CN109471984A - Shop recommended method and device - Google Patents
Shop recommended method and device Download PDFInfo
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- CN109471984A CN109471984A CN201811207199.XA CN201811207199A CN109471984A CN 109471984 A CN109471984 A CN 109471984A CN 201811207199 A CN201811207199 A CN 201811207199A CN 109471984 A CN109471984 A CN 109471984A
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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
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0282—Rating or review of business operators or products
Abstract
The invention discloses a kind of shop recommended method and devices.Wherein, shop recommended method includes: to obtain the trip mode information of customer position information and user's selection according to shop recommended requirements；According to customer position information and trip mode information, screening obtains at least one candidate shop, assessment for each candidate shop user to the shop time；For each candidate shop, according to user to the service data in the shop time prediction candidate shop；Shop recommendation is carried out according to the service data in each candidate shop.Based on scheme provided by the invention, when user selects the shop recommended to have dinner, user's time for eating meals can be shortened, user is avoided to fall into a long wait, especially for the user that the time is more nervous, user can not only be allowed to have dinner within the limited time, additionally it is possible to avoid excessively occupying user time, the user experience is improved.
Description
Technical field
The present invention relates to technical field of information processing, and in particular to a kind of shop recommended method and device.
Background technique
With the development of informationized society, people increasingly get used to that consumption shop is searched or selected using network, existing
Have in technology, usually using the specialty in shop as shop recommend foundation, or using shop activity or coupon information as
Foundation is recommended in shop, or browses record or consumer record progress shop recommendation according to user's history.
This shop recommended method does not consider period of reservation of number, causes many times, and user reaches the shop recommended
When, it is in the peak period in shop, needs etc. to be lot more time to take a seat and have dinner, alternatively, rear kitchen order volume is too big, causes to grow very much
Time does not serve, causes to eat a meal and takes a long time, and causes poor user experience, reduces the product that user uses recommendation function
Polarity.
Summary of the invention
In view of the above problems, it proposes on the present invention overcomes the above problem or at least be partially solved in order to provide one kind
State the shop recommended method and device of problem.
According to an aspect of the invention, there is provided a kind of shop recommended method, comprising:
According to shop recommended requirements, the trip mode information of customer position information and user's selection is obtained；
According to customer position information and trip mode information, screening obtains at least one candidate shop, and assessment is for every
The user in a candidate shop is to the shop time；
For each candidate shop, according to user to the service data in the shop time prediction candidate shop；
Shop recommendation is carried out according to the service data in each candidate shop.
Optionally, further comprise according to the service data in user to the shop time prediction candidate shop:
According to user to shop time, the current people information in shop, history same period stream of people tendency information and/or currently serve speed
Spend the service data in candidate shop when information prediction user reaches shop.
Optionally, service data includes: equipotential time data and/or time data of serving.
Optionally, customer position information includes: user current location information；
According to customer position information and trip mode information, screening obtains at least one candidate shop and further comprises:
According to user current location information and trip mode information sifting in user current location information preset range
At least one candidate shop.
Optionally, customer position information includes: user current location information and destination locations information；
According to customer position information and trip mode information, screening obtains at least one candidate shop and further comprises:
The candidate shop of at least one of screening in destination locations information preset range.
Optionally, assessment further comprises to the shop time for the user in each candidate shop:
According to the assessment of store location information, user current location information, trip mode information and traffic information for every
The user in a candidate shop is to the shop time.
Optionally, before assessing the user to shop time for each candidate shop, method further include:
According to shop basic score, screening obtains at least one candidate of shop basic score more than or equal to preset threshold
Shop.
Optionally, carrying out shop recommendation according to the service data in each candidate shop further comprises:
At least one candidate shop is ranked up according to service data；
According to ranking results, generates the shop comprising service data and recommend the page.
According to another aspect of the present invention, a kind of shop recommendation apparatus is provided, comprising:
Module is obtained, is suitable for obtaining the trip mode of customer position information and user's selection according to shop recommended requirements
Information；
Processing module is suitable for according to customer position information and trip mode information, and screening obtains at least one candidate shop
Paving, assessment for each candidate shop user to the shop time；
Prediction module is suitable for for each candidate shop, according to user to the service number in the shop time prediction candidate shop
According to；
Recommending module, suitable for carrying out shop recommendation according to the service data in each candidate shop.
Optionally, prediction module is further adapted for: according to user to shop time, the current people information in shop, the history same period
The service data in candidate shop when stream of people's tendency information and/or the velocity information prediction user that currently serves reach shop.
Optionally, service data includes: equipotential time data and/or time data of serving.
Optionally, customer position information includes: user current location information；
Processing module is further adapted for: according to user current location information and trip mode information sifting in user's present bit
Confidence ceases at least one candidate shop in preset range.
Optionally, customer position information includes: user current location information and destination locations information；
Processing module is further adapted for: the candidate shop of at least one of screening in destination locations information preset range.
Optionally, processing module is further adapted for: according to store location information, user current location information, trip mode
Information and traffic information assessment for each candidate shop user to the shop time.
Optionally, processing module is further adapted for: according to shop basic score, screening obtains shop basic score and is greater than or equal to
The candidate shop of at least one of preset threshold.
Optionally, recommending module is further adapted for: being ranked up according to service data at least one candidate shop；According to
Ranking results generate the shop comprising service data and recommend the page.
According to another aspect of the invention, provide a kind of calculating equipment, comprising: processor, memory, communication interface and
Communication bus, processor, memory and communication interface complete mutual communication by communication bus；
Memory makes processor execute above-mentioned shop recommended method for storing an at least executable instruction, executable instruction
Corresponding operation.
In accordance with a further aspect of the present invention, a kind of computer storage medium is provided, at least one is stored in storage medium
Executable instruction, executable instruction make processor execute such as the corresponding operation of above-mentioned shop recommended method.
The scheme provided according to the present invention obtains customer position information and user's selection according to shop recommended requirements
Trip mode information；According to customer position information and trip mode information, screening obtains at least one candidate shop, assesses needle
To the user in each candidate shop to shop time；For each candidate shop, according to user to the shop time prediction candidate shop
Service data；Shop recommendation is carried out according to the service data in each candidate shop.Based on scheme provided by the invention, in user
The shop that selection is recommended can shorten user's time for eating meals, user is avoided to fall into a long wait when having dinner, especially for the time compared with
For nervous user, user can not only be allowed to have dinner within the limited time, additionally it is possible to avoid excessively occupying user time, be promoted
User experience.
The above description is only an overview of the technical scheme of the present invention, in order to better understand the technical means of the present invention,
And it can be implemented in accordance with the contents of the specification, and in order to allow above and other objects of the present invention, feature and advantage can
It is clearer and more comprehensible, the followings are specific embodiments of the present invention.
Detailed description of the invention
By reading the following detailed description of the preferred embodiment, various other advantages and benefits are common for this field
Technical staff will become clear.The drawings are only for the purpose of illustrating a preferred embodiment, and is not considered as to the present invention
Limitation.And throughout the drawings, the same reference numbers will be used to refer to the same parts.In the accompanying drawings:
Fig. 1 shows the flow diagram of shop recommended method according to an embodiment of the invention；
Fig. 2A shows the flow diagram of shop recommended method in accordance with another embodiment of the present invention；
Fig. 2 B- Fig. 2 C is the schematic diagram that the page is recommended in shop；
Fig. 3 shows the structural schematic diagram of shop recommendation apparatus according to an embodiment of the invention；
Fig. 4 shows the structural schematic diagram according to an embodiment of the invention for calculating equipment.
Specific embodiment
Exemplary embodiments of the present disclosure are described in more detail below with reference to accompanying drawings.Although showing the disclosure in attached drawing
Exemplary embodiment, it being understood, however, that may be realized in various forms the disclosure without should be by embodiments set forth here
It is limited.On the contrary, these embodiments are provided to facilitate a more thoroughly understanding of the present invention, and can be by the scope of the present disclosure
It is fully disclosed to those skilled in the art.
Fig. 1 shows the flow diagram of shop recommended method according to an embodiment of the invention.As shown in Figure 1, should
Method the following steps are included:
Step S100 obtains the trip mode information of customer position information and user's selection according to shop recommended requirements.
In the present embodiment, user can recommend shop by the application request with shop recommendation function, wherein application
The local program (nativeApp) that can be mounted on terminal device, or can also be browser on terminal device
One web page program (webApp).
Using that can show the shop recommendation request page to user, various trips are shown in the shop recommendation request page
Mode option and customer position information input options or position position option, wherein common trip mode has following several:
Walking rides, public transport, drives, and therefore, can be arranged in correspondence with the selection option of above-mentioned trip mode, and push away by shop
It recommends request page and shows user, selected for user according to practical trip situation, for example, user is currently that walking is advanced,
It then can choose walking option；If the current vehicles of user are shared bicycles, option of riding can choose, it is not another here
One enumerates explanation；User, which can be manually entered customer position information or position option by trigger position, determines that user location is believed
Breath selects trip mode in user and determines customer position information, can be considered as to server-side and have sent shop recommendation request.
In another optional embodiment of the invention, which can also show recommendation button,
After user selects trip mode and determines customer position information, user, which triggers, recommends button, that is, is considered as to server-side and sends out
Shop recommendation request has been sent, which carries the trip mode information of customer position information and user's selection,
Server-side obtains the trip mode information of customer position information and user's selection according to shop recommendation request.
Step S101, according to customer position information and trip mode information, screening obtains at least one candidate shop, comments
User for each candidate shop is estimated to the shop time.
Server-side maintenance has a large amount of shop, these shops are distributed in each position, in order to push away suitable shop
It recommends to user, before user is recommended in shop, needs first to carry out shop screening, specifically, can be believed according to user location
Breath and trip mode information, screening obtain at least one candidate shop, after screening obtains at least one candidate shop, for
Each candidate shop can assess user to the shop time, wherein user according to customer position information and trip mode information
It is a discreet value to the shop time, user to shop time reflects user and probably needs how long candidate shop can be reached.
In the present embodiment, the corresponding customer position information of different user is different, and the selected trip mode of user is different,
Therefore, the candidate shop screened is different, the user assessed to shop time difference.
Step S102, for each candidate shop, according to user to the service data in the shop time prediction candidate shop.
After assessing for the user to shop time in each candidate shop, for each candidate shop, can according to
Service data of the family to the shop time prediction candidate shop, wherein when service data includes: equipotential time data and/or serves
Between data, equipotential time data reflect user and reach to need to wait behind shop how long can just take a seat and have dinner, when serving
Between data reflect after user takes a seat, need to wait how long businessman can just serve vegetable.
For example, assessing to obtain user according to step S101 reaches candidate shop A needs 20 minutes, this step will be pre-
The service data of candidate shop A after twenty minutes is surveyed, for example, current time is 11:00, prediction is candidate shop A in 11:20 here
When service data.
Step S103 carries out shop recommendation according to the service data in each candidate shop.
It, can be according to each candidate shop after the service data according to user to the shop time prediction candidate shop
Service data carries out shop recommendation, so that user selects shop to have dinner according to service data.
The method provided according to that above embodiment of the present invention, according to shop recommended requirements, obtain customer position information and
The trip mode information of user's selection；According to customer position information and trip mode information, screening obtains at least one candidate
Shop, assessment for each candidate shop user to the shop time；For each candidate shop, according to user to shop time prediction
The service data in the candidate shop；Shop recommendation is carried out according to the service data in each candidate shop.Based on provided by the invention
Scheme can shorten user's time for eating meals, user is avoided to fall into a long wait, especially when user selects the shop recommended to have dinner
It is the user more nervous for the time, user can not only be allowed to have dinner within the limited time, additionally it is possible to avoid excessively occupying
User time, the user experience is improved.
Fig. 2A shows the flow diagram of shop recommended method in accordance with another embodiment of the present invention.Such as Fig. 2A institute
Show, method includes the following steps:
Step S200 obtains the trip mode information of customer position information and user's selection according to shop recommended requirements.
Server-side after receiving shop recommendation request, extracted from the shop recommendation request customer position information and
The trip mode information of user's selection, wherein trip mode information includes: walking, rides, public transport, drives.
Step S201, according to customer position information and trip mode information, screening obtains at least one candidate shop.
Server-side maintenance has a large amount of shop, these shops are distributed in each position, in order to push away suitable shop
It recommends to user, before user is recommended in shop, needs first to carry out shop screening, wherein customer position information includes: user
Current location information or user current location information and destination locations information, the screening conditions needed to refer to when screening shop
It is related to customer position information, for example, if customer position information includes: user current location information, it can be by trip mode
Information is as one of screening conditions；If customer position information includes: user current location information and destination locations information, incite somebody to action
Customer position information can not be referring again to trip mode information when carrying out shop screening as screening conditions.
Trip mode information determines the range in screening shop, for example, if user can not when trip mode information is walking
Too far place can be walked, in this case, screening range is small；If trip mode information is, since driving speed is fast, to use when driving
Family can go to place slightly a little further, and screening range is big.
When customer position information is as screening shop, reference by location foundation, that is, the shop near which position screened.
With reference to embodiment, it is described in detail how to carry out shop screening:
In a kind of optional embodiment of the present invention, if customer position information includes: that user current location information (indicates to use
The position that family is presently in), then when screening shop, it can be according to user current location information and trip mode information sifting
At least one candidate shop in user current location information preset range, the candidate shop of at least one screened here
It is the shop in user current location information preset range, which is determined by trip mode information, for example, user goes out
Line mode is walking, then the candidate shop of at least one screened should be closer apart from user current location information, such as
Using user current location as the shop within 1 kilometer of the center of circle, it can be avoided user in this way and walk too far distance；If user goes on a journey
Mode is drives, then the candidate shop of at least one screened can be slightly remote apart from user current location information, example
Such as using user current location as the shop within 5 kilometers of the center of circle, so that the selection of abundant user, is merely illustrative of here,
Those skilled in the art can be set according to actual needs preset range.
In a kind of optional embodiment of the present invention, customer position information includes: that user current location information (indicates user
The position being presently in) and destination locations information (indicating the position that user wants to go to), destination locations information embodies use
The destination at family, in this case, screening should be therefore shop near destination can be screened in purpose status
Confidence ceases at least one candidate shop in preset range, for example, using destination locations as the shop within 1 kilometer of the center of circle.
Step S202, according to shop basic score, screening obtains shop basic score extremely more than or equal to preset threshold
A few candidate shop.
In order to guarantee that user can have dinner under good eating surroundings, and delicious vegetable can be tasted, it can be with
It screens again at least one candidate shop that step S201 is obtained based on shop basic score, wherein comment on shop basis
It point is a comprehensive score to shop, being specifically can to the overall merit of the various aspects such as the vegetable, environment, service in shop
To calculate shop basic score according to user comment, shop photograph album, shop affiliated area etc., shop phase volumes is more, shop base
Plinth scoring is higher, and shop affiliated area determines store environment, it is generally the case that the environment in shop is better than market, in commercial circle
The environment in shop near school, therefore, the shop basic score in shop is higher than the shop basis in market, school area shop in commercial circle
Scoring.
Step S203 is commented according to store location information, user current location information, trip mode information and traffic information
User for each candidate shop is estimated to the shop time.
After screening obtains shop basic score more than or equal at least one candidate shop of preset threshold, this is obtained
The store location information in a little candidate shops, can calculate two positions according to store location information and user current location information
The distance between, trip mode information and traffic information determine user's travel speed, therefore, according to store location information, use
When family current location information, trip mode information and traffic information can assess the user for each candidate shop to shop
Between.Wherein, user to the shop time be a discreet value, user to shop time reflects user and probably needs how long to arrive
Up to candidate shop.
Traffic information reflection is congestion in road or unimpeded situation, and traffic information includes following several: unimpeded, substantially smooth
Logical, slight congestion, moderate congestion, heavy congestion, different traffic informations determines that user's travel speed is different, thus according to road
The user that condition information evaluation obtains is different to the shop time.
Common trip mode has following several: walking rides, public transport, drives, and different trip modes determines use
Family travel speed is different, so that the user obtained according to trip mode information evaluation is different to the shop time.
Wherein, when trip mode is walking, user walks in pavement, therefore, has no point of the coast is clear or congestion, because
This, when trip mode information is walking trip mode, can not consider traffic information, or traffic information is regarded as freely
It is logical.
In a kind of optional embodiment of the present invention, when assessment arrives the shop time for the user in each candidate shop, go back
It can be assessed in conjunction with Weather information, for example, weather conditions are different, determine that user's travel speed is different, when weather is fine,
User's travel speed is fast, and when weather is rain, user's travel speed is slow, so that the user that assessment obtains illustrates to shop time difference
Illustrate, on rainy day, drive to go on a journey, the influence due to rainwater to pilot's line of vision leads to traveling of the travel speed compared with fine day when
Speed is slow.
In this step, traffic information, Weather information can be obtained by calling third party's data, here no longer in detail
It repeats.
Step S204, according to user to shop time, the current people information in shop, history same period stream of people tendency information and/or
The service data in candidate shop when velocity information of currently serving prediction user reaches shop.
The purpose of the present embodiment is to reduce period of reservation of number in order to promote user and have dinner experience, allow users to as early as possible just
Meal saves user time, when therefore, it is necessary to predict that user reaches shop, the service data in the candidate shop, wherein service number
According to including: equipotential time data and/or time data of serving, equipotential time data, which reflect after user reaches shop, to be needed to wait
How long can just take a seat and have dinner, time data of serving reflect after user takes a seat, need to wait how long businessman's just meeting
Vegetable is served.
Specifically, before predicting service data, need first to obtain data of each candidate shop in multiple dimensions, example
Such as, the current people information in shop, history same period stream of people tendency information and/or velocity information of currently serving are obtained, wherein work as in shop
The reflection of preceding people information is the current flow of the people in shop, whether can currently be had according to lower one-state, shop vacant seat with
And row number situation determines the current people information in shop；History same period stream of people tendency message reflection stream of people's situation of change, the stream of people
Amount is increase or reduced trend；Velocity information of currently serving reflects rear kitchen processing order situation.Clothes in the present embodiment
Business end needs to get through with shop meal ordering system, rear kitchen processing system, consequently facilitating determining the current people information in shop, the history same period
Stream of people's tendency information, velocity information of currently serving.
Get the current people information in shop, history same period stream of people tendency information and/or currently serve velocity information it
Afterwards, it according to user to shop time, the current people information in shop, history same period stream of people tendency information and/or currently can serve speed
Spend the service data in candidate shop when information prediction user reaches shop.
For example, assessing to obtain user according to step S203 reaches candidate shop A needs 20 minutes, this step will be pre-
Survey the service data of candidate shop A after twenty minutes, for example, current time is 11:00, according to yesterday or it is interior for the previous period
People information obtained shop A shop A current in the history same period stream of people tendency information of period 11:00-11:20, candidate
And current velocity information of serving, come when predicting 11:20, the service data of candidate shop A.
It should be noted that in the service data in reference history same period stream of people tendency information prediction candidate shop, it should
Work Time of Day is distinguished with holiday time, for example, current time is festivals or holidays, and proxima luce (prox. luc) is working day, is being referred to
When history same period stream of people tendency information, it should be stream of people's tendency information of determining same period last week, and no longer be yesterday (working day)
Stream of people's tendency information of the same period；Current time is working day, and proxima luce (prox. luc) is festivals or holidays, is believed in reference history same period stream of people tendency
When breath, it should be stream of people's tendency information of determining same period last week, and no longer be stream of people's tendency information of yesterday (festivals or holidays) same period.
In a kind of optional embodiment of the present invention, in the service data in predicting candidate shop, weather can be combined with
Information is assessed, for example, weather conditions are different, stream of people's tendency information be would also vary from, thus the service number that prediction obtains
According to difference, the accuracy of prediction is improved, and then improves the accuracy of recommendation, improves user experience.
Step S205 is ranked up at least one candidate shop according to service data.
It is obtained when user reaches shop after the service data in the candidate shop in prediction, it can be according to service data to time
Shop is selected to be ranked up, for example, from small to large according to equipotential time data, or time data of serving are from small to large at least one
A candidate shop is ranked up.
Step S206 generates the shop comprising service data and recommends the page according to ranking results.
After being ranked up according to service data at least one candidate shop, it can be waited according at least one after sequence
Shop is selected, the shop comprising service data is generated and recommends the page, as shown in Fig. 2 B or Fig. 2 C, recommends the page to return in the shop of generation
Back to application, show on the terminal device, had dinner shop for user according to service data selection, user can according to oneself when
Between select suitable shop, for example, not needing equipotential if user time more anxiety can choose shop A；If user time compared with
To be abundant, equipotential can be received, user can be according to receptible equipotential selection of time shop B or shop C or shop D or shop
E；For another example user can be according to the suitable shop of selection of time of serving.
In addition, the page is recommended in the shop further include: option of ordering in advance, user can order in advance, prepare for a meal in advance for shop.
The method provided according to that above embodiment of the present invention obtains the trip mode of customer position information and user's selection
After information, first according to customer position information and trip mode information preliminary screening shop, again further according to shop basic score
Secondary screening shop can not only guarantee to the suitable shop of user's recommended distance, additionally it is possible to guarantee to recommend the shop matter of user
Amount makes user taste delicious vegetable；According to store location information, user current location information, trip mode information and
Traffic information assessment for each candidate shop user to the shop time, according to user to shop time, the current people information in shop,
The service number in candidate shop when history same period stream of people tendency information and/or the velocity information prediction user that currently serves reach shop
According to foundation service data is ranked up at least one candidate shop, according to ranking results, generates the shop comprising service data
Recommend the page, when can guarantee that user selects the shop recommended to have dinner, user's time for eating meals can be shortened, avoids user for a long time
It waits, especially for the user that the time is more nervous, user can not only be allowed to have dinner within the limited time, additionally it is possible to avoid
It is excessive to occupy user time, the user experience is improved.
Fig. 3 shows the structural schematic diagram of shop recommendation apparatus according to an embodiment of the invention.As shown in figure 3, should
Device includes: to obtain module 300, processing module 310, prediction module 320, recommending module 330.
Module 300 is obtained, is suitable for obtaining the trip side of customer position information and user's selection according to shop recommended requirements
Formula information.
Processing module 310 is suitable for according to customer position information and trip mode information, and screening obtains at least one candidate
Shop, assessment for each candidate shop user to the shop time.
Prediction module 320 is suitable for for each candidate shop, according to user to the service in the shop time prediction candidate shop
Data.
Recommending module 330, suitable for carrying out shop recommendation according to the service data in each candidate shop.
Optionally, prediction module 320 is further adapted for: same according to user to shop time, the current people information in shop, history
The service data in candidate shop when phase stream of people's tendency information and/or the velocity information prediction user that currently serves reach shop.
Optionally, service data includes: equipotential time data and/or time data of serving.
Optionally, customer position information includes: user current location information；
Processing module 310 is further adapted for: being worked as according to user current location information and trip mode information sifting in user
At least one candidate shop in the information preset range of front position.
Optionally, customer position information includes: user current location information and destination locations information；
Processing module 310 is further adapted for: the candidate shop of at least one of screening in destination locations information preset range
Paving.
Optionally, processing module 310 is further adapted for: according to store location information, user current location information, trip side
Formula information and traffic information assessment for each candidate shop user to the shop time.
Optionally, processing module 310 is further adapted for: according to shop basic score, screening obtain shop basic score be greater than or
Equal at least one candidate shop of preset threshold.
Optionally, recommending module 330 is further adapted for: being ranked up according to service data at least one candidate shop；
According to ranking results, generates the shop comprising service data and recommend the page.
The device provided according to that above embodiment of the present invention, according to shop recommended requirements, obtain customer position information and
The trip mode information of user's selection；According to customer position information and trip mode information, screening obtains at least one candidate
Shop, assessment for each candidate shop user to the shop time；For each candidate shop, according to user to shop time prediction
The service data in the candidate shop；Shop recommendation is carried out according to the service data in each candidate shop.Based on provided by the invention
Scheme can shorten user's time for eating meals, user is avoided to fall into a long wait, especially when user selects the shop recommended to have dinner
It is the user more nervous for the time, user can not only be allowed to have dinner within the limited time, additionally it is possible to avoid excessively occupying
User time, the user experience is improved.
The embodiment of the present application also provides a kind of nonvolatile computer storage media, the computer storage medium storage
There is an at least executable instruction, which can be performed the shop recommendation side in above-mentioned any means embodiment
Method.
Fig. 4 shows the structural schematic diagram according to an embodiment of the invention for calculating equipment, the specific embodiment of the invention
The specific implementation for calculating equipment is not limited.
As shown in figure 4, the calculating equipment may include: processor (processor) 402, communication interface
(Communications Interface) 404, memory (memory) 406 and communication bus 408.
Wherein:
Processor 402, communication interface 404 and memory 406 complete mutual communication by communication bus 408.
Communication interface 404, for being communicated with the network element of other equipment such as client or other servers etc..
Processor 402 can specifically execute the correlation in above-mentioned shop recommended method embodiment for executing program 410
Step.
Specifically, program 410 may include program code, which includes computer operation instruction.
Processor 402 may be central processor CPU or specific integrated circuit ASIC (Application
Specific Integrated Circuit), or be arranged to implement the integrated electricity of one or more of the embodiment of the present invention
Road.The one or more processors that equipment includes are calculated, can be same type of processor, such as one or more CPU；It can also
To be different types of processor, such as one or more CPU and one or more ASIC.
Memory 406, for storing program 410.Memory 406 may include high speed RAM memory, it is also possible to further include
Nonvolatile memory (non-volatile memory), for example, at least a magnetic disk storage.
Program 410 specifically can be used for so that processor 402 executes the shop recommendation side in above-mentioned any means embodiment
Method.The specific implementation of each step may refer to right in corresponding steps and unit in above-mentioned shop preferred embodiment in program 410
The description answered, this will not be repeated here.It is apparent to those skilled in the art that for convenience and simplicity of description, on
The equipment of description and the specific work process of module are stated, can refer to corresponding processes in the foregoing method embodiment description, herein
It repeats no more.
Algorithm and display are not inherently related to any particular computer, virtual system, or other device provided herein.
Various general-purpose systems can also be used together with teachings based herein.As described above, it constructs required by this kind of system
Structure be obvious.In addition, the present invention is also not directed to any particular programming language.It should be understood that can use various
Programming language realizes summary of the invention described herein, and the description done above to language-specific is to disclose this hair
Bright preferred forms.
In the instructions provided here, numerous specific details are set forth.It is to be appreciated, however, that implementation of the invention
Example can be practiced without these specific details.In some instances, well known method, structure is not been shown in detail
And technology, so as not to obscure the understanding of this specification.
Similarly, it should be understood that in order to simplify the disclosure and help to understand one or more of the various inventive aspects,
Above in the description of exemplary embodiment of the present invention, each feature of the invention is grouped together into single implementation sometimes
In example, figure or descriptions thereof.However, the disclosed method should not be interpreted as reflecting the following intention: i.e. required to protect
Shield the present invention claims features more more than feature expressly recited in each claim.More precisely, as following
Claims reflect as, inventive aspect is all features less than single embodiment disclosed above.Therefore,
Thus the claims for following specific embodiment are expressly incorporated in the specific embodiment, wherein each claim itself
All as a separate embodiment of the present invention.
Those skilled in the art will understand that can be carried out adaptively to the module in the equipment in embodiment
Change and they are arranged in one or more devices different from this embodiment.It can be the module or list in embodiment
Member or component are combined into a module or unit or component, and furthermore they can be divided into multiple submodule or subelement or
Sub-component.Other than such feature and/or at least some of process or unit exclude each other, it can use any
Combination is to all features disclosed in this specification (including adjoint claim, abstract and attached drawing) and so disclosed
All process or units of what method or apparatus are combined.Unless expressly stated otherwise, this specification is (including adjoint power
Benefit require, abstract and attached drawing) disclosed in each feature can carry out generation with an alternative feature that provides the same, equivalent, or similar purpose
It replaces.
In addition, it will be appreciated by those of skill in the art that although some embodiments described herein include other embodiments
In included certain features rather than other feature, but the combination of the feature of different embodiments mean it is of the invention
Within the scope of and form different embodiments.For example, in the following claims, embodiment claimed is appointed
Meaning one of can in any combination mode come using.
Various component embodiments of the invention can be implemented in hardware, or to run on one or more processors
Software module realize, or be implemented in a combination thereof.It will be understood by those of skill in the art that can be used in practice
Microprocessor or digital signal processor (DSP) come realize some in shop recommendation apparatus according to an embodiment of the present invention or
The some or all functions of person's whole component.The present invention is also implemented as one for executing method as described herein
Point or whole device or device programs (for example, computer program and computer program product).Such this hair of realization
Bright program can store on a computer-readable medium, or may be in the form of one or more signals.It is such
Signal can be downloaded from an internet website to obtain, and is perhaps provided on the carrier signal or is provided in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and ability
Field technique personnel can be designed alternative embodiment without departing from the scope of the appended claims.In the claims,
Any reference symbol between parentheses should not be configured to limitations on claims.Word "comprising" does not exclude the presence of not
Element or step listed in the claims.Word "a" or "an" located in front of the element does not exclude the presence of multiple such
Element.The present invention can be by means of including the hardware of several different elements and being come by means of properly programmed computer real
It is existing.In the unit claims listing several devices, several in these devices can be through the same hardware branch
To embody.The use of word first, second, and third does not indicate any sequence.These words can be explained and be run after fame
Claim.
Claims (10)
1. a kind of shop recommended method, comprising:
According to shop recommended requirements, the trip mode information of customer position information and user's selection is obtained；
According to the customer position information and the trip mode information, screening obtains at least one candidate shop, assesses needle
To the user in each candidate shop to shop time；
For each candidate shop, according to user to the service data in the shop time prediction candidate shop；
Shop recommendation is carried out according to the service data in each candidate shop.
2. described according to user to the service number in the shop time prediction candidate shop according to the method described in claim 1, wherein
According to further comprising:
According to user to shop time, the current people information in shop, history same period stream of people tendency information and/or current speed letter of serving
The service data in candidate shop when breath prediction user reaches shop.
3. method according to claim 1 or 2, wherein the service data includes: equipotential time data and/or serves
Time data.
4. method according to any one of claim 1-3, wherein the customer position information includes: user's present bit
Confidence breath；
It is described according to customer position information and the trip mode information, screening obtains at least one candidate shop and further wraps
It includes:
According to user current location information and the trip mode information sifting in user current location information preset range
At least one candidate shop.
5. method according to any one of claim 1-3, wherein the customer position information includes: user's present bit
Confidence breath and destination locations information；
It is described according to the customer position information and the trip mode information, screening obtains at least one candidate shop into one
Step includes:
The candidate shop of at least one of screening in destination locations information preset range.
6. method according to claim 4 or 5, wherein the assessment for each candidate shop user to the shop time
Further comprise:
Each time is directed to according to the assessment of store location information, user current location information, trip mode information and traffic information
Select the user in shop to the shop time.
7. method according to claim 1 to 6, wherein assessment for each candidate shop user to shop
Before time, the method also includes:
According to shop basic score, screening obtains at least one the candidate shop of shop basic score more than or equal to preset threshold
Paving.
8. a kind of shop recommendation apparatus, comprising:
Module is obtained, is suitable for obtaining the trip mode information of customer position information and user's selection according to shop recommended requirements；
Processing module is suitable for according to the customer position information and the trip mode information, and screening obtains at least one time
Select shop, assessment for each candidate shop user to the shop time；
Prediction module is suitable for for each candidate shop, according to user to the service data in the shop time prediction candidate shop；
Recommending module, suitable for carrying out shop recommendation according to the service data in each candidate shop.
9. a kind of calculating equipment, comprising: processor, memory, communication interface and communication bus, the processor, the storage
Device and the communication interface complete mutual communication by the communication bus；
The memory executes the processor as right is wanted for storing an at least executable instruction, the executable instruction
Ask recommended method corresponding operation in shop described in any one of 1-7.
10. a kind of computer storage medium, an at least executable instruction, the executable instruction are stored in the storage medium
Processor is set to execute such as the corresponding operation of shop recommended method of any of claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811207199.XA CN109471984A (en) | 2018-10-17 | 2018-10-17 | Shop recommended method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811207199.XA CN109471984A (en) | 2018-10-17 | 2018-10-17 | Shop recommended method and device |
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| CN109471984A true CN109471984A (en) | 2019-03-15 |
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| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811207199.XA Pending CN109471984A (en) | 2018-10-17 | 2018-10-17 | Shop recommended method and device |
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| CN110490650A (en) * | 2019-08-14 | 2019-11-22 | 浙江大搜车软件技术有限公司 | Merchant information processing method, device, computer equipment and storage medium |
| CN110909100A (en) * | 2019-11-20 | 2020-03-24 | 口口相传(北京)网络技术有限公司 | Shop display method and device based on walking distance |
| CN111311317A (en) * | 2020-02-06 | 2020-06-19 | 大众问问(北京)信息科技有限公司 | Information recommendation method, device, equipment and system |
| CN111861139A (en) * | 2020-06-28 | 2020-10-30 | 深圳壹账通智能科技有限公司 | Merchant recommendation method and device and computer equipment |
| CN112507240A (en) * | 2020-12-30 | 2021-03-16 | 福建诺诚数字科技有限公司 | Merchant information acquisition method and system based on position information and travel mode |
| CN113868532A (en) * | 2021-09-30 | 2021-12-31 | 北京百度网讯科技有限公司 | Location recommendation method and device, electronic equipment and storage medium |
| CN113886722A (en) * | 2021-12-08 | 2022-01-04 | 环球数科集团有限公司 | Travel food recommendation method and device and computer equipment |
| CN116664255A (en) * | 2023-08-01 | 2023-08-29 | 成都豪杰特科技有限公司 | Store recommendation method and system based on artificial intelligence |
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| CN110490650A (en) * | 2019-08-14 | 2019-11-22 | 浙江大搜车软件技术有限公司 | Merchant information processing method, device, computer equipment and storage medium |
| CN110909100A (en) * | 2019-11-20 | 2020-03-24 | 口口相传(北京)网络技术有限公司 | Shop display method and device based on walking distance |
| CN110909100B (en) * | 2019-11-20 | 2021-07-20 | 口口相传(北京)网络技术有限公司 | Shop display method and device based on walking distance |
| CN111311317A (en) * | 2020-02-06 | 2020-06-19 | 大众问问(北京)信息科技有限公司 | Information recommendation method, device, equipment and system |
| CN111861139A (en) * | 2020-06-28 | 2020-10-30 | 深圳壹账通智能科技有限公司 | Merchant recommendation method and device and computer equipment |
| CN112507240A (en) * | 2020-12-30 | 2021-03-16 | 福建诺诚数字科技有限公司 | Merchant information acquisition method and system based on position information and travel mode |
| CN113868532A (en) * | 2021-09-30 | 2021-12-31 | 北京百度网讯科技有限公司 | Location recommendation method and device, electronic equipment and storage medium |
| CN113886722A (en) * | 2021-12-08 | 2022-01-04 | 环球数科集团有限公司 | Travel food recommendation method and device and computer equipment |
| CN113886722B (en) * | 2021-12-08 | 2022-03-04 | 环球数科集团有限公司 | Travel food recommendation method and device and computer equipment |
| CN116664255A (en) * | 2023-08-01 | 2023-08-29 | 成都豪杰特科技有限公司 | Store recommendation method and system based on artificial intelligence |
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