CN106951448A - A kind of personalization, which is worn, takes recommendation method and system - Google Patents

A kind of personalization, which is worn, takes recommendation method and system Download PDF

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Publication number
CN106951448A
CN106951448A CN201710090019.3A CN201710090019A CN106951448A CN 106951448 A CN106951448 A CN 106951448A CN 201710090019 A CN201710090019 A CN 201710090019A CN 106951448 A CN106951448 A CN 106951448A
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user
takes
wear
physical trait
worn
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简仁贤
张为义
张惠棠
杨闵淳
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Intelligent Technology (shanghai) Co Ltd
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Intelligent Technology (shanghai) Co Ltd
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90Details of database functions independent of the retrieved data types
    • G06F16/95Retrieval from the web
    • G06F16/953Querying, e.g. by the use of web search engines
    • G06F16/9535Search customisation based on user profiles and personalisation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/583Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q30/00Commerce
    • G06Q30/02Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241Advertisements
    • G06Q30/0251Targeted advertisements
    • G06Q30/0255Targeted advertisements based on user history
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06QINFORMATION 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
    • G06Q30/00Commerce
    • G06Q30/02Marketing; Price estimation or determination; Fundraising
    • G06Q30/0241Advertisements
    • G06Q30/0251Targeted advertisements
    • G06Q30/0269Targeted advertisements based on user profile or attribute
    • G06Q30/0271Personalized advertisement

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  • Business, Economics & Management (AREA)
  • Theoretical Computer Science (AREA)
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  • Accounting & Taxation (AREA)
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  • General Business, Economics & Management (AREA)
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  • Game Theory and Decision Science (AREA)
  • Data Mining & Analysis (AREA)
  • General Engineering & Computer Science (AREA)
  • Library & Information Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

Worn the invention discloses a kind of personalization and take recommendation method and system, obtain the personal images information and personal shopping record of user;According to the physical trait of the personal images acquisition of information user, the individual for obtaining user according to the personal shopping record, which wears, takes preference;The physical trait and wearing of prestoring are taken into rule to be compared, formation meets wearing for the physical trait and builds view;With reference to it is described wear to build the negotiation individual and wear take preference, recommend suitably to wear the scheme of taking and merchandise news to user.The present invention more precisely can recommend meet its demand to wear the scheme of taking and clothes to user, so as to lift the purchase experiences and shopping efficiency of user.

Description

A kind of personalization, which is worn, takes recommendation method and system
Technical field
Wear the present invention relates to field of artificial intelligence, more particularly to a kind of personalization and take recommendation method and system.
Background technology
With on line, photo sharing website is (such as:Flickr, Instagram, Pinterest) prevalence, more and more people The clothes of oneself can be worn the mode of taking share these websites, other users can look for wear from the photo that these are shared and take Suggestion;But because everyone shape of face and stature have different features, the clothes of the people (model) in these photos Wear and take, be not necessarily suitable for all people, same clothes is through on the body of different people, can be because the shape of face and body of different people Shape, might have different visual effect, therefore, and these services can only provide wearing for versatility and build view, it is impossible to for individual The suitable personalization of people's offer, which is worn, takes recommendation.On the other hand, existing personalized clothes commending system, can be according to the spy of clothes Levy (such as:Color, texture, shape) and wearing for user take record, find out the hobby of user, and then suitable clothes is provided worn and take, But do not account for the feature on human body yet, therefore the clothes that can not also provide for different shapes of face and figure is worn and built View, it is impossible to reach the target of real personalized recommendation.
The content of the invention
For defect of the prior art, a kind of personalization of present invention offer, which is worn, takes recommendation method and system, can be directed to The physical trait of different user takes recommendation there is provided more personalized wearing, and meets the demand of user.
Recommendation method is taken in a first aspect, being worn the invention provides a kind of personalization, methods described includes:
Obtain the personal images information and personal shopping record of user;
According to the physical trait of the personal images acquisition of information user, obtain user's according to the personal shopping record Individual, which wears, takes preference;
The physical trait and wearing of prestoring are taken into rule to be compared, formation meets wearing for the physical trait and taken It is recommended that;
With reference to it is described wear to build the negotiation individual and wear take preference, recommend suitable to wear the scheme of taking and commodity are believed to user Breath.
Further, the physical trait according to the personal images acquisition of information user, is specifically included:According to described Personal images information, by computer vision technology and/or image recognition technology, obtains the physical trait of user.
Further, the individual for obtaining user according to the personal shopping record, which wears, takes preference, specifically includes:According to The personal shopping record, is analyzed the personal shopping record, the individual for obtaining user wears by data mining technology Take preference.
Further, the data mining technology is realized by the method for machine learning.
Further, the physical trait includes:Shape of face feature, figure feature.
Further, the merchandise news includes:Commodity image, item property.
Second aspect, wears present invention also offers a kind of personalization and takes commending system, and the system includes:Acquisition of information mould Block, feature recognition module, regular comparing module, personalized recommendation module;
Described information acquisition module, for obtaining personal images information and personal shopping record;
The feature recognition module, for the physical trait according to personal images acquisition of information user, according to individual's shopping The individual of record acquisition user, which wears, takes preference;
The regular comparing module, is compared for the physical trait and wearing of prestoring to be taken into rule, is formed Meet wearing for the physical trait and build view;
The personalized recommendation module, for reference to it is described wear to build the negotiation individual and wear take preference, recommend to user Suitably wear the scheme of taking and merchandise news.
Further, the feature recognition module includes:Image identification unit, preference recognition unit;
Described image recognition unit, for according to the personal images information, passing through biometrics identification technology and/or figure As identification technology, the physical trait of user is obtained;
The preference recognition unit, for being recorded according to the personal shopping, obtains user's by data mining technology Individual, which wears, takes preference.
Further, described image recognition unit includes:Recognition of face subelement, figure identification subelement;
The recognition of face subelement, for recognizing the shape of face feature in the physical trait;
The figure recognizes subelement, for recognizing the figure feature in the physical trait.
Further, the system also includes:Database module, takes for storing the personal images information, described wear Regular and described merchandise news.
As shown from the above technical solution, a kind of personalization of present invention offer, which is worn, takes recommendation method and system, passes through and recognizes use The physical trait at family, takes rule by the physical trait of user and wearing of prestoring and is compared and matches, and combine user's Wear and take preference, more precisely can recommend meet its demand to wear the scheme of taking and clothes to user, so as to lift the shopping body of user Test and do shopping efficiency.
Brief description of the drawings
Fig. 1 shows that the schematic flow sheet for taking recommendation method is worn in the personalization that the present invention is provided.
Fig. 2 shows that the structural representation for taking commending system is worn in the personalization that the present invention is provided.
Embodiment
The embodiment of technical solution of the present invention is described in detail below in conjunction with accompanying drawing.Following examples are only used for Clearly illustrate technical scheme, therefore be intended only as example, and the protection of the present invention can not be limited with this Scope.
Embodiment one
Fig. 1 shows that the schematic flow sheet for taking recommendation method is worn in the personalization that the embodiment of the present invention one is provided.Such as Fig. 1 institutes Show, recommendation method of taking is worn in a kind of personalization, including:
Step S101, obtains the personal images information and personal shopping record of user;
The personal images information is the image of the user absorbed by video camera or camera, such as photo or individual video Deng at least a, image is more more more is conducive to being identified exactly.It is different according to application scenarios, there can be a variety of acquisitions The mode of people's image information:If application scenarios are the entity boutique under line, after user enters shop, using taking the photograph in shop The image of shadow machine or cameras capture to the user;If application scenarios are shopping website, the image that user can be called to upload.
The acquisition of the personal shopping record can have a variety of acquisition modes according to the difference of application scenarios:If applied field Scape is the entity boutique under line, can call the shopping record of the user retained in shop, can also obtain user unsolicited Recorded in the shopping of the shop and other solid shop/brick and mortar store;If application scenarios are shopping website, shop on shopping website or line can be called The shopping record of the user retained in purchase system;When user temporarily records the adjustable used time without shopping, the individual can be passed through The identity characteristic of image information identifying user, the shopping record of other users of the search with same or similar identity characteristic, body Part feature can be occupation, age, sex, life role etc..If for example, identifying that the user is religion in the image of certain user Teacher, then search for the shopping record of other users of teacher's industry;If identifying the user for young girl or middle aged and aged women, The shopping searched for the other other users of the age bracket same sex is recorded;If it is pregnant woman to identify the user, search for same role's The shopping record of other users;It is of the same trade, which kind of dress ornament generally bought with age bracket or with the user of role, to analyzing the user Shopping tendency or preference have good referential.
Step S102, according to the physical trait of the personal images acquisition of information user, is recorded according to the personal shopping The individual of acquisition user, which wears, takes preference.
Preferably, according to the physical trait of the personal images acquisition of information user, specifically include:According to the personal figure As information, by the one or more in computer vision technology, image recognition technology, biometrics identification technology, user is obtained Physical trait;Wherein, the physical trait includes shape of face feature and figure feature, and the physical trait of identifying user includes identification Shape of face feature, such as shape of face, the colour of skin, color development, the classification to shape of face feature can be set in advance, and identification figure feature, such as square Shape figure, del figure, oval figure etc., the classification to figure feature can be set in advance.Physical trait is stability Higher feature, the identification to physical trait helps to provide the user more stable, more accurately personalized ventilation system.
Alternatively, the present embodiment can also be according in image recognition technology, computer vision technology, biometrics identification technology One or more technologies, with reference to deep learning, identify the identity characteristic of user, can be searched further for specifically according to identity characteristic The shopping record of the user of same or similar identity characteristic.
Preferably, the individual for obtaining user according to the personal shopping record, which wears, takes preference, specifically includes:According to described People's shopping record, the individual for obtaining user by data mining technology, which wears, takes preference;Specifically, by data mining technology to individual People's shopping record carries out analysis calculating, and the individual for obtaining user wears and takes preference.Wherein, individual wears to take preference and can refer to and existed in user Intrinsic hobby or custom, the hobby such as in the color of dress ornament, style, fabric in factor on clothing matching.To a plurality of People's shopping record is analyzed, and can obtain more accurate individual and wear to take preference.
Shape of face, figure and personal wear are taken by the multi-angle identification of preference are helped to provide the user the understanding of more full position, And then can more accurately find out to meet and the dress ornament of user's request and wear the scheme of taking, allow user there are more convenient purchase experiences.
It is further preferred that the data mining technology is realized by the method for machine learning, in machine learning side In method, preferred depth study.
Step S103, takes rule by the physical trait and wearing of prestoring and is compared, formation meets the body View is built in wearing for feature.
The physical trait recognized in step S102 and wearing of prestoring are taken into rule to compare and match, it is suitable to select Wear and take rule, take rule according to wearing of selecting and further formed by computing and meet wearing for the physical trait and build view.Wherein, institute State and wear that to take rule be to be taken expert by wearing and provided, wear to take to contain in rule and compare classical and popular combination in clothing matching, Physical trait is taken rule and compared with wearing, can select and take rule with higher the wearing of physical trait matching degree, it is possible to increase rule The accuracy then selected, and wear take rule be stored in advance in database, can in real time call out and be compared, Improve the real-time and efficiency of comparison.
Step S104, with reference to it is described wear to build the negotiation individual and wear take preference, recommend suitably to wear the scheme of taking to user And merchandise news.
Wearing formation to build view and wear with individual and take preference and combined, by computing, more meets its customs and morals of the people to user's recommendation Lattice and preference wear the scheme of taking, and the merchandise news includes commodity image and item property, commodity can be that clothes can also be Various ornaments, item property includes color, material, fabric, style of commodity etc., according to the difference of application scenarios, wears the scheme of taking User can be recommended in several ways:, can be by the display terminal of solid shop/brick and mortar store to user if application scenarios are solid shop/brick and mortar store under line Push meet user's request wear the scheme of taking and dependent merchandise information, if application scenarios are the shopping website on line, pass through net Stand erectly connect pushed to user meet user's request wear the scheme of taking and related merchandise news.
The application scenarios of the present embodiment technical scheme are in addition to the shopping website on the solid shop/brick and mortar store and line under line, also including line On other shopping terminals or purchase system etc., be such as available for the APP and public number of shopping.
Based on above content, the technique effect that the embodiment of the present invention one can be realized is:Recognized by a variety of identification technologies The physical trait of user, takes rule by the physical trait of user and wearing of prestoring and is compared and matches, and combines and pass through Preference is taken in wearing for the user that data mining technology is obtained, and more precisely can be met wearing for its demand to user's recommendation and be taken scheme kimonos Decorations, allow users to be quickly found the suitable dress ornament of oneself, so as to lift the purchase experiences and shopping efficiency of user.
Embodiment two
To the embodiment of the present invention one accordingly, Fig. 2 shows that a kind of personalization provided in an embodiment of the present invention is worn and takes recommendation The structural representation of system.As shown in Fig. 2 a kind of personalization, which is worn, takes commending system, including:Data obtaining module 201, feature is known Other module 202, regular comparing module 203, personalized recommendation module 204.
Described information acquisition module 201, for obtaining a described information acquisition module 201, for obtaining personal images letter Breath and personal shopping record.The image identification unit of the personal images information input feature recognition module 202 of acquisition carries out body Feature recognition, the preference recognition unit progress individual of the personal shopping record input feature vector identification module 202 of acquisition, which wears, takes preference Identification.
The feature recognition module 202, for the physical trait according to personal images acquisition of information user, according to individual's purchase The individual of thing record acquisition user, which wears, takes preference.Preferably, the feature recognition module 202 includes:Image identification unit, preference Recognition unit;Wherein, described image recognition unit, for according to the personal images information, passing through image recognition technology, computer One or more in vision technique, biometrics identification technology, the physical trait of identifying user;The preference recognition unit, For being recorded according to the personal shopping, worn by the individual of data mining technology identifying user and take preference.Feature recognition module 202 physical traits obtained are used to take regular matched with wearing in database module.
It is further preferred that described image recognition unit includes:Recognition of face subelement, figure identification subelement;It is described Recognition of face subelement, for recognizing the shape of face feature in the physical trait, such as shape of face, the colour of skin, color development;The figure is known Small pin for the case unit, for recognizing the figure feature in the physical trait, such as rectangle figure, del figure, oval figure Deng.
Alternatively, the feature recognition module 202 also includes identity recognizing unit, for according to image recognition technology, electricity One or more technologies in brain vision technique, biometrics identification technology, with reference to deep learning, identify that the identity of user is special Levy, the shopping that the user of specific same or similar identity characteristic can be searched further for according to identity characteristic is recorded.
The regular comparing module 203, is compared, shape for the physical trait and wearing of prestoring to be taken into rule View is built into wearing for the physical trait is met.Regular comparing module 203 can be selected and physical trait matching degree by comparing Rule is taken in higher wearing, and is worn to take rule and form corresponding wear according to this and is built view.
The personalized recommendation module 204, for reference to it is described wear to build the negotiation individual and wear take preference, pushed away to user Recommend and suitably wear the scheme of taking and merchandise news;Specifically, the personalized recommendation module 204 can select to close from data module storehouse Suitable wears the scheme of taking and merchandise news, is pushed to user;Recommended wear the scheme of taking and merchandise news can by display terminal or Website is pushed to user.
Preferably, the system also includes:Database module, rule are taken for storing the personal images information, described wear Then with other related datas in the merchandise news, and other individuation process.
It is further preferred that the database module also includes personal information database, wears and take rule database and commodity Database.Personal information database is used to store the personal information such as personal images information and personal shopping record;Wear and take regular number It is used to store to wear according to storehouse and wearing and taking rule for expert's offer is provided, so that the physical trait with user is matched, alternatively it is also possible to What is ultimately formed for storing wears the scheme of taking;Merchandising database is used to store the merchandise news for being provided to user.
Based on above content, what the embodiment of the present invention two can reach has the technical effect that:Recognized by a variety of identification technologies The physical trait of user, takes rule by the physical trait of user and wearing of prestoring and is compared and matches, and combines and pass through Preference is taken in wearing for the user that data mining technology is obtained, and more precisely can be met wearing for its demand to user's recommendation and be taken scheme kimonos Decorations, so as to lift the purchase experiences and shopping efficiency of user.
Based on above content, the personalization that the present invention is provided, which is worn, takes recommendation method and system, make use of image recognition, computer At least one technology such as vision, machine learning, data mining, can automatically identify the physical trait of user, and combine by Wear and take what expert was provided, preference is taken for the rule taken of wearing of different attribute and feature, and personal wearing, to reach individual character Change and wear the target of taking recommendation, using the teaching of the invention it is possible to provide the personalization for being more suitable for user is worn and takes recommendations, improves user's purchase experiences and shopping effect Rate.
Finally it should be noted that:Various embodiments above is merely illustrative of the technical solution of the present invention, rather than its limitations;To the greatest extent The present invention is described in detail with reference to foregoing embodiments for pipe, it will be understood by those within the art that:Its according to The technical scheme described in foregoing embodiments can so be modified, or which part or all technical characteristic are entered Row equivalent;And these modifications or replacement, the essence of appropriate technical solution is departed from various embodiments of the present invention technology The scope of scheme, it all should cover among the claim of the present invention and the scope of specification.

Claims (10)

1. a kind of personalization, which is worn, takes recommendation method, it is characterised in that methods described includes:
Obtain the personal images information and personal shopping record of user;
According to the physical trait of the personal images acquisition of information user, the individual of user is obtained according to the personal shopping record Wear and take preference;
The physical trait and wearing of prestoring are taken into rule to be compared, formation meets wearing for the physical trait and built View;
With reference to it is described wear to build the negotiation individual and wear take preference, recommend suitably to wear the scheme of taking and merchandise news to user.
2. personalization according to claim 1, which is worn, takes recommendation method, it is characterised in that described to be believed according to the personal images Breath obtains the physical trait of user, specifically includes:
According to the personal images information, by computer vision technology and/or image recognition technology, the body for obtaining user is special Levy.
3. personalization according to claim 1, which is worn, takes recommendation method, it is characterised in that described according to the personal shopping story The individual of record acquisition user, which wears, takes preference, specifically includes:
According to the personal shopping record, the individual for obtaining user by data mining technology, which wears, takes preference.
4. personalization according to claim 3, which is worn, takes recommendation method, it is characterised in that the data mining technology passes through machine The method of device study is realized.
5. personalization according to claim 1, which is worn, takes recommendation method, it is characterised in that the physical trait includes:Shape of face Feature, figure feature.
6. personalization according to claim 1, which is worn, takes recommendation method, it is characterised in that the merchandise news includes:Commodity Image, item property.
7. a kind of personalization, which is worn, takes commending system, it is characterised in that the system includes:Data obtaining module, feature recognition mould Block, regular comparing module, personalized recommendation module;
Described information acquisition module, for obtaining personal images information and personal shopping record;
The feature recognition module, for the physical trait according to personal images acquisition of information user, is recorded according to individual's shopping The individual of acquisition user, which wears, takes preference;
The regular comparing module, is compared, formation meets for the physical trait and wearing of prestoring to be taken into rule View is built in wearing for the physical trait;
The personalized recommendation module, for reference to it is described wear to build the negotiation individual and wear take preference, it is suitable to recommend to user Wear the scheme of taking and merchandise news.
8. personalization according to claim 7, which is worn, takes commending system, it is characterised in that the feature recognition module includes: Image identification unit, preference recognition unit;
Described image recognition unit, for according to the personal images information, being known by biometrics identification technology and/or image Other technology, obtains the physical trait of user;
The preference recognition unit, for being recorded according to the personal shopping, the individual of user is obtained by data mining technology Wear and take preference.
9. personalization according to claim 8, which is worn, takes commending system, it is characterised in that described image recognition unit includes: Recognition of face subelement, figure identification subelement;
The recognition of face subelement, for recognizing the shape of face feature in the physical trait;
The figure recognizes subelement, for recognizing the figure feature in the physical trait.
10. personalization according to claim 7, which is worn, takes commending system, it is characterised in that the system also includes:Database Module, regular and described merchandise news is taken for storing the personal images information, described wear.
CN201710090019.3A 2017-02-20 2017-02-20 A kind of personalization, which is worn, takes recommendation method and system Pending CN106951448A (en)

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Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107862277A (en) * 2017-11-02 2018-03-30 北京奇虎科技有限公司 Live dress ornament, which is dressed up, recommends method, apparatus, computing device and storage medium
CN107862544A (en) * 2017-09-30 2018-03-30 珠海格力电器股份有限公司 Method of Commodity Recommendation and device
CN108022161A (en) * 2017-12-26 2018-05-11 河北中晟易通科技有限公司 Clothing matching commending system based on image recognition and big data analysis
CN108038161A (en) * 2017-12-06 2018-05-15 北京奇虎科技有限公司 Information recommendation method, device and computing device based on photograph album
CN108629661A (en) * 2018-04-28 2018-10-09 东莞市华睿电子科技有限公司 A kind of Products Show method applied to unmanned boutique
CN109064249A (en) * 2018-06-28 2018-12-21 中山大学 A kind of clothes recommendation optimization method and its system based on feature personalization modification
CN110059247A (en) * 2019-03-19 2019-07-26 江苏皓之睿数字科技有限公司 A kind of personalization based on artificial intelligence technology, which is worn, takes recommender system
CN112163930A (en) * 2020-09-27 2021-01-01 深圳莱尔托特科技有限公司 Matching recommendation method and matching recommendation system

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH09223175A (en) * 1996-02-16 1997-08-26 Hitachi Ltd Method for supporting selling operation
CN102402756A (en) * 2010-09-16 2012-04-04 香港理工大学 Intelligent clothing business system
CN104331564A (en) * 2014-11-10 2015-02-04 深圳市中兴移动通信有限公司 Dressing instruction method based on terminal equipment and terminal equipment

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH09223175A (en) * 1996-02-16 1997-08-26 Hitachi Ltd Method for supporting selling operation
CN102402756A (en) * 2010-09-16 2012-04-04 香港理工大学 Intelligent clothing business system
CN104331564A (en) * 2014-11-10 2015-02-04 深圳市中兴移动通信有限公司 Dressing instruction method based on terminal equipment and terminal equipment

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
刘桂华: "《现代礼仪》", 31 July 2009, 南海出版公司 *

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107862544A (en) * 2017-09-30 2018-03-30 珠海格力电器股份有限公司 Method of Commodity Recommendation and device
CN107862277A (en) * 2017-11-02 2018-03-30 北京奇虎科技有限公司 Live dress ornament, which is dressed up, recommends method, apparatus, computing device and storage medium
CN108038161A (en) * 2017-12-06 2018-05-15 北京奇虎科技有限公司 Information recommendation method, device and computing device based on photograph album
CN108022161A (en) * 2017-12-26 2018-05-11 河北中晟易通科技有限公司 Clothing matching commending system based on image recognition and big data analysis
CN108629661A (en) * 2018-04-28 2018-10-09 东莞市华睿电子科技有限公司 A kind of Products Show method applied to unmanned boutique
CN108629661B (en) * 2018-04-28 2021-12-28 东莞市华睿电子科技有限公司 Product recommendation method applied to unmanned clothing store
CN109064249A (en) * 2018-06-28 2018-12-21 中山大学 A kind of clothes recommendation optimization method and its system based on feature personalization modification
CN110059247A (en) * 2019-03-19 2019-07-26 江苏皓之睿数字科技有限公司 A kind of personalization based on artificial intelligence technology, which is worn, takes recommender system
CN112163930A (en) * 2020-09-27 2021-01-01 深圳莱尔托特科技有限公司 Matching recommendation method and matching recommendation system

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