CN113516504B - Commodity recommendation method, device, equipment and storage medium - Google Patents
Commodity recommendation method, device, equipment and storage medium Download PDFInfo
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- CN113516504B CN113516504B CN202110550510.6A CN202110550510A CN113516504B CN 113516504 B CN113516504 B CN 113516504B CN 202110550510 A CN202110550510 A CN 202110550510A CN 113516504 B CN113516504 B CN 113516504B
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- G06Q30/00—Commerce
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Abstract
The invention provides a commodity recommendation method, a commodity recommendation device, commodity recommendation equipment and a storage medium, wherein the commodity recommendation method comprises the following steps: counting sales of various commodities in a sales period; calculating according to the 1/N power of sales volume to obtain initial scores of all commodities; taking the maximum value and the minimum value in the initial score of each commodity as a range, obtaining a random score through a random number generator, and taking the random score as a basic score of each commodity; sequentially displaying the commodities to the user according to the initial score of each commodity, subtracting the first value from the basic score of the commodity once when the commodities are displayed, adding the second value to the basic score of the commodity when the commodities are clicked once, and counting the basic score of each commodity after the commodities are changed after a period of time; and selecting a plurality of commodities with the values of the basic scores being the same as the values of the basic scores after the change as the recommended explosion commodities of the website front page. The commodity recommendation method disclosed by the invention has the advantages that commodity recommendation is more reasonable, and insufficient selection caused by insufficient experience of personnel or investigation is avoided.
Description
Technical Field
The present invention relates to the field of electronic commerce technologies, and in particular, to a method, an apparatus, a device, and a storage medium for recommending commodities.
Background
Electronic commerce management is abbreviated as electronic commerce, and is a novel business operation mode for realizing online shopping of consumers, online transaction and online electronic payment among merchants, various business activities, transaction interaction, financial activities and related comprehensive service activities by conducting various business activities without going around by buyers and sellers in an open network environment of the Internet in the world of wide commercial trade activities.
In the prior art, shopping guide electronics companies often cannot select massive commodities rapidly, the selection strategy is seriously dependent on personnel experience, scientific and effective cannot be achieved, and the problems of untimely updating of new product excavation and market change often exist.
Accordingly, the prior art is still in need of improvement and development.
Disclosure of Invention
The invention mainly aims to solve the technical problems that the e-commerce options in the prior art are seriously dependent on personnel experience, and the options are inaccurate and updated in time.
The first aspect of the present invention provides a commodity recommendation method, which includes:
Counting sales of various commodities in a sales period;
Calculating according to the 1/N power of sales volume to obtain initial scores of all commodities;
taking the maximum value and the minimum value in the initial score of each commodity as a range, obtaining a random score through a random number generator, and taking the random score as a basic score of each commodity;
displaying all the commodities to the user in turn according to the initial score of each commodity, wherein the basic score of the commodity subtracts a first value when the commodity is clicked once every time the commodity is displayed, the basic score of the commodity increases a second value, and the basic score of each commodity after a period of time is counted;
And selecting a plurality of commodities with the values of the basic scores being the same as the values of the basic scores after the change as the recommended explosion commodities of the website front page.
In an alternative embodiment of the first aspect of the present invention, the magnitude of the first value is smaller than the magnitude of the second value.
In an alternative embodiment of the first aspect of the present invention, the first value has a size of 1/10 of the size of the second value.
In an optional implementation manner of the first aspect of the present invention, the counting sales of each commodity in the sales period includes:
And collecting and counting sales volume of each commodity in the sales period, binding the sales volume, the corresponding commodity name, ID number, picture, price, coupon amount and coupon starting time, and storing the sales volume in a database.
In an alternative embodiment of the first aspect of the present invention, information of the commodity name, the ID number, the picture, the price, the coupon amount, the coupon start time and the sales amount is stored in the database in the form of a Key-value.
In an optional implementation manner of the first aspect of the present invention, after selecting the goods with the values of the base scores after the change and the values of the base scores before as the pop-up goods recommended by the website front page, the method includes:
And adding label information of coupon amount and coupon starting time corresponding to each burst commodity.
In an alternative embodiment of the first aspect of the present invention, the sales cycle is 2-10 days.
A second aspect of the present invention provides a commodity recommendation device including:
the statistics module is used for counting sales of various commodities in the sales period;
The calculation module is used for calculating the initial score of each commodity according to the 1/N power of sales;
The basic score generation module is used for taking the maximum value and the minimum value in the initial score of each commodity as a range, obtaining a random score through the random number generator, and taking the random score as the basic score of each commodity;
the display module is used for sequentially displaying the commodities to the user according to the initial score of each commodity, wherein the basic score of the commodity subtracts a first value when the commodity is clicked once every time, the basic score of the commodity increases a second value, and the basic score of each commodity after being changed after a period of time is counted;
And the recommending module is used for selecting a plurality of commodities with the front value of the basic score after the change as the burst commodities recommended by the website front page.
A third aspect of the present invention provides a commodity recommendation apparatus, comprising: a memory and at least one processor, the memory having instructions stored therein, the memory and the at least one processor being interconnected by a line;
the at least one processor invokes the instructions in the memory to cause the merchandise recommendation device to perform the merchandise recommendation method of any one of the above.
A fourth aspect of the present invention provides a computer readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements a commodity recommendation method according to any one of the above.
The beneficial effects are that: the invention provides a commodity recommendation method, a commodity recommendation device, commodity recommendation equipment and a storage medium, wherein the commodity recommendation method comprises the following steps: counting sales of various commodities in a sales period; calculating according to the 1/N power of sales volume to obtain initial scores of all commodities; taking the maximum value and the minimum value in the initial score of each commodity as a range, obtaining a random score through a random number generator, and taking the random score as a basic score of each commodity; sequentially displaying the commodities to the user according to the initial score of each commodity, subtracting the first value from the basic score of the commodity once when the commodities are displayed, adding the second value to the basic score of the commodity when the commodities are clicked once, and counting the basic score of each commodity after the commodities are changed after a period of time; and selecting a plurality of commodities with the values of the basic scores being the same as the values of the basic scores after the change as the recommended explosion commodities of the website front page. The commodity recommendation method disclosed by the invention has the advantages that commodity recommendation is more reasonable, and insufficient selection caused by insufficient experience of personnel or investigation is avoided.
Drawings
FIG. 1 is a schematic diagram of an embodiment of a method for recommending goods according to the present invention;
FIG. 2 is a schematic diagram of an embodiment of a merchandise recommendation apparatus according to the present invention;
FIG. 3 is a schematic diagram of an embodiment of a merchandise recommendation apparatus according to the present invention.
Detailed Description
The embodiment of the invention provides a commodity recommendation method, a commodity recommendation device, commodity recommendation equipment and a storage medium.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
For easy understanding, the following describes a specific flow of an embodiment of the present invention, referring to fig. 1, a first aspect of the present invention provides a commodity recommendation method, where the commodity recommendation method includes:
s100, counting sales of various commodities in a sales period;
S200, calculating according to the 1/N power of sales volume to obtain initial scores of all commodities;
s300, taking the maximum value and the minimum value in the initial score of each commodity as a range, obtaining a random score through a random number generator, and taking the random score as a basic score of each commodity;
S400, displaying all the commodities to the user in sequence according to the initial score of each commodity, wherein the basic score of each commodity subtracts a first value when the commodity is clicked once, the basic score of each commodity increases a second value, and the basic score of each commodity after a period of time is counted;
S500, selecting a plurality of commodities with the values of the basic scores being the same as the values of the basic scores after the change as the recommended explosion commodities of the first page of the website.
Specifically, the invention is mainly used for automatically publishing, testing and predicting potential explosive commodities and helping shopping guide companies to predict commodity sales.
In an alternative embodiment of the first aspect of the present invention, the magnitude of the first value is smaller than the magnitude of the second value. In this embodiment, since the first value is smaller than the second value, the solution of the present invention will obtain more exposure opportunities at the beginning with a high score, but if the products are approved by the user, the score will increase rapidly, and if the products are not approved by the user, the score will be exceeded by other products, so that the recommendation of the merchandise is more reasonable.
In an alternative embodiment of the first aspect of the present invention, the first value has a size of 1/10 of the size of the second value. In this embodiment, the commodity with high score will not decay too fast, the commodity with low score will not grow too fast, and the score of the commodity will be affected significantly only when the number of users is enough, so the data has more authenticity and accuracy.
In an optional implementation manner of the first aspect of the present invention, the counting sales of each commodity in the sales period includes:
And collecting and counting sales volume of each commodity in the sales period, binding the sales volume, the corresponding commodity name, ID number, picture, price, coupon amount and coupon starting time, and storing the sales volume in a database.
In this embodiment, since the commodity and the related commodity information thereof are already bound, the information displayed by the commodity can be more comprehensive when the commodity is recommended, and the interactive experience of purchasing the commodity by the user is improved.
In an alternative embodiment of the first aspect of the present invention, information of the commodity name, the ID number, the picture, the price, the coupon amount, the coupon start time and the sales amount is stored in the database in the form of a Key-value.
In particular, key-value storage is a great challenge for internet companies, traditional databases often have difficulty meeting the requirement, and most of the searches for specific systems are based on primary Key queries in many cases, and in such cases, the use of relational databases will make the efficiency low, and expansion will also be a great problem in the future, and in such cases, the use of Key-value storage will be a good choice.
In an optional implementation manner of the first aspect of the present invention, after selecting the goods with the values of the base scores after the change and the values of the base scores before as the pop-up goods recommended by the website front page, the method includes:
And adding label information of coupon amount and coupon starting time corresponding to each burst commodity. In this embodiment, the merchandise with the coupon can attract the interest of the consumer, and the purchasing desire of the consumer can be improved, so that a better sales effect can be obtained.
In an alternative embodiment of the first aspect of the present invention, the sales cycle is 2-10 days. In the embodiment, the sales period is 2-10 days, and the commodity recommendation method is mainly aimed at short-period quick-elimination commodities, and can track the popularity of the commodities in real time due to the short set period, so that quick decision making of merchants is facilitated.
An exemplary merchandise recommendation method of the present invention is as follows:
Firstly, collecting shopping guide commodities to enter a database, wherein the key required contents are as follows: product name, id, picture, price, coupon amount, coupon start time, past sales, etc.;
next, the goods that are about to start time within about 2 days are screened and the score is calculated according to the following formula: sales ≡1/2. The reason for this formula is to assume that the current sales, which were high in the past, may also be high.
Then, the commodity id and the score are written into redis sortedset data structure, and since the commodity ticket is stored in units of days, keys (keywords) are stored by day. For performance optimization considerations, other information may be stored with the commodity id as a key.
And then establishing a server api, calculating random numbers according to the highest score and the lowest score of sortedset, and taking commodity data according to the random numbers as basic scores, wherein the product score is-0.1 when the commodity data are taken each time. When the merchandise is clicked, the product score +1. Initially, a high score will get more exposure opportunities. If the products are user approved, the score will increase rapidly, and if the products are user disapproved, the score will be exceeded by other products.
And finally, a report system is established, and the explosive commodities differentiated according to the days are displayed in real time. Because the merchandise has not yet reached the ticket start time, the user will not purchase it. When the explosive commodity appears, the marketing campaign can be targeted. The method and the device can scientifically calculate the burst products in mass commodities, and avoid insufficient selection of the products caused by insufficient experience or investigation of personnel.
Referring to fig. 2, a second aspect of the present invention provides a commodity recommendation apparatus, including:
a statistics module 10, configured to count sales of each commodity in a sales period;
A calculation module 20, configured to calculate an initial score of each commodity according to the 1/N power of sales;
a base score generation module 30 for obtaining a random score by a random number generator with a maximum value and a minimum value in the initial score of each commodity as a range, and taking the random score as a base score of each commodity;
A display module 40, configured to sequentially display each commodity to the user according to the initial score of each commodity; the basic score of the commodity is increased by a second value when the commodity is clicked once, and the basic score of each commodity after being changed after a period of time is counted;
the recommending module 50 is used for selecting a plurality of commodities with the value of the basic score being higher than that of the basic score after the change as the burst commodity recommended by the website home page.
In an alternative embodiment of the second aspect of the present invention, the magnitude of the first value is smaller than the magnitude of the second value.
In an alternative embodiment of the second aspect of the present invention, the first value has a size of 1/10 of the size of the second value.
In an optional embodiment of the second aspect of the present invention, the statistics module includes:
And the statistics storage unit is used for collecting sales volume of each commodity in the statistics sales period, binding the sales volume with the commodity name, ID number, picture, price, coupon amount and coupon starting time corresponding to the sales volume, and storing the sales volume into the database.
In an alternative embodiment of the second aspect of the present invention, information of commodity name, ID number, picture, price, coupon amount, coupon start time and sales amount is stored in the database in the form of Key-value.
In an optional embodiment of the second aspect of the present invention, the commodity recommendation device further includes:
and the label adding module is used for adding label information of coupon amount and coupon starting time corresponding to each exploded commodity.
In an alternative embodiment of the second aspect of the present invention, the sales cycle is 2-10 days.
Fig. 3 is a schematic diagram of a commodity recommendation device according to an embodiment of the present invention, where the commodity recommendation device may have a relatively large difference due to different configurations or performances, and may include one or more processors 60 (central processing units, CPU) (e.g., one or more processors) and a memory 70, and one or more storage mediums 80 (e.g., one or more mass storage devices) that store application programs or data. The memory and storage medium may be transitory or persistent. The program stored on the storage medium may include one or more modules (not shown), each of which may include a series of instruction operations for the commodity recommendation device. Still further, the processor may be configured to communicate with a storage medium and execute a series of instruction operations in the storage medium on the merchandise recommendation device.
The merchandise recommendation device may also include one or more power supplies 90, one or more wired or wireless network interfaces 100, one or more input/output interfaces 110, and/or one or more operating systems, such as Windows Serve, mac OS X, unix, linux, freeBSD, etc. It will be appreciated by those skilled in the art that the article recommendation device structure illustrated in FIG. 3 is not limiting of the article recommendation device, and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
The present invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium, or may be a volatile computer readable storage medium, in which instructions are stored which, when executed on a computer, cause the computer to perform the steps of the commodity recommendation method.
It will be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the system or apparatus and unit described above may refer to the corresponding process in the foregoing method embodiment, which is not repeated herein.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (4)
1. A commodity recommendation method, characterized in that the commodity recommendation method comprises:
counting sales of each commodity in a sales period, wherein the sales period is 2-10 days;
Calculating according to the 1/N power of sales volume to obtain initial scores of all commodities;
taking the maximum value and the minimum value in the initial score of each commodity as a range, obtaining a random score through a random number generator, and taking the random score as a basic score of each commodity;
displaying all the commodities to the user in turn according to the initial score of each commodity, wherein the basic score of the commodity subtracts a first value once when the commodity is displayed once, the basic score of the commodity increases a second value when the commodity is clicked once, and the basic score of each commodity after being changed after a period of time is counted, and the first value is 1/10 of the second value;
Selecting a plurality of commodities with the values of the basic scores being the same as the values of the basic scores after the change as the recommended explosion commodities of the website home page;
The counting of sales of each commodity in the sales period comprises the following steps: collecting and counting sales volume of each commodity in a sales period, binding the sales volume, the corresponding commodity name, ID number, picture, price, coupon amount and coupon starting time, and storing the sales volume in a database; storing information of commodity names, ID numbers, pictures, prices, coupon amounts, coupon start time and sales volume in the database in the form of Key-value;
The method for selecting the goods with the values of the basic scores after the change and the values of the basic scores before the change as the recommended money-exploded goods of the website front page comprises the following steps: and adding label information of coupon amount and coupon starting time corresponding to each burst commodity.
2. A commodity recommendation device, characterized in that the commodity recommendation device comprises:
The statistics module is used for counting sales of various commodities in a sales period, wherein the sales period is 2-10 days;
The calculation module is used for calculating the initial score of each commodity according to the 1/N power of sales;
The basic score generation module is used for taking the maximum value and the minimum value in the initial score of each commodity as a range, obtaining a random score through the random number generator, and taking the random score as the basic score of each commodity;
the display module is used for sequentially displaying the commodities to the user according to the initial score of each commodity, wherein the basic score of the commodity subtracts a first value once when the commodity is displayed once, the basic score of the commodity increases a second value when the commodity is clicked once, and the basic score of each commodity after being changed after a period of time is counted, and the size of the first value is 1/10 of that of the second value;
the recommending module is used for selecting a plurality of commodities with the value of the basic score being the front after the change as the money-explosion commodities recommended by the website home page;
The statistics module comprises: the statistics storage unit is used for collecting sales volume of each commodity in the statistics sales period, binding the sales volume, the commodity name, ID number, picture, price, coupon amount and coupon starting time corresponding to the sales volume, and storing the sales volume into the database; storing information of commodity names, ID numbers, pictures, prices, coupon amounts, coupon start time and sales volume in the database in the form of Key-value;
the commodity recommendation device further includes: and the label adding module is used for adding label information of coupon amount and coupon starting time corresponding to each exploded commodity.
3. A commodity recommendation device, characterized in that the commodity recommendation device comprises: a memory and at least one processor, the memory having instructions stored therein, the memory and the at least one processor being interconnected by a line;
the at least one processor invokes the instructions in the memory to cause the merchandise recommendation device to perform the merchandise recommendation method of claim 1.
4. A computer readable storage medium having a computer program stored thereon, wherein the computer program when executed by a processor implements the merchandise recommendation method of claim 1.
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| US20100262476A1 (en) * | 2006-12-22 | 2010-10-14 | G5 Enterprizes Pty Ltd | Methods and systems for sales promotion |
| US20080294996A1 (en) * | 2007-01-31 | 2008-11-27 | Herbert Dennis Hunt | Customized retailer portal within an analytic platform |
| US8161040B2 (en) * | 2007-04-30 | 2012-04-17 | Piffany, Inc. | Criteria-specific authority ranking |
| CN102456057B (en) * | 2010-11-01 | 2016-08-17 | 阿里巴巴集团控股有限公司 | Search method based on online trade platform, device and server |
| CN102479366A (en) * | 2010-11-25 | 2012-05-30 | 阿里巴巴集团控股有限公司 | Commodity recommendation method and system |
| CN102938124A (en) * | 2012-10-29 | 2013-02-20 | 北京京东世纪贸易有限公司 | Method and device for determining festival hot commodity |
| US20150363862A1 (en) * | 2014-06-13 | 2015-12-17 | Connect Financial LLC | Financial product recommendation for a consumer |
| CN105574025B (en) * | 2014-10-15 | 2018-10-16 | 阿里巴巴集团控股有限公司 | For calculating sequence point and establishing the method, apparatus and commercial product recommending system of model |
| CN107368483B (en) * | 2016-05-11 | 2020-06-23 | 阿里巴巴集团控股有限公司 | Information recommendation method and device and server |
| CN107578293A (en) * | 2017-09-23 | 2018-01-12 | 山东浪潮云服务信息科技有限公司 | A kind of solution formulation method and device in electric business transaction business |
| CN108109052A (en) * | 2017-12-29 | 2018-06-01 | 广州优视网络科技有限公司 | Article method for pushing, device and server |
| CN111626804A (en) * | 2019-02-28 | 2020-09-04 | 北京京东尚科信息技术有限公司 | Commodity recommendation method and device, electronic equipment and computer readable medium |
| CN110363617A (en) * | 2019-06-03 | 2019-10-22 | 北京三快在线科技有限公司 | A recommended method, device, electronic device and readable storage medium |
| CN110866220B (en) * | 2019-11-14 | 2024-02-20 | 上海新蕴力电子商务有限公司 | Selection recommending system in e-commerce activity process |
| 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 |
| CN111754300A (en) * | 2020-06-22 | 2020-10-09 | 深圳市分期乐网络科技有限公司 | A product recommendation method, device, device and storage medium |
| CN112380430A (en) * | 2020-11-10 | 2021-02-19 | 腾讯科技（北京）有限公司 | Artificial intelligence based recommendation method and device and electronic equipment |
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