CN109117445B - Information correlation method in beauty information recommendation processing process - Google Patents
Information correlation method in beauty information recommendation processing process Download PDFInfo
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- CN109117445B CN109117445B CN201710488711.1A CN201710488711A CN109117445B CN 109117445 B CN109117445 B CN 109117445B CN 201710488711 A CN201710488711 A CN 201710488711A CN 109117445 B CN109117445 B CN 109117445B
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Abstract
The invention relates to an information association method in a cosmetic information recommendation processing process, which comprises the steps of providing an information association model to a system and further comprises the following steps: step S1, inputting a plurality of real-time customer information groups into the system; step S2, counting the association times between every two information parameters in the real-time customer information group; step S3, judging whether the ratio of the number of association times between every two information parameters to the number of the real-time customer information groups is more than a preset probability; if yes, go to step S4; if not, returning to the step S1; step S4, setting the associated information parameters as default association in the information association model; step S5, after the information association model is adopted to carry out default association processing on the next real-time customer information group, the recommendation processing model is adopted to map to obtain the recommended product information; the statistics can be carried out through the association times among the information parameters, and the information processing efficiency of the system is improved.
Description
Technical Field
The invention relates to an information association method, in particular to an information association method in a beauty information recommendation processing process.
Background
With the continuous temperature rise of the beauty industry, systems used for beauty are continuously upgraded, so that the increasingly huge search requirements of beauty databases and beauty information are met.
The information input and processing speed of the traditional beauty information recommendation system is limited in various aspects, the speed is slower and slower when the information quantity or the database is increased day by day, even if the repetition rate of the information is high, the traditional system needs to perform a complete input and processing process, and the efficiency is low.
Disclosure of Invention
Aiming at the problems, the invention provides an information correlation method in a beauty information recommendation processing process, which comprises the steps of providing a storage module pre-storing a recommendation processing model and a system of the storage module, wherein the recommendation processing model is mapped according to standard customer information groups to obtain recommended product information, and each standard customer information group is respectively mapped with one piece of recommended product information; wherein, including providing an information association model to the system, further includes:
step S1, inputting a plurality of real-time customer information sets into the system;
step S2, counting the association times between every two information parameters in the real-time customer information group;
step S3, judging whether the ratio of the number of the association times between every two information parameters to the number of the real-time customer information groups is more than a preset probability;
if yes, go to step S4;
if not, returning to the step S1;
step S4, setting the associated information parameters as default association in the information association model;
and step S5, performing default association processing on the next real-time customer information group by using the information association model, and mapping by using the recommendation processing model to obtain the recommended product information.
In the information association method, the preset probability is 80% to 90%.
In the above information association method, the system includes an input module, a processing module and a storage module, the input module is connected to the processing module, and the processing module is connected to the storage module;
the information association model and the recommendation processing model are stored in the storage module;
in step S1, inputting the real-time customer information group into the system through the input module;
in step S5, the processing module calls the information association model and the recommendation processing model from the storage module.
In the above information associating method, the input module is a keyboard.
In the above information associating method, in step S5, the default associating process specifically includes:
and when any one of the information parameters associated by default in the next real-time customer information group is input into the system, generating the information parameters associated by default in the real-time customer information group.
In the above information associating method, in step S5, the information associating model is used to perform default associating processing on the next real-time customer information group, and the information parameter generated by default is checked against the corresponding information parameter in the input real-time customer information group.
In the above information associating method, the system has a display interface;
in step S5, when any one of the information parameters associated by default in the next real-time customer information group is input into the system, the input information parameter is displayed.
In the above information associating method, in step S5, the input information parameter is displayed, and the information parameter generated by default association is displayed.
Has the advantages that: the information association method in the beauty information recommendation processing process can be used for counting through the association times among the information parameters, and the information processing efficiency of the system is improved.
Drawings
Fig. 1 is a flowchart illustrating steps of an information association method in a cosmetic information recommendation process according to an embodiment of the present invention.
Detailed Description
The invention is further illustrated with reference to the following figures and examples.
In a preferred embodiment, as shown in fig. 1, an information association method in a beauty information recommendation process is provided, which includes providing a storage module pre-storing a recommendation processing model and a system of the storage module, where the recommendation processing model obtains recommended product information according to a standard customer information set mapping, and each standard customer information set maps a piece of recommended product information; the method comprises the steps of providing an information association model to a system, and further comprises the following steps:
step S1, inputting a plurality of real-time customer information groups into the system;
step S2, counting the association times between every two information parameters in the real-time customer information group;
step S3, judging whether the ratio of the number of association times between every two information parameters to the number of the real-time customer information groups is more than a preset probability;
if yes, go to step S4;
if not, returning to the step S1;
step S4, setting the associated information parameters as default association in the information association model;
and step S5, performing default association processing on the next real-time customer information group by using the information association model, and mapping by using the recommendation processing model to obtain recommended product information.
In a preferred embodiment, the predetermined probability may be 80% to 90%, but this is only a preferable case and can be set according to actual needs.
In a preferred embodiment, the system may include an input module, a processing module and a storage module, the input module being connected to the processing module, the processing module being connected to the storage module;
the information association model and the recommendation processing model are stored in the storage module;
in step S1, inputting the real-time customer information group into the system through the input module;
in step S5, the processing module calls the information association model and the recommendation processing model from the storage module.
In the above embodiment, the input module may be a keyboard, but this is only a preferred case and should not be construed as a limitation to the present invention.
In a preferred embodiment, in step S5, the default association process specifically includes:
when any one of the default associated information parameters in the next real-time customer information set is input into the system, the default associated information parameter is generated in the real-time customer information set.
In the above technical solution, each real-time customer information group should include a plurality of information parameters, for example, the information parameters may include "customer age" and "customer income status", and if the probability of the number of association between the information parameter "customer age is 20 years" and the information parameter "customer income status is general" reaches a preset probability, the information parameter may be associated as "customer income status is general" by default through the information association model when "customer age is 20 years" is input, so as to improve the recording efficiency of the real-time customer information group.
In the above embodiment, in step S5, it is preferable that the default association process is performed on the next real-time customer information group by using the information association model, and the information parameter generated by default is checked against the corresponding information parameter in the input real-time customer information group.
In the above-mentioned technical solution, for example, if the information parameter "age of customer is 20" is the first information parameter in the input real-time customer information group, the information parameter "income status of customer is general" may be generated by default association, and the information parameter generated by the default association is not necessarily completely accurate, so that it may be checked against the corresponding information parameter in the input real-time customer information group, that is, against the input information parameter related to income status of customer.
In the above embodiment, preferably, the system may have a display interface;
in step S5, when any one of the default associated information parameters in the next real-time customer information group is input into the system, the input information parameter is displayed.
In the above embodiment, preferably, in step S5, the input information parameter may be displayed, and the information parameter generated by the default association may be displayed at the same time, at this time, if the information parameter generated by the default association has an actual entrance or exit, the information parameter may be found in time.
While the specification concludes with claims defining exemplary embodiments of particular structures for practicing the invention, it is believed that other modifications will be made in the spirit of the invention. While the above invention sets forth presently preferred embodiments, these are not intended as limitations.
Various alterations and modifications will no doubt become apparent to those skilled in the art after having read the above description. Therefore, the appended claims should be construed to cover all such variations and modifications as fall within the true spirit and scope of the invention. Any and all equivalent ranges and contents within the scope of the claims should be considered to be within the intent and scope of the present invention.
Claims (8)
1. An information association method in a beauty information recommendation processing process comprises the steps of providing a storage module pre-storing a recommendation processing model and a system of the storage module, wherein the recommendation processing model is mapped according to standard customer information groups to obtain recommended product information, and each standard customer information group is mapped with one piece of the recommended product information; the method is characterized by comprising the steps of providing an information association model to the system, and further comprising the following steps:
step S1, inputting a plurality of real-time customer information sets into the system;
step S2, counting the association times between every two information parameters in the real-time customer information group;
step S3, judging whether the ratio of the number of the association times between every two information parameters to the number of the real-time customer information groups is more than a preset probability;
if yes, go to step S4;
if not, returning to the step S1;
step S4, setting the associated information parameters as default association in the information association model;
and step S5, performing default association processing on the next real-time customer information group by using the information association model, and mapping by using the recommendation processing model to obtain the recommended product information.
2. The information correlation method according to claim 1, wherein the predetermined probability is 80% to 90%.
3. The information correlation method according to claim 1, wherein the system comprises an input module, a processing module and a storage module, the input module is connected with the processing module, and the processing module is connected with the storage module;
the information association model and the recommendation processing model are stored in the storage module;
in step S1, inputting the real-time customer information group into the system through the input module;
in step S5, the processing module calls the information association model and the recommendation processing model from the storage module.
4. The information correlation method according to claim 3, wherein the input module is a keyboard.
5. The information association method according to claim 1, wherein in the step S5, the default association processing specifically includes:
and when any one of the information parameters associated by default in the next real-time customer information group is input into the system, generating the information parameters associated by default in the real-time customer information group.
6. The information associating method according to claim 5, wherein in step S5, the default association processing is performed on the next real-time customer information group by using the information associating model, and the information parameter generated by default is checked against the corresponding information parameter in the input real-time customer information group.
7. The information association method according to claim 5, wherein the system has a display interface;
in step S5, when any one of the information parameters associated by default in the next real-time customer information group is input into the system, the input information parameter is displayed.
8. The information associating method according to claim 7, wherein in the step S5, the information parameter generated by default association is displayed while the input information parameter is displayed.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101408960A (en) * | 2007-10-12 | 2009-04-15 | 阿里巴巴集团控股有限公司 | Method and apparatus for recommendation of personalized information |
| CN101420460A (en) * | 2008-12-08 | 2009-04-29 | 腾讯科技（深圳）有限公司 | Method and apparatus for creating aggregation container and user matching aggregation container |
| CN102542489A (en) * | 2011-12-27 | 2012-07-04 | 纽海信息技术（上海）有限公司 | Recommendation method based on user interest association |
| US8775471B1 (en) * | 2005-04-14 | 2014-07-08 | AudienceScience Inc. | Representing user behavior information |
| CN104954410A (en) * | 2014-03-31 | 2015-09-30 | 腾讯科技（北京）有限公司 | Message pushing method, device thereof and server |
| CN106779923A (en) * | 2016-11-30 | 2017-05-31 | 广州市万表科技股份有限公司 | Recommend method and device |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP5917712B2 (en) * | 2011-12-19 | 2016-05-18 | インテル コーポレイション | Smart device support transaction |
| CN105224547A (en) * | 2014-06-05 | 2016-01-06 | 阿里巴巴集团控股有限公司 | The disposal route of object set and satisfaction thereof and device |
-
2017
- 2017-06-23 CN CN201710488711.1A patent/CN109117445B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8775471B1 (en) * | 2005-04-14 | 2014-07-08 | AudienceScience Inc. | Representing user behavior information |
| CN101408960A (en) * | 2007-10-12 | 2009-04-15 | 阿里巴巴集团控股有限公司 | Method and apparatus for recommendation of personalized information |
| CN101420460A (en) * | 2008-12-08 | 2009-04-29 | 腾讯科技（深圳）有限公司 | Method and apparatus for creating aggregation container and user matching aggregation container |
| CN102542489A (en) * | 2011-12-27 | 2012-07-04 | 纽海信息技术（上海）有限公司 | Recommendation method based on user interest association |
| CN104954410A (en) * | 2014-03-31 | 2015-09-30 | 腾讯科技（北京）有限公司 | Message pushing method, device thereof and server |
| CN106779923A (en) * | 2016-11-30 | 2017-05-31 | 广州市万表科技股份有限公司 | Recommend method and device |
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Effective date of registration: 20211206 Address after: 310000 room 1-304, building 2, Xinming commercial center, Gongshu District, Hangzhou City, Zhejiang Province Patentee after: Hangzhou Taitai Enterprise Management Co.,Ltd. Address before: Room 303, building 6, 156 Wuchang Avenue, Wuchang Street, Yuhang District, Hangzhou City, Zhejiang Province 310000 Patentee before: HANGZHOU MEIJIE TECHNOLOGY Co.,Ltd. |