CN110135646A - The method, apparatus quickly served and storage medium are estimated in a kind of dining room - Google Patents
The method, apparatus quickly served and storage medium are estimated in a kind of dining room Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 40
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- 235000012054 meals Nutrition 0.000 claims abstract description 23
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- 238000013528 artificial neural network Methods 0.000 claims abstract description 9
- 238000012549 training Methods 0.000 claims abstract description 4
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- 238000007418 data mining Methods 0.000 description 6
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- 201000004569 Blindness Diseases 0.000 description 2
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Abstract
The invention discloses a kind of dining rooms to estimate the method, apparatus quickly served and storage medium, the history service data of multiple scenes is obtained, and pre-process to the service data, to establish the scenario parameters library of all scenes respectively；Construct different scenes parameter library, and the parameter library based on the different scenes finally serve according to customer respectively menu similarity carry out interval clustering, different scenes are distributed to different section classes；The cluster of time interval is carried out in different time for eating meals sections, extract the menu data of serving served in menu prediction time for eating meals section, it inputs BP neural network and carries out nonlinear fitting, to obtain the prediction model of the menu prediction time for eating meals section of serving in the class of section, the training to the BP neural network is completed；Different weights are arranged to the prediction result of different scenes, and final menu prediction result is obtained to the prediction weighting of the vegetable for menu of serving；Speed of serving is shortened by the coordinated control for link of ordering dishes with this.
Description
Technical field
The present invention relates to culinary art fields of automation technology more particularly to a kind of dining room to estimate the method, apparatus quickly served
And storage medium.
Background technique
With the continuous development of information technology, Chinese dining room starts to be made the transition from traditional artificial to informationization, online booking
It makes a reservation since its distinctive convenience progresses into people's lives, is reserved by that will send the client of reservation order and receive
The server of order establishes connection, and dining room can obtain the order information of client from server.However, the existing online side of making a reservation
Formula can only meet the basic condition that user checks the dining rooms such as menu and price, so that the user except dining room can not
Solve dining room real time information, cause user have dinner to shop experience it is undesirable.
In the service of catering trade, the vegetable how to enable it be satisfied with for the customer recommendation that it is difficult to cater for all tastes, is always catering trade
The target of pursuit.Since the special favor in every restaurant is different, the preference of eater, number of having dinner, standard etc. of having dinner are also each
It is different, therefore it is difficult to find a kind of blanket method to meet the demand of having dinner in every restaurant and every customer.
Dish recommendation system or method in the prior art, a set of people that often only businessman summarizes the experience out according to it
For the rule of formulation, this rule is often suitable only for when specific due to being doped with excessive artificial subjective assessment standard
Phase, the restaurant of specific taste type or the crowd that specifically has dinner.For certain restaurants newly started business, these experiences are often simultaneously
It is not applicable.In addition, when attracting customer and can not know the individual demand of customer due to existing restaurant, similarly push away
Recommending vegetable may be very blindness, and be not appropriate for all people having dinner due to dish amount, price, taste etc. factor
Group not only consumes the energy in restaurant, but also can not provide experience of having dinner well to the customer that has dinner.
With the development of Internet technology and cloud computing technology, more and more traditional experiences summarized by manpower can be by
Data mining technology is replaced.Data mining (Data mining) is one of knowledge discovery in database method, is generally referred to
Search is hidden in the process of the information therein for having special relationship automatically from a large amount of data.Data mining usually with meter
Calculation machine science is related, and (relies on past warp by statistics, online analysis and processing, information retrieval, machine learning, expert system
Test rule) and all multi-methods such as pattern-recognition realize above-mentioned target.Data mining is also used as a kind of decision support processes,
It is based primarily upon artificial intelligence, machine learning, pattern-recognition, statistics, database, visualization technique etc., increasingly automatedly
The data for analyzing enterprise, make the reasoning of inductive, therefrom excavate potential mode, and aid decision making person adjusts market strategy,
Reduce risks, makes correct decision.Therefore, it is necessary to it is a kind of can utilize data mining technology dish recommendation system and method,
The problem of vegetable recommends blindness in the prior art can be efficiently solved, to improve the dining experience of eater.
Summary of the invention
The present invention is directed at least solve the technical problems existing in the prior art.For this purpose, the invention discloses a kind of dining rooms
The method quickly served is estimated, the history service data of multiple scenes is obtained, and pre-process to the service data, to build respectively
Stand the scenario parameters library of all scenes；The scene include: customer enter dining room scene, customer order scene, rear kitchen prepare field
Scape；The parameter library of different scenes is constructed, and the menu of finally serving according to customer respectively of the parameter library based on the different scenes is similar
Degree carries out interval clustering, and different scenes are distributed to different section classes；History service data is divided into multiple time for eating meals
Section, dish of the section class in different time for eating meals sections during history is obtained in the record of menu of finally serving from the customer
One-state, and in different time for eating meals sections carry out time interval cluster so that the multiple basal latency section cluster to
Different order forecasting reference periods；Extract the menu data of serving served in menu prediction time for eating meals section, input BP mind
Nonlinear fitting is carried out through network, to obtain the prediction model of the menu prediction time for eating meals section of serving in the class of section, completion pair
The training of the BP neural network；Different weights are arranged to the prediction result of different scenes, and the vegetable for menu of serving is predicted
Weighting obtains final menu prediction result；Speed of serving is shortened by the coordinated control for link of ordering dishes with this.
Further, the customer enters dining room scene, obtains the number, Gu Kexing of having dinner by image capture technology
Not, age, figure, and tentative prediction menu is obtained by BP neural network based on above-mentioned parameter.
Further, further comprise as the rear kitchen prepares scene: the reserves of food materials, vegetable production duration.
Further, customer scene of ordering includes that vegetable that guest places an order, attendant recommend vegetable.
Further, the scenario parameters include have dinner number, customer's gender, age, figure, time for eating meals, and just
The personal taste requirements of meal customer；The service data include: attendant's quantity, single service duration, vegetable type, on
Dish waiting time, attendant you recommend menu and menu of finally serving.
Further, whether defined using cosine similarity between all customers that have dinner has similar background category
Property:
Wherein, (- 1,1) S ' (u, v) ∈, Au,AvThe attribute that customer u and customer v have is indicated, since customer is with multiple
Attribute needs to calculate the similarity of all properties, if customer has m attribute, then can indicate are as follows:
Wherein, au,i,av,iIndicate the ith attribute of customer u and customer v, because cosine similarity S ' (u, v) ∈ (- 1,
1) it, need to be normalized, then,
With this, the customer high to similitude carries out similar vegetable promotion.
Further, the customer is entered the prediction menu that dining room scene obtains by real time communication device preferentially to accuse
Know attendant, prediction result dynamic corrections promotion menu while customer orders based on other scenes.
Further, facial characteristics record is carried out to the customer with special personal taste requirements.
The present invention further discloses a kind of electronic devices characterized by comprising
Processor；And
Memory, for storing the executable instruction of the processor；
Wherein, the processor is configured to estimate on quick via the execution executable instruction to execute above-mentioned dining room
The method of dish.
The present invention further discloses a kind of computer readable storage mediums, are stored thereon with computer program, feature
It is, the computer program realizes that the method quickly served is estimated in dining room as described above when being executed by processor.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this
Some embodiments of invention for those of ordinary skill in the art without creative efforts, can be with
The structure shown according to these attached drawings obtains other attached drawings.
Fig. 1 is the flow chart that the method quickly served is estimated in a kind of dining room of the invention.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
To make the objectives, technical solutions, and advantages of the present invention clearer, below in conjunction with attached drawing to the present invention make into
It is described in detail to one step, it is clear that the described embodiments are only some of the embodiments of the present invention, rather than whole implementation
Example.Based on the embodiments of the present invention, obtained by those of ordinary skill in the art without making creative efforts
All other embodiment, shall fall within the protection scope of the present invention.
Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete
Site preparation description, it is clear that described embodiments are some of the embodiments of the present invention, instead of all the embodiments.It needs to illustrate
, the detailed description illustrated in conjunction with attached drawing is intended as the description to various configurations, wherein can be real without being intended to indicate that
Trample unique configuration of concepts described herein.Installation practice and embodiment of the method documented by herein will be following detailed
It is described in thin description, and passes through various frames, module, unit, component, circuit, step, process, algorithm etc. in the accompanying drawings
(be referred to as " element ") is shown.These elements can be used electronic hardware, computer software or any combination thereof and come
It realizes.It is implemented as hardware or software as these elements, depending on specific application and the design being applied on total system
Constraint.If the term in description and claims of this specification and Figure of description uses " first ", " second " etc.
Description, this kind description is not use to describe a particular order for distinguishing different objects.
It should be appreciated that ought use in this specification and in the appended claims, term " includes " and "comprising" instruction
Described feature, entirety, step, operation, the presence of element and/or component, but one or more of the other feature, whole is not precluded
Body, step, operation, the presence or addition of element, component and/or its set.It is also understood that the institute in this description of the invention
The term used is merely for the sake of being not intended to limit the present invention for the purpose of describing particular embodiments.Such as in description of the invention
With it is used in the attached claims like that, other situations unless the context is clearly specified, otherwise singular
" one ", "one" and "the" are intended to include plural form.It will be further appreciated that being wanted in description of the invention and appended right
Term "and/or" used in book is asked to refer to any combination and all possibility of one or more of associated item listed
Combination, and including these combinations.
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
In subsequent description, it is only using the suffix for indicating such as " module ", " component " or " unit " of element
Be conducive to explanation of the invention, itself there is no a specific meaning.Therefore, " module ", " component " or " unit " can mix
Ground uses.
The method quickly served is estimated in a kind of dining room as shown in Figure 1, obtains the history service data of multiple scenes, and right
The service data pretreatment, to establish the scenario parameters library of all scenes respectively；The scene includes: that customer enters dining room
Scape, customer order scene, rear kitchen prepare scene；Construct the parameter library of different scenes, and the parameter library based on the different scenes point
Menu similarity of not serving finally according to customer carries out interval clustering, and different scenes are distributed to different section classes；By history
Service data is divided into multiple time for eating meals sections, and section class is obtained in the record of menu of finally serving from the customer in the history phase
In different time for eating meals sections in menu item aspects, and in different time for eating meals sections carry out time interval cluster, with
Cluster the multiple basal latency section to different order forecasting reference periods；Extraction serve menu prediction time for eating meals section
Interior menu data of serving, input BP neural network carry out nonlinear fitting, serve menu prediction just to obtain in the class of section
The prediction model of meal period completes the training to the BP neural network；Different power are arranged to the prediction result of different scenes
Weight, and final menu prediction result is obtained to the prediction weighting of the vegetable for menu of serving；Pass through the coordinated control for link of ordering dishes with this
Shorten speed of serving.
Further, the customer enters dining room scene, obtains the number, Gu Kexing of having dinner by image capture technology
Not, age, figure, and tentative prediction menu is obtained by BP neural network based on above-mentioned parameter.
Further, further comprise as the rear kitchen prepares scene: the reserves of food materials, vegetable production duration.
Further, customer scene of ordering includes that vegetable that guest places an order, attendant recommend vegetable.
Further, the scenario parameters include have dinner number, customer's gender, age, figure, time for eating meals, and just
The personal taste requirements of meal customer；The service data include: attendant's quantity, single service duration, vegetable type, on
Dish waiting time, attendant you recommend menu and menu of finally serving.
Further, whether defined using cosine similarity between all customers that have dinner has similar background category
Property:
Wherein, (- 1,1) S ' (u, v) ∈, Au,AvThe attribute that customer u and customer v have is indicated, since customer is with multiple
Attribute needs to calculate the similarity of all properties, if customer has m attribute, then can indicate are as follows:
Wherein, au,i,av,iIndicate the ith attribute of customer u and customer v, because cosine similarity S ' (u, v) ∈ (- 1,
1) it, need to be normalized, then,
With this, the customer high to similitude carries out similar vegetable promotion.
Further, the customer is entered the prediction menu that dining room scene obtains by real time communication device preferentially to accuse
Know attendant, prediction result dynamic corrections promotion menu while customer orders based on other scenes.
Further, facial characteristics record is carried out to the customer with special personal taste requirements.
The present invention further discloses a kind of electronic devices characterized by comprising
Processor；And
Memory, for storing the executable instruction of the processor；
Wherein, the processor is configured to estimate on quick via the execution executable instruction to execute above-mentioned dining room
The method of dish.
The present invention further discloses a kind of computer readable storage mediums, are stored thereon with computer program, feature
It is, the computer program realizes that the method quickly served is estimated in dining room as described above when being executed by processor.
It should also be noted that, the terms "include", "comprise" or its any other variant are intended to nonexcludability
It include so that the process, method, commodity or the equipment that include a series of elements not only include those elements, but also to wrap
Include other elements that are not explicitly listed, or further include for this process, method, commodity or equipment intrinsic want
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including described want
There is also other identical elements in the process, method of element, commodity or equipment.
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.
Although describing the present invention by reference to various embodiments above, but it is to be understood that of the invention not departing from
In the case where range, many changes and modifications can be carried out.Therefore, be intended to foregoing detailed description be considered as it is illustrative and
It is unrestricted, and it is to be understood that following following claims (including all equivalents) is intended to limit spirit and model of the invention
It encloses.The above embodiment is interpreted as being merely to illustrate the present invention rather than limit the scope of the invention.It is reading
After the content of record of the invention, technical staff can be made various changes or modifications the present invention, these equivalence changes and
Modification equally falls into the scope of the claims in the present invention.
Claims (10)
1. the method quickly served is estimated in a kind of dining room, which is characterized in that obtain the history service data of multiple scenes, and to institute
Service data pretreatment is stated, to establish the scenario parameters library of all scenes respectively；The scene includes: that customer enters dining room
Scape, customer order scene, rear kitchen prepare scene；Construct the parameter library of different scenes, and the parameter library based on the different scenes point
Menu similarity of not serving finally according to customer carries out interval clustering, and different scenes are distributed to different section classes；By history
Service data is divided into multiple time for eating meals sections, and section class is obtained in the record of menu of finally serving from the customer in the history phase
In different time for eating meals sections in menu item aspects, and in different time for eating meals sections carry out time interval cluster, with
Cluster the multiple basal latency section to different order forecasting reference periods；Extraction serve menu prediction time for eating meals section
Interior menu data of serving, input BP neural network carry out nonlinear fitting, serve menu prediction just to obtain in the class of section
The prediction model of meal period completes the training to the BP neural network；Different power are arranged to the prediction result of different scenes
Weight, and final menu prediction result is obtained to the prediction weighting of the vegetable for menu of serving；Pass through the coordinated control for link of ordering dishes with this
Shorten speed of serving.
2. the method quickly served is estimated in a kind of dining room as described in claim 1, which is characterized in that the customer enters dining room
Scene is had dinner number, customer's gender, age, figure by image capture technology acquisition, and passes through BP nerve based on above-mentioned parameter
Network obtains tentative prediction menu.
3. the method quickly served is estimated in a kind of dining room as claimed in claim 2, which is characterized in that as the rear kitchen prepares field
Scape further comprises: reserves, the vegetable of food materials make duration.
4. the method quickly served is estimated in a kind of dining room as claimed in claim 3, which is characterized in that the customer orders field
Scape includes the vegetable that guest places an order, attendant's recommendation vegetable.
5. the method quickly served is estimated in a kind of dining room as claimed in claim 4, which is characterized in that the scenario parameters include
It has dinner the personal taste requirements of number, customer's gender, age, figure, time for eating meals, and the customer that has dinner；The service data
Include: attendant's quantity, single service duration, vegetable type, waiting time of serving, attendant you recommend menu and final
It serves menu.
6. the method quickly served is estimated in a kind of dining room as claimed in claim 5, which is characterized in that use cosine similarity
Whether define between all customers that have dinner has similar background attribute:
Wherein, (- 1,1) S ' (u, v) ∈, Au,AvIndicate the attribute that customer u and customer v have, since customer has multiple attributes,
It needs to calculate the similarity of all properties, if customer has m attribute, then can indicate are as follows:
Wherein, au,i,av,iThe ith attribute for indicating customer u and customer v needs because of cosine similarity S ' (u, v) ∈ (- 1,1)
It is normalized, then,
With this, the customer high to similitude carries out similar vegetable promotion.
7. the method quickly served is estimated in a kind of dining room as claimed in claim 6, which is characterized in that pass through real time communication device
The customer is entered into the prediction menu that dining room scene obtains and preferentially informs attendant, is based on other while customer orders
The prediction result dynamic corrections promotion menu of scene.
8. the method quickly served is estimated in a kind of dining room as claimed in claim 7, which is characterized in that with special personal taste
It is required that customer carry out facial characteristics record.
9. a kind of electronic device characterized by comprising
Processor；And
Memory, for storing the executable instruction of the processor；
Wherein, the processor is configured to require the dining room any one of 1-8 pre- via executing the executable instruction and carry out perform claim
Estimate the method quickly served.
10. a kind of computer readable storage medium, is stored thereon with computer program, which is characterized in that the computer program
Realize that the method quickly served is estimated in the described in any item dining rooms claim 1-8 when being executed by processor.
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| CN201910422695.5A CN110135646B (en) | 2019-05-20 | 2019-05-20 | Restaurant pre-estimation quick serving method and device and storage medium |
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| CN201910422695.5A CN110135646B (en) | 2019-05-20 | 2019-05-20 | Restaurant pre-estimation quick serving method and device and storage medium |
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| CN111428944A (en) * | 2020-04-26 | 2020-07-17 | 陈霄 | Catering industry management system and method based on big data |
| CN113344666A (en) * | 2021-06-02 | 2021-09-03 | 易食便当香港有限公司 | Method, device and system for generating menu |
| CN113491432A (en) * | 2020-04-07 | 2021-10-12 | 添可智能科技有限公司 | Automatic cooking method and system of cooking machine and cooking machine |
| CN113592183A (en) * | 2021-08-05 | 2021-11-02 | 杭州企智互联科技有限公司 | Dining peak prediction method and device |
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| CN113592183A (en) * | 2021-08-05 | 2021-11-02 | 杭州企智互联科技有限公司 | Dining peak prediction method and device |
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| CN110135646B (en) | 2021-07-20 |
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