CN109325816A - Recommended method and device under shops's scene - Google Patents
Recommended method and device under shops's scene Download PDFInfo
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- CN109325816A CN109325816A CN201810789899.8A CN201810789899A CN109325816A CN 109325816 A CN109325816 A CN 109325816A CN 201810789899 A CN201810789899 A CN 201810789899A CN 109325816 A CN109325816 A CN 109325816A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
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- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C21/00—Navigation; Navigational instruments not provided for in groups G01C1/00 - G01C19/00
- G01C21/20—Instruments for performing navigational calculations
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- G—PHYSICS
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0281—Customer communication at a business location, e.g. providing product or service information, consulting
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Abstract
This application discloses the recommended methods under a kind of shops's scene, comprising: the identity of user in acquisition shops；According to shops's classification of the shops, the identity is obtained in the historical use data of the associated online service platform of shops's classification；Recommend the shops's commodity for meeting threshold value with the matching degree of the historical use data to user；Corresponding recommendation movement is executed according to the end article that user selects in shops's commodity of recommendation.Recommended method under shops's scene provided by the present application recommends shops's commodity to user on the basis of capturing user demand, recommends success rate also higher also more accurate, meanwhile, user is improved in the shopping experience of unmanned shops.
Description
Technical field
This application involves Internet technical fields, and in particular to the recommended method under a kind of shops's scene.The application is simultaneously
The recommendation apparatus and a kind of electronic equipment being related under a kind of shops's scene.
Background technique
With the rapid development of the technologies such as Internet of Things, big data, various technologies relevant to Internet of Things, big data have been goed deep into
Different social sectors are applied to, especially in robot field, many industry appearance are gradually substituted artificial by robot
The trend of service, but replace the service manually provided more single currently based on robot, interaction sex service is less, faces user
Satisfied consumption experience demand also needs to go deep into development.
Documents 1 (CN106651474A) provide a kind of intelligent shopping guide system, can be realized online and offline interaction,
Merchandise news and advertising information real-time update and can enhance the Interactive Experience of consumer, but do not have and capture customer demand
Ability, shoppers' guide is the same under no normal direction line leaves for giving user's Recommendations from subjective point, can not capture user demand.
Summary of the invention
The application provides the recommended method under a kind of shops's scene, to solve defect of the existing technology.The application is same
When be related to recommendation apparatus and a kind of electronic equipment under a kind of shops's scene.
The application provides the recommended method under a kind of shops's scene, comprising: the identity of user in acquisition shops；According to
Shops's classification of the shops obtains the identity in the historical user of the associated online service platform of shops's classification
Data；Recommend the shops's commodity for meeting threshold value with the matching degree of the historical use data to user；According to user in recommendation
The end article selected in shops's commodity executes corresponding recommendation movement.
Optionally, shops's classification according to the shops obtains the identity and is associated in shops's classification
Online service platform historical use data, comprising: judge that the identity takes on the associated line of shops's classification
Platform be engaged in the presence or absence of corresponding user account, and if it exists, obtain the identity on the associated line of shops's classification
Historical use data under the corresponding user account of service platform；Wherein, the customer transaction data of the shops, with the shops
The customer transaction data interchange of the associated online service platform of classification.
Optionally, there is data dependence, the shops and the line between the shops and the online service platform
Data dependence coefficient between upper service platform, according to the historical use data of each online service platform determine to user
The recommendation success rate of shops's commodity of recommendation determines that the data dependence coefficient is positively correlated with success rate is recommended.
Optionally, the shops's commodity for recommending to meet threshold value with the matching degree of the historical use data to user, packet
It includes: the historical use data and shops's commodity is subjected to matching primitives, obtain shops's commodity that matching degree meets threshold value；
According to the recommendation order of the data dependence coefficient between the shops and the online service platform from high to low, pushed away to user
Recommend shops's commodity.
Optionally, the end article selected in shops's commodity of recommendation according to user executes corresponding recommendation
Movement, comprising: according to the end article that user selects in shops's commodity of recommendation, based on the end article on the line
Service platform obtains the merchandise related information of the end article；To the merchandise related information got described in user's displaying.
Optionally, the end article selected in shops's commodity of recommendation according to user executes corresponding recommendation
After action step executes, the method also includes: according to user region locating for shops present position and the end article, meter
Calculate the routing information generated from user region locating for shops present position to the end article；The path is exported to user
Information.
Optionally, the identity for acquiring user in shops, comprising: the human body biological characteristic information of user is acquired,
Identify the corresponding identity of the human body biological characteristic information.
Optionally, the recommended method under shops's scene, it is real based on the service robot configured with user's interactive interface
Existing, user's interactive interface includes the display screen of the service robot；Correspondingly, it is described according to user in recommendation described in
The end article selected in shops's commodity executes the step of corresponding recommendation movement, is executed based on user's interactive interface, tool
Body includes:
The corresponding recommendation movement of the end article is shown to user by the display screen；User is received for described aobvious
Touch control operation is chosen in the end article input that display screen is shown；Using it is described choose the corresponding end article of touch control operation as
Commodity to be recommended；According to user region locating for shops present position and the commodity to be recommended, calculates and generate from user in door
The routing information in region locating for shop present position to the commodity to be recommended；The routing information is exported by the display screen.
Optionally, described according to user region locating for shops present position and the commodity to be recommended, calculate generate from
The routing information in user region locating for shops present position to the commodity to be recommended, comprising: judge the commodity to be recommended
Number whether be greater than 1, cover all commodity to be recommended and the shortest routing information in path if so, calculating；And the clothes
Business robot is when marching to region locating for any commodity to be recommended according to the routing information, show in the display screen described in
The evaluation information of Recommendations, the trade order information of the commodity to be recommended and/or the commodity to be recommended.
The application also provides the recommendation apparatus under a kind of shops's scene, comprising:
Identity acquisition unit, for acquiring the identity of user in shops；
Historical data acquiring unit obtains the identity in the door for shops's classification according to the shops
The historical use data of the associated online service platform of shop classification；
Shops's commercial product recommending unit, for recommending the door for meeting threshold value with the matching degree of the historical use data to user
Shop commodity；
Recommend action execution unit, the end article for selecting in shops's commodity of recommendation according to user executes
Corresponding recommendation movement.
Optionally, the historical data acquiring unit is specifically used for judging that the identity is closed in shops's classification
The online service platform of connection whether there is corresponding user account, and if it exists, obtain the identity in shops's classification
Historical use data under the corresponding user account of associated online service platform；Wherein, the customer transaction data of the shops,
With the customer transaction data interchange of the associated online service platform of shops's classification.
Optionally, there is data dependence, the shops and the line between the shops and the online service platform
Data dependence coefficient between upper service platform, according to the historical use data of each online service platform determine to user
The recommendation success rate of shops's commodity of recommendation determines that the data dependence coefficient is positively correlated with success rate is recommended.
Optionally, the recommendation apparatus under shops's scene is transported based on the service robot configured with user's interactive interface
Row, user's interactive interface includes the display screen of the service robot；Correspondingly, the recommendation action execution unit is based on
User's interactive interface operation, specifically includes:
Recommend action demonstration subelement, for showing the corresponding recommendation of the end article to user by the display screen
Movement；
Touch control operation receiving subelement, for receiving end article input of the user for display screen displaying
Choose touch control operation；
Commodity to be recommended determine subelement, for choosing the corresponding end article of touch control operation as quotient to be recommended for described
Product；
Routing information computation subunit, for according to user area locating for shops present position and the commodity to be recommended
Domain calculates the routing information generated from user region locating for shops present position to the commodity to be recommended；
Routing information exports subelement, for exporting the routing information by the display screen.
The application also provides a kind of electronic equipment, comprising: memory and processor；The memory is for storing computer
Executable instruction, the processor are used to execute the computer executable instructions: the identity of user in acquisition shops；Root
According to shops's classification of the shops, the history for obtaining the identity in the associated online service platform of shops's classification is used
User data；Recommend the shops's commodity for meeting threshold value with the matching degree of the historical use data to user；Recommended according to user
Shops's commodity in the end article that selects execute corresponding recommendation movement.
Recommended method under shops's scene provided by the present application, comprising: the identity of user in acquisition shops；Root
According to shops's classification of the shops, the history for obtaining the identity in the associated online service platform of shops's classification is used
User data；Recommend the shops's commodity for meeting threshold value with the matching degree of the historical use data to user；Recommended according to user
Shops's commodity in the end article that selects execute corresponding recommendation movement.
Recommended method under shops's scene provided by the present application, during into shops, user recommends,
By acquiring and identifying the identity of user in shops, and on the basis of identifying User Identity, existed according to user
The historical use data of the associated online service platform of shops's classification, for user the consumer behavior of unmanned shops carry out guidance and
It helps, so that the historical use data based on user's service platform on line is that user recommends suitable shops's commodity, realizes
Recommend shops's commodity to user on the basis of capturing user demand, recommends success rate also higher also more accurate, meanwhile, it is promoted
Shopping experience of the user in unmanned shops.
Detailed description of the invention
Attached drawing 1 is the process flow diagram of the recommended method embodiment under a kind of shops's scene provided by the present application；
Attached drawing 2 is a kind of schematic diagram of the recommended method of unmanned shops of supermarket provided by the present application；
Attached drawing 3 is the schematic diagram of the recommendation apparatus embodiment under a kind of shops's scene provided by the present application；
Attached drawing 4 is the schematic diagram of a kind of electronic equipment provided by the present application.
Specific embodiment
Many details are explained in the following description in order to fully understand the application.But the application can be with
Much it is different from other modes described herein to implement, those skilled in the art can be without prejudice to the application intension the case where
Under do similar popularization, therefore the application is not limited by following public specific implementation.
The application provides the recommended method under a kind of shops's scene, and the application also provides the recommendation dress under a kind of shops's scene
It sets and a kind of electronic equipment.It is described in detail one by one below in conjunction with the attached drawing of embodiment provided by the present application, and
Each step of method is illustrated.
Recommended method embodiment under a kind of shops's scene provided by the present application is as follows:
Referring to attached drawing 1, it illustrates the processing streams of the recommended method embodiment under a kind of shops's scene provided by the present application
Cheng Tu, referring to attached drawing 2, it illustrates a kind of schematic diagrames of the recommended method of unmanned shops of supermarket provided by the present application.
Step S101 acquires the identity of user in shops.
Unmanned shops in new public safety, compared with entity shops under traditional wire, disadvantage is that shopping guide recommends link,
The outstanding shopping guide of entity shops can capture the demand of user by the communication with user under traditional wire, so that user be guided to purchase
The commodity of needs are bought, and for unmanned shops, the shopping guide of user demand is linked up, captured with user due to lacking, causes to order
Single loss is more.In addition, data on line can not be counted for shopping guide under line, usually by user oneself in purchase commodity
Check that commodity are evaluated on shopping website before, to be made whether the decision of purchase.Particularly, online service platform is being surrounded
In the new retail ecosphere made, each link has many online trading data, such as demand data, the review number of user
According to etc., if these data can be used well as foundation is recommended, in the premise for possessing more online trading data
Under, demand, which is carried out, based on online trading data captures with commercial product recommending to help user to carry out decision, it is more accurate and effective,
It is more representative.
The embodiment of the present application is by taking unmanned shops as an example, by the recommended method under shops's scene provided by the present application,
The identity of user in shops is acquired and identifies, and on the basis of identifying user, according to user in other online services
The historical use data of platform is consumer behavior progress guidance and help of the user in unmanned shops, proposes that purchase is suggested, thus
User is promoted in the shopping experience of unmanned shops.
Recommended method under shops's scene provided by the present application can be realized in terminal device side, for example be based on nobody
The service robot of shops's configuration is realized, can also be realized in server-side, can also be common by both client and server-side
It realizes, it may be assumed that the part steps of the recommended method under shops's scene realize that remaining step is realized in server-side in client,
For example the service robot configured by unmanned shops will be transmitted to server after the progress preliminary treatment of collected data and carry out
Reason, returns to service robot for processing result by server and is presented to the user.
This step acquires the identity of user in shops, and purpose is in order to identify the identity of user, in the specific implementation, knows
The identity of user in other shops preferably can identify the human body biological characteristics by the human body biological characteristic information of acquisition user
The corresponding identity of information, such as the face image of image acquisition device user being arranged by unmanned shops, pass through
Recognition of face determines that collected face image corresponds to the identity of user.
It is associated in shops's classification to obtain the identity according to shops's classification of the shops by step S102
The historical use data of online service platform.
Shops's classification of shops described in the embodiment of the present application refers to that the classification of the affiliated industry of the shops, shops's classification are
The label that service industry classifies, for example shops's classification of unmanned shops of supermarket is retail, shops's class of unmanned food and drink shops
Mesh is food and drink.For a shops, shops's classification of the shops is uniquely determined.Certainly, if for
For one unmanned shops, if there are multiple shops's classifications for the unmanned shops, for example certain unmanned shops not only provides food and drink clothes
Business, while retail service being also provided, then there are two shops's classifications of the unmanned shops: food and drink classification and retail classification, this
In the case of, it can be directed to respectively each shops's classification, according to user on the associated line of each classification on the basis of identifying user
The historical use data of service platform is instructed and is helped in each shops's class consumer behavior now of unmanned shops for user
It helps, proposes that purchase is suggested, promote user in the shopping experience of unmanned shops.
This step obtains the identity on the associated line of shops's classification according to shops's classification of the shops
The historical use data of service platform, it is preferred to use such as under type: judge that the identity is associated in shops's classification
Online service platform whether there is corresponding user account, and if it exists, obtains the identity and is associated in shops's classification
The corresponding user account of online service platform under historical use data；If it does not exist, it does not deal with；Wherein, described
The customer transaction data of shops, the customer transaction data interchange with the associated online service platform of shops's classification.
In the new retail environment around online service platform construction, food and beverage sevice is flat on the line including providing food and beverage sevice
Platform (such as public praise) provides the online trading platform (for example, Taobao, day cat) of shopping online, provides the line of music/video service
Upper music/video service platform (for example, Ali's music, youku.com), provide online trading service online trading platform (for example,
Taobao, day cat), sport/health platform (for example, Ali's sport, Ali's health) on sport/health service line on line is provided,
And platform (than pig like flying) etc. is booked tickets on the line of offer ticket-booking service.
For example, user unmanned shops of supermarket confirm identity after, the unmanned associated online service platform of shops of supermarket
Including Taobao, Ali's health and Ali's music, then further judge the user for confirming identity whether in Taobao, Ali's health
At least one of work as with Ali's music and registered user account, if at least one registered user account wherein, Taobao,
Ali's health and Ali's music registered each of user account, obtained user and worked as in Taobao, Ali's health and Ali's music
In the registered historical use data for crossing user account each；If not yet any one in Taobao, Ali's health and Ali's music
Person registered user account, then user is not present in currently associated Taobao of unmanned shops of supermarket, Ali's health and Ali's music
Historical use data is not dealt with.
Step S103 recommends the shops's commodity for meeting threshold value with the matching degree of the historical use data to user.
When it is implemented, it is preferred, there is data dependence, into one between the shops and the online service platform
Step, the data dependence coefficient between the shops and the online service platform, according to the history of each online service platform
User data determine shops's commodity recommended to the user recommendation success rate determine, the data dependence coefficient and recommend at
Power is positively correlated.Data dependence coefficient between shops and online service platform is bigger, then shows online service platform
The reference value of historical use data is bigger, based on historical use data to the recommendation of user more accurately and with more representative
Property.
Further, the data dependence coefficient between shops and online service platform, can be by operation personnel or system
One initialization values is set, then as the continuous progress of recommendation process, can reversely correct shops according to recommendation results
Data dependence coefficient between online service platform, to make the data dependence system between shops and online service platform
Number is more reasonable, practical application scene of also more coincideing.
For example, user may search transaction platform on line when unmanned bookstore buys books for the unmanned bookstore under line
Rope browsed related book information, and the data dependence coefficient with online trading platform (for example, Taobao, day cat) is 0.9；
In addition, user may be paid close attention to or be watched sports tournament by sport platform on line within nearest a period of time just in star-pursuing,
Data dependence coefficient with sport platform on line is 0.6；Alternatively, if user passes through Ali's health within nearest a period of time
It is purposeful to consult related medical knowledge or by Ali's health drug purchase, then recommend the related book of some health to user
The data dependence coefficient of healthy platform is 0.3 on nationality, with line.
On this basis, this step recommends the shops quotient for meeting threshold value with the matching degree of the historical use data to user
Product, comprising: the historical use data and shops's commodity are subjected to matching primitives, obtain the shops that matching degree meets threshold value
Commodity；According to the recommendation order of the data dependence coefficient between the shops and the online service platform from high to low, to
User recommends shops's commodity.
For example, user A searched for " paper diaper ", " newborn's treasured book ", " cooking treasured book " and " nipple " in Taobao in the recent period,
The clothes of certain soccer star and the admission ticket of certain soccer star were bought in Ali's sport, had purchased insurance in Ali's health, and go to have seen tooth
Doctor；When user A buys books in unmanned bookstore, the data that can be searched for according to user A in Taobao recommend child-bearing books to user A
In neonatal most popular books, can also recommend certain soccer star most to user A according to user A in the related data of Ali's sport
Books salable, finally, also the books to take care of one's teeth can be recommended to give user A according to user A in the related data of Ali's health.
It is dynamic to execute corresponding recommendation according to the end article that user selects in shops's commodity of recommendation by step S104
Make.
In a kind of preferred embodiment provided by the embodiments of the present application, this step according to user recommendation the shops quotient
The end article selected in product executes corresponding recommendation movement, comprising: the mesh selected in shops's commodity of recommendation according to user
Commodity are marked, obtain the merchandise related information of the end article in the online service platform based on the end article；Xiang Yong
The merchandise related information got described in the displaying of family.
For example, according to the data that user A was searched in Taobao, recommending to user A when user A buys books in unmanned bookstore
Neonatal most popular books in child-bearing books, and, according to user A in the related data of Ali's sport, recommend to user A
The best-selling books of certain soccer star, finally, can according to user A Ali's health related data, recommend the books to take care of one's teeth to
User A；In the three kinds of books recommended to user A, user A selects the books to take care of one's teeth, then obtains protection tooth in Taobao
The comparative situation of the newest evaluations of tooth this kind books, sales volume ranking and similar subject matter books shows user A.
It is provided by the embodiments of the present application another kind preferred embodiment in, this step according to user recommendation the shops
After the end article that selects in commodity executes corresponding recommendations action step execution, further includes: according to user in shops locating for position
It sets and generates with region locating for the end article, calculating from user region locating for shops present position to the end article
Routing information；The routing information is exported to user.
In practical applications, it is directed to the recommendation effect of shops user in order to further enhance unmanned shops, can also pass through
" service robot " is configured in unmanned shops, " shopping guide " of unmanned shops this angle is served as by " service robot " that configures
Color.It should be noted that " service robot " that is configured in unmanned shops be not limited only in traditional sense can be in unmanned door
The robot of mobile guidance user shopping in shop, further include played in unmanned shops shopping guide's recommendation function electric advertisement screen or
Moving advertising equipment, for example, shopping guide's recommendation function of " service robot " is realized by the electric advertisement screen in unmanned shops, with
The difference of the robot of mobile guidance user shopping is that its is immovable, but is realizing that shopping guide's recommendation function this point is consistent
's.
Preferably, the technical solution that this Shen embodiment provides is real based on the service robot configured with user's interactive interface
Existing, user's interactive interface includes the display screen of the service robot；Based on this, this step according to user recommendation institute
It states the end article selected in shops's commodity and executes corresponding recommendation movement, executed based on user's interactive interface, it is specific to wrap
It includes:
The corresponding recommendation movement of the end article is shown to user by the display screen；User is received for described aobvious
Touch control operation is chosen in the end article input that display screen is shown；Using it is described choose the corresponding end article of touch control operation as
Commodity to be recommended；According to user region locating for shops present position and the commodity to be recommended, calculates and generate from user in door
The routing information in region locating for shop present position to the commodity to be recommended；The routing information is exported by the display screen.
Further, above-mentioned according to user region locating for shops present position and the commodity to be recommended, calculate generate from
The routing information in user region locating for shops present position to the commodity to be recommended, preferably can also be real in the following way
It is existing: to judge whether the number of the commodity to be recommended is greater than 1, if so, calculating covers all commodity to be recommended and path is most short
Routing information；And the service robot is when marching to region locating for any commodity to be recommended according to the routing information,
The commodity to be recommended, the trade order information of the commodity to be recommended and/or the quotient to be recommended are shown in the display screen
The evaluation information of product.
Explanation is further explained to the recommended method under above-mentioned shops's scene below by a complete example:
Referring to attached drawing 2, when user B comes into a unmanned shops of supermarket, pass through face recognition device automatic identification user B's
Alipay ID (identity), then according to Alipay ID inquire user B with the associated day cat of Alipay, Taobao, A Liti
It educates and the online services platforms such as Ali's health is with the presence or absence of the register account number of relative users B, query result is user B in day
Cat, Taobao, Ali's sport and Ali's health have registered account.
For the unmanned shops of supermarket under line, for user B when unmanned shops of supermarket does shopping, there is a strong possibility in Taobao, day
Dependent merchandise information is searched for or browsed to cat, and the data dependence coefficient with Taobao, day cat is 0.9；User B is in Ali's health
Disease has been seen, some pairs of unfavorable food of user's disease recovery can be excluded, the data dependence coefficient with Ali's health is 0.6；
User B can recommend star's peripheral product to user B, the data dependence coefficient with Ali's sport is in Ali's sport star-pursuing
0.3。
The sequence of data dependence coefficient from big to small are as follows: day cat, Taobao > Ali's health > Ali's sport, then it is suitable according to this
Sequence successively inquire user B day cat, Taobao, Ali's sport and Ali's health relevant historical data, the historical data inquired
Are as follows: user B searches for paper diaper in Taobao, has seen primary disease: diabetes in Ali's health, and in Ali's sport star-pursuing.
Based on this, when user B does shopping in unmanned shops of supermarket, the data that can be searched for according to user B in Taobao, Xiang Yong
Family B recommends paper diaper product, can also recommend the food for helping to restore diabetes according to user B in the related data of Ali's health
Product give user B, and, according to user B in the related data of Ali's sport, recommend star's peripheral product to user B.
Recommend a series of products to user B, food and star's peripheral product including paper diaper, recovery diabetes, if
User B selects a kind of product paper diaper of intention purchase in a series of products of recommendation, then is drawn by service robot from Taobao
Write off amount highest or the highest paper diaper brand of overall merit and model show user B, at the same time it can also to user's exhibition
Show the sales volume data and evaluation information of paper diaper various brands or each model, saves user B and oneself remove web search paper diaper
Time；User B selected from the paper diaper brand and model of displaying in the display screen of service robot it is a, it is selected for user
This paper diaper, as service robot guidance user B go to the paper diaper where shelf area picking.
Further, can also according to recommendation results, i.e., user whether buy recommendation commodity or user's purchase which kind of
Commodity, to be repaired to the data dependence coefficient between unmanned shops of supermarket and Taobao, day cat, Ali's health and Ali's sport
Just:
If within one section of period (week, the moon or season) according to success rate of some online service platform Recommendations with
Data dependence coefficient in unmanned shops of supermarket and the line platform between service mismatches, and success rate refers to time of user's purchase
Number and the ratio for recommending both numbers of user are then related to the data on the line platform between service to unmanned shops of supermarket
Property coefficient is adjusted；Specifically, if being less than unmanned supermarket's door according to the success rate of some online service platform Recommendations
Data dependence coefficient on shop and the line platform between service, then between service in unmanned shops of supermarket and the line platform
Data dependence coefficient carry out drop power adjustment, that is, reduce unmanned shops of supermarket on the line platform service between data it is related
Property coefficient；, whereas if success rate is greater than data dependence coefficient, then a liter power adjustment is carried out for data dependence coefficient, i.e.,
Increase data dependence coefficient.
For example, data dependence coefficient initial between unmanned shops of supermarket and day cat, Taobao is 0.9, with Ali's sport
Between initial data dependence coefficient be 0.6, initial data dependence coefficient is 0.3 between Ali's health.
Assuming that in first month, according to Ali's health to the success rate of user's Recommendations be 70%, it is super greater than nobody
Initial data dependence coefficient 0.3, the success according to day cat, Taobao to user's Recommendations between shops of city and Ali's health
Rate is 10%, less than data dependence coefficient 0.9 initial between unmanned shops of supermarket and day cat, Taobao, according to Ali's sport
It is 20% to the success rate of user's Recommendations, less than data dependence system initial between unmanned shops of supermarket and Ali's sport
Number 0.6, liter power adjustment when according to adjustment after data dependence coefficient=current data relative coefficient+0.3* success rate this
Rule increase data dependence coefficient, drop power adjustment when according to adjustment after data dependence coefficient=current data correlation system
This rule of number -0.3* (1- success rate) reduces data dependence coefficient, then unmanned shops of supermarket adjusted and Ali day cat,
Data dependence coefficient=0.9-0.3* (1-0.1)=0.63 between Taobao, unmanned shops of supermarket adjusted and Ali's body
Data dependence coefficient=0.6-0.3* (1-0.2)=0.36 between educating, unmanned shops of supermarket adjusted and Ali's health
Between data dependence coefficient=0.3+0.3*0.7=0.51.
In first month second month adjusted, on the basis of data dependence coefficient after the adjustment to user into
Row commercial product recommending, if recommend success rate it is identical with the previous moon, continue to adjust: unmanned shops of supermarket adjusted and
Data dependence coefficient=0.63-0.3* (1-0.1)=0.36 between Ali day cat, Taobao, unmanned supermarket's door adjusted
Data dependence coefficient=0.36-0.3* (1-0.2)=0.12 between shop and Ali's sport, unmanned shops of supermarket adjusted
With data dependence coefficient=0.51+0.3*0.7=0.72 between Ali's health.
In second month third adjusted month, if hit rate still there is no variation, it is adjusted nobody
Data dependence coefficient 0.72 between shops of supermarket and Ali's health is substantially close to hit rate, then without to unmanned supermarket's door
Data dependence coefficient between shop and Ali's health is adjusted, only need to be to unmanned shops of supermarket and day cat, Taobao and Ali
Data dependence between data dependence coefficient between sport, unmanned shops of supermarket adjusted and Ali day cat, Taobao
Coefficient=0.36-0.3* (1-0.1)=0.12, the data dependence system between unmanned shops of supermarket adjusted and Ali's sport
Number=0.12+0.3* (1-0.2)=0.36.
And so on, data relative coefficient is adjusted according to this adjustment thinking, the purpose of adjustment makes data phase
It closes property coefficient and reaches balance, so that commodity recommended to the user be enable to tend to the final choice of client.
In conclusion the recommended method under shops's scene provided by the present application, into shops user recommend
During, by acquiring and identifying the identity of user in shops, and on the basis of identifying User Identity, root
According to user the associated online service platform of shops's classification historical use data, be user unmanned shops consumer behavior into
Row guidance and help, so that the historical use data based on user's service platform on line is that user recommends suitable shops quotient
Product realize and recommend shops's commodity to user on the basis of capturing user demand, recommend success rate also higher also more accurate,
Meanwhile user is improved in the shopping experience of unmanned shops.
Recommendation apparatus embodiment under a kind of shops's scene provided by the present application is as follows:
In the above-described embodiment, the recommended method under a kind of shops's scene is provided, corresponding, the application is also
The recommendation apparatus under a kind of shops's scene is provided, is illustrated with reference to the accompanying drawing.Referring to attached drawing 3, it illustrates the application
The schematic diagram of recommendation apparatus embodiment under a kind of shops's scene provided.Implement since Installation practice is substantially similar to method
Example, so describing fairly simple, relevant part refers to the corresponding explanation of the embodiment of the method for above-mentioned offer.It is following
The Installation practice of description is only schematical.
The application provides the recommendation apparatus under a kind of shops's scene, comprising:
Identity acquisition unit 301, for acquiring the identity of user in shops；
Historical data acquiring unit 302 obtains the identity described for shops's classification according to the shops
The historical use data of the associated online service platform of shops's classification；
Shops's commercial product recommending unit 303 meets threshold value with the matching degree of the historical use data for recommending to user
Shops's commodity；
Recommend action execution unit 304, the end article for selecting in shops's commodity of recommendation according to user
Execute corresponding recommendation movement.
Optionally, the historical data acquiring unit 302 is specifically used for judging the identity in shops's classification
Associated online service platform whether there is corresponding user account, and if it exists, obtain the identity in shops's class
Historical use data under the corresponding user account of the associated online service platform of mesh；Wherein, the customer transaction number of the shops
According to customer transaction data interchange with the associated online service platform of shops's classification.
Optionally, there is data dependence, the shops and the line between the shops and the online service platform
Data dependence coefficient between upper service platform, according to the historical use data of each online service platform determine to user
The recommendation success rate of shops's commodity of recommendation determines that the data dependence coefficient is positively correlated with success rate is recommended.
Optionally, shops's commercial product recommending unit 303, comprising:
Shops's goods matching subelement, for the historical use data and shops's commodity to be carried out matching primitives,
Obtain shops's commodity that matching degree meets threshold value；
Shops's commercial product recommending subelement, for according to the data dependence between the shops and the online service platform
The recommendation order of coefficient from high to low recommends shops's commodity to user.
Optionally, the recommendation action execution unit 304, comprising:
Merchandise related information acquisition subelement, the end article for being selected in shops's commodity of recommendation according to user,
The merchandise related information of the end article is obtained in the online service platform based on the end article；
Merchandise related information shows subelement, the merchandise related information for getting described in showing to user.
Optionally, the recommendation apparatus under shops's scene, comprising:
Routing information generation unit, for according to user region locating for shops present position and the end article, meter
Calculate the routing information generated from user region locating for shops present position to the end article；
Routing information output unit, for exporting the routing information to user.
Optionally, the identity acquisition unit 301 is known specifically for acquiring the human body biological characteristic information of user
The corresponding identity of not described human body biological characteristic information.
Optionally, the recommendation apparatus under shops's scene is transported based on the service robot configured with user's interactive interface
Row, user's interactive interface includes the display screen of the service robot；Correspondingly, the recommendation action execution unit is based on
User's interactive interface operation, specifically includes:
Recommend action demonstration subelement, for showing the corresponding recommendation of the end article to user by the display screen
Movement；
Touch control operation receiving subelement, for receiving end article input of the user for display screen displaying
Choose touch control operation；
Commodity to be recommended determine subelement, for choosing the corresponding end article of touch control operation as quotient to be recommended for described
Product；
Routing information computation subunit, for according to user area locating for shops present position and the commodity to be recommended
Domain calculates the routing information generated from user region locating for shops present position to the commodity to be recommended；
Routing information exports subelement, for exporting the routing information by the display screen.
Optionally, whether the routing information computation subunit, the number specifically for judging the commodity to be recommended are big
In 1, all commodity to be recommended and the shortest routing information in path are covered if so, calculating；And the service robot according to
When the routing information marches to region locating for any commodity to be recommended, the commodity to be recommended, institute are shown in the display screen
State the trade order information of commodity to be recommended and/or the evaluation information of the commodity to be recommended.
A kind of electronic equipment embodiment provided by the present application is as follows:
In the above-described embodiment, the recommended method under a kind of shops's scene is provided, in addition, present invention also provides one
Kind is illustrated with reference to the accompanying drawing for realizing the electronic equipment of the recommended method under shops's scene.Reference attached drawing 4,
It illustrates the schematic diagrames of a kind of electronic equipment provided in this embodiment.The electronic equipment embodiment description provided by the present application
Must be fairly simple, relevant part refers to the corresponding explanation of the recommended method embodiment under shops's scene of above-mentioned offer
?.Embodiment described below is only schematical.
The application provides a kind of electronic equipment, comprising: memory 401 and processor 402；The memory 401 is for depositing
Computer executable instructions are stored up, the processor 402 is used to execute following computer executable instructions: user in acquisition shops
Identity；According to shops's classification of the shops, the identity is obtained in the associated online service of shops's classification
The historical use data of platform；Recommend the shops's commodity for meeting threshold value with the matching degree of the historical use data to user；Root
Corresponding recommendation movement is executed according to the end article that user selects in shops's commodity of recommendation.
Optionally, shops's classification according to the shops obtains the identity and is associated in shops's classification
Online service platform historical use data, comprising: judge that the identity takes on the associated line of shops's classification
Platform be engaged in the presence or absence of corresponding user account, and if it exists, obtain the identity on the associated line of shops's classification
Historical use data under the corresponding user account of service platform；Wherein, the customer transaction data of the shops, with the shops
The customer transaction data interchange of the associated online service platform of classification.
Optionally, there is data dependence, the shops and the line between the shops and the online service platform
Data dependence coefficient between upper service platform, according to the historical use data of each online service platform determine to user
The recommendation success rate of shops's commodity of recommendation determines that the data dependence coefficient is positively correlated with success rate is recommended.
Optionally, the shops's commodity for recommending to meet threshold value with the matching degree of the historical use data to user, packet
It includes: the historical use data and shops's commodity is subjected to matching primitives, obtain shops's commodity that matching degree meets threshold value；
According to the recommendation order of the data dependence coefficient between the shops and the online service platform from high to low, pushed away to user
Recommend shops's commodity.
Optionally, the end article selected in shops's commodity of recommendation according to user executes corresponding recommendation
Movement, comprising: according to the end article that user selects in shops's commodity of recommendation, based on the end article on the line
Service platform obtains the merchandise related information of the end article；To the merchandise related information got described in user's displaying.
Optionally, the end article selected in shops's commodity of recommendation according to user executes corresponding recommendation
After action command executes, the processor 402 is also used to execute following computer executable instructions:
According to user region locating for shops present position and the end article, calculates and generate from user locating for the shops
The routing information in region locating for position to the end article；The routing information is exported to user.
Optionally, the identity for acquiring user in shops, comprising: the human body biological characteristic information of user is acquired,
Identify the corresponding identity of the human body biological characteristic information.
Optionally, the computer executable instructions are executed based on the service robot configured with user's interactive interface, institute
State the display screen that user's interactive interface includes the service robot；Correspondingly, it is described according to user recommendation the shops
The end article selected in commodity executes the instruction of corresponding recommendation movement, is executed based on user's interactive interface, specific to wrap
It includes:
The corresponding recommendation movement of the end article is shown to user by the display screen；User is received for described aobvious
Touch control operation is chosen in the end article input that display screen is shown；Using it is described choose the corresponding end article of touch control operation as
Commodity to be recommended；According to user region locating for shops present position and the commodity to be recommended, calculates and generate from user in door
The routing information in region locating for shop present position to the commodity to be recommended；The routing information is exported by the display screen.
Optionally, described according to user region locating for shops present position and the commodity to be recommended, calculate generate from
The routing information in user region locating for shops present position to the commodity to be recommended, comprising: judge the commodity to be recommended
Number whether be greater than 1, cover all commodity to be recommended and the shortest routing information in path if so, calculating；And the clothes
Business robot is when marching to region locating for any commodity to be recommended according to the routing information, show in the display screen described in
The evaluation information of Recommendations, the trade order information of the commodity to be recommended and/or the commodity to be recommended.
Although the application is disclosed as above with preferred embodiment, it is not for limiting the application, any this field skill
Art personnel are not departing from spirit and scope, can make possible variation and modification, therefore the guarantor of the application
Shield range should be subject to the range that the claim of this application defined.
In a typical configuration, calculating equipment includes that one or more processors, input/output interface, network connect
Mouth and memory.
Memory may include the non-volatile memory in computer-readable medium, random access memory (RAM) and/or
The forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM).Memory is computer-readable medium
Example.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer readable instructions, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase change memory (PRAM), static random access memory (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), flash memory or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or other magnetic storage devices
Or any other non-transmission medium, can be used for storage can be accessed by a computing device information.As defined in this article, it calculates
Machine readable medium does not include non-temporary computer readable media (transitory media), such as the data-signal and carrier wave of modulation.
It will be understood by those skilled in the art that embodiments herein can provide as method, system or computer program product.
Therefore, complete hardware embodiment, complete software embodiment or embodiment combining software and hardware aspects can be used in the application
Form.It is deposited moreover, the application can be used to can be used in the computer that one or more wherein includes computer usable program code
The shape for the computer program product implemented on storage media (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
Formula.
Claims (10)
1. the recommended method under a kind of shops's scene characterized by comprising
Acquire the identity of user in shops；
According to shops's classification of the shops, the identity is obtained in the associated online service platform of shops's classification
Historical use data；
Recommend the shops's commodity for meeting threshold value with the matching degree of the historical use data to user；
Corresponding recommendation movement is executed according to the end article that user selects in shops's commodity of recommendation.
2. the recommended method under shops's scene according to claim 1, which is characterized in that the door according to the shops
Shop classification obtains the identity in the historical use data of the associated online service platform of shops's classification, comprising:
Judge that the identity whether there is corresponding user account in the associated online service platform of shops's classification, if
In the presence of obtaining history of the identity under the corresponding user account of the associated online service platform of shops's classification and use
User data；
Wherein, the customer transaction data of the shops, the customer transaction number with the associated online service platform of shops's classification
According to intercommunication.
3. the recommended method under shops's scene according to claim 2, which is characterized in that taken on the shops and the line
It is engaged between platform with data dependence, the data dependence coefficient between the shops and the online service platform, according to
The recommendation success rate for shops's commodity recommended to the user that the historical use data of each online service platform determines determines, described
Data dependence coefficient is positively correlated with success rate is recommended.
4. the recommended method under shops's scene according to claim 3, which is characterized in that it is described to user recommend with it is described
The matching degree of historical use data meets shops's commodity of threshold value, comprising:
The historical use data and shops's commodity are subjected to matching primitives, obtain the shops quotient that matching degree meets threshold value
Product；
According to the recommendation order of the data dependence coefficient between the shops and the online service platform from high to low, Xiang Yong
Recommend shops's commodity in family.
5. the recommended method under shops's scene according to claim 4, which is characterized in that it is described according to user in recommendation
The end article selected in shops's commodity executes corresponding recommendation movement, comprising:
It is flat in the online service based on the end article according to the end article that user selects in shops's commodity of recommendation
Platform obtains the merchandise related information of the end article；
To the merchandise related information got described in user's displaying.
6. the recommended method under shops's scene according to claim 4, which is characterized in that it is described according to user in recommendation
After the end article selected in shops's commodity executes corresponding recommendation action step execution, the method also includes:
According to user region locating for shops present position and the end article, calculates and generate from user in shops present position
To the routing information in region locating for the end article；
The routing information is exported to user.
7. the recommended method under shops's scene according to claim 1, which is characterized in that user in the acquisition shops
Identity, comprising:
The human body biological characteristic information for acquiring user, identifies the corresponding identity of the human body biological characteristic information.
8. according to claim 1 to the recommended method under shops's scene described in 7 any one, which is characterized in that the shops
Recommended method under scene realizes, user's interactive interface includes based on the service robot configured with user's interactive interface
The display screen of the service robot；
Correspondingly, the end article selected in shops's commodity of recommendation according to user executes corresponding recommendation movement
The step of, it is executed, is specifically included based on user's interactive interface:
The corresponding recommendation movement of the end article is shown to user by the display screen；
It receives user and chooses touch control operation for what the end article that the display screen is shown inputted；
Choose the corresponding end article of touch control operation as commodity to be recommended for described；
According to user region locating for shops present position and the commodity to be recommended, calculates and generate from user position locating for shops
Set the routing information in region locating for the commodity to be recommended；
The routing information is exported by the display screen.
9. the recommendation apparatus under a kind of shops's scene characterized by comprising
Identity acquisition unit, for acquiring the identity of user in shops；
Historical data acquiring unit obtains the identity in shops's class for shops's classification according to the shops
The historical use data of the associated online service platform of mesh；
Shops's commercial product recommending unit, for recommending the shops quotient for meeting threshold value with the matching degree of the historical use data to user
Product；
Recommend action execution unit, the end article for selecting in shops's commodity of recommendation according to user executes correspondence
Recommendation movement.
10. a kind of electronic equipment characterized by comprising
Memory and processor；
The memory is for storing computer executable instructions, and for executing, the computer is executable to be referred to the processor
It enables:
Acquire the identity of user in shops；
According to shops's classification of the shops, the identity is obtained in the associated online service platform of shops's classification
Historical use data；
Recommend the shops's commodity for meeting threshold value with the matching degree of the historical use data to user；
Corresponding recommendation movement is executed according to the end article that user selects in shops's commodity of recommendation.
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| CN201810789899.8A CN109325816A (en) | 2018-07-18 | 2018-07-18 | Recommended method and device under shops's scene |
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| CN201810789899.8A CN109325816A (en) | 2018-07-18 | 2018-07-18 | Recommended method and device under shops's scene |
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Application publication date: 20190212 |