CN108038735A - Data creation method and device - Google Patents
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- CN108038735A CN108038735A CN201711431025.7A CN201711431025A CN108038735A CN 108038735 A CN108038735 A CN 108038735A CN 201711431025 A CN201711431025 A CN 201711431025A CN 108038735 A CN108038735 A CN 108038735A
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Abstract
Embodiment of the present invention provides data creation method and device, is related to Computer Applied Technology field.Wherein, data creation method includes：Based on the transaction data of the target trade company collected, the characteristic value of the target trade company is counted；It is regular according to setting corresponding with the type of the characteristic value, determine the feature normalizing value of the characteristic value；The health degree score of the target trade company is generated according to the feature normalizing value.Method provided by the present invention generates according to feature normalizing value the health degree score of trade company according to the feature normalizing value of the definite characteristic value of setting rule corresponding with the type of trade company characteristic value, therefore, it is possible to realize the accurate health degree for portraying trade company.
Description
Technical field
The present invention relates to Computer Applied Technology field, more particularly, it is related to data creation method and device.
Background technology
As O2O (Online To Offline, under line on online offline/line) business model becoming increasingly popular and sending out
Exhibition, more and more trade companies are by this business model of O2O platform layouts, for example, food and drink shops is flat by entering Baidu's take-away
Platform realizes the business model of O2O.It is different that the income of platform can be brought due to the trade company of different high-quality degree, it is how accurate
Portray it is particularly important that high-quality degree of trade company is for platform in ground.Trade company draw a portrait field, usually using trade company's health degree this
One index weighs the high-quality degree of trade company.
However, the technical solution of trade company's health degree is not accurately generated in currently available technology.
The content of the invention
In existing solution, the technical solution of trade company's health degree is not accurately generated.
In this regard, embodiment of the present invention provides data creation method and device, in the presence of solving the prior art
Above-mentioned technical problem.
In a first aspect, embodiment of the present invention provides a kind of data creation method.
Specifically, the described method includes：
Based on the transaction data of the target trade company collected, the characteristic value of the target trade company is counted；
It is regular according to setting corresponding with the type of the characteristic value, determine the feature normalizing value of the characteristic value；
The health degree score of the target trade company is generated according to the feature normalizing value.
In the present embodiment, according to setting rule corresponding with the type of trade company characteristic value, the feature of characteristic value is determined
Normalizing value, and according to the health degree score of feature normalizing value generation trade company, therefore, it is possible to realize the accurate health for portraying trade company
Degree.
With reference to first aspect, in certain embodiments of the present invention, set according to corresponding with the type of the characteristic value
Then, determine the feature normalizing value of the characteristic value includes set pattern：
If the characteristic value is the matter characteristic value for indicating merchant type, indicated by acquisition and the characteristic value
The corresponding setting numerical value of merchant type, wherein, the setting numerical value is between 0 to 1；
The feature normalizing value is determined according to the setting numerical value.
With reference to first aspect, in certain embodiments of the present invention, set according to corresponding with the type of the characteristic value
Then, determine the feature normalizing value of the characteristic value includes set pattern：
If the characteristic value is positive correlation quantization characteristic value, to the element in the characteristic value collection containing the characteristic value
Carry out ascending sort；
According to the sorting position of the characteristic value and the positive correlation normalization creep function of setting, the feature normalizing value is determined.
With reference to first aspect, in certain embodiments of the present invention, set according to corresponding with the type of the characteristic value
Then, determine the feature normalizing value of the characteristic value includes set pattern：
If the characteristic value is negatively correlated quantization characteristic value, to the element in the characteristic value collection containing the characteristic value
Carry out descending sort；
According to the sorting position of the characteristic value and the negatively correlated normalization creep function of setting, the feature normalizing value is determined.
With reference to first aspect, in certain embodiments of the present invention, the target is generated according to the feature normalizing value
The health degree score of trade company includes：
Processing is weighted to the feature normalizing value；
Trade company's score of the target trade company is generated according to the feature normalizing value through the weighting processing；
Ascending sort is carried out to the element in trade company's score set containing trade company's score；
According to the sorting position of trade company's score and the element number of trade company's score set, the target business is generated
The health degree score at family.
Second aspect, embodiment of the present invention provide a kind of data generating device.
Specifically, described device includes：
Statistical module, for the transaction data based on the target trade company collected, counts the characteristic value of the target trade company；
Determining module, for according to the spy for setting rule, determining the characteristic value corresponding with the type of the characteristic value
Levy normalizing value；
Generation module, for generating the health degree score of the target trade company according to the feature normalizing value.
In the present embodiment, according to setting rule corresponding with the type of trade company characteristic value, the feature of characteristic value is determined
Normalizing value, and according to the health degree score of feature normalizing value generation trade company, therefore, it is possible to realize the accurate health for portraying trade company
Degree.
With reference to second aspect, in certain embodiments of the present invention, the determining module includes：
Acquiring unit, for obtaining setting numerical value corresponding with the merchant type indicated by the characteristic value, wherein, it is described
Numerical value is set between 0 to 1；
Determination unit, for determining the feature normalizing value according to the setting numerical value.
With reference to second aspect, in certain embodiments of the present invention, the determining module includes：
First ascending sort unit, for carrying out ascending order row to the element in the characteristic value collection containing the characteristic value
Sequence；
Determination unit, for the sorting position according to the characteristic value and the positive correlation normalization creep function of setting, determines institute
State feature normalizing value.
With reference to second aspect, in certain embodiments of the present invention, the determining module includes：
Descending alignment unit, for carrying out descending sort to the element in the characteristic value collection containing the characteristic value；
Determination unit, for the sorting position according to the characteristic value and the negatively correlated normalization creep function of setting, determines institute
State feature normalizing value.
With reference to second aspect, in certain embodiments of the present invention, the generation module includes：
Weighting processing unit, for being weighted processing to the feature normalizing value；
First generation unit, for generating the trade company of the target trade company according to the feature normalizing value through the weighting processing
Score；
Second ascending sort unit, for carrying out ascending order to the element in trade company's score set containing trade company's score
Sequence；
Second generation unit, for the sorting position according to trade company's score and the element of trade company's score set
Number, generates the health degree score of the target trade company.
The aspects of the invention or other aspects can more straightforwards in the description of detailed description below.
Brief description of the drawings
It is required in being described below to embodiment in order to illustrate more clearly of the technical solution of embodiment of the present invention
The attached drawing used is made one and is simply introduced, it should be apparent that, drawings in the following description are some embodiments of the present invention, right
For those of ordinary skill in the art, without creative efforts, it can also be obtained according to these attached drawings
His attached drawing.
Fig. 1 is the flow chart of the data creation method of method embodiment 1 according to the present invention；
Fig. 2 is the flow chart of the data creation method of method embodiment 2 according to the present invention；
Fig. 3 is the flow chart of the data creation method of method embodiment 3 according to the present invention；
Fig. 4 is the flow chart of the data creation method of method embodiment 4 according to the present invention；
Fig. 5 is the flow chart of the data creation method of method embodiment 5 according to the present invention；
Fig. 6 is the structure diagram of the data generating device of product embodiment 1 according to the present invention；
Fig. 7 shows a kind of embodiment of the determining module 12 shown in Fig. 6；
Fig. 8 shows the another embodiment of the determining module 12 shown in Fig. 6；
Fig. 9 shows another embodiment of the determining module 12 shown in Fig. 6；
Figure 10 shows a kind of embodiment of the generation module 13 shown in Fig. 6；
Figure 11 is a kind of structure diagram of terminal device of embodiment according to the present invention.
Embodiment
It is described in detail to various aspects of the present invention below in conjunction with the drawings and specific embodiments.Wherein, in this hair
In bright each embodiment, well-known operating process, program module, unit and its mutual connection, chain
Connect, communicate or operate and be not shown or do not elaborate.
Also, described feature, framework or function can combine in any way in one or more embodiments.
In addition, it will be appreciated by those skilled in the art that following various embodiments be served only for for example, not for
Limit the scope of the invention.Those skilled in the art can also be readily appreciated that, each reality described herein and shown in the drawings
Applying the program module in mode, unit or step can be combined and be designed by a variety of different configurations.
, unless otherwise specified, all should be with ability for the technical term not being specifically described in the present specification
The broadest meaning in domain explains.
In some flows of description in description and claims of this specification and above-mentioned attached drawing, contain according to
Particular order occur multiple operations, but it should be clearly understood that these operation can not occur herein according to it is suitable
Sequence is performed or performed parallel, and label such as S10, S11 of operation etc., be only used for distinguishing each different operation, sequence number
Any execution sequence is not represented for itself.In addition, these flows can include more or fewer operations, and these operations can
To perform or perform parallel in order.It should be noted that the description such as " first " herein, " second ", is to be used to distinguish not
Message together, equipment, module etc., do not represent sequencing, it is different types also not limit " first " and " second ".
Below in conjunction with attached drawing, the technical solution in embodiment of the present invention is clearly and completely described, it is clear that
Described embodiment is only a part of embodiment of the present invention, rather than whole embodiments.Based on the present invention
In embodiment, the every other embodiment party that those skilled in the art are obtained on the premise of not making the creative labor
Formula, belongs to the scope of protection of the invention.
【Method embodiment 1】
Fig. 1 is the flow chart of the data creation method of method embodiment 1 according to the present invention.Referring to Fig. 1, in this embodiment party
In formula, the described method includes：
S11：Based on the transaction data of the target trade company collected, the characteristic value of the target trade company is counted.
S12：It is regular according to setting corresponding with the type of the characteristic value, determine the feature normalizing value of the characteristic value.
Wherein, the feature normalizing value refers to characteristic value be normalized rear obtained result.
S13：The health degree score of the target trade company is generated according to the feature normalizing value.
In the present embodiment, according to setting rule corresponding with the type of trade company characteristic value, the feature of characteristic value is determined
Normalizing value, and according to the health degree score of feature normalizing value generation trade company, therefore, it is possible to realize the accurate health for portraying trade company
Degree.
【Method embodiment 2】
Fig. 2 is the flow chart of the data creation method of method embodiment 2 according to the present invention.Referring to Fig. 2, in this embodiment party
In formula, the described method includes：
S21：Based on the transaction data of the target trade company collected, the characteristic value of the target trade company is counted.
S22：It is the matter characteristic value for indicating merchant type to determine the characteristic value.
Wherein, the matter characteristic value refers to the feature for (for example, type for indicating trade company) qualitative to trade company
Value.
S23：Obtain setting numerical value corresponding with the merchant type indicated by the characteristic value.
Wherein, the setting numerical value is between 0 to 1.
S24：The feature normalizing value of the characteristic value is determined according to the setting numerical value.
For example, directly using the setting numerical value as the feature normalizing value.It is of course also possible to it is described setting numerical value into
Row calculation process is to obtain the feature normalizing value.
S25：The health degree score of the target trade company is generated according to the feature normalizing value.
【Method embodiment 3】
Fig. 3 is the flow chart of the data creation method of method embodiment 3 according to the present invention.Referring to Fig. 3, in this embodiment party
In formula, the described method includes：
S31：Based on the transaction data of the target trade company collected, the characteristic value of the target trade company is counted.
S32：It is positive correlation quantization characteristic value to determine the characteristic value.
Wherein, the positive correlation quantization characteristic value refers to be proportionate with the health degree score of trade company and for describing trade company
Amount attribute feature value.
S33：Ascending sort is carried out to the element in the characteristic value collection containing the characteristic value.
S34：According to the sorting position of the characteristic value and the positive correlation normalization creep function of setting, the characteristic value is determined
Feature normalizing value.
Wherein, positive correlation normalization creep function refers to：Input quantity is proportionate with output quantity and the value of output quantity is 0 to 1
Between model.
S35：The health degree score of the target trade company is generated according to the feature normalizing value.
【Method embodiment 4】
Fig. 4 is the flow chart of the data creation method of method embodiment 4 according to the present invention.Referring to Fig. 4, in this embodiment party
In formula, the described method includes：
S41：Based on the transaction data of the target trade company collected, the characteristic value of the target trade company is counted.
S42：It is negatively correlated quantization characteristic value to determine the characteristic value.
Wherein, the negatively correlated quantization characteristic value refers to negatively correlated with the health degree score of trade company and is used to describe trade company
Amount attribute feature value.
S43：Descending sort is carried out to the element in the characteristic value collection containing the characteristic value.
S44：According to the sorting position of the characteristic value and the negatively correlated normalization creep function of setting, the characteristic value is determined
Feature normalizing value.
Wherein, negatively correlated normalization creep function refers to：Input quantity is negatively correlated with output quantity and the value of output quantity is 0 to 1
Between model.
S45：The health degree score of the target trade company is generated according to the feature normalizing value.
【Method embodiment 5】
Fig. 5 is the flow chart of the data creation method of method embodiment 5 according to the present invention.Referring to Fig. 5, in this embodiment party
In formula, the described method includes：
S51：Based on the transaction data of the target trade company collected, the characteristic value of the target trade company is counted.
S52：It is regular according to setting corresponding with the type of the characteristic value, determine the feature normalizing value of the characteristic value.
S53：Processing is weighted to the feature normalizing value.
S54：Trade company's score of the target trade company is generated according to the feature normalizing value through the weighting processing.
S55：Ascending sort is carried out to the element in trade company's score set containing trade company's score.
S56：According to the sorting position of trade company's score and the element number of trade company's score set, the mesh is generated
Mark the health degree score of trade company.
【Method embodiment 6】
The data creation method provided with reference to specific example present embodiment is specifically described.In this implementation
In mode, the mode includes：
(1) merchant list is obtained from electric business platform.
(2) trade company for meeting following two conditions is selected from the merchant list：1st, there is lower forms data in nearly one month；
2nd, there is no missing for each feature (attribute) of trade company.
(3) trade company selected for each, the characteristic value of all features in statistical form 1.
Table 1
(4) each trade company selected is directed to, calculates the feature normalizing value (normalized feature score) of all features.
Below by taking the feature j of trade company i as an example, the realization for calculating feature normalizing value (normalized feature score) is illustrated
Mode.
If it is positive correlation quantization characteristic A, to identify feature j, will the feature j through all trade companies that step (2) select
Value carry out ascending sort, determine the sorting position rank of the feature j of trade company iij, pass through the spy of following formula calculating trade company i
Levy the feature normalizing value (normalized feature score) of j：
Wherein, N is expressed as the quantity of the trade company selected through step (2).
If it is negatively correlated quantization characteristic B, to identify feature j, will the feature j through all trade companies that step (2) select
Value carry out descending sort, determine the sorting position rank of the feature j of trade company iij, pass through the spy of following formula calculating trade company i
Levy the feature normalizing value (normalized feature score) of j：
Wherein, N is expressed as the quantity of the trade company selected through step (2).
If it is the matter feature for indicating merchant type C, to identify feature j, obtain signified with the characteristic value of feature j
The corresponding setting numerical value of merchant type (the setting numerical value is between 0 to 1) shown, using the numerical value got as feature j's
Feature normalizing value.
For example, if the value instruction trade company i of feature j is the exclusive trade company of platform, feature normalizing value is 1, if feature j's takes
Value instruction trade company i is not the exclusive trade company of platform, then feature normalizing value is 0, if the value instruction trade company i of feature j is NKA trade companies,
Then feature normalizing value is 1, if the value instruction trade company i of feature j is LKA trade companies, feature normalizing value is 0.5, if feature j's takes
Value instruction trade company i is not KA trade companies, then feature normalizing value is 0.
(5) for the trade company that each is selected, trade company's score is calculated according to all feature normalizing values.
For example, the trade company score Score of trade company i is calculated by the following formulai：
Wherein, wjThe weight of j is characterized, n represents the quantity of feature.
(6) for the trade company that each is selected, normalization trade company score is calculated.
Below by taking trade company i as an example, the implementation for calculating normalization trade company score is illustrated.
Ascending sort will be carried out through the trade company's score for all trade companies that step (2) select, and determine trade company's score of trade company i
ScoreiSorting position rank (Scorei), pass through the normalization trade company score UScore of the following formula calculating trade company ii：
Wherein, N is expressed as the quantity of the trade company selected through step (2).
(7) for the trade company that each is selected, health degree score of trade company's score as trade company will be normalized.
【Product embodiment 1】
Fig. 6 is the structure diagram of the data generating device of product embodiment 1 according to the present invention.Referring to Fig. 6, in this reality
Apply in mode, data generating device 10 includes：Statistical module 11, determining module 12 and generation module 13, specifically：
Statistical module 11 is used for the transaction data based on the target trade company collected, counts the feature of the target trade company
Value.
Determining module 12 is used for basis setting rule corresponding with the type for the characteristic value that statistical module 11 counts, and determines
The feature normalizing value of the characteristic value.
The feature normalizing value that generation module 13 is used to be determined according to determining module 12 generates the health of the target trade company
Spend score.
In the present embodiment, according to setting rule corresponding with the type of trade company characteristic value, the feature of characteristic value is determined
Normalizing value, and according to the health degree score of feature normalizing value generation trade company, therefore, it is possible to realize the accurate health for portraying trade company
Degree.
【Product embodiment 2】
The data generating device that present embodiment is provided includes the full content in product embodiment 1, herein no longer
Repeat.As shown in fig. 7, in the present embodiment, determining module 12 includes：Acquiring unit 121 and determination unit 122, specifically：
Acquiring unit 121 is used to obtain setting numerical value corresponding with the merchant type indicated by the characteristic value.
Wherein, the setting numerical value is between 0 to 1.
The numerical value that determination unit 122 is used to be got according to acquiring unit 121 determines the feature normalizing value.
【Product embodiment 3】
The data generating device that present embodiment is provided includes the full content in product embodiment 1, herein no longer
Repeat.As shown in figure 8, in the present embodiment, determining module 12 includes：First ascending sort unit 121 ' and determination unit
122 ', specifically：
First ascending sort unit 121 ' is used to carry out ascending order to the element in the characteristic value collection containing the characteristic value
Sequence.
Determination unit 122 ' is used for the ascending sort according to performed by the characteristic value in the first ascending sort unit 121 '
In sorting position and setting positive correlation normalization creep function, determine the feature normalizing value.
【Product embodiment 4】
The data generating device that present embodiment is provided includes the full content in product embodiment 1, herein no longer
Repeat.As shown in figure 9, in the present embodiment, determining module 12 includes：Descending alignment unit 121 " and determination unit 122 ",
Specifically：
Descending sort unit 121 " is used to carry out descending sort to the element in the characteristic value collection containing the characteristic value.
Determination unit 122 " is used in the descending sort according to performed by the characteristic value in descending alignment unit 121 "
Sorting position and the negatively correlated normalization creep function of setting, determine the feature normalizing value.
【Product embodiment 5】
It is any into product embodiment 4 that the data generating device that present embodiment is provided includes product embodiment 1
The full content of item, details are not described herein.As shown in Figure 10, in the present embodiment, generation module 13 includes：Weighting processing is single
First 131, first generation unit 132, the second ascending sort unit 133 and the second generation unit 134, specifically：
Weighting processing unit 131 is used to be weighted processing to the feature normalizing value.
The feature normalizing value that first generation unit 132 is used to be weighted processing according to weighted processing unit 131 generates
Trade company's score of the target trade company.
Second ascending sort unit 133 is used for trade company's score to the trade company's score generated containing the first generation unit 132
Element in set carries out ascending sort.
Second generation unit 134 is used for the ascending order according to performed by trade company's score in the second ascending sort unit 133
The element number of sorting position and trade company's score set in sequence, generates the health degree score of the target trade company.
As shown in figure 11, embodiments of the present invention additionally provide a kind of terminal device, including memory 21 and processor
22；Wherein,
Memory 21 is used to store one or more computer instruction, wherein, the one or more computer instruction quilt
Processor 22 can realize the method as described in any one into method embodiment 6 of method embodiment 1 when performing.
In the present embodiment, according to setting rule corresponding with the type of trade company characteristic value, the feature of characteristic value is determined
Normalizing value, and according to the health degree score of feature normalizing value generation trade company, therefore, it is possible to realize the accurate health for portraying trade company
Degree.
In addition, embodiments of the present invention also provide a kind of computer-readable storage medium, the computer-readable storage medium is used for
One or more computer instruction is stored, wherein, it can be realized such as side when one or more computer instruction is performed
Method of the method embodiment 1 into method embodiment 6 described in any one.
In the present embodiment, according to setting rule corresponding with the type of trade company characteristic value, the feature of characteristic value is determined
Normalizing value, and according to the health degree score of feature normalizing value generation trade company, therefore, it is possible to realize the accurate health for portraying trade company
Degree.
Those skilled in the art can be understood that the present invention can be realized all by software, also can be by software
Realized with reference to the mode of hardware platform.Based on such understanding, technical scheme contributes background technology
It can be embodied in whole or in part in the form of software product, the computer software product can be stored in storage medium
In, such as ROM/RAM, magnetic disc, CD, including some instructions are used so that computer equipment (can be personal computer,
Server, smart mobile phone either network equipment etc.) perform some part institutes of each embodiment of the present invention or embodiment
The method stated.
Words such as " softwares " used herein refers both to any type of computer code or calculating in general sense
Machine executable instruction set, can run the coding or instruction set to make computer or other processor programs perform such as
The various aspects of the upper technical scheme.Furthermore, it is necessary to explanation, one side according to embodiment,
The one or more computer programs for implementing the method for technical scheme upon execution necessarily will be in a computer
Or on processor, but in the module that can be distributed in multiple computers or processor, to perform the technical side of the present invention
The various aspects of case.
Computer executable instructions can have many forms, such as program module, can by one or more computer or
Other equipment performs.Usually, program module includes routine, program, object, component and data structure etc., performs specific
Task or implement specific abstract data type.Especially, in various embodiments, the operation that program module carries out can
To be combined or split according to the needs of each different embodiments.
Also, technical scheme can be presented as a kind of method, and have been provided for the method at least
One example.Action suitably can be sequentially performed by any type, the movement displaying is the part in the method.
Therefore, embodiment can be configured to that action can be performed according to the order different from shown execution sequence, wherein it is possible to
Including simultaneously performing some actions (although in the embodiment as shown, these actions are continuous).
Definition that is given in this article and using, definition in the document for dictionary should be compareed, being incorporated by reference into,
And/or it usually looks like and is understood.
In detail in the claims and in above-mentioned specification, all excessive phrases, such as " comprising ", " having ", " bag
Containing ", " carrying ", " having ", " being related to ", " mainly by ... form " and similar word be understood as it is open, i.e. bag
Contain but be not limited to.
The term and wording used in description of the invention is just to for example, be not intended to form restriction.Ability
Field technique personnel should be appreciated that on the premise of the basic principle of disclosed embodiment is not departed from, to the above embodiment
In each details can carry out various change.Therefore, the scope of the present invention is only determined by claim, in the claims, unless
It is otherwise noted, all terms should be understood by the broadest rational meaning.
A variety of embodiments of the present invention described in detail above, the description present invention is each in another form below
The various aspects or feature of the technical solution of embodiment, and it is not limited to a series of following paragraphs, for the sake of clarity, can
Alphanumeric is specified to some or all of paragraphs in these paragraphs.Each section in these paragraphs can be with any suitable side
Formula is combined with the content of other one or more paragraphs.Under conditions of the example of some in not limiting suitable combination, under
Some paragraphs in text especially quote other paragraphs and further limit other paragraphs.
A1, a kind of data creation method, the described method includes：
Based on the transaction data of the target trade company collected, the characteristic value of the target trade company is counted；
It is regular according to setting corresponding with the type of the characteristic value, determine the feature normalizing value of the characteristic value；
The health degree score of the target trade company is generated according to the feature normalizing value.
In A2, the method as described in A1, according to setting rule corresponding with the type of the characteristic value, the feature is determined
The feature normalizing value of value includes：
If the characteristic value is the matter characteristic value for indicating merchant type, indicated by acquisition and the characteristic value
The corresponding setting numerical value of merchant type, wherein, the setting numerical value is between 0 to 1；
The feature normalizing value is determined according to the setting numerical value.
In A3, the method as described in A1, according to setting rule corresponding with the type of the characteristic value, the feature is determined
The feature normalizing value of value includes：
If the characteristic value is positive correlation quantization characteristic value, to the element in the characteristic value collection containing the characteristic value
Carry out ascending sort；
According to the sorting position of the characteristic value and the positive correlation normalization creep function of setting, the feature normalizing value is determined.
In A4, the method as described in A1, according to setting rule corresponding with the type of the characteristic value, the feature is determined
The feature normalizing value of value includes：
If the characteristic value is negatively correlated quantization characteristic value, to the element in the characteristic value collection containing the characteristic value
Carry out descending sort；
According to the sorting position of the characteristic value and the negatively correlated normalization creep function of setting, the feature normalizing value is determined.
In A5, the method as any one of A1 to A4, the target trade company is generated according to the feature normalizing value
Health degree score includes：
Processing is weighted to the feature normalizing value；
Trade company's score of the target trade company is generated according to the feature normalizing value through the weighting processing；
Ascending sort is carried out to the element in trade company's score set containing trade company's score；
According to the sorting position of trade company's score and the element number of trade company's score set, the target business is generated
The health degree score at family.
B6, a kind of data generating device, described device include：
Statistical module, for the transaction data based on the target trade company collected, counts the characteristic value of the target trade company；
Determining module, for according to the spy for setting rule, determining the characteristic value corresponding with the type of the characteristic value
Levy normalizing value；
Generation module, for generating the health degree score of the target trade company according to the feature normalizing value.
In B7, the device as described in B6, the determining module includes：
Acquiring unit, for obtaining setting numerical value corresponding with the merchant type indicated by the characteristic value, wherein, it is described
Numerical value is set between 0 to 1；
Determination unit, for determining the feature normalizing value according to the setting numerical value.
In B8, the device as described in B6, the determining module includes：
First ascending sort unit, for carrying out ascending order row to the element in the characteristic value collection containing the characteristic value
Sequence；
Determination unit, for the sorting position according to the characteristic value and the positive correlation normalization creep function of setting, determines institute
State feature normalizing value.
In B9, the device as described in B6, the determining module includes：
Descending alignment unit, for carrying out descending sort to the element in the characteristic value collection containing the characteristic value；
Determination unit, for the sorting position according to the characteristic value and the negatively correlated normalization creep function of setting, determines institute
State feature normalizing value.
In B10, the device as any one of B6 to B9, the generation module includes：
Weighting processing unit, for being weighted processing to the feature normalizing value；
First generation unit, for generating the trade company of the target trade company according to the feature normalizing value through the weighting processing
Score；
Second ascending sort unit, for carrying out ascending order to the element in trade company's score set containing trade company's score
Sequence；
Second generation unit, for the sorting position according to trade company's score and the element of trade company's score set
Number, generates the health degree score of the target trade company.
C11, a kind of terminal device, including memory and processor；Wherein,
The memory is used to store one or more computer instruction, wherein, one or more computer instruction
The method as any one of A1 to A5 can be realized when being performed by the processor.
D12, a kind of computer-readable storage medium, for storing one or more computer instruction, wherein, when described one or
A plurality of computer instruction is performed the method that can be realized as any one of A1 to A5.
Claims (10)
- A kind of 1. data creation method, it is characterised in that the described method includes：Based on the transaction data of the target trade company collected, the characteristic value of the target trade company is counted；It is regular according to setting corresponding with the type of the characteristic value, determine the feature normalizing value of the characteristic value；The health degree score of the target trade company is generated according to the feature normalizing value.
- 2. the method as described in claim 1, it is characterised in that it is regular according to setting corresponding with the type of the characteristic value, Determining the feature normalizing value of the characteristic value includes：If the characteristic value is the matter characteristic value for indicating merchant type, obtain and the trade company indicated by the characteristic value The corresponding setting numerical value of type, wherein, the setting numerical value is between 0 to 1；The feature normalizing value is determined according to the setting numerical value.
- 3. the method as described in claim 1, it is characterised in that it is regular according to setting corresponding with the type of the characteristic value, Determining the feature normalizing value of the characteristic value includes：If the characteristic value is positive correlation quantization characteristic value, the element in the characteristic value collection containing the characteristic value is carried out Ascending sort；According to the sorting position of the characteristic value and the positive correlation normalization creep function of setting, the feature normalizing value is determined.
- 4. the method as described in claim 1, it is characterised in that it is regular according to setting corresponding with the type of the characteristic value, Determining the feature normalizing value of the characteristic value includes：If the characteristic value is negatively correlated quantization characteristic value, the element in the characteristic value collection containing the characteristic value is carried out Descending sort；According to the sorting position of the characteristic value and the negatively correlated normalization creep function of setting, the feature normalizing value is determined.
- 5. method according to any one of claims 1 to 4, it is characterised in that according to feature normalizing value generation The health degree score of target trade company includes：Processing is weighted to the feature normalizing value；Trade company's score of the target trade company is generated according to the feature normalizing value through the weighting processing；Ascending sort is carried out to the element in trade company's score set containing trade company's score；According to the sorting position of trade company's score and the element number of trade company's score set, the target trade company is generated Health degree score.
- 6. a kind of data generating device, it is characterised in that described device includes：Statistical module, for the transaction data based on the target trade company collected, counts the characteristic value of the target trade company；Determining module, for according to setting rule corresponding with the type of the characteristic value, determining that the feature of the characteristic value is returned One value；Generation module, for generating the health degree score of the target trade company according to the feature normalizing value.
- 7. device as claimed in claim 6, it is characterised in that the determining module includes：Acquiring unit, for obtaining setting numerical value corresponding with the merchant type indicated by the characteristic value, wherein, the setting Numerical value is between 0 to 1；Determination unit, for determining the feature normalizing value according to the setting numerical value.
- 8. device as claimed in claim 6, it is characterised in that the determining module includes：First ascending sort unit, for carrying out ascending sort to the element in the characteristic value collection containing the characteristic value；Determination unit, for the sorting position according to the characteristic value and the positive correlation normalization creep function of setting, determines the spy Levy normalizing value.
- 9. device as claimed in claim 6, it is characterised in that the determining module includes：Descending alignment unit, for carrying out descending sort to the element in the characteristic value collection containing the characteristic value；Determination unit, for the sorting position according to the characteristic value and the negatively correlated normalization creep function of setting, determines the spy Levy normalizing value.
- 10. the device as any one of claim 6 to 9, it is characterised in that the generation module includes：Weighting processing unit, for being weighted processing to the feature normalizing value；First generation unit, the trade company for generating the target trade company according to the feature normalizing value through the weighting processing obtain Point；Second ascending sort unit, for carrying out ascending order row to the element in trade company's score set containing trade company's score Sequence；Second generation unit, for the sorting position according to trade company's score and the element number of trade company's score set, Generate the health degree score of the target trade company.
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| CN201711431025.7A CN108038735A (en) | 2017-12-26 | 2017-12-26 | Data creation method and device |
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| CN201711431025.7A CN108038735A (en) | 2017-12-26 | 2017-12-26 | Data creation method and device |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109658193A (en) * | 2018-12-20 | 2019-04-19 | 拉扎斯网络科技（上海）有限公司 | Method and device for determining importance of system object, electronic equipment and storage medium |
| CN112561550A (en) * | 2019-09-26 | 2021-03-26 | 中移动信息技术有限公司 | Method, device, equipment and storage medium for classifying health degrees of merchants |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103716351A (en) * | 2012-09-29 | 2014-04-09 | 阿里巴巴集团控股有限公司 | Information display method and server |
| US20150019290A1 (en) * | 2013-07-12 | 2015-01-15 | Capital One Financial Corporation | Systems and methods for representing consumer behavior |
| CN105894360A (en) * | 2016-03-31 | 2016-08-24 | 百度在线网络技术（北京）有限公司 | Cheated order identification method, device and system |
| CN106980988A (en) * | 2016-12-29 | 2017-07-25 | ***股份有限公司 | Trade company's value assessment method |
| CN107133805A (en) * | 2017-05-09 | 2017-09-05 | 北京小度信息科技有限公司 | Method of adjustment, device and the equipment of user's cheating category forecasting Model Parameter |
-
2017
- 2017-12-26 CN CN201711431025.7A patent/CN108038735A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103716351A (en) * | 2012-09-29 | 2014-04-09 | 阿里巴巴集团控股有限公司 | Information display method and server |
| US20150019290A1 (en) * | 2013-07-12 | 2015-01-15 | Capital One Financial Corporation | Systems and methods for representing consumer behavior |
| CN105894360A (en) * | 2016-03-31 | 2016-08-24 | 百度在线网络技术（北京）有限公司 | Cheated order identification method, device and system |
| CN106980988A (en) * | 2016-12-29 | 2017-07-25 | ***股份有限公司 | Trade company's value assessment method |
| CN107133805A (en) * | 2017-05-09 | 2017-09-05 | 北京小度信息科技有限公司 | Method of adjustment, device and the equipment of user's cheating category forecasting Model Parameter |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109658193A (en) * | 2018-12-20 | 2019-04-19 | 拉扎斯网络科技（上海）有限公司 | Method and device for determining importance of system object, electronic equipment and storage medium |
| CN112561550A (en) * | 2019-09-26 | 2021-03-26 | 中移动信息技术有限公司 | Method, device, equipment and storage medium for classifying health degrees of merchants |
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