CN107507039A - Data processing method and device - Google Patents

Data processing method and device Download PDF

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CN107507039A
CN107507039A CN201710783390.8A CN201710783390A CN107507039A CN 107507039 A CN107507039 A CN 107507039A CN 201710783390 A CN201710783390 A CN 201710783390A CN 107507039 A CN107507039 A CN 107507039A
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commodity
mrow
user
msub
sale
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张蔷
李聚信
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Beijing Jingdong Century Trading Co Ltd
Beijing Jingdong Shangke Information Technology Co Ltd
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Beijing Jingdong Century Trading Co Ltd
Beijing Jingdong Shangke Information Technology Co Ltd
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    • G—PHYSICS
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    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0278—Product appraisal

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Abstract

The invention discloses a kind of data processing method and device, it is related to field of information processing.Method therein includes：According to the transaction data of commodity, the irreplaceability index of commodity is calculated, wherein, the irreplaceability index expression users of commodity buys other commodity and substitutes the probability that purchase commodity this events do not occur；According to the transaction data of commodity, the halo effect index of commodity is calculated, wherein, the halo effect index expression commodity of commodity attract the ability that user is consumed；According to the halo effect index of the sales volume of commodity, the irreplaceability index of commodity and commodity, the value of commodity is calculated.It is achieved thereby that the quantization for commodity value, more objective, the accurate value for weighing commodity.

Description

Data processing method and device
Technical field
The present invention relates to field of information processing, more particularly to a kind of data processing method and device.
Background technology
With the fast development of ecommerce, the commodity that consumer can select are increasing, in face of the business of such magnanimity Product, the value how business personnel correctly assesses commodity are particularly important.
Commodity are mainly respectively divided into different stalls by existing evaluating commodity value method using the sales volume of commodity, The value of commodity is assessed by gear where commodity.Or adopt pin personnel by buy commodity old and new users's number, commodity it is multiple The historical data index such as purchase rate, commodity value is assessed by professional knowledge.
The content of the invention
Inventor, which studies, to be found, objective to commodity value, accurate quantization that prior art can not be realized.
The technical problem that the present invention solves is how to realize the quantization for commodity value, so as to more objective, accurate The value of true measurement commodity.
One side according to embodiments of the present invention, there is provided a kind of data processing method, including：According to the transaction of commodity Data, the irreplaceability index of commodity is calculated, wherein, the irreplaceability index expression user of commodity buys other commodity and replaced Buy on behalf and buy the probability that commodity this events does not occur；According to the transaction data of commodity, the halo effect index of commodity is calculated, its In, the halo effect index expression commodity of commodity attract the ability that user is consumed；According to the sales volume of commodity, commodity not The halo effect index of substitutability index and commodity, calculate the value of commodity.
In one embodiment, by the sales volume of commodity, the irreplaceability index of commodity and the halo effect of commodity Index is multiplied, and the value of commodity is calculated.
In one embodiment, according to the transaction data of commodity, calculating the irreplaceability index of commodity includes：According to certain History Order data of the user in continuous order pair, calculate certain user in continuous order pair, from commodity to another commodity Alternative consumption；By all users in all continuous orders pair, adding from commodity to the alternative consumption of other each commodity With make ratio with the sales volume of commodity, the proxy indicator of commodity be calculated；Commodity are calculated according to the proxy indicator of commodity Irreplaceability index.
In one embodiment, alternative consumption of certain user from commodity A to commodity B is calculated using equation below：
Wherein, S (A, B) represents alternative consumption of certain user from commodity A to commodity B, Sale1ARepresent that certain user first orders The commodity A amount of money, Sale in list2BRepresent the amount of money of commodity B in certain order of user second, Sale2Represent certain order of user second Total amount, the first order and the second order are the continuous order of certain user.
In one embodiment, commodity A irreplaceability index is calculated using equation below：
Wherein, Switch (A) represents commodity A irreplaceability index, and T represents another substitute goods, SARepresent commodity A Sales volume.
In one embodiment, halo effect index is that loyal user's halo effect index and new user's halo effect refer to Target add and, loyal user's halo effect index expression commodity attract the ability that old user buys commodity, new user's halo effect Index expression commodity attract the ability that new user buys other commodity.
In one embodiment, loyal user's halo effect index is calculated using equation below：
Wherein, Halo (A)focusRepresent commodity A loyal user's halo effect index, Sale (A)focusRepresent commodity A's Loyal user's sales volume, Sale (A)regularCommodity A non-loyal user's sales volume is represented, α represents commodity A loyal user pin Sell the weight factor of volume.
In one embodiment, the weight factor of commodity A loyal user's sales volume is calculated using equation below：
Wherein, ∑focusF (A) represents that sales volume caused by loyalty user is lost during commodity A undercarriages, and Switch (A) represents business Product A irreplaceability index.
In one embodiment, sales volume caused by loyal user is lost when calculating commodity A undercarriages using equation below：
F (A)=PA(SaleA+SaleB+SaleC)+(1-PA)*SaleA*Switch(A)
Wherein, SaleARepresent commodity A certain loyal user's sales volume, SaleBRepresent commodity B certain loyal user's sale Volume, SaleCCommodity C certain loyal user's sales volume, the commodity with commodity A same types that commodity B buys for certain loyal user, business Product C is certain loyal user's purchase and the different types of commodity of commodity A, PALoyal user leaves during expression commodity A undercarriages Probability.
In one embodiment, the probability that loyal user leaves when calculating commodity A undercarriages using equation below：
In one embodiment, profit calculates commodity A loyal user's sales volume and commodity A non-loyalty with the following method User's sales volume：If certain user is more than pre- to the commodity A amount of consumption with the ratio of the amount of consumption of all commodity similar to commodity A If value, then certain user to be regarded as to commodity A loyal user, remaining user is regarded as to commodity A non-loyal user；By commodity A loyal user sums up to the commodity A amount of consumption, obtains commodity A loyal user's sales volume；By commodity A non-loyalty User sums up to the commodity A amount of consumption, obtains commodity A non-loyal user's sales volume.
In one embodiment, commodity A new user's halo effect index is calculated using equation below：
Wherein, Halo (A)newRepresent commodity A new user's halo effect index, hARepresent commodity A new user's ring of light effect It should be worth, SARepresent commodity A sales volume.
In one embodiment, new user's halo effect that commodity A is calculated using equation below is worth：
Wherein, Sale represents the follow-up order amount of money of purchase commodity A system head single users, and γ represents decay factor, t tables Under showing first the follow-up order of single commodity A user relative to single commodity A under first time.
Other side according to embodiments of the present invention, there is provided a kind of data processing equipment, including：Irreplaceability refers to Computing unit is marked, the transaction data according to commodity is configured as, calculates the irreplaceability index of commodity, wherein, commodity are not Substitutability index expression user buys the probability that other this event of commodity replacement purchase commodity do not occur；Halo effect index Computing unit, the transaction data according to commodity is configured as, calculates the halo effect index of commodity, wherein, the ring of light effect of commodity The ability for answering index expression commodity to attract user to be consumed；Commodity value computing unit, it is configured as the sale according to commodity The halo effect index of volume, the irreplaceability index of commodity and commodity, calculate the value of commodity.
In one embodiment, commodity value computing unit is configured as：By the sales volume of commodity, commodity it is irreplaceable Property index and the halo effect indexs of commodity be multiplied, the values of commodity is calculated.
In one embodiment, irreplaceability indicator calculating unit is configured as：According to certain user in continuous order pair In History Order data, certain user is calculated in continuous order pair, from commodity to the alternative consumption of another commodity；Will be all User is in all continuous orders pair, adding and the sales volume with commodity from commodity to the alternative consumption of other each commodity Make ratio, the proxy indicator of commodity is calculated；The irreplaceability index of commodity is calculated according to the proxy indicator of commodity.
In one embodiment, irreplaceability indicator calculating unit is configured as：Certain user is calculated using equation below Alternative consumption from commodity A to commodity B：
Wherein, S (A, B) represents alternative consumption of certain user from commodity A to commodity B, Sale1ARepresent that certain user first orders The commodity A amount of money, Sale in list2BRepresent the amount of money of commodity B in certain order of user second, Sale2Represent certain order of user second Total amount, the first order and the second order are the continuous order of certain user.
In one embodiment, irreplaceability indicator calculating unit is configured as：Calculate commodity A's using equation below Irreplaceability index：
Wherein, Switch (A) represents commodity A irreplaceability index, and T represents another substitute goods, SARepresent commodity A Sales volume.
In one embodiment, halo effect index is that loyal user's halo effect index and new user's halo effect refer to Target add and, loyal user's halo effect index expression commodity attract the ability that old user buys commodity, new user's halo effect Index expression commodity attract the ability that new user buys other commodity.
In one embodiment, halo effect indicator calculating unit is configured as：Loyal user is calculated using equation below Halo effect index：
Wherein, Halo (A)focusExpression commodity A loyal user's halo effect index, Sale (A (focusRepresent commodity A's Loyal user's sales volume, Sale (A)regularCommodity A non-loyal user's sales volume is represented, α represents commodity A loyal user pin Sell the weight factor of volume.
In one embodiment, halo effect indicator calculating unit is configured as：Commodity A loyalty is calculated using equation below The weight factor of sincere user's sales volume：
Wherein, ∑focusF (A) represents that sales volume caused by loyalty user is lost during commodity A undercarriages, and Switch (A) represents business Product A irreplaceability index.
In one embodiment, halo effect indicator calculating unit is configured as：Commodity A undercarriages are calculated using equation below When caused by loyal user sales volume lose：
F (A)=PA(SaleA+SaleB+SaleC)+(1-PA)*SaleA*Switch(A)
Wherein, SaleARepresent commodity A certain loyal user's sales volume, SaleBRepresent commodity B certain loyal user's sale Volume, SaleCCommodity C certain loyal user's sales volume, the commodity with commodity A same types that commodity B buys for certain loyal user, business Product C is certain loyal user's purchase and the different types of commodity of commodity A, PALoyal user leaves during expression commodity A undercarriages Probability.
In one embodiment, halo effect indicator calculating unit is configured as：Commodity A undercarriages are calculated using equation below When the probability that leaves of loyal user：
In one embodiment, halo effect indicator calculating unit is configured as：Profit calculates commodity A loyalty with the following method Non- loyal user's sales volume of sincere user's sales volume and commodity A：If certain user is similar with to commodity A to the commodity A amount of consumption The ratio of the amount of consumption of all commodity be more than preset value, then certain user is regarded as to commodity A loyal user, by remaining user Regard as commodity A non-loyal user；Commodity A loyal user is summed up to the commodity A amount of consumption, obtains commodity A's Loyal user's sales volume；Commodity A non-loyal user is summed up to the commodity A amount of consumption, obtains commodity A non-loyal use Family sales volume.
In one embodiment, halo effect indicator calculating unit is configured as：
Commodity A new user's halo effect index is calculated using equation below：
Wherein, Halo (A)newRepresent commodity A new user's halo effect index, hARepresent commodity A new user's ring of light effect It should be worth, SARepresent commodity A sales volume.
In one embodiment, halo effect indicator calculating unit is configured as：
New user's halo effect that commodity A is calculated using equation below is worth：
Wherein, Sale represents the follow-up order amount of money of purchase commodity A system head single users, and γ represents decay factor, t tables Under showing first the follow-up order of single commodity A user relative to single commodity A under first time.
Another aspect according to embodiments of the present invention, there is provided a kind of data processing equipment, including：Memory；And The processor of memory is coupled to, processor is configured as the instruction based on storage in memory, performed at foregoing data Reason method.
Another aspect according to embodiments of the present invention, there is provided a kind of computer-readable recording medium, it is computer-readable Storage medium is stored with computer instruction, and instruction realizes foregoing data processing method when being executed by processor.
Data processing method provided by the invention, the quantization for commodity value can be realized, so as to more objective, accurate Measurement commodity value.
By referring to the drawings to the present invention exemplary embodiment detailed description, further feature of the invention and its Advantage will be made apparent from.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing There is the required accompanying drawing used in technology description to be briefly described, it should be apparent that, drawings in the following description are only this Some embodiments of invention, for those of ordinary skill in the art, without having to pay creative labor, may be used also To obtain other accompanying drawings according to these accompanying drawings.
Fig. 1 shows the schematic flow sheet of one embodiment of data processing method of the present invention.
Fig. 2 shows the structural representation of the evaluating commodity value system based on commodity halo effect of one embodiment of the invention Figure.
Fig. 3 shows the structural representation of one embodiment of data processing equipment of the present invention.
Fig. 4 shows the structural representation of another embodiment of data processing equipment of the present invention.
Fig. 5 shows the structural representation of another embodiment of data processing equipment of the present invention.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete Site preparation describes, it is clear that described embodiment is only part of the embodiment of the present invention, rather than whole embodiments.Below Description only actually at least one exemplary embodiment is illustrative, is never used as to the present invention and its application or makes Any restrictions.Based on the embodiment in the present invention, those of ordinary skill in the art are not making creative work premise Lower obtained all other embodiment, belongs to the scope of protection of the invention.
Inventor, which studies, to be found, by the sales volume of commodity, old and new users's number of purchase commodity, purchase rate etc. is as assessment commodity again The index of value, can only reflect the current state of itself of commodity, and dimensional comparison is single, it is impossible between effective reflection commodity Pulling production, so as to can not accurate service guidance personnel operation.Because being connected each other between commodity, user is buying One commodity continues to buy other commodity later, can pull the sales volume of other commodity, here it is the halo effect of commodity, the ring of light The high commodity of effect can more bring the extra sales volume in addition to Sales Volume of Commodity itself, so adopting day of the pin personnel in commodity Often in operation, not only it should be understood that the actual sales volume of commodity, while need to consider the halo effect of commodity, commodity are assessed with this Value, could preferably make Operation Decision.
The data processing method that Fig. 1 introduces one embodiment of the invention is combined first.
Fig. 1 shows the schematic flow sheet of the data processing method of one embodiment of the invention.As shown in figure 1, the embodiment Data processing method include：
Step S102, according to the transaction data of commodity, calculate the irreplaceability index of commodity.Wherein, commodity can not Proxy indicator represents that user buys the probability that other this event of commodity replacement purchase commodity do not occur.
A kind of optional embodiment is, according to History Order data of certain user in continuous order pair, to calculate certain use Family is in continuous order pair, from commodity to the alternative consumption of another commodity；By all users in all continuous orders pair, from Commodity to the alternative consumption of other each commodity plus and, make ratio with the sales volume of commodity, the alternative of commodity be calculated Index；The irreplaceability index of commodity is calculated according to the proxy indicator of commodity.
The proxy indicator of commodity can be in first latter two order according to same user in the History Order data of commodity Alternative consumption calculate.For example, user have purchased commodity A in the first order, purchased in next order (the second order) Buy commodity B, then consumption of the user in the first order on the commodity A amount of money S (A, B) that commodity B is shifted into the second order, Sales volume accounting (i.e. in second order commodity B pair of the commodity B in order 2 are multiplied by for spending amount of the user on commodity A In substitute goods A accounting).Equation below (1) can be utilized to calculate the alternative consumption from commodity A to commodity B：
Wherein, S (A, B) represents the alternative consumption from commodity A to commodity B, Sale1ARepresent commodity A in the first order The amount of money, Sale2BRepresent the amount of money of commodity B in the second order, Sale2Represent the total amount of the second order, the first order and second Order is the continuous order of same user.
It is then possible to which the alternative consumption that the History Order by each user is calculated takes together, commodity are calculated Between it is alternative.For example, formula (2) calculating commodity A irreplaceability index can be utilized：
Wherein, Switch (A) represents commodity A irreplaceability index, and T represents another substitute goods, SARepresent commodity A Sales volume.
Step S104, according to the transaction data of commodity, the halo effect index of commodity is calculated, wherein, the ring of light effect of commodity The ability for answering index expression commodity to attract user to be consumed.
Commodity A halo effect index H (A) specifically could be arranged to loyal user's halo effect index Halo (A)focusWith And new user halo effect index Halo (A)newPlus and.Wherein, loyal user's halo effect index expression commodity attract old use The ability of commodity is bought at family, and new user's halo effect index expression commodity attract the ability that new user buys other commodity.It is loyal The circular of user's halo effect index and new user's halo effect index describes in detail later.
It will be understood by those skilled in the art that the halo effect index of commodity can also include other indexs, such as across category Halo effect index and non-loyal user's halo effect index between halo effect index, category.Calculating halo effect Can be fixed value (such as numerical value 1) by non-loyal user's halo effect setup measures during the numerical value of index.Certainly, it is if non- Influence very little of the loyal user's halo effect index to commodity value, non-loyal user's halo effect index can be ignored.
Step S106, according to the halo effect index of the sales volume of commodity, the irreplaceability index of commodity and commodity, Calculate the value of commodity.
A kind of optional embodiment is, by the sales volume of commodity, the irreplaceability index of commodity and the light of commodity Toroidal effect index is multiplied, such as shown in formula (3), commodity A value U (A) is calculated.
U (A)=SA*Switch(A)*H(A) (3)
Above-described embodiment introduces halo effect index and irreplaceability index the two concepts.It is general by the two Read, the quantization for commodity value can be realized, so as to more objective, the accurate value for weighing commodity, effectively reflect business Pulling production between product.The commodity value that the present embodiment is calculated, the influence that reflection new product that can be well is stimulated consumption And the consumption demand of consumer, while considering the relation between commodity and commodity, the value of objective, quantization commodity contributes to More comprehensively, the incremental value brought after commodity introduce is accurately understood, and then service guidance personnel carry out the operation of commodity.
Below to loyal user's halo effect index Halo (A)focusComputational methods be illustrated.
It is possible, firstly, to the probability that loyal user leaves when calculating commodity A undercarriages using formula (4)：
Wherein, SaleARepresent commodity A certain loyal user's sales volume, SaleBRepresent commodity B certain loyal user's sale Volume, the commodity with commodity A same types that commodity B buys for certain loyal user, PARepresent that loyal user leaves during commodity A undercarriages Probability.Formula (4) can reflect importance of the commodity A for client, loyal during so as to for calculating commodity A undercarriages The probability that user leaves.
It is then possible to sales volume caused by loyal user loses F when calculating commodity A undercarriages using equation below (5) (A)：
F (A)=PA(SaleA+SaleB+SaleC)+(1-PA)*SaleA*Switch(A)
(5)
Wherein, SaleCCommodity C certain loyal user's sales volume, commodity C are the different from commodity A of certain loyal user's purchase The commodity of type.PA(SaleA+SaleB+SaleC) the sales volume loss brought in the case that loyal user leaves can be weighed, (1-PA)*SaleA* Switch (A) can weigh the sales volume loss that loyal user brings without departing from the case of.
Next, define the real value that V (A) is commodity A.So, V (A) can be respectively by formula (6) (7) come table Show：
V (A)=∑focusF(A)+∑regularSale(A)*Switch(A) (6)
V (A)=Halo (A)focus*Sale(A)*Switch(A) (7)
So, line translation is entered to formula (6) and obtains formula (8)：
Further conversion obtains formula (9)
U (A)=[α ∑sfocusSaleA+∑regularSaleA]*Switch(A) (9)
Wherein, α represents the weight factor of commodity A loyal user's sales volume.
Wherein, Sale (A)focusRepresent commodity A loyal user's sales volume.
Formula (11) can be obtained according to formula (9) and formula (10)
Formula (12) can be obtained by formula (7) and formula (11)
Wherein, Sale (A)regularRepresent commodity A non-loyal user's sales volume.
It will be understood by those skilled in the art that commodity A loyal user's sales volume and commodity A is calculated according to transaction data The mode of non-loyal user's sales volume is various.A kind of mode therein is, if certain user is to the commodity A amount of consumption and to business The ratio of the amount of consumption of all commodity similar product A is more than preset value (such as 80%), then certain user is regarded as to commodity A loyalty Sincere user, remaining user is regarded as to commodity A non-loyal user.Then, by consumption of the commodity A loyal user to commodity A Volume sums up, and obtains commodity A loyal user's sales volume；Commodity A non-loyal user is added to the commodity A amount of consumption With obtain commodity A non-loyal user's sales volume.
In above-described embodiment, loyal user's halo effect index can be determined by transaction data, taken into full account commodity Old user is attracted to continue to buy the ability of commodity.Loyal user's halo effect index may bring pin after can reflecting commodity undercarriage The loss of volume is sold, so as to more objective, the accurate value for weighing commodity so that the value of commodity can effectively reflect commodity Between pulling production.
Below to new user's halo effect index Halo (A)newComputational methods be illustrated.
According to the follow-up order data of purchase commodity A system head single users, commodity A new user ring of light effect can be calculated Answer index Halo (A)new.For example, according to the follow-up order data of purchase commodity A system head single users, in same category Place an order first and first single commodity bundle A containing commodity user, it is believed that commodity A brings the user, therefore is renewed after the user Single amount of money is shared on commodity A by a certain percentage, and new user's halo effect as the commodity is worth, and is designated as hA.It can utilize Equation below (13) calculates commodity A new user's halo effect value：
hA=∑New user∑OrderSale*e-γt (13)
Wherein, hACommodity A new user's halo effect value is represented, Sale represents purchase commodity A system head single users The follow-up order amount of money, γ represents decay factor, such as can be with value 0.5, and single commodity A user's is follow-up under t is represented first Order, can be in units of year relative to the time of single commodity A under first.
It is then possible to commodity A new user's halo effect index is calculated using formula (14)：
Wherein, SARepresent commodity A sales volume.
In above-described embodiment, new user's halo effect index can be determined by transaction data, taken into full account new commodity User is attracted to continue to buy the ability of other commodity.New user's halo effect index can reflect the multiple purchase viscosity of commodity, so as to More objective, the accurate value for weighing commodity so that the pulling production that the value of commodity can effectively reflect between commodity.
A kind of implementation of the evaluating commodity value system based on commodity halo effect is introduced with reference to Fig. 2.
Fig. 2 shows the structural representation of the evaluating commodity value system based on commodity halo effect of one embodiment of the invention Figure.As shown in Fig. 2 the system mainly includes three modules：Data module 202, algoritic module 204, subscriber interface module 206.
Data module 202 includes transaction data module, alternative data module and user data module.Transaction data is main Including data such as commodity price, sales volume, sales volumes.Alternative data refers to that consumer occurs to buy target turn in shopping process The probability of shifting, it can be calculated by transaction data.User data refers to consumer behavior track of the user in purchasing process And user profile.
Algoritic module 204 includes the calculating of halo effect index, two parts of assessment of commodity value.Halo effect index Commodity can be weighed by commodity halo effect model and pull the amount of consumption of the client on other commodity.Commodity halo effect and business Product value assessment can be output to user interface.
Subscriber interface module 206 allows user to check the halo effect index of commodity various pieces, instructs it to carry out different Migration efficiency.
Above-described embodiment assesses the value of commodity by the association pulling production between weighing commodity.User is by this System adjusts operation plan it is recognized that the new user's halo effect index and loyal user's halo effect index of commodity with this Slightly.According to the halo effect index of the commodity calculated, it is possible to achieve the assessment to commodity value.
The data processing equipment of one embodiment of the invention is introduced with reference to Fig. 3.
Fig. 3 shows the structural representation of the data processing equipment of one embodiment of the invention.As shown in figure 3, the present embodiment Data processing equipment 30 include：
Irreplaceability indicator calculating unit 302, the transaction data according to commodity is configured as, calculates can not replacing for commodity For property index, wherein, the irreplaceability index expression user of commodity buys other this event of commodity replacement purchase commodity not The probability of generation；
Halo effect indicator calculating unit 304, the transaction data according to commodity is configured as, calculates the halo effect of commodity Index, wherein, the halo effect index expression commodity of commodity attract the ability that user is consumed；
Commodity value computing unit 306, be configured as the sales volume according to commodity, the irreplaceability index of commodity and The halo effect index of commodity, calculate the value of commodity.
In one embodiment, commodity value computing unit 306 is configured as：By the sales volume of commodity, commodity can not The halo effect index of proxy indicator and commodity is multiplied, and the value of commodity is calculated.
In one embodiment, irreplaceability indicator calculating unit 302 is configured as：
According to History Order data of certain user in continuous order pair, certain user is calculated in continuous order pair, from business Alternative consumption of the product to another commodity；
By all users in all continuous orders pair, from commodity to the alternative consumption of other each commodity plus and, Make ratio with the sales volume of commodity, the proxy indicator of commodity is calculated；
The irreplaceability index of commodity is calculated according to the proxy indicator of commodity.
In one embodiment, irreplaceability indicator calculating unit 302 is configured as：
Alternative consumption of certain user from commodity A to commodity B is calculated using formula (1)；
Wherein, S (A, B) represents alternative consumption of certain user from commodity A to commodity B, Sale1ARepresent that certain user first orders The commodity A amount of money, Sale in list2BRepresent the amount of money of commodity B in certain order of user second, Sale2Represent certain order of user second Total amount, the first order and the second order are the continuous order of certain user.
In one embodiment, irreplaceability indicator calculating unit 302 is configured as：
Commodity A irreplaceability index is calculated using formula (2)；
Wherein, Switch (A) represents commodity A irreplaceability index, and T represents another substitute goods, SARepresent commodity A Sales volume.
In one embodiment, halo effect index is that loyal user's halo effect index and new user's halo effect refer to Target add and, loyal user's halo effect index expression commodity attract the ability that old user buys commodity, new user's halo effect Index expression commodity attract the ability that new user buys other commodity.
In one embodiment, halo effect indicator calculating unit 304 is configured as：
Loyal user's halo effect index is calculated using formula (12)；
Wherein, Halo (A)focusRepresent commodity A loyal user's halo effect index, Sale (A)focusRepresent commodity A's Loyal user's sales volume, Sale (A)regularCommodity A non-loyal user's sales volume is represented, α represents commodity A loyal user pin Sell the weight factor of volume.
In one embodiment, halo effect indicator calculating unit 304 is configured as：
The weight factor of commodity A loyal user's sales volume is calculated using formula (10)；
Wherein, ∑focusF (A) represents that sales volume caused by loyalty user is lost during commodity A undercarriages, and Switch (A) represents business Product A irreplaceability index.
In one embodiment, halo effect indicator calculating unit 304 is configured as：
Sales volume caused by loyal user is lost when calculating commodity A undercarriages using formula (5)；
Wherein, SaleARepresent commodity A certain loyal user's sales volume, SaleBRepresent commodity B certain loyal user's sale Volume, SaleCCommodity C certain loyal user's sales volume, the commodity with commodity A same types that commodity B buys for certain loyal user, business Product C is certain loyal user's purchase and the different types of commodity of commodity A, PALoyal user leaves during expression commodity A undercarriages Probability.
In one embodiment, halo effect indicator calculating unit 304 is configured as：Calculated using formula (4) under commodity A The probability that loyal user leaves during frame.
In one embodiment, halo effect indicator calculating unit 304 is configured as：
Profit calculates commodity A loyal user's sales volume and commodity A non-loyal user's sales volume with the following method：If certain User is more than preset value to the commodity A amount of consumption with the ratio of the amount of consumption of all commodity similar to commodity A, then by certain user Commodity A loyal user is regarded as, remaining user is regarded as to commodity A non-loyal user；By commodity A loyal user to business The product A amount of consumption sums up, and obtains commodity A loyal user's sales volume；Commodity A non-loyal user is disappeared to commodity A Expense volume sums up, and obtains commodity A non-loyal user's sales volume.
In one embodiment, halo effect indicator calculating unit 304 is configured as：New user is calculated using formula (13) Halo effect index；
Wherein, hACommodity A new user's halo effect value is represented, Sale represents purchase commodity A system head single users The follow-up order amount of money, γ represent decay factor, t represent first under single commodity A user follow-up order relative under first Single commodity A time.
In one embodiment, halo effect indicator calculating unit 304 is configured as：Commodity A is calculated using formula (14) New user's halo effect index：
Wherein, Halo (A)newRepresent commodity A new user's halo effect index, SARepresent commodity A sales volume.
In one embodiment, halo effect indicator calculating unit 304 is configured as：
Commodity A new user's halo effect index is calculated using formula (14)；Wherein, Halo (A)newRepresent that commodity A's is new User's halo effect index, hARepresent commodity A new user's halo effect value, SARepresent commodity A sales volume.
In one embodiment, halo effect indicator calculating unit 304 is configured as：
New user's halo effect that commodity A is calculated using formula (13) is worth；Wherein, Sale expressions purchase commodity A's is The follow-up order amount of money for first single user of uniting, γ represent decay factor, the follow-up order phase of single commodity A user under t expressions first For the time of single commodity A under first.
Another aspect according to embodiments of the present invention, there is provided a kind of data processing equipment, including：Memory；And The processor of memory is coupled to, processor is configured as the instruction based on storage in memory, performed at foregoing data Reason method.
In above-described embodiment, the value value of commodity is calculated first with commodity value function, is then based on commodity value Value establishes selection Optimized model.So as to propose a kind of optimal selection method of target, introducing, cost is minimum and meet client Maximum revenue is realized in the case of demand, so as to instruct businessman to carry out the upper undercarriage decision-making of commodity.
Fig. 4 shows the structural representation of another embodiment of data processing equipment of the present invention.As shown in figure 4, the reality Applying the data processing equipment 40 of example includes：Memory 410 and the processor 420 for being coupled to the memory 410, processor 420 The instruction in store 410 based on storage is configured as, performs the data processing method in any one foregoing embodiment.
Wherein, memory 410 is such as can include system storage, fixed non-volatile memory medium.System stores Device is such as being stored with operating system, application program, Boot loader (Boot Loader) and other programs.
Fig. 5 shows the structural representation of another embodiment of data processing equipment of the present invention.As shown in figure 5, the reality Applying the data processing equipment 50 of example includes：Memory 410 and processor 420, input/output interface 530, net can also be included Network interface 540, memory interface 550 etc..For example may be used between these interfaces 530,540,550 and memory 410 and processor 420 To be connected by bus 550.Wherein, input/output interface 530 is the input-output equipment such as display, mouse, keyboard, touch-screen Connecting interface is provided.Network interface 540 provides connecting interface for various networked devices.Memory interface 550 is that SD card, USB flash disk etc. are outer Put storage device and connecting interface is provided.
Present invention additionally comprises a kind of computer-readable recording medium, computer instruction is stored thereon with, the instruction is processed Device realizes the data processing method in any one foregoing embodiment when performing.
It should be understood by those skilled in the art that, embodiments of the invention can be provided as method, system or computer program Product.Therefore, the present invention can use the reality in terms of complete hardware embodiment, complete software embodiment or combination software and hardware Apply the form of example.Moreover, the present invention can use the computer for wherein including computer usable program code in one or more The calculating implemented in non-transient storage medium (including but is not limited to magnetic disk storage, CD-ROM, optical memory etc.) can be used The form of machine program product.
The present invention is the flow with reference to method according to embodiments of the present invention, equipment (system) and computer program product Figure and/or block diagram describe.It should be understood that can be by every first-class in computer program instructions implementation process figure and/or block diagram Journey and/or the flow in square frame and flow chart and/or block diagram and/or the combination of square frame.These computer programs can be provided The processors of all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing devices is instructed to produce A raw machine so that produced by the instruction of computer or the computing device of other programmable data processing devices for real The device for the function of being specified in present one flow of flow chart or one square frame of multiple flows and/or block diagram or multiple square frames.
These computer program instructions, which may be alternatively stored in, can guide computer or other programmable data processing devices with spy Determine in the computer-readable memory that mode works so that the instruction being stored in the computer-readable memory, which produces, to be included referring to Make the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one square frame of block diagram or The function of being specified in multiple square frames.
These computer program instructions can be also loaded into computer or other programmable data processing devices so that counted Series of operation steps is performed on calculation machine or other programmable devices to produce computer implemented processing, so as in computer or The instruction performed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one The step of function of being specified in individual square frame or multiple square frames.
The foregoing is only presently preferred embodiments of the present invention, be not intended to limit the invention, it is all the present invention spirit and Within principle, any modification, equivalent substitution and improvements made etc., it should be included in the scope of the protection.

Claims (28)

  1. A kind of 1. data processing method, it is characterised in that including：
    According to the transaction data of commodity, the irreplaceability index of the commodity is calculated, wherein, the irreplaceability of the commodity Index expression user buys other commodity and substitutes the probability that described this event of commodity of purchase does not occur；
    According to the transaction data of commodity, the halo effect index of the commodity is calculated, wherein, the halo effect index of the commodity Represent the ability that the commodity attract user to be consumed；
    According to the halo effect index of the sales volume of the commodity, the irreplaceability index of the commodity and the commodity, Calculate the value of the commodity.
  2. 2. data processing method as claimed in claim 1, it is characterised in that by the sales volume of the commodity, the commodity Irreplaceability index and the halo effect index of the commodity are multiplied, and the value of the commodity is calculated.
  3. 3. data processing method as claimed in claim 1, it is characterised in that the transaction data according to commodity, calculate institute Stating the irreplaceability index of commodity includes：
    According to History Order data of certain user in continuous order pair, certain user is calculated in the continuous order pair, from institute State alternative consumption of the commodity to another commodity；
    By all users in all continuous orders pair, from the commodity to the alternative consumption of other each commodity plus and, Make ratio with the sales volume of the commodity, the proxy indicator of the commodity is calculated；
    The irreplaceability index of the commodity is calculated according to the proxy indicator of the commodity.
  4. 4. data processing method as claimed in claim 3, it is characterised in that calculate certain user from commodity A using equation below To commodity B alternative consumption：
    <mrow> <mi>S</mi> <mrow> <mo>(</mo> <mi>A</mi> <mo>,</mo> <mi>B</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>Sale</mi> <mrow> <mn>1</mn> <mi>A</mi> </mrow> </msub> <mo>*</mo> <mfrac> <mrow> <msub> <mi>Sale</mi> <mrow> <mn>2</mn> <mi>B</mi> </mrow> </msub> </mrow> <mrow> <msub> <mi>Sale</mi> <mn>2</mn> </msub> </mrow> </mfrac> </mrow>
    Wherein, S (A, B) represents alternative consumption of certain user from commodity A to commodity B, Sale1ARepresent in certain order of user first The commodity A amount of money, Sale2BRepresent the amount of money of commodity B in certain order of user second, Sale2Represent the total of certain order of user second The amount of money, first order and second order are the continuous order of certain user.
  5. 5. data processing method as claimed in claim 4, it is characterised in that calculate can not replacing for commodity A using equation below For property index：
    Wherein, Switch (A) represents commodity A irreplaceability index, and T represents another substitute goods, SARepresent commodity A pin Sell volume.
  6. 6. data processing method as claimed in claim 1, it is characterised in that the halo effect index is loyal user's ring of light Effect index and new user's halo effect index plus and, commodity described in loyal user's halo effect index expression attract Old user buys the ability of the commodity, and commodity described in new user's halo effect index expression attract new user's purchase other The ability of commodity.
  7. 7. data processing method as claimed in claim 6, it is characterised in that calculate loyal user's light using equation below Toroidal effect index：
    <mrow> <mi>H</mi> <mi>a</mi> <mi>l</mi> <mi>o</mi> <msub> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mrow> <mi>f</mi> <mi>o</mi> <mi>c</mi> <mi>u</mi> <mi>s</mi> </mrow> </msub> <mo>=</mo> <mfrac> <mrow> <mi>&amp;alpha;</mi> <mo>*</mo> <mi>S</mi> <mi>a</mi> <mi>l</mi> <mi>e</mi> <msub> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mrow> <mi>f</mi> <mi>o</mi> <mi>c</mi> <mi>u</mi> <mi>s</mi> </mrow> </msub> <mo>+</mo> <mi>S</mi> <mi>a</mi> <mi>l</mi> <mi>e</mi> <msub> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>g</mi> <mi>u</mi> <mi>l</mi> <mi>a</mi> <mi>r</mi> </mrow> </msub> </mrow> <mrow> <mi>S</mi> <mi>a</mi> <mi>l</mi> <mi>e</mi> <msub> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mrow> <mi>f</mi> <mi>o</mi> <mi>c</mi> <mi>u</mi> <mi>s</mi> </mrow> </msub> <mo>+</mo> <mi>S</mi> <mi>a</mi> <mi>l</mi> <mi>e</mi> <msub> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>g</mi> <mi>u</mi> <mi>l</mi> <mi>a</mi> <mi>r</mi> </mrow> </msub> </mrow> </mfrac> </mrow>
    Wherein, Halo (A)focusRepresent commodity A loyal user's halo effect index, Sale (A)focusRepresent commodity A loyalty User's sales volume, Sale (A)regularCommodity A non-loyal user's sales volume is represented, α represents commodity A loyal user's sales volume Weight factor.
  8. 8. data processing method as claimed in claim 7, it is characterised in that the loyalty of the commodity A is calculated using equation below The weight factor of sincere user's sales volume：
    <mrow> <mi>&amp;alpha;</mi> <mo>=</mo> <mfrac> <mrow> <msub> <mi>&amp;Sigma;</mi> <mrow> <mi>f</mi> <mi>o</mi> <mi>c</mi> <mi>u</mi> <mi>s</mi> </mrow> </msub> <mi>F</mi> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mi>S</mi> <mi>a</mi> <mi>l</mi> <mi>e</mi> <msub> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mrow> <mi>f</mi> <mi>o</mi> <mi>c</mi> <mi>u</mi> <mi>s</mi> </mrow> </msub> <mo>*</mo> <mi>S</mi> <mi>w</mi> <mi>i</mi> <mi>t</mi> <mi>c</mi> <mi>h</mi> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> </mrow> </mfrac> </mrow>
    Wherein, ∑focusF (A) represents that sales volume caused by loyalty user is lost during commodity A undercarriages, and Switch (A) represents commodity A Irreplaceability index.
  9. 9. data processing method as claimed in claim 8, it is characterised in that when calculating commodity A undercarriages using equation below Sales volume caused by loyal user is lost：
    F (A)=PA(SaleA+SaleB+SaleC)+(1-PA)*SaleA*Switch(A)
    Wherein, SaleARepresent commodity A certain loyal user's sales volume, SaleBCommodity B certain loyal user's sales volume is represented, SaleCCommodity C certain loyal user's sales volume, the commodity with commodity A same types that commodity B buys for certain loyal user, commodity C For certain loyal user's purchase and the different types of commodity of commodity A, PARepresent that loyal user leaves general during commodity A undercarriages Rate.
  10. 10. data processing method as claimed in claim 9, it is characterised in that when calculating commodity A undercarriages using equation below The probability that loyal user leaves：
    <mrow> <msub> <mi>P</mi> <mi>A</mi> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>Sale</mi> <mi>A</mi> </msub> <mo>*</mo> <mi>S</mi> <mi>w</mi> <mi>i</mi> <mi>t</mi> <mi>c</mi> <mi>h</mi> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> </mrow> <mrow> <msub> <mi>Sale</mi> <mi>A</mi> </msub> <mo>+</mo> <msub> <mi>Sale</mi> <mi>B</mi> </msub> </mrow> </mfrac> </mrow>
  11. 11. the data processing method as described in any one of claim 7 to 10, it is characterised in that profit calculates business with the following method Product A loyal user's sales volume and commodity A non-loyal user's sales volume：
    If certain user is more than preset value to the commodity A amount of consumption with the ratio of the amount of consumption of all commodity similar to commodity A, Certain user is regarded as to commodity A loyal user, remaining user is regarded as to commodity A non-loyal user；
    Commodity A loyal user is summed up to the commodity A amount of consumption, obtains commodity A loyal user's sales volume；
    Commodity A non-loyal user is summed up to the commodity A amount of consumption, obtains commodity A non-loyal user's sales volume.
  12. 12. data processing method as claimed in claim 6, it is characterised in that
    Commodity A new user's halo effect index is calculated using equation below：
    <mrow> <mi>H</mi> <mi>a</mi> <mi>l</mi> <mi>o</mi> <msub> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mrow> <mi>n</mi> <mi>e</mi> <mi>w</mi> </mrow> </msub> <mo>=</mo> <mn>1</mn> <mo>+</mo> <mfrac> <msub> <mi>h</mi> <mi>A</mi> </msub> <msub> <mi>S</mi> <mi>A</mi> </msub> </mfrac> </mrow>
    Wherein, Halo (A)newRepresent commodity A new user's halo effect index, hARepresent commodity A new user's halo effect valency Value, SARepresent commodity A sales volume.
  13. 13. data processing method as claimed in claim 12, it is characterised in that commodity A new use is calculated using equation below Family halo effect value：
    Wherein, Sale represents the follow-up order amount of money of purchase commodity A system head single users, and γ represents decay factor, and t represents first Under secondary the follow-up order of single commodity A user relative to single commodity A under first time.
  14. A kind of 14. data processing equipment, it is characterised in that including：
    Irreplaceability indicator calculating unit, the transaction data according to commodity is configured as, calculates the irreplaceable of the commodity Property index, wherein, the irreplaceability index expression users of the commodity buy other commodity substitute buy the commodity this The probability that event does not occur；
    Halo effect indicator calculating unit, the transaction data according to commodity is configured as, the halo effect for calculating the commodity refers to Mark, wherein, commodity described in the halo effect index expression of the commodity attract the ability that user is consumed；
    Commodity value computing unit, be configured as the sales volume according to the commodity, the irreplaceability index of the commodity with And the halo effect index of the commodity, calculate the values of the commodity.
  15. 15. data processing equipment as claimed in claim 14, it is characterised in that the commodity value computing unit is configured For：The halo effect index of the sales volume of the commodity, the irreplaceability index of the commodity and the commodity is multiplied, The value of the commodity is calculated.
  16. 16. data processing equipment as claimed in claim 14, it is characterised in that the irreplaceability indicator calculating unit quilt It is configured to：
    According to History Order data of certain user in continuous order pair, certain user is calculated in the continuous order pair, from institute State alternative consumption of the commodity to another commodity；
    By all users in all continuous orders pair, from the commodity to the alternative consumption of other each commodity plus and, Make ratio with the sales volume of the commodity, the proxy indicator of the commodity is calculated；
    The irreplaceability index of the commodity is calculated according to the proxy indicator of the commodity.
  17. 17. data processing equipment as claimed in claim 16, it is characterised in that the irreplaceability indicator calculating unit quilt It is configured to：
    Alternative consumption of certain user from commodity A to commodity B is calculated using equation below：
    <mrow> <mi>S</mi> <mrow> <mo>(</mo> <mi>A</mi> <mo>,</mo> <mi>B</mi> <mo>)</mo> </mrow> <mo>=</mo> <msub> <mi>Sale</mi> <mrow> <mn>1</mn> <mi>A</mi> </mrow> </msub> <mo>*</mo> <mfrac> <mrow> <msub> <mi>Sale</mi> <mrow> <mn>2</mn> <mi>B</mi> </mrow> </msub> </mrow> <mrow> <msub> <mi>Sale</mi> <mn>2</mn> </msub> </mrow> </mfrac> </mrow>
    Wherein, S (A, B) represents alternative consumption of certain user from commodity A to commodity B, Sale1ARepresent in certain order of user first The commodity A amount of money, Sale2BRepresent the amount of money of commodity B in certain order of user second, Sale2Represent the total of certain order of user second The amount of money, first order and second order are the continuous order of certain user.
  18. 18. data processing equipment as claimed in claim 17, it is characterised in that the irreplaceability indicator calculating unit quilt It is configured to：
    Commodity A irreplaceability index is calculated using equation below：
    Wherein, Switch (A) represents commodity A irreplaceability index, and T represents another substitute goods, SARepresent commodity A pin Sell volume.
  19. 19. data processing equipment as claimed in claim 14, it is characterised in that the halo effect index is loyal user's light Toroidal effect index and new user's halo effect index plus and, commodity described in loyal user's halo effect index expression are inhaled Draw the ability that old user buys the commodity, commodity attract new user to buy it described in new user's halo effect index expression The ability of its commodity.
  20. 20. data processing equipment as claimed in claim 19, it is characterised in that the halo effect indicator calculating unit by with It is set to：Loyal user's halo effect index is calculated using equation below：
    <mrow> <mi>H</mi> <mi>a</mi> <mi>l</mi> <mi>o</mi> <msub> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mrow> <mi>f</mi> <mi>o</mi> <mi>c</mi> <mi>u</mi> <mi>s</mi> </mrow> </msub> <mo>=</mo> <mfrac> <mrow> <mi>&amp;alpha;</mi> <mo>*</mo> <mi>S</mi> <mi>a</mi> <mi>l</mi> <mi>e</mi> <msub> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mrow> <mi>f</mi> <mi>o</mi> <mi>c</mi> <mi>u</mi> <mi>s</mi> </mrow> </msub> <mo>+</mo> <mi>S</mi> <mi>a</mi> <mi>l</mi> <mi>e</mi> <msub> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>g</mi> <mi>u</mi> <mi>l</mi> <mi>a</mi> <mi>r</mi> </mrow> </msub> </mrow> <mrow> <mi>S</mi> <mi>a</mi> <mi>l</mi> <mi>e</mi> <msub> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mrow> <mi>f</mi> <mi>o</mi> <mi>c</mi> <mi>u</mi> <mi>s</mi> </mrow> </msub> <mo>+</mo> <mi>S</mi> <mi>a</mi> <mi>l</mi> <mi>e</mi> <msub> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mrow> <mi>r</mi> <mi>e</mi> <mi>g</mi> <mi>u</mi> <mi>l</mi> <mi>a</mi> <mi>r</mi> </mrow> </msub> </mrow> </mfrac> </mrow>
    Wherein, Halo (A)focusRepresent commodity A loyal user's halo effect index, Sale (A)focusRepresent commodity A loyalty User's sales volume, Sale (A)regularCommodity A non-loyal user's sales volume is represented, α represents commodity A loyal user's sales volume Weight factor.
  21. 21. data processing equipment as claimed in claim 20, it is characterised in that the halo effect indicator calculating unit by with It is set to：The weight factor of loyal user's sales volume of the commodity A is calculated using equation below：
    <mrow> <mi>&amp;alpha;</mi> <mo>=</mo> <mfrac> <mrow> <msub> <mi>&amp;Sigma;</mi> <mrow> <mi>f</mi> <mi>o</mi> <mi>c</mi> <mi>u</mi> <mi>s</mi> </mrow> </msub> <mi>F</mi> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> </mrow> <mrow> <mi>S</mi> <mi>a</mi> <mi>l</mi> <mi>e</mi> <msub> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mrow> <mi>f</mi> <mi>o</mi> <mi>c</mi> <mi>u</mi> <mi>s</mi> </mrow> </msub> <mo>*</mo> <mi>S</mi> <mi>w</mi> <mi>i</mi> <mi>t</mi> <mi>c</mi> <mi>h</mi> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> </mrow> </mfrac> </mrow>
    Wherein, ∑focusF (A) represents that sales volume caused by loyalty user is lost during commodity A undercarriages, and Switch (A) represents commodity A Irreplaceability index.
  22. 22. data processing equipment as claimed in claim 21, it is characterised in that the halo effect indicator calculating unit by with It is set to：Sales volume caused by loyal user is lost when calculating commodity A undercarriages using equation below：
    F (A)=PA(SaleA+SaleB+SaleC)+(1-PA)*SaleA*Switch(A)
    Wherein, SaleARepresent commodity A certain loyal user's sales volume, SaleBCommodity B certain loyal user's sales volume is represented, SaleCCommodity C certain loyal user's sales volume, the commodity with commodity A same types that commodity B buys for certain loyal user, commodity C For certain loyal user's purchase and the different types of commodity of commodity A, PARepresent that loyal user leaves general during commodity A undercarriages Rate.
  23. 23. data processing equipment as claimed in claim 22, it is characterised in that the halo effect indicator calculating unit by with It is set to：The probability that loyal user leaves when calculating commodity A undercarriages using equation below：
    <mrow> <msub> <mi>P</mi> <mi>A</mi> </msub> <mo>=</mo> <mfrac> <mrow> <msub> <mi>Sale</mi> <mi>A</mi> </msub> <mo>*</mo> <mi>S</mi> <mi>w</mi> <mi>i</mi> <mi>t</mi> <mi>c</mi> <mi>h</mi> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> </mrow> <mrow> <msub> <mi>Sale</mi> <mi>A</mi> </msub> <mo>+</mo> <msub> <mi>Sale</mi> <mi>B</mi> </msub> </mrow> </mfrac> </mrow>
  24. 24. the data processing equipment as described in any one of claim 20 to 23, it is characterised in that the halo effect index meter Unit is calculated to be configured as：Profit calculates commodity A loyal user's sales volume and commodity A non-loyal user's sale with the following method Volume：
    If certain user is more than preset value to the commodity A amount of consumption with the ratio of the amount of consumption of all commodity similar to commodity A, Certain user is regarded as to commodity A loyal user, remaining user is regarded as to commodity A non-loyal user；
    Commodity A loyal user is summed up to the commodity A amount of consumption, obtains commodity A loyal user's sales volume；
    Commodity A non-loyal user is summed up to the commodity A amount of consumption, obtains commodity A non-loyal user's sales volume.
  25. 25. data processing equipment as claimed in claim 19, it is characterised in that the halo effect indicator calculating unit by with It is set to：
    Commodity A new user's halo effect index is calculated using equation below：
    <mrow> <mi>H</mi> <mi>a</mi> <mi>l</mi> <mi>o</mi> <msub> <mrow> <mo>(</mo> <mi>A</mi> <mo>)</mo> </mrow> <mrow> <mi>n</mi> <mi>e</mi> <mi>w</mi> </mrow> </msub> <mo>=</mo> <mn>1</mn> <mo>+</mo> <mfrac> <msub> <mi>h</mi> <mi>A</mi> </msub> <msub> <mi>S</mi> <mi>A</mi> </msub> </mfrac> </mrow>
    Wherein, Halo (A)newRepresent commodity A new user's halo effect index, AARepresent commodity A new user's halo effect valency Value, SARepresent commodity A sales volume.
  26. 26. data processing equipment as claimed in claim 25, it is characterised in that the halo effect indicator calculating unit by with It is set to：
    New user's halo effect that commodity A is calculated using equation below is worth：
    Wherein, Sale represents the follow-up order amount of money of purchase commodity A system head single users, and γ represents decay factor, and t represents first Under secondary the follow-up order of single commodity A user relative to single commodity A under first time.
  27. A kind of 27. data processing equipment, it is characterised in that including：
    Memory；And
    The processor of the memory is coupled to, the processor is configured as based on the instruction being stored in the memory, Perform the data processing method as described in any one of claim 1 to 13.
  28. 28. a kind of computer-readable recording medium, it is characterised in that the computer-readable recording medium storage has computer to refer to The data processing method described in any one of claim 1 to 13 is realized in order, the instruction when being executed by processor.
CN201710783390.8A 2017-09-04 2017-09-04 Data processing method and device Pending CN107507039A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110880119A (en) * 2018-09-05 2020-03-13 北京京东尚科信息技术有限公司 Data processing method and device

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110880119A (en) * 2018-09-05 2020-03-13 北京京东尚科信息技术有限公司 Data processing method and device

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