CN104392370A - Electronic commerce system and method for automatically acquiring customer information - Google Patents
Electronic commerce system and method for automatically acquiring customer information Download PDFInfo
- Publication number
- CN104392370A CN104392370A CN201410618589.1A CN201410618589A CN104392370A CN 104392370 A CN104392370 A CN 104392370A CN 201410618589 A CN201410618589 A CN 201410618589A CN 104392370 A CN104392370 A CN 104392370A
- Authority
- CN
- China
- Prior art keywords
- module
- customer
- client
- acquisition
- stored data
- 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
Abstract
The invention discloses an electronic commerce system and method for automatically acquiring customer information. According to the electronic commerce system and method for automatically acquiring customer information, facial feature data of customers who have patronized a shop are recorded and are matched with the facial features of customers who enter the shop and perform payment, if matching information is found, basic membership data and cumulative consumption data related to the customers are retrieved, if matching information is not found, the facial features of the customers are saved. According to the electronic commerce system and method for automatically acquiring customer information, face recognition technologies are combined with an electronic commerce platform, so that customers can be automatically recognized, and therefore, timely grasp of consumption preferences can be facilitated for operators, and high-efficiency shopping guide can be realized, and payment speed can be increased.
Description
Technical field
The present invention relates to a kind of e-commerce system and method, specifically refer to a kind of e-commerce system based on face recognition technology automatic acquisition Customer Information and method.
Background technology
Along with the development and progress of science and technology, face recognition technology is ripe day by day.Therefore, based on face recognition technology, can make that various business platform is more intelligent serves the general public more easily.
Present all kinds of retail shops, there is every day a lot of client to pass in and out and browse shopping, with human brain memory, Shopping Guide only cannot remember that the current client coming into retail shop is patron or new client at all, if the words of patron, it is partial to the commodity liking what style or type, consumer record once, discount enjoyed etc. information.
Therefore, present all kinds of retail shops, no matter scale, all all kinds of consumption information being carried out management of consumer by membership system, but this category information could read after also only only showing member card when client checks and show, Shopping Guide cannot know its name and hobby client in entering shop, shooting the arrow at the target for not accomplishing during customer recommendation commodity, the shopping side often touching not potential client to.
Based on above-mentioned, need to provide a kind of can based on the e-commerce system of the automatic quick obtaining Customer Information of face recognition technology and method, it can assist Shopping Guide better is in time customer service.
Summary of the invention
The object of the present invention is to provide a kind of e-commerce system and method for automatic acquisition Customer Information, based on face recognition technology, it is combined with e-commerce platform, client is identified automatically, be conducive to operator and grasp consumption deflection in time, efficient shopping guide can be realized, and accelerate checkout speed.
In order to achieve the above object, the invention provides a kind of e-commerce system of automatic acquisition Customer Information, comprise: stored data base, the face feature data of the client of retail shop and corresponding user profile patronized in its record; Face recognition module, it is connected with described stored data base, carries out recognition of face to as the client advancing into retail shop and in stored data base, finds the customer files of face feature data match; User profile acquisition module, it is connected with described face recognition module and stored data base respectively, according to the customer files of the coupling that face recognition module searches out, calls corresponding user profile in stored data base.
Described face recognition module comprises: the first acquisition module, and it is arranged on position, doorway, shop, carries out acquisition and recording to the facial image information of the client entering shop; Second acquisition module, it is arranged on cash register location, carries out acquisition and recording to the facial image information of the client of shopping checkout; Extraction module, it is connected with the first described acquisition module and the second acquisition module respectively, receives the customer face image information of the first acquisition module or the second acquisition module record, and extracts the face feature data of this client; Matching module, it is connected with described extraction module, the customer files that the customer face characteristic that searching and extraction module obtain in stored data base matches.
The first described acquisition module and the second acquisition module are camera or camera.
Described user profile acquisition module comprises: calling module, it is connected with described matching module and stored data base respectively, according to the customer files of the coupling that matching module searches out, in stored data base, call the user profile corresponding with it, comprise basic member data and cumulative consumption data; Analysis module, it is connected with described calling module, receives the cumulative consumption data that calling module obtains, analyzes and generate customer consumption deflection figure; Display module, it is connected with described calling module and analysis module respectively, the customer consumption deflection figure of display analysis CMOS macro cell, and the basic member data that display calling module obtains.
The present invention also provides a kind of E-commerce method of automatic acquisition Customer Information, comprises following steps:
S1, face recognition module are carried out recognition of face to as the client advancing into retail shop and in stored data base, find the customer files that whether there is face feature data match; As found, then performing step S2, as do not found, then performing step S3;
The customer files matched that S2, user profile acquisition module search out according to face recognition module, calls the cumulative consumption data in corresponding user profile in stored data base;
S3, the face characteristic data of current customer are recorded in stored data base;
Settle accounts after S4, customer purchase, the customer files matched that user profile acquisition module searches out according to face recognition module, in stored data base, call the basic member data in corresponding user profile, and the consumption data of this shopping of client is recorded in stored data base.
Described step S1 comprises following steps:
S1.1, the first acquisition module facial image information to the client entering shop carries out acquisition and recording;
S1.2, extraction module receive the facial image information of the client of the first acquisition module record, and extract the face feature data of this client;
The customer files that the customer face characteristic that S1.3, matching module are found in stored data base and extraction module obtains matches; As found, performing step S2.1, as do not found, performing step S3.
Described step S2 comprises following steps:
The customer files of the coupling that S2.1, calling module search out according to matching module, finds the cumulative consumption data in the user profile corresponding with it in stored data base; As found, performing step S2.2, as do not found, performing step S4;
S2.2, analysis module receive the cumulative consumption data that calling module obtains, and analyze and generate customer consumption deflection figure;
The customer consumption deflection figure of S2.3, display module display analysis CMOS macro cell.
Described step S4 comprises following steps:
S4.1, client this time non-purchase and consumption, terminates;
Settle accounts after S4.2, customer purchase, face recognition module is carried out recognition of face to the client of current checkout and in stored data base, is found the customer files of face feature data match;
The customer files of the coupling that S4.3, user profile acquisition module search out according to face recognition module, the basic member data in the user profile corresponding with it is found in stored data base, complete checkout, and this consumption data of doing shopping is recorded in stored data base.
Described step S4.2 specifically comprises following steps:
Settle accounts after S4.2.1, customer purchase, the second acquisition module carries out acquisition and recording to the facial image information of this checkout client;
S4.2.2, extraction module receive the facial image information of the client of the second acquisition module record, and extract the face feature data of this client;
The customer files that the customer face characteristic that S4.2.3, matching module are found in stored data base and extraction module obtains matches.
Described step S4.3 specifically comprises following steps:
The customer files of the coupling that S4.3.1, calling module search out according to matching module, finds the basic member data in the user profile corresponding with it in stored data base, as found, performs step S4.3.2; As do not found, perform step S4.3.3;
Basic member data described in the display of S4.3.2, display module, cashier completes checkout according to this basic member data, and is recorded in stored data base by this consumption data of doing shopping;
S4.3.3, complete checkout, and the consumption data of the basic member data of client and this shopping is recorded in stored data base.
In sum, the e-commerce system of automatic acquisition Customer Information provided by the present invention and method, based on face recognition technology, it is combined with e-commerce platform, client is identified automatically, is conducive to operator and grasps consumption deflection in time, efficient shopping guide can be realized, and accelerate checkout speed, greatly reduce the situation of queuing checkout time in market.
Accompanying drawing explanation
Fig. 1 is the structural representation of the e-commerce system of automatic acquisition Customer Information provided by the invention;
Fig. 2 is the basic flow sheet of the E-commerce method of automatic acquisition Customer Information provided by the invention;
Fig. 3 is the particular flow sheet of the E-commerce method of automatic acquisition Customer Information provided by the invention.
Embodiment
Below in conjunction with Fig. 1 ~ Fig. 3, by describing a preferably specific embodiment in detail, the present invention is further elaborated.
As shown in Figure 1, be the structural representation of the e-commerce system of automatic acquisition Customer Information provided by the present invention, this system comprises: stored data base 1, and the face feature data of the client of retail shop and corresponding user profile patronized in its record; Face recognition module 2, it is connected with described stored data base 1, carries out recognition of face to as the client advancing into retail shop and in stored data base 1, finds the customer files of face feature data match; User profile acquisition module 3, it is connected with described face recognition module 2 and stored data base 1 respectively, according to the customer files of the coupling that face recognition module 2 searches out, calls corresponding user profile in stored data base 1.
Further, described face recognition module 2 comprises: the first acquisition module 21, and it is arranged on position, doorway, shop, carries out acquisition and recording to the facial image information of the client entering shop; Second acquisition module 24, it is arranged on cash register location, carries out acquisition and recording to the facial image information of the client of shopping checkout; Extraction module 22, it is connected with the first described acquisition module 21 and the second acquisition module 24 respectively, receives the customer face image information of the first acquisition module 21 or the second acquisition module 24 record, and extracts the face feature data of this client; Matching module 23, it is connected with described extraction module 22, the customer files that the customer face characteristic that searching and extraction module 22 obtain in stored data base 1 matches.
The first described acquisition module 21 and the second acquisition module 24 are camera or camera.
Described user profile acquisition module 3 comprises: calling module 31, it is connected with described matching module 23 and stored data base 1 respectively, according to the customer files of the coupling that matching module 23 searches out, in stored data base 1, call the user profile corresponding with it, comprise basic member data and cumulative consumption data; Analysis module 32, it is connected with described calling module 31, receives the cumulative consumption data that calling module 31 obtains, analyzes and generate customer consumption deflection figure; Display module 33, it is connected with described calling module 31 and analysis module 32 respectively, the customer consumption deflection figure that display analysis module 32 generates, and the basic member data that display calling module 31 obtains.
Described basic member data comprises: the name of client, the age, birthday, Shipping Address, telephone number, scores accumulated, the discount information etc. that should enjoy; Described cumulative consumption data comprise the passing consumer record of client, such as its inventory once bought, the type of merchandise bought and the style information etc. of preference.
As shown in Figures 2 and 3, be the process flow diagram of the E-commerce method of automatic acquisition Customer Information provided by the invention, the method includes the steps of:
S1, face recognition module 2 are carried out recognition of face to as the client advancing into retail shop and in stored data base 1, find the customer files that whether there is face feature data match; As found, then performing step S2, as do not found, then performing step S3;
The customer files matched that S2, user profile acquisition module 3 search out according to face recognition module 2, calls the cumulative consumption data in corresponding user profile in stored data base 1;
S3, the face characteristic data of current customer are recorded in stored data base 1;
S4, when client settles accounts after shopping, the customer files matched that user profile acquisition module 3 searches out according to face recognition module 2, in stored data base 1, call the basic member data in corresponding user profile, and the consumption data of this shopping of client is recorded in stored data base 1.
Wherein, described step S1 comprises following steps:
S1.1, the facial image information of the first acquisition module 21 to the client entering shop carry out acquisition and recording;
S1.2, extraction module 22 receive the facial image information of the client that the first acquisition module 21 records, and extract the face feature data of this client;
The customer files that the customer face characteristic that S1.3, matching module 23 are found in stored data base 1 and extraction module 22 obtains matches; As found, illustrating and once coming head store between this client, then perform step S2.1, as do not found, illustrating that this client comes head store first time, then performing step S3.
Described step S2 comprises following steps:
The customer files of the coupling that S2.1, calling module 31 search out according to matching module 23, finds the cumulative consumption data in the user profile corresponding with it in stored data base 1; As found, once at head store post-consumer before this client being described, performing step S2.2, as do not found, only coming head store before this client is described, but not consuming, perform step S4;
S2.2, analysis module 32 receive the cumulative consumption data that calling module 31 obtains, and analyze and generate customer consumption deflection figure;
The customer consumption deflection figure that S2.3, display module 33 display analysis module 32 generate, makes Shopping Guide specifically can like for client and carries out shopping guide's service.
Described step S4 comprises following steps:
S4.1, client this time non-purchase and consumption, terminates;
Settle accounts after S4.2, customer purchase, face recognition module 2 is carried out recognition of face to the client of current checkout and in stored data base 1, is found the customer files of face feature data match;
The customer files of the coupling that S4.3, user profile acquisition module 3 search out according to face recognition module 2, the basic member data in the user profile corresponding with it is found in stored data base 1, complete checkout, and this consumption data of doing shopping is recorded in stored data base 1.
Described step S4.2 specifically comprises following steps:
Settle accounts after S4.2.1, customer purchase, the second acquisition module 24 carries out acquisition and recording to the facial image information of this checkout client;
S4.2.2, extraction module 22 receive the facial image information of the client that the second acquisition module 24 records, and extract the face feature data of this client;
The customer files that the customer face characteristic that S4.2.3, matching module 23 are found in stored data base 1 and extraction module 22 obtains matches.
Described step S4.3 specifically comprises following steps:
The customer files of the coupling that S4.3.1, calling module 31 search out according to matching module 23, the basic member data in the user profile corresponding with it is found in stored data base 1, as found, once at head store post-consumer before this client is described, perform step S4.3.2; As do not found, this being described customers first time in head store consumption, performing step S4.3.3;
S4.3.2, display module 33 show described basic member data, after cashier and client confirm the relevant information such as name, Shipping Address (if the deliver goods of customer need retail shop), the discount information should enjoyed according to it completes checkout and cumulative integral, is finally recorded in stored data base 1 by this consumption data of doing shopping;
S4.3.3, complete checkout, and the consumption data of the basic member data of client and this shopping is recorded in stored data base 1.
In sum, the e-commerce system of automatic acquisition Customer Information provided by the present invention and method, based on face recognition technology, it is combined with e-commerce platform, client is identified automatically, is conducive to operator and grasps consumption deflection in time, efficient shopping guide can be realized, and accelerate checkout speed, greatly reduce the situation of queuing checkout time in market.
Although content of the present invention has done detailed introduction by above preferred embodiment, will be appreciated that above-mentioned description should not be considered to limitation of the present invention.After those skilled in the art have read foregoing, for multiple amendment of the present invention and substitute will be all apparent.Therefore, protection scope of the present invention should be limited to the appended claims.
Claims (10)
1. an e-commerce system for automatic acquisition Customer Information, is characterized in that, comprises:
Stored data base (1), the face feature data of the client of retail shop and corresponding user profile patronized in its record;
Face recognition module (2), it is connected with described stored data base (1), carries out recognition of face to as the client advancing into retail shop and in stored data base (1), finds the customer files of face feature data match;
User profile acquisition module (3), it is connected with described face recognition module (2) and stored data base (1) respectively, according to the customer files of the coupling that face recognition module (2) searches out, in stored data base (1), call corresponding user profile.
2. the e-commerce system of automatic acquisition Customer Information as claimed in claim 1, it is characterized in that, described face recognition module (2) comprises:
First acquisition module (21), it is arranged on position, doorway, shop, carries out acquisition and recording to the facial image information of the client entering shop;
Second acquisition module (24), it is arranged on cash register location, carries out acquisition and recording to the facial image information of the client of shopping checkout;
Extraction module (22), it is connected with described the first acquisition module (21) and the second acquisition module (24) respectively, receive the customer face image information that the first acquisition module (21) or the second acquisition module (24) record, and extract the face feature data of this client;
Matching module (23), it is connected with described extraction module (22), the customer files that the customer face characteristic that searching and extraction module (22) obtain in stored data base (1) matches.
3. the e-commerce system of automatic acquisition Customer Information as claimed in claim 2, it is characterized in that, described the first acquisition module (21) and the second acquisition module (24) are camera or camera.
4. the e-commerce system of automatic acquisition Customer Information as claimed in claim 2, it is characterized in that, described user profile acquisition module (3) comprises:
Calling module (31), it is connected with described matching module (23) and stored data base (1) respectively, according to the customer files of the coupling that matching module (23) searches out, in stored data base (1), call the user profile corresponding with it, comprise basic member data and cumulative consumption data;
Analysis module (32), it is connected with described calling module (31), receives the cumulative consumption data that calling module (31) obtains, analyzes and generate customer consumption deflection figure;
Display module (33), it is connected with described calling module (31) and analysis module (32) respectively, the customer consumption deflection figure that display analysis module (32) generates, and the basic member data that display calling module (31) obtains.
5. an E-commerce method for automatic acquisition Customer Information, is characterized in that, the method comprises following steps:
S1, face recognition module (2) carry out recognition of face and the customer files that whether there is face feature data match in the middle searching of stored data base (1) to working as the client advancing into retail shop; As found, then performing step S2, as do not found, then performing step S3;
The customer files matched that S2, user profile acquisition module (3) search out according to face recognition module (2), calls the cumulative consumption data in corresponding user profile in stored data base (1);
S3, the face characteristic data of current customer are recorded in stored data base (1);
Settle accounts after S4, customer purchase, the customer files matched that user profile acquisition module (3) searches out according to face recognition module (2), in stored data base (1), call the basic member data in corresponding user profile, and the consumption data of this shopping of client is recorded in stored data base (1).
6. the E-commerce method of automatic acquisition Customer Information as claimed in claim 5, it is characterized in that, described step S1 comprises following steps:
S1.1, the facial image information of the first acquisition module (21) to the client entering shop carry out acquisition and recording;
S1.2, extraction module (22) receive the facial image information of the client that the first acquisition module (21) records, and extract the face feature data of this client;
The customer files that the customer face characteristic that S1.3, matching module (23) are found in stored data base (1) and extraction module (22) obtains matches; As found, performing step S2.1, as do not found, performing step S3.
7. the E-commerce method of automatic acquisition Customer Information as claimed in claim 6, it is characterized in that, described step S2 comprises following steps:
The customer files of the coupling that S2.1, calling module (31) search out according to matching module (23), finds the cumulative consumption data in the user profile corresponding with it in stored data base (1); As found, performing step S2.2, as do not found, performing step S4;
S2.2, analysis module (32) receive the cumulative consumption data that calling module (31) obtains, and analyze and generate customer consumption deflection figure;
The customer consumption deflection figure that S2.3, display module (33) display analysis module (32) generate.
8. the E-commerce method of automatic acquisition Customer Information as claimed in claim 5, it is characterized in that, described step S4 comprises following steps:
S4.1, client this time non-purchase and consumption, terminates;
Settle accounts after S4.2, customer purchase, face recognition module (2) is carried out recognition of face to the client of current checkout and in stored data base (1), is found the customer files of face feature data match;
The customer files of the coupling that S4.3, user profile acquisition module (3) search out according to face recognition module (2), the basic member data in the user profile corresponding with it is found in stored data base (1), complete checkout, and this consumption data of doing shopping is recorded in stored data base (1).
9. the E-commerce method of automatic acquisition Customer Information as claimed in claim 8, it is characterized in that, described step S4.2 specifically comprises following steps:
Settle accounts after S4.2.1, customer purchase, the second acquisition module (24) carries out acquisition and recording to the facial image information of this checkout client;
S4.2.2, extraction module (22) receive the facial image information of the client that the second acquisition module (24) records, and extract the face feature data of this client;
The customer files that the customer face characteristic that S4.2.3, matching module (23) are found in stored data base (1) and extraction module (22) obtains matches.
10. the E-commerce method of automatic acquisition Customer Information as claimed in claim 9, it is characterized in that, described step S4.3 specifically comprises following steps:
The customer files of the coupling that S4.3.1, calling module (31) search out according to matching module (23), finds the basic member data in the user profile corresponding with it in stored data base (1), as found, performs step S4.3.2; As do not found, perform step S4.3.3;
Basic member data described in the display of S4.3.2, display module (33), cashier completes checkout according to this basic member data, and is recorded in stored data base (1) by this consumption data of doing shopping;
S4.3.3, complete checkout, and the consumption data of the basic member data of client and this shopping is recorded in stored data base (1).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410618589.1A CN104392370A (en) | 2014-11-06 | 2014-11-06 | Electronic commerce system and method for automatically acquiring customer information |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410618589.1A CN104392370A (en) | 2014-11-06 | 2014-11-06 | Electronic commerce system and method for automatically acquiring customer information |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104392370A true CN104392370A (en) | 2015-03-04 |
Family
ID=52610268
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410618589.1A Pending CN104392370A (en) | 2014-11-06 | 2014-11-06 | Electronic commerce system and method for automatically acquiring customer information |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104392370A (en) |
Cited By (26)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104657885A (en) * | 2015-03-08 | 2015-05-27 | 卢丽花 | System for positioning and shopping guidance in shopping mall |
| CN104657870A (en) * | 2015-03-08 | 2015-05-27 | 卢丽花 | Method for positioning and shopping guidance in shopping mall |
| CN106297222A (en) * | 2016-08-24 | 2017-01-04 | 深圳市新国都支付技术有限公司 | A kind of wireless retail shop management system and device |
| CN106384237A (en) * | 2016-08-31 | 2017-02-08 | 北京志光伯元科技有限公司 | Member authentication-management method, device and system based on face identification |
| CN106779836A (en) * | 2016-12-12 | 2017-05-31 | 衡阳县海得利网络技术有限公司 | Purchase guiding system based on intelligent headset |
| CN106920122A (en) * | 2017-01-18 | 2017-07-04 | 北京光年无限科技有限公司 | A kind of customer data processing method and system based on robot |
| CN106981017A (en) * | 2017-04-01 | 2017-07-25 | 智码迅付信息科技有限公司 | A kind of big data precision marketing device and marketing method based on face recognition technology |
| CN106981150A (en) * | 2017-04-19 | 2017-07-25 | 西安超嗨网络科技有限公司 | A kind of supermarket's intelligent anti-theft system and method |
| CN107291732A (en) * | 2016-03-31 | 2017-10-24 | 苏宁云商集团股份有限公司 | A kind of information-pushing method and device |
| CN107348749A (en) * | 2017-08-25 | 2017-11-17 | 深圳三七九美发生活有限公司 | A kind of detection method of time counting cushion and its chair and shops's customer's stay time |
| CN107369030A (en) * | 2016-05-11 | 2017-11-21 | 镇江雅迅软件有限责任公司 | Customer's dependency degree analysis system |
| CN107368770A (en) * | 2016-05-12 | 2017-11-21 | 深圳市维杰乐思科技有限公司 | A kind of frequent customer's automatic identifying method and system |
| CN107563343A (en) * | 2017-09-18 | 2018-01-09 | 南京甄视智能科技有限公司 | The self-perfection method and system of FaceID databases based on face recognition technology |
| CN107852438A (en) * | 2015-07-30 | 2018-03-27 | Lg电子株式会社 | Mobile terminal and its control method |
| CN107944348A (en) * | 2017-11-07 | 2018-04-20 | 杭州盟山网络科技有限公司 | Purchase system based on camera |
| CN108182411A (en) * | 2017-12-29 | 2018-06-19 | 深圳云天励飞技术有限公司 | Data processing system and device |
| CN108876426A (en) * | 2017-07-04 | 2018-11-23 | 北京旷视科技有限公司 | Data managing method, system and calculating equipment and non-volatile memory medium |
| CN108898109A (en) * | 2018-06-29 | 2018-11-27 | 北京旷视科技有限公司 | The determination methods, devices and systems of article attention rate |
| CN108985835A (en) * | 2018-07-09 | 2018-12-11 | 上海小蚁科技有限公司 | Target group determines method and device, storage medium, terminal |
| CN109191182A (en) * | 2018-08-08 | 2019-01-11 | 深圳市科脉技术股份有限公司 | Commodity air navigation aid and device based on unmanned supermarket |
| CN109213958A (en) * | 2018-09-18 | 2019-01-15 | 宁波众鑫网络科技股份有限公司 | A method of it is loaded for Website page |
| CN110047228A (en) * | 2018-01-15 | 2019-07-23 | 澄果传媒科技股份有限公司 | Integration checkout media system |
| CN110348365A (en) * | 2019-07-05 | 2019-10-18 | 秒针信息技术有限公司 | The recording method of operation and device |
| CN110735580A (en) * | 2018-07-03 | 2020-01-31 | 蔡聪源 | Automatic AI two-way internet and automatic AI |
| CN111091412A (en) * | 2019-11-22 | 2020-05-01 | 丁萍 | Data acquisition system based on consumer age and consumption preference |
| EP3806021A4 (en) * | 2018-07-25 | 2022-03-23 | Beijing Jingdong Shangke Information Technology Co., Ltd. | Commodity recommendation method, apparatus and system, and computer readable storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102306364A (en) * | 2011-10-09 | 2012-01-04 | 江苏省莱科信息技术有限公司 | Intelligent shopping system and intelligent shopping method |
| CN102750895A (en) * | 2012-06-28 | 2012-10-24 | 宇龙计算机通信科技(深圳)有限公司 | Intelligent building information terminal and system as well as communication method |
| CN103606093A (en) * | 2013-10-28 | 2014-02-26 | 燕山大学 | Intelligent chain VIP customer service system based on human characteristics |
| CN203773629U (en) * | 2013-11-06 | 2014-08-13 | 上海煦荣信息技术有限公司 | Intelligent self-service vending system |
-
2014
- 2014-11-06 CN CN201410618589.1A patent/CN104392370A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102306364A (en) * | 2011-10-09 | 2012-01-04 | 江苏省莱科信息技术有限公司 | Intelligent shopping system and intelligent shopping method |
| CN102750895A (en) * | 2012-06-28 | 2012-10-24 | 宇龙计算机通信科技(深圳)有限公司 | Intelligent building information terminal and system as well as communication method |
| CN103606093A (en) * | 2013-10-28 | 2014-02-26 | 燕山大学 | Intelligent chain VIP customer service system based on human characteristics |
| CN203773629U (en) * | 2013-11-06 | 2014-08-13 | 上海煦荣信息技术有限公司 | Intelligent self-service vending system |
Cited By (30)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104657870A (en) * | 2015-03-08 | 2015-05-27 | 卢丽花 | Method for positioning and shopping guidance in shopping mall |
| CN104657870B (en) * | 2015-03-08 | 2018-09-25 | 卢丽花 | A kind of store positioning shopping guide method |
| CN104657885B (en) * | 2015-03-08 | 2018-05-18 | 卢丽花 | A kind of store positions purchase guiding system |
| CN104657885A (en) * | 2015-03-08 | 2015-05-27 | 卢丽花 | System for positioning and shopping guidance in shopping mall |
| CN107852438A (en) * | 2015-07-30 | 2018-03-27 | Lg电子株式会社 | Mobile terminal and its control method |
| CN107291732A (en) * | 2016-03-31 | 2017-10-24 | 苏宁云商集团股份有限公司 | A kind of information-pushing method and device |
| CN107369030A (en) * | 2016-05-11 | 2017-11-21 | 镇江雅迅软件有限责任公司 | Customer's dependency degree analysis system |
| CN107368770A (en) * | 2016-05-12 | 2017-11-21 | 深圳市维杰乐思科技有限公司 | A kind of frequent customer's automatic identifying method and system |
| CN106297222A (en) * | 2016-08-24 | 2017-01-04 | 深圳市新国都支付技术有限公司 | A kind of wireless retail shop management system and device |
| CN106384237A (en) * | 2016-08-31 | 2017-02-08 | 北京志光伯元科技有限公司 | Member authentication-management method, device and system based on face identification |
| CN106779836A (en) * | 2016-12-12 | 2017-05-31 | 衡阳县海得利网络技术有限公司 | Purchase guiding system based on intelligent headset |
| CN106920122A (en) * | 2017-01-18 | 2017-07-04 | 北京光年无限科技有限公司 | A kind of customer data processing method and system based on robot |
| CN106981017A (en) * | 2017-04-01 | 2017-07-25 | 智码迅付信息科技有限公司 | A kind of big data precision marketing device and marketing method based on face recognition technology |
| CN106981150A (en) * | 2017-04-19 | 2017-07-25 | 西安超嗨网络科技有限公司 | A kind of supermarket's intelligent anti-theft system and method |
| CN108876426A (en) * | 2017-07-04 | 2018-11-23 | 北京旷视科技有限公司 | Data managing method, system and calculating equipment and non-volatile memory medium |
| CN107348749A (en) * | 2017-08-25 | 2017-11-17 | 深圳三七九美发生活有限公司 | A kind of detection method of time counting cushion and its chair and shops's customer's stay time |
| CN107563343A (en) * | 2017-09-18 | 2018-01-09 | 南京甄视智能科技有限公司 | The self-perfection method and system of FaceID databases based on face recognition technology |
| CN107563343B (en) * | 2017-09-18 | 2020-05-19 | 南京甄视智能科技有限公司 | FaceID database self-improvement method based on face recognition technology |
| CN107944348A (en) * | 2017-11-07 | 2018-04-20 | 杭州盟山网络科技有限公司 | Purchase system based on camera |
| CN108182411A (en) * | 2017-12-29 | 2018-06-19 | 深圳云天励飞技术有限公司 | Data processing system and device |
| CN110047228A (en) * | 2018-01-15 | 2019-07-23 | 澄果传媒科技股份有限公司 | Integration checkout media system |
| CN108898109A (en) * | 2018-06-29 | 2018-11-27 | 北京旷视科技有限公司 | The determination methods, devices and systems of article attention rate |
| CN110735580A (en) * | 2018-07-03 | 2020-01-31 | 蔡聪源 | Automatic AI two-way internet and automatic AI |
| CN110735580B (en) * | 2018-07-03 | 2021-07-16 | 蔡聪源 | AI automatic door bidirectional internet and AI automatic door |
| CN108985835A (en) * | 2018-07-09 | 2018-12-11 | 上海小蚁科技有限公司 | Target group determines method and device, storage medium, terminal |
| EP3806021A4 (en) * | 2018-07-25 | 2022-03-23 | Beijing Jingdong Shangke Information Technology Co., Ltd. | Commodity recommendation method, apparatus and system, and computer readable storage medium |
| CN109191182A (en) * | 2018-08-08 | 2019-01-11 | 深圳市科脉技术股份有限公司 | Commodity air navigation aid and device based on unmanned supermarket |
| CN109213958A (en) * | 2018-09-18 | 2019-01-15 | 宁波众鑫网络科技股份有限公司 | A method of it is loaded for Website page |
| CN110348365A (en) * | 2019-07-05 | 2019-10-18 | 秒针信息技术有限公司 | The recording method of operation and device |
| CN111091412A (en) * | 2019-11-22 | 2020-05-01 | 丁萍 | Data acquisition system based on consumer age and consumption preference |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104392370A (en) | Electronic commerce system and method for automatically acquiring customer information | |
| JP7038543B2 (en) | Information processing equipment, systems, control methods for information processing equipment, and programs | |
| CN109165992A (en) | A kind of intelligent shopping guide method, apparatus, system and computer storage medium | |
| WO2010053194A1 (en) | Customer behavior recording device, customer behavior recording method, and recording medium | |
| CN107507017A (en) | Shopping guide method and device under a kind of line | |
| JP5704279B1 (en) | Associated program and information processing apparatus | |
| CN107332910B (en) | Information pushing method and device | |
| CN110163715A (en) | Information recommendation method, device, equipment and system | |
| JP2014049014A (en) | Commodity recognition apparatus and commodity recognition program | |
| CN109658194A (en) | A kind of lead referral method and system based on video frequency tracking | |
| JP2010140287A (en) | Purchase action analysis device, method and computer program | |
| TWM443899U (en) | An intelligent point-of-sales system with active identification of customer group | |
| CN114782116B (en) | Advertisement pushing system based on shopping habits of users | |
| KR101771524B1 (en) | Method for extracting price information from a receipt and method for providing price information | |
| CN111125288A (en) | Area deployment method, device and storage medium | |
| JP2003099582A (en) | Method and system for supporting situation analysis using picture data | |
| CN107678545A (en) | A kind of information interactive terminal and method | |
| US20130290107A1 (en) | Behavior based bundling | |
| JP6354232B2 (en) | Sales promotion device, sales promotion method and program | |
| CN112036865A (en) | Service providing method, device and equipment | |
| CN116051208A (en) | Retail system user behavior analysis method and system based on intelligent analysis | |
| CN109978672A (en) | A kind of marketing system and method based on image recognition | |
| CN105589927B (en) | A kind of video recording labeling method and device convenient for retrieval | |
| JP5962747B2 (en) | Associated program and information processing apparatus | |
| CN110348925A (en) | Shops's system, article matching method, device and electronic equipment |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20150304 |
|
| RJ01 | Rejection of invention patent application after publication |