CN114428897A - High-quality product information sharing push system based on big data - Google Patents
High-quality product information sharing push system based on big data Download PDFInfo
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- CN114428897A CN114428897A CN202011105672.0A CN202011105672A CN114428897A CN 114428897 A CN114428897 A CN 114428897A CN 202011105672 A CN202011105672 A CN 202011105672A CN 114428897 A CN114428897 A CN 114428897A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
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- G—PHYSICS
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- 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
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
Abstract
The invention discloses a high-quality product information sharing and pushing system based on big data, which comprises a user side, wherein a shopping APP is downloaded in the user side, and the remote data of the output end of the shopping APP is connected with a shopping APP mall server. According to the invention, by arranging the user side, the shopping APP mall server, the cloud storage, the keyword extraction module, the timing module, the keyword clearing module, the E-business side, the merchant real-time data module, the data analysis module, the data pushing module, the merchant sequencing module and the user analysis module, the information of the goods purchase quantity and the purchase experience can be integrally integrated, so that high-quality products can be more easily selected, and the problem that the information is scattered and satisfactory information cannot be obtained due to the fact that the information of the goods purchase quantity and the purchase experience cannot be integrally integrated in the using process of the shared pushing system, and the shared pushing system is not high-quality enough for selecting the products is solved.
Description
Technical Field
The invention relates to the technical field of information pushing, in particular to a high-quality product information sharing and pushing system based on big data.
Background
The information push is a new technology for reducing information overload by periodically transmitting information required by a user on the internet through a certain technical standard or protocol, the push technology reduces the time for searching on the network by automatically transmitting the information to the user, searches and filters the information according to the interest of the user and periodically pushes the information to the user to help the user to efficiently discover valuable information, technically, the information push is a comprehensive direction based on a plurality of technologies such as data mining, natural language processing and the internet, and pushes appropriate information to appropriate people, and is a challenging work, the process needs to fully analyze the information, carefully depict the interest and the behavior of the people and effectively match the people, and a shared push system needs to be used in the information push process, the existing shared pushing system cannot integrate the information of the goods purchase amount and the purchase experience in the using process, so that the information is scattered, satisfactory information cannot be obtained, the problem that the selected products are not high enough in quality is caused in the shared pushing system, and great economic loss is brought to users.
Disclosure of Invention
The invention aims to provide a high-quality product information sharing and pushing system based on big data, which has the advantage of integrally integrating the information of the purchase quantity of goods and the purchase experience and solves the problem that the information is scattered and satisfactory information cannot be obtained due to the fact that the information of the purchase quantity of goods and the purchase experience cannot be integrally integrated in the using process of the sharing and pushing system, and therefore the sharing and pushing system is not good enough in quality of selected products.
In order to achieve the purpose, the invention provides the following technical scheme: a high-quality product information sharing and pushing system based on big data comprises a user side, wherein shopping APPs are downloaded in the user side, the output end of each shopping APP is remotely and data-connected with a shopping APP mall server, the shopping APP mall server is bidirectionally and signal-connected with a cloud storage, the output end of each shopping APP mall server is signal-connected with a keyword extraction module, the keyword extraction module is bidirectionally signal-connected with a timing module, the output end of the timing module is signal-connected with a keyword clearing module, the output ends of the keyword extraction module and the keyword clearing module are both signal-connected with an e-commerce end, the output end of the e-commerce end is signal-connected with a merchant real-time data module, the output end of the merchant real-time data module is signal-connected with a data analysis module, and the output end of the data analysis module is signal-connected with a data pushing module, the output end of the data pushing module is in signal connection with a merchant sequencing module, the output end of the e-commerce end is in signal connection with the merchant sequencing module, the output end of the shopping APP mall server is in signal connection with a user analysis module, and the output end of the user analysis module is in signal connection with the merchant sequencing module;
the real-time data module of the merchant comprises purchase quantity data, good evaluation quantity data, poor evaluation quantity data and buyback quantity data, the input ends of the purchase quantity data, the good evaluation quantity data, the poor evaluation quantity data and the buyback quantity data are in signal connection with the output end of the e-commerce terminal, the output ends of the purchase quantity data, the good evaluation quantity data, the poor evaluation quantity data and the buyback quantity data are in signal connection with the input end of the data analysis module, the user analysis module comprises a browsing quantity analysis module, a poor evaluation analysis module, a good evaluation analysis module and a buyback analysis module, the input ends of the browsing quantity analysis module, the poor evaluation analysis module, the good evaluation analysis module and the buyback analysis module are in signal connection with the output end of the shopping APP mall server, and the output ends of the browsing quantity analysis module, the poor evaluation module, the good analysis module and the buyback analysis module are in signal connection with the input end of the merchant sorting module, the merchant sequencing module comprises a user analysis sequencing module and a merchant data information sequencing module, the output end signals of the user analysis sequencing module and the merchant data information sequencing module are connected with a summary information sequencing module, and the output end of the summary information sequencing module is connected with the input end signal of the shopping APP mall server.
Preferably, the output ends of the browsing amount analysis module, the difference score analysis module, the good score analysis module and the buyback analysis module are in signal connection with the input end of the user analysis sorting module.
Preferably, the input end of the merchant data information sorting module is in signal connection with the output end of the data pushing module, and the output end of the e-commerce end is in signal connection with the input end of the summary information sorting module.
Preferably, the user side comprises a smart phone, a tablet computer, a desktop computer and a notebook computer.
Preferably, the merchant real-time data module accounts for sixty percent of the total proportion of information pushing, and the purchase quantity data, the good evaluation quantity data, the poor evaluation quantity data and the buyback quantity data are evenly distributed to the sixty percent of the proportion.
Preferably, the user analysis module accounts for forty percent of the total proportion of information pushing, and the browsing amount analysis module, the difference score analysis module, the good score analysis module and the buyback analysis module are used for carrying out average distribution on the forty percent of proportion.
Preferably, a method for using a big data-based high-quality product information sharing push system includes the following steps:
A) a shopping user enters a shopping APP through a user side, the name of an article to be purchased is input in a shopping APP interface, the name is led into a shopping APP mall server after being input, the input information enters a cloud storage and enters a big data platform for sharing, a keyword extraction module extracts keywords from the input information, and the extracted keywords enter corresponding e-commerce terminals for screening;
B) if the keyword is wrong, the keyword is deleted in the timing range of the timing module, and the keyword input at this time is not recorded;
C) the data analysis module analyzes purchase quantity data, good evaluation quantity data, poor evaluation quantity data and buyback quantity data contained in the merchant real-time data module and then enters the data push module, various types of data are collected and sorted, and the sorted merchant data are led into a merchant data information sorting module of the merchant sorting module;
D) the shopping information of a shopping user is left in a shopping APP mall server in the shopping process, when the user purchases again, the user can carry out self analysis and sequencing on merchants according to the information of purchased articles, the sequencing is based on a browsing amount analysis module, a difference analysis module, a good evaluation analysis module and a buyback analysis module, and the user analysis and sequencing module in the merchant sequencing module is introduced after the analysis is finished;
E) the user analysis sequencing module and the merchant data information sequencing module are together led into the summary information sequencing module, merchants at the e-commerce end are led into the summary information sequencing module again, and sequenced merchant information is displayed in a shopping APP mall server so as to be pushed.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the invention, by arranging the user side, the shopping APP mall server, the cloud storage, the keyword extraction module, the timing module, the keyword clearing module, the E-business side, the merchant real-time data module, the data analysis module, the data pushing module, the merchant sequencing module and the user analysis module, the information of the goods purchase quantity and the purchase experience can be integrally integrated, so that high-quality products can be more easily selected, the problem that the information is scattered and satisfactory information cannot be obtained due to the fact that the information of the goods purchase quantity and the purchase experience cannot be integrally integrated in the using process of the shared pushing system is solved, and the problem that the selected products are not high enough in quality of the shared pushing system is solved, so that the shared pushing system is worthy of popularization.
Drawings
FIG. 1 is a schematic diagram of the system of the present invention;
FIG. 2 is a schematic diagram of a merchant real-time data module system of the present invention;
FIG. 3 is a schematic diagram of a user analysis module system of the present invention;
FIG. 4 is a schematic diagram of a merchant sequencing module system of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and 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.
Referring to fig. 1-4, a big data-based high-quality product information sharing and pushing system comprises a user side, a shopping APP is downloaded in the user side, the output end of the shopping APP is remotely and data-connected with a shopping APP mall server, the shopping APP mall server is bidirectionally and signal-connected with a cloud storage, the output end of the shopping APP mall server is signal-connected with a keyword extraction module, the keyword extraction module is bidirectionally signal-connected with a timing module, the output end of the timing module is signal-connected with a keyword clearing module, the output ends of the keyword extraction module and the keyword clearing module are both signal-connected with an e-commerce terminal, the output end of the e-commerce terminal is signal-connected with a merchant real-time data module, the output end of the merchant real-time data module is signal-connected with a data analysis module, the output end of the data analysis module is signal-connected with a data pushing module, the output end of the data pushing module is signal-connected with a merchant sequencing module, the output end of the E-business end is in signal connection with the merchant sequencing module, the output end of the shopping APP mall server is in signal connection with the user analysis module, and the output end of the user analysis module is in signal connection with the merchant sequencing module;
the merchant real-time data module comprises purchase quantity data, good evaluation quantity data, poor evaluation quantity data and buyback quantity data, the input ends of the purchase quantity data, the good evaluation quantity data, the poor evaluation quantity data and the buyback quantity data are all in signal connection with the output end of the e-commerce terminal, the output ends of the purchase quantity data, the good evaluation quantity data, the poor evaluation quantity data and the buyback quantity data are all in signal connection with the input end of the data analysis module, the user analysis module comprises a browsing quantity analysis module, a poor evaluation analysis module, a good evaluation analysis module and a buyback analysis module, the input ends of the browsing quantity analysis module, the poor evaluation analysis module, the good evaluation analysis module and the buyback analysis module are all in signal connection with the output end of the shopping APP mall server, the output ends of the browsing quantity analysis module, the poor evaluation analysis module, the good evaluation analysis module and the buyback analysis module are all in signal connection with the input end of the merchant sorting module, the merchant sorting module comprises a user analysis sorting module and a merchant data information sorting module, the output ends of the user analysis sequencing module and the merchant data information sequencing module are in signal connection with a summary information sequencing module, the output end of the summary information sequencing module is in signal connection with the input end of the shopping APP mall server, and the information of the goods purchase amount and the purchase experience can be integrally integrated by arranging the user end, the shopping APP mall server, the cloud memory, the keyword extraction module, the timing module, the keyword clearing module, the E-commerce end, the merchant real-time data module, the data analysis module, the data pushing module, the merchant sequencing module and the user analysis module, so that high-quality products can be selected more easily, and the problem that the information is scattered and satisfactory information cannot be obtained due to the fact that the information of the goods purchase amount and the purchase experience cannot be integrally integrated in the using process of the sharing pushing system is solved, therefore, the problem that the quality of the selected products is not enough in the shared pushing system is caused, and the method is worthy of popularization;
the output ends of the browsing amount analysis module, the difference analysis module, the good evaluation analysis module and the buyback analysis module are in signal connection with the input end of the user analysis sorting module;
the input end of the merchant data information sorting module is in signal connection with the output end of the data pushing module, and the output end of the e-commerce end is in signal connection with the input end of the summary information sorting module;
the user side comprises a smart phone, a tablet computer, a desktop computer and a notebook computer;
the merchant real-time data module accounts for sixty percent of the total proportion of information pushing, and the proportion of the purchase quantity data, the good evaluation quantity data, the poor evaluation quantity data and the buyback quantity data is evenly distributed;
the user analysis module accounts for forty percent of the total proportion of information pushing, and the browsing amount analysis module, the difference score analysis module, the good score analysis module and the buyback analysis module are used for carrying out average distribution on the forty percent proportion;
a use method of a big data-based high-quality product information sharing push system comprises the following steps:
A) a shopping user enters a shopping APP through a user side, the name of an article to be purchased is input in a shopping APP interface, the name is led into a shopping APP mall server after being input, the input information enters a cloud storage and enters a big data platform for sharing, a keyword extraction module extracts keywords from the input information, and the extracted keywords enter corresponding e-commerce terminals for screening;
B) if the keyword is wrong, the keyword is deleted in the timing range of the timing module, and the keyword input at this time is not recorded;
C) the data analysis module analyzes purchase quantity data, good evaluation quantity data, poor evaluation quantity data and buyback quantity data contained in the merchant real-time data module and then enters the data push module, various types of data are collected and sorted, and the sorted merchant data are led into a merchant data information sorting module of the merchant sorting module;
D) the shopping information of a shopping user is left in a shopping APP mall server in the shopping process, when the user purchases again, the user can carry out self analysis and sequencing on merchants according to the information of purchased articles, the sequencing is based on a browsing amount analysis module, a difference analysis module, a good evaluation analysis module and a buyback analysis module, and the user analysis and sequencing module in the merchant sequencing module is introduced after the analysis is finished;
E) the user analysis sequencing module and the merchant data information sequencing module are together led into the summary information sequencing module, merchants at the e-commerce end are led into the summary information sequencing module again, and sequenced merchant information is displayed in a shopping APP mall server so as to be pushed.
In summary, the following steps: this high-quality product information sharing push system based on big data, through setting up the user side, shopping APP mall server, cloud memory, the keyword draws the module, the timing module, the keyword clears away the module, the electricity merchant end, trade company real-time data module, data analysis module, data push module, trade company's sequencing module and user analysis module's cooperation is used, shared push system has been solved in the use, because of can not carrying out the whole integration to the information of goods purchase volume and purchase experience, make the information comparatively sporadic, can't obtain satisfied information, thereby lead to shared push system to appear to push the problem of selecting the product not high-quality enough.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. The utility model provides a high-quality product information sharing push system based on big data, includes the user, its characterized in that: shopping APP is downloaded in the user side, the output end of the shopping APP is remotely and data-connected with a shopping APP mall server, the shopping APP mall server is bidirectionally signal-connected with a cloud storage, the output end of the shopping APP mall server is signal-connected with a keyword extraction module, the keyword extraction module is bidirectionally signal-connected with a timing module, the output end of the timing module is signal-connected with a keyword clearing module, the output ends of the keyword extraction module and the keyword clearing module are both signal-connected with an e-commerce end, the output end of the e-commerce end is signal-connected with a merchant real-time data module, the output end of the merchant real-time data module is signal-connected with a data analysis module, the output end of the data analysis module is signal-connected with a data push module, and the output end of the data push module is signal-connected with a merchant sequencing module, the output end of the E-commerce end is in signal connection with a merchant sequencing module, the output end of the shopping APP mall server is in signal connection with a user analysis module, and the output end of the user analysis module is in signal connection with the merchant sequencing module;
the real-time data module of the merchant comprises purchase quantity data, good evaluation quantity data, poor evaluation quantity data and buyback quantity data, the input ends of the purchase quantity data, the good evaluation quantity data, the poor evaluation quantity data and the buyback quantity data are in signal connection with the output end of the e-commerce terminal, the output ends of the purchase quantity data, the good evaluation quantity data, the poor evaluation quantity data and the buyback quantity data are in signal connection with the input end of the data analysis module, the user analysis module comprises a browsing quantity analysis module, a poor evaluation analysis module, a good evaluation analysis module and a buyback analysis module, the input ends of the browsing quantity analysis module, the poor evaluation analysis module, the good evaluation analysis module and the buyback analysis module are in signal connection with the output end of the shopping APP mall server, and the output ends of the browsing quantity analysis module, the poor evaluation module, the good analysis module and the buyback analysis module are in signal connection with the input end of the merchant sorting module, the merchant sequencing module comprises a user analysis sequencing module and a merchant data information sequencing module, the output end signals of the user analysis sequencing module and the merchant data information sequencing module are connected with a summary information sequencing module, and the output end of the summary information sequencing module is connected with the input end signal of the shopping APP mall server.
2. The big data-based good product information sharing and pushing system according to claim 1, wherein: the output ends of the browsing amount analysis module, the difference analysis module, the good evaluation analysis module and the buyback analysis module are in signal connection with the input end of the user analysis sorting module.
3. The big data-based good product information sharing and pushing system according to claim 1, wherein: the input end of the merchant data information sorting module is in signal connection with the output end of the data pushing module, and the output end of the e-commerce end is in signal connection with the input end of the summary information sorting module.
4. The big data-based good product information sharing and pushing system according to claim 1, wherein: the user side comprises a smart phone, a tablet computer, a desktop computer and a notebook computer.
5. The big data-based good product information sharing and pushing system according to claim 1, wherein: the merchant real-time data module accounts for sixty percent of the total proportion of information pushing, and the purchase quantity data, the good evaluation quantity data, the poor evaluation quantity data and the buyback quantity data are evenly distributed to the sixty percent of the proportion.
6. The big data-based good product information sharing and pushing system according to claim 1, wherein: the user analysis module accounts for forty percent of the total proportion of information pushing, and the browsing amount analysis module, the difference score analysis module, the good score analysis module and the buyback analysis module are used for carrying out average distribution on the forty percent proportion.
7. The use method of the big data-based good quality product information sharing push system according to any one of claims 1 to 6, comprising the following steps:
A) a shopping user enters a shopping APP through a user side, the name of an article to be purchased is input in a shopping APP interface, the name is led into a shopping APP mall server after being input, the input information enters a cloud storage and enters a big data platform for sharing, a keyword extraction module extracts keywords from the input information, and the extracted keywords enter corresponding e-commerce terminals for screening;
B) if the keyword is wrong, the keyword is deleted in the timing range of the timing module, and the keyword input at this time is not recorded;
C) the data analysis module analyzes purchase quantity data, good evaluation quantity data, poor evaluation quantity data and buyback quantity data contained in the merchant real-time data module and then enters the data push module, various types of data are collected and sorted, and the sorted merchant data are led into a merchant data information sorting module of the merchant sorting module;
D) the shopping information of a shopping user is left in a shopping APP mall server in the shopping process, when the user purchases again, the user can carry out self analysis and sequencing on merchants according to the information of purchased articles, the sequencing is based on a browsing amount analysis module, a difference analysis module, a good evaluation analysis module and a buyback analysis module, and the user analysis and sequencing module in the merchant sequencing module is introduced after the analysis is finished;
E) the user analysis sequencing module and the merchant data information sequencing module are together led into the summary information sequencing module, merchants at the e-commerce end are led into the summary information sequencing module again, and sequenced merchant information is displayed in a shopping APP mall server so as to be pushed.
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| CN115545828A (en) * | 2022-09-26 | 2022-12-30 | 江苏经贸职业技术学院 | E-commerce data push analysis system based on artificial intelligence |
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| CN115545828A (en) * | 2022-09-26 | 2022-12-30 | 江苏经贸职业技术学院 | E-commerce data push analysis system based on artificial intelligence |
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