CN112116421A - Method and system for optimizing and recommending commodities in self-built welfare mall - Google Patents
Method and system for optimizing and recommending commodities in self-built welfare mall Download PDFInfo
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Abstract
The invention relates to a method and a system for optimizing and recommending commodities in a self-built welfare mall, wherein the method comprises the following steps: inputting a name of a commodity to be purchased in a shopping APP search box; selecting some attributes of the commodity, and giving corresponding weights to the attributes according to the attributes of the commodity; judging similarity values between the similar commodities and the attributes of the commodities; according to the weight and the similarity value of the correlation attributes between the commodities, the similarity between the same class of commodities is calculated by weighted summation; and respectively comparing the similarity between the similar commodities, and recommending a plurality of commodities with the highest similarity to the consumer. The invention can accurately recommend the commodities with higher similarity according to the search record and the browsing record of the user, can flexibly adjust the weight of the related attributes, and can recommend welfare commodities more pertinently, so that consumers can shop more conveniently, quickly and accurately.
Description
Technical Field
The invention belongs to the technical field of internet, and particularly relates to a method and a system for optimizing and recommending commodities in a self-built welfare mall.
Background
Along with the continuous development and adjustment of social economy, various commodities are popular (national products, marine products, mountain village products and the like, and the types of the commodities relate to various aspects), along with the continuous surge of the commodities, the commodities are closely related to the wild shopping of a shopper, the shopping in the past is that the shopper visits shopping malls and all shopping malls are compared, then the shopping of an entity shop is very limited, on one hand, the consumer feels tired while shopping, on the other hand, the shopping is only limited to a certain area for purchasing, the purchased commodities are relatively single, and the appearance of online shopping in the last decade raises the enthusiasm of online shopping of the consumer.
The online shopping not only enriches the shopping, but also greatly reduces the shopping fatigue of the consumers, so that the consumers can see and buy the commodities all over the world at home.
However, the existing online shopping APP (Taobao, Jingdong, Wei article meeting and the like) has a relatively obvious defect, namely, when a shopper purchases the heart instrument commodity, the shopper searches keywords in a search box to obtain a recommended commodity, so that the number of commodity lists presented to the shopper is huge, the similarity among the commodities cannot be guaranteed, and the shopper is provided with a purchase problem in the face of the huge quantity of commodities, namely, the shopper cannot timely and accurately purchase the heart instrument product, so that the subsequent procedures of returning and changing goods are increased, and further more invariability is brought to the shopper.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a method and a system for optimizing and recommending commodities in a self-built welfare mall.
In order to achieve the purpose, the invention adopts the technical scheme that: a method for optimizing and recommending commodities in a self-built welfare mall comprises the following steps:
(1) inputting a name of a commodity to be purchased in a shopping APP search box;
(2) selecting some attributes of the commodity, and giving corresponding weights to the attributes according to the attributes of the commodity;
(3) judging similarity values between the similar commodities and the attributes of the commodities;
(4) according to the weight and the similarity value of the correlation attributes between the commodities, the similarity between the same class of commodities is calculated by weighted summation;
(5) and respectively comparing the similarity between the similar commodities, and recommending a plurality of commodities with the highest similarity to the consumer.
Optimally, the attributes of the commodity in the step (2) comprise the type, color, shape, price and the like of the commodity.
Optimally, in the step (3), the similarity value is 1 when the attributes of the commodities are the same, and is 0 when the attributes of the commodities are different.
Optimally, the method for calculating the similarity in the step (4) comprises the following steps: the similarity is x + y +. the similarity is n.
Optimally, the step (5) can also calculate the commodities with higher similarity to the browsing records according to the browsing records of the user, and then recommend the commodities to the consumer.
According to another aspect of the present invention, there is provided a system for optimizing and recommending commodities in a self-built welfare mall, comprising: it includes:
the weight module is used for giving weights to all attributes of the selected commodities;
the calculation module is used for calculating the similarity between the similar commodities according to the weight and the similarity value;
and the recommending module is used for recommending the products with the highest similarity to the consumers.
Due to the application of the technical scheme, compared with the prior art, the invention has the following advantages: the method and the system for optimizing and recommending the commodities in the self-built welfare mall preferentially recommend the commodities with high similarity to the consumers by selecting certain attributes of the commodities and giving corresponding weights to the commodities according to the attributes of the commodities and calculating the similarity between the commodities by using a weighted summation method, so that the consumers can more conveniently, more accurately and more quickly shop. The invention can also accurately recommend the commodities with higher similarity according to the browsing records of the user, can flexibly adjust the weight of the related attributes and recommend welfare commodities in a more targeted manner.
Drawings
FIG. 1 is a flow chart of a method for optimizing and recommending merchandise in a self-building welfare mall in accordance with the present invention;
fig. 2 is a schematic structural diagram of a system for optimizing and recommending commodities in a self-built welfare mall according to the present invention.
Detailed Description
The invention will be further described with reference to examples of embodiments shown in the drawings to which the invention is attached.
As shown in the attached figure 1, the method for optimizing and recommending commodities in the self-built welfare mall comprises the following steps:
in step S1, the name of the commodity to be purchased is entered in the shopping APP search box.
Alternatively, the consumer may enter the name of the item to be purchased into the search box, for example, a pen, and the consumer may enter a "ball point pen" into the search box.
And step S2, selecting some attributes of the commodity, and giving corresponding weight to the attributes according to the attributes of the commodity.
Optionally, the attributes of the commodity include, but are not limited to, the type, shape, price, color, etc. of the commodity, and different weights are given to the commodity according to the attributes, taking a pen as an example, and the attributes of the pen are classified into types (ball point pen, pencil, etc.), colors (red, black, blue, etc.) and line widths of the pen point (0.2mm, 0.5mm, etc.). Therefore, the weight of the pen type is set to 0.5, the weight of the pen color is set to 0.3, and the weight of the pen point line width is set to 0.2.
In step S3, the similarity value between the similar product and each attribute of the product is determined.
Optionally, the similarity value is 1 when the commodity attributes are the same, and is 0 when the commodity attributes are different, and still taking a pen as an example, three pens (pen A: ball-point pen, black and 0.5 mm; pen B: pen, black and 0.2 mm; pen C: ball-point pen, blue and 0.5mm) are provided, wherein the similarity value of the pen A and the pen B is 0 on the type attribute, the similarity value of the pen A and the pen B is 1 on the color attribute, and the similarity value of the pen point is 0 on the line amplitude attribute; the pen A and the pen C have a similarity value of 1 in type attribute, a similarity value of 0 in color attribute and a similarity value of 1 in nib linewidth attribute.
And step S4, calculating the similarity between each two similar commodities by weighted summation according to the weight and the similarity value of the correlation attributes between the commodities.
In the present embodiment, the similarity is the weight x × the similarity value x + the weight y × the similarity value y + -. Therefore, by the above calculation formula of the similarity, it is possible to obtain:
similarity between pen A and pen B: 0 x 0.5+1 x 0.3+0 x 0.2 ═ 0.3
Similarity between pen a and pen C: 1 × 0.5+ 0.3+1 × 0.2 ═ 0.7
And step S5, respectively comparing the similarity between the similar commodities, and recommending a plurality of commodities with the highest similarity to the consumers.
Optionally, as can be seen from the comparison, the pen C is more similar to the pen a than the pen a, and therefore, when the search box clicks and browses the pen a, the pen C is preferentially recommended instead of the pen B.
Furthermore, the commodities with higher similarity can be accurately recommended according to the browsing records of the user, so that the user can conveniently and quickly search the commodities browsed before or with the highest similarity.
Optionally, the user has browsed 5 commodities recently, there is a relationship between 50 commodities and one or more of the recently browsed 5 commodities, the similarity between the 50 commodities and one or more of the recently browsed 5 commodities is calculated, and then 10 or more commodities with the highest similarity are recommended to the user according to the size of the similarity.
As shown in fig. 2, the system for optimizing and recommending commodities in a welfare mall according to the present invention includes:
the weight module is used for giving weights to all attributes of the selected commodities;
the calculation module is used for calculating the similarity between the similar commodities according to the weight and the similarity value;
and the recommending module is used for recommending the products with the highest similarity to the consumers.
Specifically, according to the system provided by the above embodiment of the present invention, when a consumer purchases a commodity, the name of the commodity to be purchased is input into the search box, and the weighting module assigns a corresponding weight to the attribute of the selected commodity; then the calculation module calculates the similarity value and similarity between the attributes of the same type of commodities; the recommending module recommends a plurality of commodities with highest similarity to the consumer.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and the purpose thereof is to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the protection scope of the present invention. All equivalent changes and modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.
Claims (6)
1. A method for optimizing and recommending commodities in a self-built welfare mall is characterized by comprising the following steps:
(1) inputting a name of a commodity to be purchased in a shopping APP search box;
(2) selecting some attributes of the commodity, and giving corresponding weights to the attributes according to the attributes of the commodity;
(3) judging similarity values between the similar commodities and the attributes of the commodities;
(4) according to the weight and the similarity value of the correlation attributes between the commodities, the similarity between the same class of commodities is calculated by weighted summation;
(5) and respectively comparing the similarity between the similar commodities, and recommending a plurality of commodities with the highest similarity to the consumer.
2. The method of claim 1, wherein the method comprises: the attributes of the goods in the step (2) comprise the type, color, shape, price and the like of the goods.
3. The method for optimizing and recommending commodities in self-built welfare mall according to claim 1 or 2, wherein: and (4) in the step (3), the similarity value is 1 when the attributes of the commodities are the same, and is 0 when the attributes of the commodities are different.
4. The method for optimizing and recommending commodities in self-built welfare mall according to claim 1 or 2, wherein: the method for calculating the similarity in the step (4) comprises the following steps: the similarity is x + y +. the similarity is n.
5. The method of claim 1, wherein the method comprises: and (5) calculating the commodities with higher similarity to the browsing records according to the browsing records of the user, and recommending the commodities to the consumer.
6. A system for optimizing and recommending commodities in a self-built welfare mall is characterized in that: it includes:
the weight module is used for giving weights to all attributes of the selected commodities;
the calculation module is used for calculating the similarity between the similar commodities according to the weight and the similarity value;
and the recommending module is used for recommending the products with the highest similarity to the consumers.
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| CN202010941884.6A CN112116421A (en) | 2020-09-09 | 2020-09-09 | Method and system for optimizing and recommending commodities in self-built welfare mall |
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| CN202010941884.6A CN112116421A (en) | 2020-09-09 | 2020-09-09 | Method and system for optimizing and recommending commodities in self-built welfare mall |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113065919A (en) * | 2021-04-08 | 2021-07-02 | 北京京东乾石科技有限公司 | Data pushing method and device |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102542490A (en) * | 2011-12-27 | 2012-07-04 | 纽海信息技术（上海）有限公司 | Commodity recommendation method based on model matching |
| CN105913290A (en) * | 2016-07-01 | 2016-08-31 | 中国传媒大学 | Commodity matching recommending method and recommending system |
| CN106708821A (en) * | 2015-07-21 | 2017-05-24 | 广州市本真网络科技有限公司 | User personalized shopping behavior-based commodity recommendation method |
| CN109919728A (en) * | 2019-03-12 | 2019-06-21 | 贵州大学 | A kind of Method of Commodity Recommendation in difference quotient city |
| CN109934684A (en) * | 2019-03-20 | 2019-06-25 | 上海证大喜马拉雅网络科技有限公司 | A kind of Method of Commodity Recommendation, device, terminal and storage medium |
| CN109978580A (en) * | 2017-12-28 | 2019-07-05 | 北京京东尚科信息技术有限公司 | Object recommendation method, apparatus and computer readable storage medium |
| CN110852818A (en) * | 2018-08-20 | 2020-02-28 | 北京京东尚科信息技术有限公司 | Commodity sorting method and device and computer-readable storage medium |
| CN111445302A (en) * | 2019-01-17 | 2020-07-24 | 北京京东尚科信息技术有限公司 | Commodity sorting method, system and device |
-
2020
- 2020-09-09 CN CN202010941884.6A patent/CN112116421A/en active Pending
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102542490A (en) * | 2011-12-27 | 2012-07-04 | 纽海信息技术（上海）有限公司 | Commodity recommendation method based on model matching |
| CN106708821A (en) * | 2015-07-21 | 2017-05-24 | 广州市本真网络科技有限公司 | User personalized shopping behavior-based commodity recommendation method |
| CN105913290A (en) * | 2016-07-01 | 2016-08-31 | 中国传媒大学 | Commodity matching recommending method and recommending system |
| CN109978580A (en) * | 2017-12-28 | 2019-07-05 | 北京京东尚科信息技术有限公司 | Object recommendation method, apparatus and computer readable storage medium |
| CN110852818A (en) * | 2018-08-20 | 2020-02-28 | 北京京东尚科信息技术有限公司 | Commodity sorting method and device and computer-readable storage medium |
| CN111445302A (en) * | 2019-01-17 | 2020-07-24 | 北京京东尚科信息技术有限公司 | Commodity sorting method, system and device |
| CN109919728A (en) * | 2019-03-12 | 2019-06-21 | 贵州大学 | A kind of Method of Commodity Recommendation in difference quotient city |
| CN109934684A (en) * | 2019-03-20 | 2019-06-25 | 上海证大喜马拉雅网络科技有限公司 | A kind of Method of Commodity Recommendation, device, terminal and storage medium |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113065919A (en) * | 2021-04-08 | 2021-07-02 | 北京京东乾石科技有限公司 | Data pushing method and device |
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