushing corresponding to tradable commodity type that type matches gives described user.
CN201510617766.9A 2015-09-24 2015-09-24 Transaction data processing method and device Pending CN105931066A (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201510617766.9A CN105931066A (en) 2015-09-24 2015-09-24 Transaction data processing method and device
PCT/CN2016/099224 WO2017050188A1 (en) 2015-09-24 2016-09-18 Transaction data processing method and device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510617766.9A CN105931066A (en) 2015-09-24 2015-09-24 Transaction data processing method and device

Publications (1)

Publication Number Publication Date
CN105931066A true CN105931066A (en) 2016-09-07

Family

ID=56840073

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510617766.9A Pending CN105931066A (en) 2015-09-24 2015-09-24 Transaction data processing method and device

Country Status (2)

Country Link
CN (1) CN105931066A (en)
WO (1) WO2017050188A1 (en)

Cited By (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017050188A1 (en) * 2015-09-24 2017-03-30 中国银联股份有限公司 Transaction data processing method and device
CN106600341A (en) * 2016-12-29 2017-04-26 江西博瑞彤芸科技有限公司 Commodity sales volume statistical method
CN106649555A (en) * 2016-11-08 2017-05-10 深圳市中博睿存科技有限公司 Memory unit state marking method and distributed memory system
CN106846132A (en) * 2017-04-12 2017-06-13 杭州纳戒科技有限公司 Merchandise news method for pushing, device and system
CN107403311A (en) * 2017-06-27 2017-11-28 阿里巴巴集团控股有限公司 The recognition methods of account purposes and device
CN108182625A (en) * 2017-12-28 2018-06-19 广州品唯软件有限公司 A kind of electric business user Method of Commodity Recommendation and device
CN109474703A (en) * 2018-12-24 2019-03-15 杭州云纪网络科技有限公司 Personalized product combines method for pushing, apparatus and system
CN109961309A (en) * 2017-12-25 2019-07-02 网智天元科技集团股份有限公司 Business recommended method and system
CN111371853A (en) * 2020-02-24 2020-07-03 中国银联股份有限公司 Resource information pushing method and device, server and storage medium
CN115392406A (en) * 2022-10-28 2022-11-25 山东智豆数字科技有限公司 User classification management method based on historical transaction information
CN116737790A (en) * 2023-05-15 2023-09-12 佛山市大迈信息科技有限公司 Method and system for processing business data of building selling

Families Citing this family (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109492891B (en) * 2018-10-26 2022-04-29 创新先进技术有限公司 User loss prediction method and device
CN110766441A (en) * 2019-09-05 2020-02-07 口碑(上海)信息技术有限公司 Resource object processing method and device, storage medium and computer equipment
CN111159398B (en) * 2019-12-05 2023-10-31 银联智策顾问（上海）有限公司 Method and device for identifying merchant types
CN111368543B (en) * 2020-02-18 2023-06-02 银联智策顾问（上海）有限公司 Method and device for determining merchant category
CN113344665A (en) * 2021-05-31 2021-09-03 北京百度网讯科技有限公司 Method and device for updating commodity information, electronic equipment and storage medium
CN113837800A (en) * 2021-09-23 2021-12-24 中国银联股份有限公司 Transaction processing method and device

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101960479A (en) * 2008-03-03 2011-01-26 雅虎公司 Method and apparatus for social network marketing with advocate referral
CN103325052A (en) * 2013-07-03 2013-09-25 姚明东 Commodity recommendation method based on multidimensional user consumption propensity modeling
CN103927675A (en) * 2014-04-18 2014-07-16 北京京东尚科信息技术有限公司 Method and device for judging age brackets of users
CN104835057A (en) * 2015-04-02 2015-08-12 百度在线网络技术（北京）有限公司 Method and device for obtaining consumption feature information of network user

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101930576A (en) * 2009-06-23 2010-12-29 微析科技股份有限公司 Customer consumption analysis system
CN102254028A (en) * 2011-07-22 2011-11-23 青岛理工大学 Personalized commodity recommending method and system which integrate attributes and structural similarity
CN104809626A (en) * 2015-03-17 2015-07-29 徐邑江 Customized commodity recommending method based on user credit assessment
CN105931066A (en) * 2015-09-24 2016-09-07 中国银联股份有限公司 Transaction data processing method and device

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101960479A (en) * 2008-03-03 2011-01-26 雅虎公司 Method and apparatus for social network marketing with advocate referral
CN103325052A (en) * 2013-07-03 2013-09-25 姚明东 Commodity recommendation method based on multidimensional user consumption propensity modeling
CN103927675A (en) * 2014-04-18 2014-07-16 北京京东尚科信息技术有限公司 Method and device for judging age brackets of users
CN104835057A (en) * 2015-04-02 2015-08-12 百度在线网络技术（北京）有限公司 Method and device for obtaining consumption feature information of network user

Cited By (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2017050188A1 (en) * 2015-09-24 2017-03-30 中国银联股份有限公司 Transaction data processing method and device
CN106649555A (en) * 2016-11-08 2017-05-10 深圳市中博睿存科技有限公司 Memory unit state marking method and distributed memory system
CN106600341A (en) * 2016-12-29 2017-04-26 江西博瑞彤芸科技有限公司 Commodity sales volume statistical method
CN106846132A (en) * 2017-04-12 2017-06-13 杭州纳戒科技有限公司 Merchandise news method for pushing, device and system
CN107403311B (en) * 2017-06-27 2020-04-21 阿里巴巴集团控股有限公司 Account use identification method and device
CN107403311A (en) * 2017-06-27 2017-11-28 阿里巴巴集团控股有限公司 The recognition methods of account purposes and device
CN109961309A (en) * 2017-12-25 2019-07-02 网智天元科技集团股份有限公司 Business recommended method and system
CN109961309B (en) * 2017-12-25 2021-09-28 网智天元科技集团股份有限公司 Service recommendation method and system
CN108182625A (en) * 2017-12-28 2018-06-19 广州品唯软件有限公司 A kind of electric business user Method of Commodity Recommendation and device
CN109474703A (en) * 2018-12-24 2019-03-15 杭州云纪网络科技有限公司 Personalized product combines method for pushing, apparatus and system
CN111371853A (en) * 2020-02-24 2020-07-03 中国银联股份有限公司 Resource information pushing method and device, server and storage medium
WO2021169659A1 (en) * 2020-02-24 2021-09-02 中国银联股份有限公司 Resource information pushing method and device, server, and storage medium
TWI803823B (en) * 2020-02-24 2023-06-01 大陸商中國銀聯股份有限公司 Resource information pushing method, device, server and storage medium
CN115392406A (en) * 2022-10-28 2022-11-25 山东智豆数字科技有限公司 User classification management method based on historical transaction information
CN115392406B (en) * 2022-10-28 2023-04-28 山东智豆数字科技有限公司 User classification management method based on historical transaction information
CN116737790A (en) * 2023-05-15 2023-09-12 佛山市大迈信息科技有限公司 Method and system for processing business data of building selling

Also Published As

Publication number Publication date
WO2017050188A1 (en) 2017-03-30

Similar Documents

Publication Publication Date Title
CN105931066A (en) Transaction data processing method and device
TWI740106B (en) Product recommendation method and device
US11790431B2 (en) Systems and methods for generating recommendations using a corpus of data
Wang et al. What affects mobile application use? The roles of consumption values
CN108960992A (en) A kind of information recommendation method and relevant device
CN105630946B (en) A kind of field intersection recommended method and device based on big data
CN106326248B (en) The storage method and device of database data
CN103208077B (en) A kind of collaborative booking method and equipment, system
Walker Banking without banks: Exploring the disruptive effects of converging technologies that will shape the future of banking
CN107862530A (en) Establish the method and device of user's interpersonal relationships information
CN101183450A (en) Virtual costume real man try-on system and constructing method thereof
CN104636950A (en) Group object commodity recommendation system and method
CN110782267A (en) System and method for cognitive adjacency planning and cognitive planogram design
CN110210899A (en) Advertisement sending method, device and equipment based on advertisement similitude
Earl et al. Alternative perspectives on connections in economic systems
CN109064293A (en) Method of Commodity Recommendation, device, computer equipment and storage medium
WO2019169050A1 (en) Inventory placement recommendation system
CN102024224A (en) E-commerce system and method for getting commodities on and/or off shelves at optimal time
CN106846112A (en) Food booking method and system
CN107395680A (en) Shop group's information push and output intent and device, equipment
CN109034958A (en) A method of it spelling single charging and reminds payment
CN104021485A (en) Commodity push method and device based on physiological index parameters
CN108122126A (en) Method for extending association rule, device using same and computer readable medium
CN112967109A (en) Intelligent flash shop product selection method
CN107256224B (en) A kind of generation method of the element structure of knowledge, searching method, apparatus and system

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
REG Reference to a national code

Ref country code: HK

Ref legal event code: DE

Ref document number: 1225141

Country of ref document: HK

RJ01 Rejection of invention patent application after publication

Application publication date: 20160907

RJ01 Rejection of invention patent application after publication
REG Reference to a national code

Ref country code: HK

Ref legal event code: WD

Ref document number: 1225141

Country of ref document: HK