CN107481058A - A kind of Products Show method and Products Show device - Google Patents
A kind of Products Show method and Products Show device Download PDFInfo
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- CN107481058A CN107481058A CN201710711944.3A CN201710711944A CN107481058A CN 107481058 A CN107481058 A CN 107481058A CN 201710711944 A CN201710711944 A CN 201710711944A CN 107481058 A CN107481058 A CN 107481058A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0251—Targeted advertisements
- G06Q30/0269—Targeted advertisements based on user profile or attribute
- G06Q30/0271—Personalized advertisement
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0241—Advertisements
- G06Q30/0277—Online advertisement
Abstract
This application provides a kind of Products Show method and Products Show device, interest degrees of data of this method according to user to each financial product, determine preference of the user to each financial product, then the attribute information and user of the financial product by format specificationization processing are screened to the investigational data of each financial product, finally, according to the target product data and the user to the preference of each financial product, target recommended products is determined.Realize and Products Show is carried out according to the interest-degree of user, and then improve the conversion ratio of Products Show.
Description
Technical field
The application is related to technical field of data processing, and in particular to a kind of Products Show method and Products Show device.
Background technology
With the fast development of financial industry, some financial products to be promoted can be recommended each use by financial institution at present
Family, specifically, the way of recommendation have it is a variety of, such as by way of sending short messages in groups, by the link of a financial product and briefly in
Hold and send to all users of the financial institution, or the promotion message of the financial product is set in financial APP homepages
Predeterminated position.
However, it is found by the inventors that current Products Show conversion ratio is relatively low, therefore, a kind of Products Show side how is provided
Method, corresponding Products Show can be carried out according to the interest-degree of user, and then improve the conversion ratio of Products Show, be this area skill
An art personnel big technical problem urgently to be resolved hurrily.
The content of the invention
In view of this, the embodiment of the present application provides a kind of Products Show method and device, can be according to the emerging of user
Interesting degree, priority division is carried out to product to be recommended, user is then targetedly recommended, to improve pushing away for corresponding product
Recommend conversion ratio.
To achieve the above object, the embodiment of the present application provides following technical scheme：
A kind of Products Show method, applied to server, including：
The multi-dimensional data of each financial product is obtained, the multi-dimensional data includes the attribute information of the financial product,
Interest degrees of data of the user to the investigational data of each financial product and user to each financial product；
Attribute information and the user to the financial product enter professional etiquette to the investigational data of each financial product
Generalized processing, obtains the quantized data for meeting preset data form；
Interest degrees of data according to the user to each financial product, determine user to the inclined of each financial product
Good degree；
It is target product data to determine the product data for meeting preparatory condition in the quantized data；
According to the target product data and the user to the preference of each financial product, target is determined
Recommended products.
Preferably, the investigation to the attribute information and the user of the financial product to each financial product
Data carry out standardization processing, obtain the quantized data for meeting preset data form, including：
Boolean type data normalization processing is carried out to the investigational data of each financial product to the user, it is determined that described
The data attribute of investigational data.
Preferably, the interest degrees of data according to the user to each financial product, determines user to each described
The preference of financial product, including：
The quantity of financial product and user are obtained in the interest degrees of data to interest of each financial product etc.
Level；
According to the quantity of the financial product and user to the levels of interest of each financial product, user couple is determined
The preference of each financial product, wherein, each preference belongs to [0,1], and the preference sum is
1。
Preferably, the product data for determining to meet preparatory condition in the quantized data are target product data, bag
Include：
Determine that the standardization value of the attribute information of the financial product is more than or equal to the user and each finance is produced
The data of the financial product of the standardization value of the investigational data of product are target product data.
Preferably, the preference journey according to the target product data and the user to each financial product
Degree, determines target recommended products, including：
Create the matrix of the target product data and the user to the preference of each financial product；
Determine the positive ideal solution and minus ideal result of each target product data in the matrix；
Determine that the preference of the financial product recommends production apart from the nearest product of the positive ideal solution for the target
Product.
A kind of Products Show device, including：
Acquisition module, for obtaining the multi-dimensional data of each financial product, the multi-dimensional data includes the finance and produced
The attribute information of product, the interest number of degrees of the user to the investigational data of each financial product and user to each financial product
According to；
Processing module, the tune for the attribute information to the financial product and the user to each financial product
Grind data and carry out standardization processing, obtain the quantized data for meeting preset data form；
First determining module, for the interest degrees of data according to the user to each financial product, determine user couple
The preference of each financial product；
Second determining module, for determining that the product data for meeting preparatory condition in the quantized data are target product number
According to；
3rd determining module, for according to the target product data and the user to the inclined of each financial product
Good degree, determines target recommended products.
Preferably, the processing module includes：
First determining unit, for carrying out Boolean type data rule to the investigational data of each financial product to the user
Generalized processing, determine the data attribute of the investigational data.
Preferably, first determining module includes：
Acquiring unit, for obtaining in the interest degrees of data quantity of financial product and user to each finance
The levels of interest of product；
Second determining unit, for the quantity according to the financial product and user to the emerging of each financial product
Interesting grade, preference of the user to each financial product is determined, wherein, each preference belongs to [0,1], and institute
Preference sum is stated as 1.
Preferably, second determining module includes：
3rd determining unit, for determining that the standardization value of attribute information of the financial product is more than or equal to the use
Family is target product data to the data of the financial product of the standardization value of the investigational data of each financial product.
Preferably, the 3rd determining module includes：
Creating unit, for creating the preference journey of the target product data and the user to each financial product
The matrix of degree；
4th determining unit, for determining the positive ideal solution of each target product data and negative reason in the matrix
Want to solve；
5th determining unit, for determining the preference of the financial product apart from the nearest product of the positive ideal solution
For the target recommended products.
Based on above-mentioned technical proposal, this application provides a kind of Products Show method, and each finance is produced according to user
The interest degrees of data of product, preference of the user to each financial product is determined, then to by format specificationization processing
The attribute information of financial product and user screen to the investigational data of each financial product, finally, are produced according to the target
Product data and the user determine target recommended products to the preference of each financial product.Realize according to
The interest-degree at family carries out Products Show, and then improves the conversion ratio of Products Show.
Brief description of the drawings
, below will be to embodiment or existing in order to illustrate more clearly of the embodiment of the present application or technical scheme of the prior art
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
The embodiment of application, for those of ordinary skill in the art, on the premise of not paying creative work, can also basis
The accompanying drawing of offer obtains other accompanying drawings.
Fig. 1 is a kind of structural framing figure for Products Show system that the embodiment of the present application provides；
Fig. 2 is a kind of flow chart for Products Show method that the embodiment of the present application provides；
Fig. 3 is the schematic flow sheet for another Products Show method that the embodiment of the present application provides；
Fig. 4 is a kind of structured flowchart for Products Show device that the embodiment of the present application provides；
Fig. 5 is the structured flowchart for another Products Show device that the embodiment of the present application provides；
Fig. 6 is the structured flowchart for another Products Show device that the embodiment of the present application provides；
Fig. 7 is the structured flowchart for another Products Show device that the embodiment of the present application provides；
Fig. 8 is the structured flowchart for another Products Show device that the embodiment of the present application provides；
Fig. 9 is a kind of hardware architecture diagram for server that the embodiment of the present application provides.
Embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present application, the technical scheme in the embodiment of the present application is carried out clear, complete
Site preparation describes, it is clear that described embodiment is only some embodiments of the present application, rather than whole embodiments.It is based on
Embodiment in the application, those of ordinary skill in the art are obtained every other under the premise of creative work is not made
Embodiment, belong to the scope of the application protection.
Fig. 1 is a kind of structural framing figure for Products Show system that the embodiment of the present application provides, and the product shown in the figure pushes away
The system of recommending can be used for a kind of Products Show method for realizing that the embodiment of the present application provides.Reference picture 1, a kind of Products Show system
System can include：Server 100 and multiple client 200；
Wherein, server is the service equipment that network side provides the user service, and it is probably what multiple servers formed
Server cluster, it is also possible to single server.
Client is corresponding with server, provides the user the program of local service, in actual applications, client
It can typically be loaded on the user equipmenies such as mobile phone, tablet personal computer, notebook computer, in the present embodiment, client can be
The financial class APP being loaded on these user equipmenies.
Based on a kind of Products Show system shown in Fig. 1, a kind of production provided below from the angle of server the application
Product recommend method to be introduced.As shown in Fig. 2 a kind of flow chart of the Products Show method provided for the embodiment of the present application, should
Method can include：
S21, the multi-dimensional data for obtaining each financial product.
In the present embodiment, the multi-dimensional data includes the attribute information of the financial product, and user is to each gold
Melt product investigational data and user to the interest degrees of data of each financial product.Wherein, the attribute information of financial product
It is the data of the user recorded in database attribute interested, user records useful to the investigational data of each financial product
The demand information that family is fed back based on different financial products, e.g., whether user has purchasing demand etc. to product A's.
S22, the attribute information of the financial product and the user are entered to the investigational data of each financial product
Row standardization processing, obtain the quantized data for meeting preset data form.
Specifically, in the present embodiment, Boolean type number is carried out to the investigational data of each financial product to the user
According to standardization processing, then, it is determined that the data attribute of the investigational data.Because user is to the investigation number of each financial product
It is that above-mentioned data are carried out to the process of uniform format according to that may have different forms, different dimensions, therefore this step so that
User has unified dimension to the investigational data of each financial product.
Schematically, investigational data is unified into Boolean type data format, due to Boolean type data only comprising TRUE and
Two kinds of data of FALSE.Therefore can according to actual conditions by TRUE and FALSE standardize respectively positive attribute be 1 negative attribute be 0 with
And positive attribute is that 0 negative attribute is 1.For example, " whether there is risk " dimension, user is more desirable to buy the product of no risk, is negative
Attribute, so TRUE can be set into 0, FALSE is set to 1；" whether having interest " dimension, user are more desirable to buy the product of interest,
It is positive attribute, so TRUE can be set into 1, FALSE is set to 0.
S23, the interest degrees of data according to the user to each financial product, determine user to each financial product
Preference.
The user data that above-mentioned steps are got includes user to the interest-degree of a variety of financial products, and this step will be multiple emerging
Interesting degree carries out the processing of unified dimensional, can be by obtaining in the interest degrees of data quantity of financial product and user to every
The levels of interest of the individual financial product, then, each finance is produced according to the quantity of the financial product and user
The levels of interest of product, determine preference of the user to each financial product.Wherein, each preference belong to [0,
1], and the preference sum is 1.
For example, user to product A levels of interest for 3 (levels of interest can be understood as user satisfaction, similar to 1 star,
2 stars, 3 stars, 4 stars, 5 stars), the levels of interest to product B is 1, and the levels of interest to products C is 0, to product D levels of interest
For 2, the levels of interest to product E is 0, then, according to the quantity and levels of interest of product user can be determined to every successively
The preference of individual financial product, e.g., it is 3/ (3+1+0+2+0) to product A preference to determine user, to the inclined of product B
Good degree is 1/ (3+1+0+2+0), and the preference to products C is 0/ (3+1+0+2+0), and the preference to product D is 2/
(3+1+0+2+0), the preference to product E are 0/ (3+1+0+2+0).
Wherein, user to the preference of each product plus and be 1, i.e. preference of the user to each product
Between 0 and 1.Equally, preference also characterizes user and the interest of the product is inclined to, and preference is higher, shows to use
Family is interested in the product.
S24, determine that the product data for meeting preparatory condition in the quantized data are target product data.
Specifically, institute is more than or equal to by the standardization value for the attribute information for determining the financial product in the present embodiment
It is target product data to the data of the financial product of the standardization value of the investigational data of each financial product to state user.
For example, by the attribute information of the financial product after standardization and user to the investigational data of each financial product
It is compared, filters out the product data for meeting user's request.Meet that the product of user's request refers to each attribute herein
Standardization value be all higher than be equal to user's survey feedback interest dimension standardization value.
S25, according to the target product data and the user to the preference of each financial product, determine
Target recommended products.
Specifically, as shown in figure 3, step S25 can be achieved by the steps of：
S31, create the matrix of the target product data and the user to the preference of each financial product；
S32, the positive ideal solution and minus ideal result for determining each target product data in the matrix；
S33, determine that the preference of the financial product pushes away apart from the nearest product of the positive ideal solution for the target
Recommend product.
In the present embodiment, in similarity to ideal solution method, the positive ideal solution for defining decision-making problem of multi-objective and negative reason are passed through
Want to solve, a scheme is then selected from the scheme of meet demand so that the program and positive ideal solution volume are closest, and negative reason
Think that the distance of solution is farthest.
For example, when user is entering to select purchase product, it often selects to disclosure satisfy that the best of oneself inclined demand
Product.Create the target product data and the user to the matrix of the preference of each financial product it
Afterwards, positive ideal solution is exactly the maximum composition solution (solution that the maximum of i.e. each product attribute is formed) in decision matrix, bears reason
It is exactly the minimum composition solution (solution that the minimum value of i.e. each product attribute is formed) in decision matrix to think solution.
So, in preference analysis result, obtained solution is closer to 1, then illustrate the product closer to positive ideal solution,
Namely more match the preference of user.Equally, if numerical value if 0 if represent the product closer to minus ideal result,
It is namely more remote from user preference.Therefore, the present embodiment need to only determine the preference of the financial product apart from the correct principle
Want that it is the target recommended products to solve nearest product.
It can be seen that the present embodiment uses multiple attribute decision making (MADM), it is determined that minus ideal result is tried to achieve while positive ideal solution, finally with Europe
The each solution of family name's range measurement and finally determines user preference to the bias degree of plus-minus ideal solutions.
Below to the embodiment of the present application provide server be introduced, server described below with above with server
A kind of Products Show method of angle description is mutually to should refer to.As shown in figure 4, the server provided for the embodiment of the present application
Structured flowchart, reference picture 4, the server can include
Acquisition module 41, for obtaining the multi-dimensional data of each financial product, the multi-dimensional data includes the finance
The attribute information of product, interest-degree of the user to the investigational data of each financial product and user to each financial product
Data；
Processing module 42, for the attribute information to the financial product and the user to each financial product
Investigational data carries out standardization processing, obtains the quantized data for meeting preset data form；
First determining module 43, for the interest degrees of data according to the user to each financial product, determine user
To the preference of each financial product；
Second determining module 44, for determining that the product data for meeting preparatory condition in the quantized data are target product
Data；
3rd determining module 45, for according to the target product data and the user to each financial product
Preference, determine target recommended products.
Optionally, as shown in figure 5, the processing module 42 includes：
First determining unit 51, for carrying out Boolean type data to the investigational data of each financial product to the user
Standardization processing, determine the data attribute of the investigational data.
Optionally, as shown in fig. 6, first determining module 43 includes：
Acquiring unit 61, for obtaining in the interest degrees of data quantity of financial product and user to each gold
Melt the levels of interest of product；
Second determining unit 62, for the quantity according to the financial product and user to each financial product
Levels of interest, preference of the user to each financial product is determined, wherein, each preference belongs to [0,1], and
The preference sum is 1.
Optionally, as shown in fig. 7, second determining module 44 includes：
3rd determining unit 71, for determining that it is described that the standardization value of attribute information of the financial product is more than or equal to
User is target product data to the data of the financial product of the standardization value of the investigational data of each financial product.
Optionally, as shown in figure 8, the 3rd determining module 45 includes：
Creating unit 81, for creating the preference of the target product data and the user to each financial product
The matrix of degree；
4th determining unit 82, for determining the positive ideal solution of each target product data in the matrix and bearing
Ideal solution；
5th determining unit 83, for determining the preference of the financial product apart from the nearest production of the positive ideal solution
Product are the target recommended products.
Its operation principle is referring to above method embodiment, not repeated description herein.
Above-described is the software function module framework of server, and on the hardware configuration of server, server can lead to
Cross following manner and realize a kind of Products Show scheme；
The hardware block diagram for the server that Fig. 9 provides for the embodiment of the present application, reference picture 9, the server can include：
Processor 91, communication interface 92, memory 93 and communication bus 94；
Wherein processor 91, communication interface 92, memory 93 complete mutual communication by communication bus 94；
Optionally, communication interface 92 can be the interface of communication module, such as the interface of gsm module；
Processor 91, for configuration processor；
Memory 93, for depositing program；
Program can include program code, and described program code includes computer-managed instruction.
Processor 91 is probably a central processor CPU, or specific integrated circuit ASIC (Application
Specific Integrated Circuit), or it is arranged to implement the integrated electricity of one or more of the embodiment of the present application
Road.
Memory 93 may include high-speed RAM memory, it is also possible to also including nonvolatile memory (non-volatile
Memory), a for example, at least magnetic disk storage.
Wherein, program can be specifically used for：
The multi-dimensional data of each financial product is obtained, the multi-dimensional data includes the attribute information of the financial product,
Interest degrees of data of the user to the investigational data of each financial product and user to each financial product；
Attribute information and the user to the financial product enter professional etiquette to the investigational data of each financial product
Generalized processing, obtains the quantized data for meeting preset data form；
Interest degrees of data according to the user to each financial product, determine user to the inclined of each financial product
Good degree；
It is target product data to determine the product data for meeting preparatory condition in the quantized data；
According to the target product data and the user to the preference of each financial product, target is determined
Recommended products.
Preferably, the investigation to the attribute information and the user of the financial product to each financial product
Data carry out standardization processing, obtain the quantized data for meeting preset data form, including：
Boolean type data normalization processing is carried out to the investigational data of each financial product to the user, it is determined that described
The data attribute of investigational data.
Preferably, the interest degrees of data according to the user to each financial product, determines user to each described
The preference of financial product, including：
The quantity of financial product and user are obtained in the interest degrees of data to interest of each financial product etc.
Level；
According to the quantity of the financial product and user to the levels of interest of each financial product, user couple is determined
The preference of each financial product, wherein, each preference belongs to [0,1], and the preference sum is
1。
Preferably, the product data for determining to meet preparatory condition in the quantized data are target product data, bag
Include：
Determine that the standardization value of the attribute information of the financial product is more than or equal to the user and each finance is produced
The data of the financial product of the standardization value of the investigational data of product are target product data.
Preferably, the preference journey according to the target product data and the user to each financial product
Degree, determines target recommended products, including：
Create the matrix of the target product data and the user to the preference of each financial product；
Determine the positive ideal solution and minus ideal result of each target product data in the matrix；
Determine that the preference of the financial product recommends production apart from the nearest product of the positive ideal solution for the target
Product.
In summary, this application provides a kind of Products Show method and Products Show device, this method is according to user
To the interest degrees of data of each financial product, preference of the user to each financial product is determined, then to by lattice
The attribute information of the financial product of formula standardization processing and user screen to the investigational data of each financial product, finally,
According to the target product data and the user to the preference of each financial product, determine that target recommends production
Product.Realize and Products Show is carried out according to the interest-degree of user, and then improve the conversion ratio of Products Show.
Each embodiment is described by the way of progressive in this specification, what each embodiment stressed be and other
The difference of embodiment, between each embodiment identical similar portion mutually referring to.For device disclosed in embodiment
For, because it is corresponded to the method disclosed in Example, so description is fairly simple, related part is said referring to method part
It is bright.
Professional further appreciates that, with reference to the unit of each example of the embodiments described herein description
And algorithm steps, can be realized with electronic hardware, computer software or the combination of the two, in order to clearly demonstrate hardware and
The interchangeability of software, the composition and step of each example are generally described according to function in the above description.These
Function is performed with hardware or software mode actually, application-specific and design constraint depending on technical scheme.Specialty
Technical staff can realize described function using distinct methods to each specific application, but this realization should not
Think to exceed scope of the present application.
Directly it can be held with reference to the step of method or algorithm that the embodiments described herein describes with hardware, processor
Capable software module, or the two combination are implemented.Software module can be placed in random access memory (RAM), internal memory, read-only deposit
Reservoir (ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or technology
In any other form of storage medium well known in field.
The foregoing description of the disclosed embodiments, professional and technical personnel in the field are enable to realize or using the application.
A variety of modifications to these embodiments will be apparent for those skilled in the art, as defined herein
General Principle can be realized in other embodiments in the case where not departing from spirit herein or scope.Therefore, the application
The embodiments shown herein is not intended to be limited to, and is to fit to and principles disclosed herein and features of novelty phase one
The most wide scope caused.
Claims (10)
- A kind of 1. Products Show method, it is characterised in that applied to server, including：The multi-dimensional data of each financial product is obtained, the multi-dimensional data includes the attribute information of the financial product, user The interest degrees of data of investigational data and user to each financial product to each financial product；Attribute information and the user to the financial product standardize to the investigational data of each financial product Processing, obtains the quantized data for meeting preset data form；Interest degrees of data according to the user to each financial product, determine preference journey of the user to each financial product Degree；It is target product data to determine the product data for meeting preparatory condition in the quantized data；According to the target product data and the user to the preference of each financial product, determine that target is recommended Product.
- 2. Products Show method according to claim 1, it is characterised in that the attribute information to the financial product And the user carries out standardization processing to the investigational data of each financial product, obtains the amount for meeting preset data form Change data, including：Boolean type data normalization processing is carried out to the investigational data of each financial product to the user, determines the investigation The data attribute of data.
- 3. Products Show method according to claim 1, it is characterised in that it is described according to the user to each finance The interest degrees of data of product, preference of the user to each financial product is determined, including：Obtain the levels of interest of the quantity of financial product in the interest degrees of data and user to each financial product；According to the quantity of the financial product and user to the levels of interest of each financial product, determine user to each institute The preference of financial product is stated, wherein, each preference belongs to [0,1], and the preference sum is 1.
- 4. Products Show method according to claim 1, it is characterised in that meet in the determination quantized data pre- If the product data of condition are target product data, including：Determine that the standardization value of the attribute information of the financial product is more than or equal to the user to each financial product The data of the financial product of the standardization value of investigational data are target product data.
- 5. Products Show method according to claim 1, it is characterised in that it is described according to the target product data and The user determines target recommended products to the preference of each financial product, including：Create the matrix of the target product data and the user to the preference of each financial product；Determine the positive ideal solution and minus ideal result of each target product data in the matrix；Determine that the preference of the financial product apart from the positive nearest product of ideal solution is the target recommended products.
- A kind of 6. Products Show device, it is characterised in that including：Acquisition module, for obtaining the multi-dimensional data of each financial product, the multi-dimensional data includes the financial product Attribute information, interest degrees of data of the user to the investigational data of each financial product and user to each financial product；Processing module, the investigation number for the attribute information to the financial product and the user to each financial product According to standardization processing is carried out, the quantized data for meeting preset data form is obtained；First determining module, for the interest degrees of data according to the user to each financial product, determine user to each institute State the preference of financial product；Second determining module, for determining that the product data for meeting preparatory condition in the quantized data are target product data；3rd determining module, for the preference journey according to the target product data and the user to each financial product Degree, determines target recommended products.
- 7. Products Show device according to claim 6, it is characterised in that the processing module includes：First determining unit, for carrying out Boolean type data normalization to the investigational data of each financial product to the user Processing, determine the data attribute of the investigational data.
- 8. Products Show device according to claim 6, it is characterised in that first determining module includes：Acquiring unit, for obtaining in the interest degrees of data quantity of financial product and user to each financial product Levels of interest；Second determining unit, for the quantity according to the financial product and user to interest of each financial product etc. Level, determines preference of the user to each financial product, wherein, each preference belongs to [0,1], and described inclined Good degree sum is 1.
- 9. Products Show device according to claim 6, it is characterised in that second determining module includes：3rd determining unit, for determining that the standardization value of attribute information of the financial product is more than or equal to the user couple The data of the financial product of the standardization value of the investigational data of each financial product are target product data.
- 10. Products Show device according to claim 6, it is characterised in that the 3rd determining module includes：Creating unit, for creating the target product data and the user to the preference of each financial product Matrix；4th determining unit, for determining the positive ideal solution of each target product data and negative ideal in the matrix Solution；5th determining unit, it is institute for determining the preference of the financial product apart from the positive nearest product of ideal solution State target recommended products.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201710711944.3A CN107481058A (en) | 2017-08-18 | 2017-08-18 | A kind of Products Show method and Products Show device |
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| Application Number | Priority Date | Filing Date | Title |
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| CN201710711944.3A CN107481058A (en) | 2017-08-18 | 2017-08-18 | A kind of Products Show method and Products Show device |
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| CN107481058A true CN107481058A (en) | 2017-12-15 |
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| CN201710711944.3A Pending CN107481058A (en) | 2017-08-18 | 2017-08-18 | A kind of Products Show method and Products Show device |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109299356A (en) * | 2018-08-22 | 2019-02-01 | 中国平安人寿保险股份有限公司 | Activity recommendation method, apparatus, electronic equipment and storage medium based on big data |
| CN111681114A (en) * | 2020-06-02 | 2020-09-18 | 重庆第二师范学院 | Financial classification management system and working method thereof |
| CN111814032A (en) * | 2019-04-11 | 2020-10-23 | 阿里巴巴集团控股有限公司 | Cold start recommendation method and device and electronic equipment |
| CN111815440A (en) * | 2020-09-14 | 2020-10-23 | 杭州连银科技有限公司 | Loan supermarket marketing data processing system |
| CN112200669A (en) * | 2020-09-11 | 2021-01-08 | 许宗宝 | Intelligent financial investment management system based on market trading big data |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103049865A (en) * | 2012-12-17 | 2013-04-17 | 中国农业大学 | Method and system for initiatively recommending product information service |
| US20130325745A1 (en) * | 2012-06-04 | 2013-12-05 | Apple Inc. | Providing Feedback via a Social Network from a Media Distribution Platform |
| CN104463630A (en) * | 2014-12-11 | 2015-03-25 | 新一站保险代理有限公司 | Product recommendation method and system based on characteristics of online shopping insurance products |
-
2017
- 2017-08-18 CN CN201710711944.3A patent/CN107481058A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130325745A1 (en) * | 2012-06-04 | 2013-12-05 | Apple Inc. | Providing Feedback via a Social Network from a Media Distribution Platform |
| CN103049865A (en) * | 2012-12-17 | 2013-04-17 | 中国农业大学 | Method and system for initiatively recommending product information service |
| CN104463630A (en) * | 2014-12-11 | 2015-03-25 | 新一站保险代理有限公司 | Product recommendation method and system based on characteristics of online shopping insurance products |
Non-Patent Citations (1)
| Title |
|---|
| 罗斯: "债券类金融产品推荐系统的设计与实现", 《中国优秀硕士学位论文全文数据库》 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109299356A (en) * | 2018-08-22 | 2019-02-01 | 中国平安人寿保险股份有限公司 | Activity recommendation method, apparatus, electronic equipment and storage medium based on big data |
| CN109299356B (en) * | 2018-08-22 | 2024-02-06 | 中国平安人寿保险股份有限公司 | Activity recommendation method and device based on big data, electronic equipment and storage medium |
| CN111814032A (en) * | 2019-04-11 | 2020-10-23 | 阿里巴巴集团控股有限公司 | Cold start recommendation method and device and electronic equipment |
| CN111681114A (en) * | 2020-06-02 | 2020-09-18 | 重庆第二师范学院 | Financial classification management system and working method thereof |
| CN112200669A (en) * | 2020-09-11 | 2021-01-08 | 许宗宝 | Intelligent financial investment management system based on market trading big data |
| CN111815440A (en) * | 2020-09-14 | 2020-10-23 | 杭州连银科技有限公司 | Loan supermarket marketing data processing system |
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Application publication date: 20171215 |