CN113065928A - E-commerce transaction method based on big data - Google Patents
E-commerce transaction method based on big data Download PDFInfo
- Publication number
- CN113065928A CN113065928A CN202110437914.4A CN202110437914A CN113065928A CN 113065928 A CN113065928 A CN 113065928A CN 202110437914 A CN202110437914 A CN 202110437914A CN 113065928 A CN113065928 A CN 113065928A
- Authority
- CN
- China
- Prior art keywords
- buyer
- module
- product
- transaction
- seller
- 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.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000011156 evaluation Methods 0.000 claims abstract description 34
- 238000005065 mining Methods 0.000 claims abstract description 9
- 238000007405 data analysis Methods 0.000 claims description 13
- 238000005516 engineering process Methods 0.000 claims description 10
- 238000010219 correlation analysis Methods 0.000 claims description 7
- 238000011157 data evaluation Methods 0.000 claims description 7
- 238000004458 analytical method Methods 0.000 claims description 4
- 238000007418 data mining Methods 0.000 claims description 4
- 239000002537 cosmetic Substances 0.000 claims description 3
- 238000005034 decoration Methods 0.000 claims description 3
- 230000004927 fusion Effects 0.000 claims description 3
- 230000009191 jumping Effects 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 238000012552 review Methods 0.000 claims description 3
- 230000009286 beneficial effect Effects 0.000 abstract description 5
- 239000000284 extract Substances 0.000 abstract description 3
- 238000013480 data collection Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 230000036651 mood Effects 0.000 description 2
- 238000004422 calculation algorithm Methods 0.000 description 1
- 238000013079 data visualisation Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 238000003860 storage Methods 0.000 description 1
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
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0605—Supply or demand aggregation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/36—Creation of semantic tools, e.g. ontology or thesauri
- G06F16/367—Ontology
-
- 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
- G06Q20/00—Payment architectures, schemes or protocols
- G06Q20/08—Payment architectures
- G06Q20/12—Payment architectures specially adapted for electronic shopping systems
-
- 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
- G06Q30/0282—Rating or review of business operators or products
-
- 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
-
- 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]
- G06Q30/0633—Lists, e.g. purchase orders, compilation or processing
- G06Q30/0635—Processing of requisition or of purchase orders
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Theoretical Computer Science (AREA)
- Strategic Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Development Economics (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Economics (AREA)
- Life Sciences & Earth Sciences (AREA)
- Animal Behavior & Ethology (AREA)
- Computational Linguistics (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- General Engineering & Computer Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Game Theory and Decision Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention discloses an E-commerce transaction method based on big data, which belongs to the technical field of electronic commerce and comprises the following specific steps: (1) constructing a novel e-commerce transaction platform; (2) releasing the buyer demand information; (3) recommending big data products; (4) comparing and clearing the seller products; (5) evaluating and mining big data; (6) payment for the transaction; the invention provides a novel E-commerce transaction platform taking a buyer as a center, wherein the buyer can obtain targeted seller product recommendation by issuing demand information on the platform, so that the buyer can buy commodities of own mind in less time; in addition, the invention also provides a product evaluation knowledge map, which extracts high-quality product evaluation by removing repeated words, stop words, whispering words and whispering words from the comments, thereby being beneficial to the buyer to comprehensively know and recognize the product of the seller.
Description
Technical Field
The invention relates to the technical field of electronic commerce, in particular to an E-commerce transaction method based on big data.
Background
Through retrieval, the Chinese patent No. CN108229876A discloses an E-commerce transaction method and an E-commerce transaction system based on big data, and although the method can be used for matching orders among consumers to improve the efficiency of logistics transportation, the advertisement promotion cost of sellers cannot be reduced, the transaction speed of products cannot be improved, and comprehensive product information evaluation cannot be provided; the big data refers to a data set which has an extremely large data volume and cannot be analyzed by using a traditional data collection mode, a traditional database and a traditional research method; the big data technology is a technology for extracting big data value, and is a technology for providing scientific basis for final decision through data collection, storage, screening, algorithm analysis and prediction, data analysis result display and the like based on a specific target; the big data technology originates from the traditional data mining and business intelligence technology, is an important product of high-speed development of information technology, and mainly comprises important technologies such as cloud computing, data acquisition, a file system, a database system, data analysis, data visualization and the like at present; with the continuous development of electronic commerce, the transaction data volume is also changed exponentially, and how to fuse the transaction data volume with big data solves the actual transaction problem, which becomes a problem to be solved urgently; therefore, it becomes important to invent a big data-based e-commerce transaction method;
the existing e-commerce transaction method is a rabbit-keeping sales mode, a seller can only wait passively and does not know where, how many and what a customer wants to buy, and in order to promote sales, the seller usually carries out advertisement promotion to increase the flow, which undoubtedly increases the sales cost of the seller; moreover, such transaction methods also tend to increase the time for the buyer to select the goods, and thus the transaction speed of the product cannot be increased; in addition, the seller of the transaction method occupies an information dominance position, so that the buyer cannot comprehensively know the product evaluation; therefore, an E-commerce transaction method based on big data is provided.
Disclosure of Invention
The invention aims to solve the defects in the prior art and provides an E-commerce transaction method based on big data.
In order to achieve the purpose, the invention adopts the following technical scheme:
an E-commerce transaction method based on big data comprises the following specific steps:
(1) constructing a novel e-commerce transaction platform: constructing a novel E-commerce transaction platform taking a buyer as a center, taking a third-party payment center as a transaction guarantee party, and registering the buyer and a seller into the platform by filling basic information;
(2) and (3) publishing the buyer requirement information: a buyer logs in the novel e-commerce transaction platform in the step (1) through a client mobile terminal, selects a corresponding commodity transaction module according to the self requirement and simultaneously releases specific requirement information of products needing to be purchased;
(3) big data product recommendation: the novel e-commerce transaction platform carries out automatic correlation analysis on a buyer demand and a seller product by using background big data analysis software, and pushes the seller product to the buyer if the correlation between the buyer demand information and the seller product is greater than a set threshold value;
(4) comparing and clearing the seller products: after receiving the seller products recommended in the step (3), the buyer performs self-expectation comparison, if the seller products meet the expected requirements, the seller products can be added into the shopping cart module or the seller products are selected to jump to the step (6) for direct transaction, otherwise, the seller products are removed and filtered;
(5) and (3) big data evaluation and mining: if the buyer needs to know the evaluation information of the seller products added into the shopping cart module in the step (4), the big data evaluation mining of the seller products can be selected through a product evaluation module; if the mined evaluation information meets the requirements of the buyer, the buyer can jump to the step (6) to carry out transaction, otherwise, the buyer can jump to the step (3) through a secondary recommendation module to carry out two rounds of big data product recommendation;
(6) transaction payment: and the buyer carries out the transaction payment of the third-party payment center through the transaction payment module, if the payment is successful, the corresponding logistics information and the transaction information are formed, otherwise, the transaction is failed, and the payment is carried out again.
Further, the novel e-commerce transaction platform in the step (1) comprises a commodity transaction module, a demand information publishing module, a big data analysis recommending module, a recommended product selecting module, a shopping cart module, a product evaluating module, a secondary recommending module and a transaction payment module.
Further, the commodity transaction module is used for the buyer to select the corresponding field of the required product; the demand information publishing module is used for describing specific demand information of a demand product by a buyer, wherein the demand information comprises color, model, style, size and brand; the big data analysis recommending module is used for carrying out automatic correlation analysis on the buyer requirement and the seller product by utilizing background big data analysis software; the recommended product selection module is used for selecting and removing the filter processing of the recommendation of the seller products according to the expected demands of the buyers; the shopping cart module is used for storing recommended seller products of the buyer psychoscope; the product evaluation module is used for mining useful and high-quality product comment information from each large platform by using a knowledge graph technology; the secondary recommendation module is used for jumping to the big data analysis recommendation module to perform secondary or multiple analysis recommendation; the transaction payment module is used for the buyer to carry out transaction payment through the third-party payment center.
Further, the commodity transaction module in the step (2) comprises clothes, food, digital products, cosmetics, home decoration and toys; in the step (3), the threshold value is 85%; and (3) the specific number of the seller products pushed at one time is 15.
Further, the product evaluation module in the step (5) is specifically a product evaluation knowledge graph, and the specific generation process is as follows:
the method comprises the following steps: acquiring original comment data from a plurality of product comment data sources, and extracting the original comment data to form a subject-predicate-object triple;
step two: and (4) removing repeated words, stop words, whispering words and pseudonyms from the triples in the step one, performing part-of-speech tagging, and then performing data fusion to generate a product evaluation knowledge graph.
Further, the plurality of product review data sources include Baidu encyclopedia, Taobao, Jingdong, Temple, West concerts, Small Red Books, Bar Sticks, and Forum.
Compared with the prior art, the invention has the beneficial effects that:
1. the E-commerce transaction method based on the big data provides a novel E-commerce transaction platform taking a buyer as a center, completely subverts the traditional E-commerce transaction method, and the buyer can obtain targeted seller product recommendation by releasing the demand information in the platform, so that the buyer can buy commodities of own mood instrument in less time; the novel e-commerce transaction platform is provided with a big data analysis recommendation module, and the module automatically analyzes the correlation between the buyer requirement and the seller product and recommends the seller product with the correlation larger than a set threshold value, so that the advertisement promotion cost of the seller about the product is reduced, personalized product recommendation is provided for the buyer, and the product transaction speed is improved;
2. the E-commerce transaction method based on the big data provides a product evaluation knowledge map, and the product evaluation knowledge map extracts high-quality product evaluation by removing repeated words, stop words, whispering words and whispering words from comments, thereby being beneficial to the buyer to comprehensively know and recognize the product of the seller.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
Fig. 1 is an overall flowchart of an e-commerce transaction method based on big data according to 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.
In the description of the present invention, it is to be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are merely for convenience in describing the present invention and simplifying the description, and do not indicate or imply that the device or element being referred to must have a particular orientation, be constructed and operated in a particular orientation, and thus, should not be construed as limiting the present invention.
Referring to fig. 1, an e-commerce transaction method based on big data includes the following specific steps:
(1) constructing a novel e-commerce transaction platform: constructing a novel E-commerce transaction platform taking a buyer as a center, taking a third-party payment center as a transaction guarantee party, and registering the buyer and a seller into the platform by filling basic information;
(2) and (3) publishing the buyer requirement information: a buyer logs in the novel E-commerce transaction platform in the step (1) through a client mobile terminal, selects a corresponding commodity transaction module according to the self requirement and simultaneously releases specific requirement information of products needing to be purchased;
(3) big data product recommendation: the method comprises the following steps that (1) the novel e-commerce transaction platform utilizes background big data analysis software to perform automatic correlation analysis of a buyer requirement and a seller product, and if the correlation degree of buyer requirement information and the seller product is larger than a set threshold value, the seller product is pushed to the buyer;
(4) comparing and clearing the seller products: after receiving the seller products recommended in the step (3), the buyer performs self-expectation comparison, if the seller products meet the expected requirements, the seller products can be added into the shopping cart module or the seller products are selected to jump to the step (6) for direct transaction, otherwise, the seller products are removed and filtered;
(5) and (3) big data evaluation and mining: if the buyer needs to know the evaluation information of the seller products added into the shopping cart module in the step (4), the big data evaluation mining of the seller products can be selected through a product evaluation module; if the mined evaluation information meets the requirements of the buyer, the buyer can jump to the step (6) to carry out transaction, otherwise, the buyer can jump to the step (3) through a secondary recommendation module to carry out two rounds of big data product recommendation;
(6) transaction payment: and the buyer carries out the transaction payment of the third-party payment center through the transaction payment module, if the payment is successful, the corresponding logistics information and the transaction information are formed, otherwise, the transaction is failed, and the payment is carried out again.
The specific scheme of the embodiment is as follows: the novel E-commerce transaction platform in the step (1) comprises a commodity transaction module, a demand information publishing module, a big data analysis recommending module, a recommended product selecting module, a shopping cart module, a product evaluating module, a secondary recommending module and a transaction payment module.
The commodity transaction module is used for the buyer to select the corresponding field of the required product; the demand information publishing module is used for describing specific demand information of a demand product by a buyer, wherein the demand information comprises color, model, style, size and brand; the big data analysis recommending module is used for carrying out automatic correlation analysis on the buyer requirement and the seller product by utilizing background big data analysis software; the recommended product selection module is used for selecting and removing the filtering processing of the recommendation of the seller products according to the expected demand of the buyer; the shopping cart module is used for storing recommended seller products of the buyer; the product evaluation module is used for mining useful and high-quality product comment information from each large platform by using a knowledge graph technology; the secondary recommendation module is used for jumping to the big data analysis recommendation module to perform secondary or multiple analysis recommendation; the transaction payment module is used for the buyer to carry out transaction payment through the third-party payment center.
The commodity transaction module in the step (2) comprises clothes, food, digital products, cosmetics, home decoration and toys; the threshold value in the step (3) is 85 percent; and (3) the specific quantity of the products pushed by the seller at one time is 15.
The specific scheme of the embodiment is as follows: the product evaluation module in the step (5) is specifically a product evaluation knowledge graph, and the specific generation process is as follows:
the method comprises the following steps: acquiring original comment data from a plurality of product comment data sources, and extracting the original comment data to form a subject-predicate-object triple;
step two: and (4) removing repeated words, stop words, whispering words and pseudonyms from the triples in the step one, performing part-of-speech tagging, and then performing data fusion to generate a product evaluation knowledge graph.
The multiple product review data sources include Baidu encyclopedia, Taobao, Jingdong, Temple, Wei Hui, Small Red book, Bar and Forum.
The working principle and the using process of the invention are as follows: when the E-commerce transaction method based on the big data is used, a novel E-commerce transaction platform is constructed in the first step: constructing a novel E-commerce transaction platform taking a buyer as a center, taking a third-party payment center as a transaction guarantee party, and registering the buyer and a seller into the platform by filling basic information; secondly, releasing the buyer requirement information: a buyer logs in a first-step novel e-commerce transaction platform through a client mobile terminal, selects a corresponding commodity transaction module according to own requirements, and simultaneously releases specific requirement information of products to be purchased; thirdly, recommending big data products: the novel e-commerce transaction platform utilizes background big data analysis software to perform automatic correlation analysis of the buyer requirement and the seller product, and pushes the seller product to the buyer if the correlation degree of the buyer requirement information and the seller product is greater than a set threshold value; fourthly, comparing and clearing the seller products: the buyer carries out self-expectation comparison after receiving the seller products recommended in the third step, if the seller products meet the expectation requirements, the seller products can be added into the shopping cart module or the sixth step is selected to be skipped to for direct transaction, otherwise, the seller products are removed and filtered; fifthly, evaluating and mining big data: if the buyer needs to know the evaluation information of the seller products added into the shopping cart module, the buyer can choose to conduct big data evaluation mining on the seller products through a product evaluation module; if the mined evaluation information meets the requirements of the buyer, the buyer can jump to the sixth step for transaction, otherwise, the buyer can jump to the third step through the secondary recommendation module to perform two rounds of big data product recommendation; sixthly, transaction payment: the buyer carries out transaction payment of the third-party payment center through the transaction payment module, if the payment is successful, corresponding logistics information and transaction information are formed, otherwise, the transaction is failed, and the payment is carried out again; the invention provides a novel e-commerce transaction platform taking a buyer as a center, which completely subverts the traditional e-commerce transaction method, and the buyer can obtain targeted seller product recommendation by releasing demand information on the platform, thereby being beneficial to the buyer to buy the commodity of the own mood instrument in less time; the novel e-commerce transaction platform is provided with a big data analysis recommendation module, and the module automatically analyzes the correlation between the buyer requirement and the seller product and recommends the seller product with the correlation larger than a set threshold value, so that the advertisement promotion cost of the seller about the product is reduced, personalized product recommendation is provided for the buyer, and the product transaction speed is improved; in addition, the invention also provides a product evaluation knowledge map, which extracts high-quality product evaluation by removing repeated words, stop words, whispering words and whispering words from the comments, thereby being beneficial to the buyer to comprehensively know and recognize the product of the seller.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (6)
1. The E-commerce transaction method based on big data is characterized by comprising the following specific steps:
(1) constructing a novel e-commerce transaction platform: constructing a novel E-commerce transaction platform taking a buyer as a center, taking a third-party payment center as a transaction guarantee party, and registering the buyer and a seller into the platform by filling basic information;
(2) and (3) publishing the buyer requirement information: a buyer logs in the novel e-commerce transaction platform in the step (1) through a client mobile terminal, selects a corresponding commodity transaction module according to the self requirement and simultaneously releases specific requirement information of products needing to be purchased;
(3) big data product recommendation: the novel e-commerce transaction platform carries out automatic correlation analysis on a buyer demand and a seller product by using background big data analysis software, and pushes the seller product to the buyer if the correlation between the buyer demand information and the seller product is greater than a set threshold value;
(4) comparing and clearing the seller products: after receiving the seller products recommended in the step (3), the buyer performs self-expectation comparison, if the seller products meet the expected requirements, the seller products can be added into the shopping cart module or the seller products are selected to jump to the step (6) for direct transaction, otherwise, the seller products are removed and filtered;
(5) and (3) big data evaluation and mining: if the buyer needs to know the evaluation information of the seller products added into the shopping cart module in the step (4), the big data evaluation mining of the seller products can be selected through a product evaluation module; if the mined evaluation information meets the requirements of the buyer, the buyer can jump to the step (6) to carry out transaction, otherwise, the buyer can jump to the step (3) through a secondary recommendation module to carry out two rounds of big data product recommendation;
(6) transaction payment: and the buyer carries out the transaction payment of the third-party payment center through the transaction payment module, if the payment is successful, the corresponding logistics information and the transaction information are formed, otherwise, the transaction is failed, and the payment is carried out again.
2. The big data-based e-commerce transaction method according to claim 1, wherein the novel e-commerce transaction platform of step (1) comprises a commodity transaction module, a demand information release module, a big data analysis recommendation module, a recommended product selection module, a shopping cart module, a product evaluation module, a secondary recommendation module and a transaction payment module.
3. The big data-based e-commerce transaction method according to claim 2, wherein the commodity transaction module is used for the buyer to select a corresponding field of the required product; the demand information publishing module is used for describing specific demand information of a demand product by a buyer, wherein the demand information comprises color, model, style, size and brand; the big data analysis recommending module is used for carrying out automatic correlation analysis on the buyer requirement and the seller product by utilizing background big data analysis software; the recommended product selection module is used for selecting and removing the filter processing of the recommendation of the seller products according to the expected demands of the buyers; the shopping cart module is used for storing recommended seller products of the buyer psychoscope; the product evaluation module is used for mining useful and high-quality product comment information from each large platform by using a knowledge graph technology; the secondary recommendation module is used for jumping to the big data analysis recommendation module to perform secondary or multiple analysis recommendation; the transaction payment module is used for the buyer to carry out transaction payment through the third-party payment center.
4. The big data-based e-commerce transaction method according to claim 1, wherein the commodity transaction module of step (2) comprises clothing, food, digital products, cosmetics, home decoration and toys; in the step (3), the threshold value is 85%; and (3) the specific number of the seller products pushed at one time is 15.
5. The big data-based e-commerce transaction method according to claim 1, wherein the product evaluation module in step (5) is a product evaluation knowledge graph, and the generation process is as follows:
the method comprises the following steps: acquiring original comment data from a plurality of product comment data sources, and extracting the original comment data to form a subject-predicate-object triple;
step two: and (4) removing repeated words, stop words, whispering words and pseudonyms from the triples in the step one, performing part-of-speech tagging, and then performing data fusion to generate a product evaluation knowledge graph.
6. The big-data-based e-commerce transaction method of claim 5, wherein the plurality of product review data sources comprise Baidu encyclopedia, Taobao, Jingdong, Teddy, Wei Hui, Small Red book, post Bar, and Forum.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110437914.4A CN113065928A (en) | 2021-04-22 | 2021-04-22 | E-commerce transaction method based on big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110437914.4A CN113065928A (en) | 2021-04-22 | 2021-04-22 | E-commerce transaction method based on big data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113065928A true CN113065928A (en) | 2021-07-02 |
Family
ID=76567669
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202110437914.4A Pending CN113065928A (en) | 2021-04-22 | 2021-04-22 | E-commerce transaction method based on big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113065928A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113902522A (en) * | 2021-09-29 | 2022-01-07 | 鹏城实验室 | Patent recommendation method and terminal based on graph neural network |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105912656A (en) * | 2016-04-07 | 2016-08-31 | 桂林电子科技大学 | Construction method of commodity knowledge graph |
| CN110532462A (en) * | 2019-07-25 | 2019-12-03 | 北京三快在线科技有限公司 | A kind of recommended method, device, equipment and readable storage medium storing program for executing |
| CN110942365A (en) * | 2019-09-14 | 2020-03-31 | 深圳家电网科技实业股份有限公司 | E-commerce transaction method and E-commerce transaction system for big data |
| CN111047382A (en) * | 2018-10-15 | 2020-04-21 | 薛康泰华 | Online transaction method and system with buyer as center |
| CN111429214A (en) * | 2020-03-13 | 2020-07-17 | 贝壳技术有限公司 | Transaction data-based buyer and seller matching method and device |
| CN111611399A (en) * | 2020-04-15 | 2020-09-01 | 广发证券股份有限公司 | Information event mapping system and method based on natural language processing |
| CN111681085A (en) * | 2020-06-10 | 2020-09-18 | 创新奇智(成都)科技有限公司 | Commodity pushing method and device, server and readable storage medium |
| CN111897914A (en) * | 2020-07-20 | 2020-11-06 | 杭州叙简科技股份有限公司 | Entity information extraction and knowledge graph construction method for field of comprehensive pipe gallery |
| CN111985998A (en) * | 2020-08-19 | 2020-11-24 | 江苏经贸职业技术学院 | Electronic commerce transaction architecture and process |
| CN112070552A (en) * | 2020-09-15 | 2020-12-11 | 苏宇航 | Electronic commerce platform based on big data |
| CN112465540A (en) * | 2020-11-19 | 2021-03-09 | 马鞍山因特莱信息科技有限公司 | Online transaction cloud platform based on big data |
-
2021
- 2021-04-22 CN CN202110437914.4A patent/CN113065928A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105912656A (en) * | 2016-04-07 | 2016-08-31 | 桂林电子科技大学 | Construction method of commodity knowledge graph |
| CN111047382A (en) * | 2018-10-15 | 2020-04-21 | 薛康泰华 | Online transaction method and system with buyer as center |
| CN110532462A (en) * | 2019-07-25 | 2019-12-03 | 北京三快在线科技有限公司 | A kind of recommended method, device, equipment and readable storage medium storing program for executing |
| CN110942365A (en) * | 2019-09-14 | 2020-03-31 | 深圳家电网科技实业股份有限公司 | E-commerce transaction method and E-commerce transaction system for big data |
| CN111429214A (en) * | 2020-03-13 | 2020-07-17 | 贝壳技术有限公司 | Transaction data-based buyer and seller matching method and device |
| CN111611399A (en) * | 2020-04-15 | 2020-09-01 | 广发证券股份有限公司 | Information event mapping system and method based on natural language processing |
| CN111681085A (en) * | 2020-06-10 | 2020-09-18 | 创新奇智(成都)科技有限公司 | Commodity pushing method and device, server and readable storage medium |
| CN111897914A (en) * | 2020-07-20 | 2020-11-06 | 杭州叙简科技股份有限公司 | Entity information extraction and knowledge graph construction method for field of comprehensive pipe gallery |
| CN111985998A (en) * | 2020-08-19 | 2020-11-24 | 江苏经贸职业技术学院 | Electronic commerce transaction architecture and process |
| CN112070552A (en) * | 2020-09-15 | 2020-12-11 | 苏宇航 | Electronic commerce platform based on big data |
| CN112465540A (en) * | 2020-11-19 | 2021-03-09 | 马鞍山因特莱信息科技有限公司 | Online transaction cloud platform based on big data |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113902522A (en) * | 2021-09-29 | 2022-01-07 | 鹏城实验室 | Patent recommendation method and terminal based on graph neural network |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109542916A (en) | Platform commodity enter method, apparatus, computer equipment and storage medium | |
| CN103914492B (en) | Query word fusion method, merchandise news dissemination method and searching method and system | |
| CN108960992A (en) | A kind of information recommendation method and relevant device | |
| US20190156395A1 (en) | System and Method for Analyzing and Searching for Features Associated with Objects | |
| CN107332910B (en) | Information pushing method and device | |
| WO2022156529A1 (en) | Commodity recommendation method and apparatus for enterprise user | |
| US20230214895A1 (en) | Methods and systems for product discovery in user generated content | |
| US10664888B2 (en) | Method and system for attribute extraction from product titles using sequence labeling algorithms | |
| CN107993134A (en) | A kind of smart shopper exchange method and system based on user interest | |
| CN106708821A (en) | User personalized shopping behavior-based commodity recommendation method | |
| CN111666275B (en) | Data processing method and device, electronic equipment and storage medium | |
| CN105718184A (en) | Data processing method and apparatus | |
| KR20210098884A (en) | A method of providing a fashion item recommendation service using a body shape and purchase history | |
| CN101840559A (en) | Online international commodity trading system | |
| CN103903152A (en) | Online shopping center system | |
| CN104615721B (en) | For the method and system based on return of goods related information Recommendations | |
| US20200226168A1 (en) | Methods and systems for optimizing display of user content | |
| CN103412938A (en) | Commodity price comparing method based on picture interactive type multiple-target extraction | |
| CN103544608A (en) | Network transaction platform system with commodity subscription structure and network transaction method | |
| CN111667337A (en) | Commodity evaluation ordering method and system | |
| CN112365283B (en) | Coupon issuing method and device, terminal equipment and storage medium | |
| CN103544627A (en) | Information analyzing system and information analyzing method in network transaction | |
| CN109767292A (en) | A kind of buyer company recommended method | |
| CN113065928A (en) | E-commerce transaction method based on big data | |
| CN111177581A (en) | Multi-platform-based social e-commerce website commodity recommendation method and device |
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 |