CN113095876A - Commodity recommendation method and device - Google Patents
Commodity recommendation method and device Download PDFInfo
- Publication number
- CN113095876A CN113095876A CN202110381711.8A CN202110381711A CN113095876A CN 113095876 A CN113095876 A CN 113095876A CN 202110381711 A CN202110381711 A CN 202110381711A CN 113095876 A CN113095876 A CN 113095876A
- Authority
- CN
- China
- Prior art keywords
- commodity
- identification
- recommended
- identification category
- sequence
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- 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
- G06Q30/0255—Targeted advertisements based on user history
Landscapes
- Business, Economics & Management (AREA)
- Strategic Management (AREA)
- Engineering & Computer Science (AREA)
- Accounting & Taxation (AREA)
- Development Economics (AREA)
- Finance (AREA)
- Economics (AREA)
- Game Theory and Decision Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses a commodity recommendation method and a device, the method comprises the steps of obtaining a recommended commodity sequence of a user, wherein the recommended commodity sequence comprises a commodity ID, a commodity name, an identification category and a sequencing score, reordering the recommended commodity sequence according to the identification category and the latest purchase date of a commodity purchased by the user and the identification category and the sequencing score of each commodity in the recommended commodity sequence to obtain a recommendation result, and sending the recommendation result to the user. By identifying the purchased commodities and the re-purchasing period of the purchased commodities, the arrangement sequence of the recommended commodities is optimized, the click rate of the recommended commodities is improved, and the shopping experience of the user is improved.
Description
Technical Field
The invention relates to the technical field of intelligent recommendation, in particular to a commodity recommendation method and device.
Background
The traditional recommendation algorithm analyzes the commodities which are interested by the user based on data of shopping, browsing, collecting and the like of the user, so as to construct a recommendation sequence. However, these methods often recommend the same kind of products that the user has purchased, such as shampoo of brand a and refrigerator of brand B, and the system also recommends shampoo of other brands and refrigerator, and the product recommendation is limited, which results in a reduction in the click rate of the recommended products.
The reason for this is that it is difficult for the system to identify which items belong to the same category.
Disclosure of Invention
The embodiment of the invention provides a commodity recommendation method and a commodity recommendation device, which are used for optimizing the arrangement sequence of recommended commodities, improving the click rate of the recommended commodities and improving the shopping experience of a user by identifying the purchased commodities and the reconstruction period of the commodities.
In a first aspect, an embodiment of the present invention provides a commodity recommendation method, including:
acquiring a recommended commodity sequence of a user, wherein the recommended commodity sequence comprises a commodity ID, a commodity name, an identification category and a sequencing score;
reordering the recommended commodity sequence according to the identification category of the commodity purchased by the user, the latest purchase date and the identification category and the ordering score of each commodity in the recommended commodity sequence to obtain a recommended result;
and sending the recommendation result to the user.
According to the technical scheme, the commodity purchased by the user and the re-purchasing period of the commodity are identified, the arrangement sequence of the recommended commodities is optimized, the click rate of the recommended commodities is improved, and the shopping experience of the user is improved.
Optionally, the reordering the recommended commodity sequence according to the identification category of the commodity purchased by the user, the latest purchase date, and the identification category and the ranking score of each commodity in the recommended commodity sequence to obtain a recommended result includes:
calculating the identification category in the re-purchasing period based on the identification category of the commodity purchased by the user and the latest purchasing date;
determining commodities in the recommended commodity sequence, which are the same as the identification categories in the re-purchasing period, according to the identification categories in the re-purchasing period;
and reducing the ranking scores of the commodities in the recommended commodity sequence, which are the same as the identification categories in the re-purchasing period, and generating a recommendation result after re-ranking.
Optionally, before the obtaining of the recommended commodity sequence of the user, the method further includes:
acquiring commodity information of newly warehoused commodities;
identifying the identification category information of the newly warehoused commodities according to the commodity information, and updating the identification category information of the newly warehoused commodities into the identification category of the commodity information; the identification category information includes an identification category name and a repurchase period.
Optionally, the method further includes:
if the identification category name in the identification category information is called as a new identification category name, configuring a re-purchasing period corresponding to the new identification category name; and updating the re-purchasing period corresponding to the new identification category name into the identification category information.
Optionally, the recommendation result is a first ranked commodity in the reordered recommended commodity sequence.
In a second aspect, an embodiment of the present invention provides a product recommendation device, including:
the system comprises an acquisition unit, a display unit and a control unit, wherein the acquisition unit is used for acquiring a recommended commodity sequence of a user, and the recommended commodity sequence comprises a commodity ID, a commodity name, an identification category and a sequencing score;
the processing unit is used for reordering the recommended commodity sequence according to the identification category of the commodity purchased by the user, the latest purchase date and the identification category and the ordering score of each commodity in the recommended commodity sequence to obtain a recommended result; and sending the recommendation result to the user.
Optionally, the processing unit is specifically configured to:
calculating the identification category in the re-purchasing period based on the identification category of the commodity purchased by the user and the latest purchasing date;
determining commodities in the recommended commodity sequence, which are the same as the identification categories in the re-purchasing period, according to the identification categories in the re-purchasing period;
and reducing the ranking scores of the commodities in the recommended commodity sequence, which are the same as the identification categories in the re-purchasing period, and generating a recommendation result after re-ranking.
Optionally, the processing unit is further configured to:
before the recommended commodity sequence of the user is obtained, commodity information of a newly warehoused commodity is obtained;
identifying the identification category information of the newly warehoused commodities according to the commodity information, and updating the identification category information of the newly warehoused commodities into the identification category of the commodity information; the identification category information includes an identification category name and a repurchase period.
Optionally, the processing unit is further configured to:
if the identification category name in the identification category information is called as a new identification category name, configuring a re-purchasing period corresponding to the new identification category name; and updating the re-purchasing period corresponding to the new identification category name into the identification category information.
Optionally, the recommendation result is a first ranked commodity in the reordered recommended commodity sequence.
In a third aspect, an embodiment of the present invention further provides a computing device, including:
a memory for storing program instructions;
and the processor is used for calling the program instructions stored in the memory and executing the commodity recommendation method according to the obtained program.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable non-volatile storage medium, which includes computer-readable instructions, and when the computer-readable instructions are read and executed by a computer, the computer is caused to execute the above commodity recommendation method.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic diagram of a system architecture according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of a commodity recommendation method according to an embodiment of the present invention;
fig. 3 is a schematic diagram of an information processing flow of a product category management system according to an embodiment of the present invention;
fig. 4 is a schematic diagram of an information processing flow of a recommendation result optimization system according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of a commodity recommending apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a system architecture provided in an embodiment of the present invention. As shown in fig. 1, the system architecture may be a server 100, and the server 100 may include a processor 110, a communication interface 120, and a memory 130.
The communication interface 120 is used for communicating with a terminal device, and transceiving information transmitted by the terminal device to implement communication.
The processor 110 is a control center of the server 100, connects various parts of the entire server 100 using various interfaces and lines, performs various functions of the server 100 and processes data by running or executing software programs and/or modules stored in the memory 130 and calling data stored in the memory 130. Alternatively, processor 110 may include one or more processing units.
The memory 130 may be used to store software programs and modules, and the processor 110 executes various functional applications and data processing by operating the software programs and modules stored in the memory 130. The memory 130 may mainly include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function, and the like; the storage data area may store data created according to a business process, and the like. Further, the memory 130 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other volatile solid state storage device.
It should be noted that the structure shown in fig. 1 is only an example, and the embodiment of the present invention is not limited thereto.
Based on the above description, fig. 2 shows in detail a flow of a product recommendation method according to an embodiment of the present invention, where the flow may be executed by a product recommendation device.
As shown in fig. 2, the process specifically includes:
In the embodiment of the present invention, the recommended article sequence includes, but is not limited to, an article ID, an article name, an identification category, and a ranking score.
When a recommended commodity sequence of a user is obtained, the commodity needs to be subjected to category management, and the method is mainly used for warehousing new commodities. Specifically, commodity information of a newly warehoused commodity is acquired, identification category information of the newly warehoused commodity is identified according to the commodity information, the identification category information of the newly warehoused commodity is updated to an identification category of the commodity information, and the identification category information comprises an identification category name and a repurchase period. If the identification category name in the identification category information is called as a new identification category name, configuring a re-purchasing period corresponding to the new identification category name; and updating the re-purchasing period corresponding to the new identification category name into the identification category information.
The above commodity information is exemplified as follows, including:
1) and a commodity number: each commodity has a unique number;
2) and the commodity name: name and description of the commodity;
3) first-level standard category: predefining names of primary standard categories;
4) and a second-level standard category: predefining names of secondary standard categories;
5) and identifying the category: automatically generated categories.
Specifically, the results are shown in Table 1.
TABLE 1
Identification of the categories of goods:
based on the commodity name, standard category and other information in the commodity information, the identification category is automatically generated by using an algorithm, and the algorithm may include:
(one) a rule-based method;
and (II) a machine learning-based method.
Regarding the identification category information:
an example of the identification category information may be as shown in table 2, and the identification category information may include an identification category and a repurchase period.
TABLE 2
| Identifying categories | Repeat purchasing cycle (sky) |
| Shampoo liquid | 30 |
| Shower gel | 30 |
| Hair conditioner | 30 |
Specifically, the identification category in the re-purchasing period is calculated based on the identification category and the latest purchasing date of the commodities purchased by the user, then the commodities in the recommended commodity sequence, which are the same as the identification category in the re-purchasing period, are determined according to the identification category in the re-purchasing period, and finally the ranking score of the commodities in the recommended commodity sequence, which are the same as the identification category in the re-purchasing period, is reduced, and the recommendation result is generated after the ranking is performed again.
That is, after obtaining the recommended commodity sequence of the user, the recommended commodity sequence may be optimized according to the identification category and the re-purchasing period of the commodity purchased by the user.
In a specific implementation process, the scheme of the embodiment of the invention can realize the commodity recommendation process through the commodity category management system and the recommendation result optimization system, and can be specifically divided into an information processing process of the commodity category management system and an information processing process of the recommendation result optimization system.
As shown in fig. 3, the product category management system may include a product category identification module and a product category management module. The information processing procedure of the goods category management system is described as follows:
step 301, putting the new goods into a warehouse.
The commodity information of the newly stocked commodity includes, but is not limited to, a commodity ID, a commodity name, a standard category, and the like.
Step 302, identifying the identification category information of the newly warehoused goods.
The commodity type identification module automatically identifies the identification type information of the newly warehoused commodities and updates the identified identification type information into the identification type name of the commodity information.
And step 303, storing the newly identified identification category information.
The commodity category management module is responsible for managing the identification categories of commodities, identification category information is stored in a commodity database, and the content comprises but is not limited to identification category names, reconstruction periods and the like. When the identification category of the newly put goods in the goods database is updated, the goods category management module checks whether the new identification category name already exists in the identification category information. If a new identification category name is found, it is updated into the identification category information.
At step 304, a repurchase period for the newly identified identification category is configured.
And the commodity category management module configures the reconstruction period of the newly identified identification category through a manual method for the newly appeared identification category name.
At step 305, the repurchase period for the newly identified identification category is updated.
And the commodity category management module updates the reconstruction period of the identification category into the identification category information of the commodity database.
As shown in fig. 4, the recommendation optimization system may include a recommendation optimization module, and an information processing flow of the recommendation optimization system is described as follows:
step 401, a recommended commodity sequence of a user is received.
The recommendation result optimization module receives a recommended commodity sequence of the user, including but not limited to commodity ID, commodity name, identification category, sorting score and the like.
And 402, optimizing a commodity recommendation sequence by using the shopping data of the user and the reconstruction period of the identification category to which the shopping data belongs, and generating a recommendation result.
And the recommendation result optimization module calculates the identification categories in the re-purchase period based on the identification categories of the commodities purchased by the user and the latest purchase date, and then reduces the ranking scores of the commodities belonging to the identification categories in the recommended commodity sequence. And reordering the commodity sequence to generate a recommendation result.
And step 403, sending the recommendation result to the user.
And the recommendation result optimization module sends the reordered recommendation results to the user.
The recommendation may be the first ranked item in the reordered sequence of recommended items.
In order to better explain the embodiment of the present invention, the above-mentioned commodity recommendation process will be described in the following specific implementation scenarios.
1. An example of the product information is shown in table 1.
2. An example of the identification category information is shown in table 2.
3. The process of commodity category management is as follows:
a) the new goods are put in storage, and the goods information is shown in table 3.
TABLE 3
b) The identification category of the newly stocked goods is automatically identified, and the corresponding data is updated as shown in table 4.
TABLE 4
c) A new identification class is detected and the identification class information is updated as shown in table 5.
TABLE 5
| Identifying categories | Repeat purchasing cycle (sky) |
| Yoghurt |
d) The repurchase period for the new identification category is configured manually and updated into the identification category information as shown in table 6.
TABLE 6
| Identifying categories | Repeat purchasing cycle (sky) |
| Yoghurt | 1 |
4. The recommended result optimization processing procedure is as follows:
a) a sequence of recommended items is received, the list of recommended items including, but not limited to, item ID, item name, identification category, ranking score, etc. information. The following examples are specific:
{
(10002 Brand B shampoo 700 ml/bottle, shampoo, 0.8)
(10004 brand D Marine shower gel 300ml, shower gel, 0.7)
(10006, Brand F malt extract Nutrition Hair conditioner 200ml, Hair conditioner, 0.6)
}
b) Calculating the identification category in the re-purchasing period based on the identification category of the purchased goods of the user and the latest purchasing date:
the commodity information of the commodity purchased by the user is shown in table 7.
TABLE 7
The current date is 2020.11.05, and the product belongs to the repurchase period of the product, so the identification category 'shampoo' of the product is judged as the identification category in the repurchase period.
c) Reducing the ranking score of the goods in the recommended goods sequence that belong to the identified category within the re-shopping period: optionally, the ranking score is set to 0. Reordering is then performed, examples of which are as follows:
{
(10004 brand D Marine shower gel 300ml, shower gel, 0.7)
(10006, Brand F malt extract Nutrition Hair conditioner 200ml, Hair conditioner, 0.6)
(10002 Brand B shampoo 700 ml/bottle, shampoo, 0)
}
d) And generating a recommendation result and sending the recommendation result to the user.
And pushing the first ranked commodity from the user recommendation result to the user, wherein the result is that:
(10004, 300ml brand D marine shower gel, 0.7).
In the embodiment of the invention, a recommended commodity sequence of a user is obtained, the recommended commodity sequence comprises a commodity ID, a commodity name, identification categories and sorting scores, the recommended commodity sequence is reordered according to the identification categories of commodities purchased by the user, the latest purchase date and the identification categories and sorting scores of the commodities in the recommended commodity sequence to obtain a recommendation result, and the recommendation result is sent to the user. By identifying the purchased commodities and the re-purchasing period of the purchased commodities, the arrangement sequence of the recommended commodities is optimized, the click rate of the recommended commodities is improved, and the shopping experience of the user is improved.
Based on the same technical concept, fig. 5 exemplarily shows a structure of a product recommendation device provided by an embodiment of the present invention, and the device can execute a product recommendation process.
As shown in fig. 5, the apparatus specifically includes:
an obtaining unit 501, configured to obtain a recommended commodity sequence of a user, where the recommended commodity sequence includes a commodity ID, a commodity name, an identification category, and a ranking score;
the processing unit 502 is configured to reorder the recommended commodity sequence according to the identification category of the commodity purchased by the user, the latest purchase date, and the identification category and the ordering score of each commodity in the recommended commodity sequence, so as to obtain a recommendation result; and sending the recommendation result to the user.
Optionally, the processing unit 502 is specifically configured to:
calculating the identification category in the re-purchasing period based on the identification category of the commodity purchased by the user and the latest purchasing date;
determining commodities in the recommended commodity sequence, which are the same as the identification categories in the re-purchasing period, according to the identification categories in the re-purchasing period;
and reducing the ranking scores of the commodities in the recommended commodity sequence, which are the same as the identification categories in the re-purchasing period, and generating a recommendation result after re-ranking.
Optionally, the processing unit 502 is further configured to:
before the recommended commodity sequence of the user is obtained, commodity information of a newly warehoused commodity is obtained;
identifying the identification category information of the newly warehoused commodities according to the commodity information, and updating the identification category information of the newly warehoused commodities into the identification category of the commodity information; the identification category information includes an identification category name and a repurchase period.
Optionally, the processing unit 502 is further configured to:
if the identification category name in the identification category information is called as a new identification category name, configuring a re-purchasing period corresponding to the new identification category name; and updating the re-purchasing period corresponding to the new identification category name into the identification category information.
Optionally, the recommendation result is a first ranked commodity in the reordered recommended commodity sequence.
Based on the same technical concept, an embodiment of the present invention further provides a computing device, including:
a memory for storing program instructions;
and the processor is used for calling the program instructions stored in the memory and executing the commodity recommendation method according to the obtained program.
Based on the same technical concept, embodiments of the present invention also provide a computer-readable non-volatile storage medium, which includes computer-readable instructions, and when the computer reads and executes the computer-readable instructions, the computer is caused to execute the above commodity recommendation method.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
While preferred embodiments of the present invention have been described, additional variations and modifications in those embodiments may occur to those skilled in the art once they learn of the basic inventive concepts. Therefore, it is intended that the appended claims be interpreted as including preferred embodiments and all such alterations and modifications as fall within the scope of the invention.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. A method for recommending an article, comprising:
acquiring a recommended commodity sequence of a user, wherein the recommended commodity sequence comprises a commodity ID, a commodity name, an identification category and a sequencing score;
reordering the recommended commodity sequence according to the identification category of the commodity purchased by the user, the latest purchase date and the identification category and the ordering score of each commodity in the recommended commodity sequence to obtain a recommended result;
and sending the recommendation result to the user.
2. The method of claim 1, wherein the reordering of the sequence of recommended goods according to the identification category of the goods purchased by the user, the latest purchase date, and the identification category and ranking score of each goods in the sequence of recommended goods to obtain a recommendation comprises:
calculating the identification category in the re-purchasing period based on the identification category of the commodity purchased by the user and the latest purchasing date;
determining commodities in the recommended commodity sequence, which are the same as the identification categories in the re-purchasing period, according to the identification categories in the re-purchasing period;
and reducing the ranking scores of the commodities in the recommended commodity sequence, which are the same as the identification categories in the re-purchasing period, and generating a recommendation result after re-ranking.
3. The method of claim 1, wherein before obtaining the recommended sequence of merchandise for the user, further comprising:
acquiring commodity information of newly warehoused commodities;
identifying the identification category information of the newly warehoused commodities according to the commodity information, and updating the identification category information of the newly warehoused commodities into the identification category of the commodity information; the identification category information includes an identification category name and a repurchase period.
4. The method of claim 3, wherein the method further comprises:
if the identification category name in the identification category information is called as a new identification category name, configuring a re-purchasing period corresponding to the new identification category name; and updating the re-purchasing period corresponding to the new identification category name into the identification category information.
5. The method of any one of claims 1 to 4, wherein the recommendation is the first ranked item in the reordered sequence of recommended items.
6. An article recommendation device, comprising:
the system comprises an acquisition unit, a display unit and a control unit, wherein the acquisition unit is used for acquiring a recommended commodity sequence of a user, and the recommended commodity sequence comprises a commodity ID, a commodity name, an identification category and a sequencing score;
the processing unit is used for reordering the recommended commodity sequence according to the identification category of the commodity purchased by the user, the latest purchase date and the identification category and the ordering score of each commodity in the recommended commodity sequence to obtain a recommended result; and sending the recommendation result to the user.
7. The apparatus as claimed in claim 6, wherein said processing unit is specifically configured to:
calculating the identification category in the re-purchasing period based on the identification category of the commodity purchased by the user and the latest purchasing date;
determining commodities in the recommended commodity sequence, which are the same as the identification categories in the re-purchasing period, according to the identification categories in the re-purchasing period;
and reducing the ranking scores of the commodities in the recommended commodity sequence, which are the same as the identification categories in the re-purchasing period, and generating a recommendation result after re-ranking.
8. The apparatus as recited in claim 6, said processing unit to further:
before the recommended commodity sequence of the user is obtained, commodity information of a newly warehoused commodity is obtained;
identifying the identification category information of the newly warehoused commodities according to the commodity information, and updating the identification category information of the newly warehoused commodities into the identification category of the commodity information; the identification category information includes an identification category name and a repurchase period.
9. A computing device, comprising:
a memory for storing program instructions;
a processor for calling program instructions stored in said memory to execute the method of any one of claims 1 to 5 in accordance with the obtained program.
10. A computer-readable non-transitory storage medium including computer-readable instructions which, when read and executed by a computer, cause the computer to perform the method of any one of claims 1 to 5.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110381711.8A CN113095876B (en) | 2021-04-09 | 2021-04-09 | Commodity recommendation method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110381711.8A CN113095876B (en) | 2021-04-09 | 2021-04-09 | Commodity recommendation method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113095876A true CN113095876A (en) | 2021-07-09 |
| CN113095876B CN113095876B (en) | 2022-10-18 |
Family
ID=76675607
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110381711.8A Active CN113095876B (en) | 2021-04-09 | 2021-04-09 | Commodity recommendation method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113095876B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102346894A (en) * | 2010-08-03 | 2012-02-08 | 阿里巴巴集团控股有限公司 | Output method, system and server of recommendation information |
| CN106157097A (en) * | 2016-08-22 | 2016-11-23 | 北京京东尚科信息技术有限公司 | Method of Commodity Recommendation and system |
| CN109697652A (en) * | 2018-06-29 | 2019-04-30 | 京东方科技集团股份有限公司 | A kind of Method of Commodity Recommendation and server in market |
| CN111316306A (en) * | 2017-11-09 | 2020-06-19 | 深圳传音通讯有限公司 | Intelligent terminal-based commodity recommendation method and commodity recommendation system |
| CN111325609A (en) * | 2020-02-28 | 2020-06-23 | 京东数字科技控股有限公司 | Commodity recommendation list determining method and device, electronic equipment and storage medium |
| CN111681055A (en) * | 2020-06-11 | 2020-09-18 | 广东微谱网络科技有限公司 | Commodity re-purchasing pushing method, system, equipment and computer readable medium |
-
2021
- 2021-04-09 CN CN202110381711.8A patent/CN113095876B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102346894A (en) * | 2010-08-03 | 2012-02-08 | 阿里巴巴集团控股有限公司 | Output method, system and server of recommendation information |
| CN106157097A (en) * | 2016-08-22 | 2016-11-23 | 北京京东尚科信息技术有限公司 | Method of Commodity Recommendation and system |
| CN111316306A (en) * | 2017-11-09 | 2020-06-19 | 深圳传音通讯有限公司 | Intelligent terminal-based commodity recommendation method and commodity recommendation system |
| CN109697652A (en) * | 2018-06-29 | 2019-04-30 | 京东方科技集团股份有限公司 | A kind of Method of Commodity Recommendation and server in market |
| CN111325609A (en) * | 2020-02-28 | 2020-06-23 | 京东数字科技控股有限公司 | Commodity recommendation list determining method and device, electronic equipment and storage medium |
| CN111681055A (en) * | 2020-06-11 | 2020-09-18 | 广东微谱网络科技有限公司 | Commodity re-purchasing pushing method, system, equipment and computer readable medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113095876B (en) | 2022-10-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN112837118B (en) | Commodity recommendation method and device for enterprise users | |
| CN110400103B (en) | Replenishment quantity determination method and device, computer device and storage medium | |
| US10176508B2 (en) | System, method, and non-transitory computer-readable storage media for evaluating search results for online grocery personalization | |
| US10430854B2 (en) | System, method, and non-transitory computer-readable storage media for evaluating search results for personalized product substitutions | |
| CN107203866B (en) | Order processing method and device | |
| CN112837106A (en) | Commodity recommendation method and device and computer equipment | |
| CN110969512B (en) | Commodity recommendation method and device based on user purchasing behavior | |
| CN104615721B (en) | For the method and system based on return of goods related information Recommendations | |
| US20150193853A1 (en) | Methods and Apparatus to Generate Product Recommendations | |
| CN111899068A (en) | Commodity shopping guide method and device, storage medium and computer equipment | |
| CN113689259A (en) | Commodity personalized recommendation method and system based on user behaviors | |
| CN112884547A (en) | Intelligent commodity recommendation method, device, medium and terminal equipment | |
| US10417688B2 (en) | System, method, and non-transitory computer-readable storage media for evaluating search results for matching ingredients to products | |
| CN110362702A (en) | Picture management method and equipment | |
| US20180232750A1 (en) | Systems and methods for predicting customer behavior from social media activity | |
| CN113095876B (en) | Commodity recommendation method and device | |
| CN113327132A (en) | Multimedia recommendation method, device, equipment and storage medium | |
| CN112488771B (en) | Method, apparatus, device and storage medium for automatically setting commodity price | |
| CN111639274B (en) | Online commodity intelligent sorting method, device, computer equipment and storage medium | |
| CN108665345B (en) | Label mapping method | |
| CN110084541B (en) | Method and apparatus for predicting supplier delivery duration | |
| CN111415219B (en) | Commodity recommendation method and device based on big data of home and community shopping | |
| CN111192112A (en) | Multi-platform interaction method and device | |
| CN111667208A (en) | Article storage control method, device, equipment and medium | |
| CN110858337A (en) | Method and device for generating configuration information |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |