CN108229748A - For the matching process, device and electronic equipment of rideshare service - Google Patents
For the matching process, device and electronic equipment of rideshare service Download PDFInfo
- Publication number
- CN108229748A CN108229748A CN201810039558.9A CN201810039558A CN108229748A CN 108229748 A CN108229748 A CN 108229748A CN 201810039558 A CN201810039558 A CN 201810039558A CN 108229748 A CN108229748 A CN 108229748A
- Authority
- CN
- China
- Prior art keywords
- interest
- service
- service requester
- target group
- target
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 43
- 230000008569 process Effects 0.000 title claims abstract description 25
- 230000006399 behavior Effects 0.000 claims description 15
- 238000004590 computer program Methods 0.000 claims description 6
- 230000000875 corresponding effect Effects 0.000 description 45
- 238000010586 diagram Methods 0.000 description 7
- 230000008859 change Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 238000011161 development Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 239000000835 fiber Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 241000208340 Araliaceae Species 0.000 description 1
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 1
- 235000003140 Panax quinquefolius Nutrition 0.000 description 1
- 244000124853 Perilla frutescens Species 0.000 description 1
- 235000004348 Perilla frutescens Nutrition 0.000 description 1
- 206010053615 Thermal burn Diseases 0.000 description 1
- 230000009471 action Effects 0.000 description 1
- 230000006978 adaptation Effects 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 235000021168 barbecue Nutrition 0.000 description 1
- 230000003542 behavioural effect Effects 0.000 description 1
- 238000007796 conventional method Methods 0.000 description 1
- 230000002596 correlated effect Effects 0.000 description 1
- 235000021185 dessert Nutrition 0.000 description 1
- 235000013399 edible fruits Nutrition 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 235000008434 ginseng Nutrition 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 239000011435 rock Substances 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 235000011888 snacks Nutrition 0.000 description 1
Classifications
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
- G06Q10/047—Optimisation of routes or paths, e.g. travelling salesman problem
-
- 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/40—Business processes related to the transportation industry
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Marketing (AREA)
- General Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- Game Theory and Decision Science (AREA)
- Quality & Reliability (AREA)
- Operations Research (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application provides a kind of matching process, device and electronic equipment for rideshare service, and a specific embodiment of the method includes：Target group is determined based on the multiple rideshare service requests received, and the target group includes the corresponding service requester of the part rideshare service request；Obtain the similar parameter of service requester in target group interest between any two；The service requester for determining to match in the target group according to the similar parameter.The embodiment can match the close service requester of interest, so as to improve the matched reasonability of service requester, not only promote the raising of efficiency of service, can also improve the utilization rate of Service Source during rideshare service is provided.
Description
Technical field
This application involves technical field of internet application, more particularly to a kind of matching process, device for rideshare service
And electronic equipment.
Background technology
With the continuous development of Internet technology, there is new O2O (Online To Offline, online offline/line
On under line) business model, internet is made to become the platform of off-line transaction.At present, the O2O services of the vehicles are the ratios of development
More successful O2O services.By taking net about vehicle service as an example, at present, there is the about vehicle service of some type of net that can provide rideshare service.
When providing rideshare service, need to match two or more with the passenger multiplied, it therefore, can if passenger's matching is unreasonable
It can lead to problems, so as to not only reduce efficiency of service, also reduce the utilization rate of Service Source.
Invention content
In order to solve the above-mentioned technical problem one of, the application provide it is a kind of for the matching process of rideshare service, device and
Electronic equipment.
According to the embodiment of the present application in a first aspect, provide a kind of matching process for rideshare service, including：
Target group is determined based on the multiple rideshare service requests received, and the target group includes the part rideshare service
Ask corresponding service requester；
Obtain the similar parameter of service requester in target group interest between any two；
The service requester for determining to match in the target group according to the similar parameter.
Optionally, the similar parameter of the service requester obtained in the target group interest between any two, including：
Determine one or more target interest types；
Obtain the interest characteristics vector that each service requester is directed to each target interest types；
The similar parameter of service requester interest between any two is obtained based on the interest characteristics vector.
Optionally, determining one or more target interest types, including：
Obtain the liveness that each service requester is directed to each preset alternative interest types；
The target interest types are chosen from the alternative interest types based on the liveness.
Optionally, the liveness is based on the corresponding user behavior data acquisition of each service requester.
Optionally, it is described obtain each service requester be directed to the interest characteristics of each target interest types to
Amount, including：
Obtain the corresponding user behavior data of each service requester；
The user behavior data is parsed using preset topic model, obtains objective result, the objective result includes
Each service requester is directed to each multiple interest tags of the target interest types and the weight of each interest tags；
The interest characteristics vector is generated based on the objective result.
Optionally, the similar ginseng that service requester interest between any two is obtained based on the interest characteristics vector
Number, including：
The service requester is calculated between any two for each target interest kind based on the interest characteristics vector
The Euclidean distance of class；
The interest similar parameter of the service requester between any two is obtained based on the Euclidean distance.
Optionally, it is described to determine target group based on the multiple rideshare service requests received, including：
Obtain start of a run and the stroke end that each rideshare service request carries；
The target group is determined based on the start of a run and stroke end.
According to the second aspect of the embodiment of the present application, a kind of coalignment for rideshare service is provided, including：
First determining module, for determining target group, the target group packet based on the multiple rideshare service requests received
Include the corresponding service requester of the part rideshare service request；
Acquisition module, for obtaining the similar parameter of the interest between any two of the service requester in the target group；
Second determining module, for the service requester for determining to match in the target group according to the similar parameter.
According to the third aspect of the embodiment of the present application, a kind of computer readable storage medium is provided, the storage medium is deposited
Computer program is contained, the computer program is realized when being executed by processor to be used for described in any one of above-mentioned first aspect
The matching process of rideshare service.
According to the fourth aspect of the embodiment of the present application, a kind of electronic equipment is provided, including memory, processor and is stored in
On memory and the computer program that can run on a processor, the processor realize above-mentioned first party when performing described program
The matching process for rideshare service described in any one of face.
The technical solution that embodiments herein provides can include the following benefits：
The matching process and device for rideshare service that embodiments herein provides, by multiple based on what is received
Rideshare service request determines target group, which includes the corresponding service requester of part rideshare service request, obtains target
The similar parameter of service requester in group interest between any two, and the clothes for determining to match in target group according to the similar parameter
Be engaged in requesting party.So as to which during rideshare service is provided, the close service requester of interest can be matched, so as to improve
The matched reasonability of service requester, not only promotes the raising of efficiency of service, can also improve the utilization rate of Service Source.
It should be understood that above general description and following detailed description are only exemplary and explanatory, not
The application can be limited.
Description of the drawings
Attached drawing herein is incorporated into specification and forms the part of this specification, shows the implementation for meeting the application
Example, and for explaining the principle of the application together with specification.
Fig. 1 is the exemplary system architecture schematic diagram using the embodiment of the present application；
Fig. 2 is a kind of flow of matching process for rideshare service of the application according to an exemplary embodiment
Figure；
Fig. 3 is flow of another kind of the application according to an exemplary embodiment for the matching process of rideshare service
Figure；
Fig. 4 is flow of another kind of the application according to an exemplary embodiment for the matching process of rideshare service
Figure；
Fig. 5 is a kind of block diagram of coalignment for rideshare service of the application according to an exemplary embodiment；
Fig. 6 is frame of another kind of the application according to an exemplary embodiment for the coalignment of rideshare service
Figure；
Fig. 7 is the structure diagram of a kind of electronic equipment of the application according to an exemplary embodiment.
Specific embodiment
Here exemplary embodiment will be illustrated in detail, example is illustrated in the accompanying drawings.Following description is related to
During attached drawing, unless otherwise indicated, the same numbers in different attached drawings represent the same or similar element.Following exemplary embodiment
Described in embodiment do not represent all embodiments consistent with the application.On the contrary, they be only with it is such as appended
The example of the consistent device and method of some aspects be described in detail in claims, the application.
It is only merely for the purpose of description specific embodiment in term used in this application, and is not intended to be limiting the application.
It is also intended in the application and " one kind " of singulative used in the attached claims, " described " and "the" including majority
Form, unless context clearly shows that other meanings.It is also understood that term "and/or" used herein refers to and wraps
Containing one or more associated list items purposes, any or all may be combined.
It will be appreciated that though various information, but this may be described using term first, second, third, etc. in the application
A little information should not necessarily be limited by these terms.These terms are only used for same type of information being distinguished from each other out.For example, not departing from
In the case of the application range, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as
One information.Depending on linguistic context, word as used in this " if " can be construed to " ... when " or " when ...
When " or " in response to determining ".
Referring to Fig. 1, the exemplary system architecture schematic diagram for application the embodiment of the present application：
As shown in Figure 1, system architecture 100 can include 101,102,103,104 network 105 of terminal device and server
106.It should be understood that the number or type of the terminal device, network and server in Fig. 1 are only schematical.According to realization
It needs, can have arbitrary number or terminal device, network and the server of type.
Network 105 is used to provide the medium of communication link between terminal device, server.Network 105 can include each
Kind connection type, such as wired, wireless communication link or fiber optic cables etc..
Terminal device 101,102,103,104 can be interacted by network 105 with server, be asked with receiving or sending
It asks or information etc..Terminal device 101,102,103,104 can be various electronic equipments, including but not limited to smart mobile phone, flat
Plate computer, intelligent wearable device and personal digital assistant etc..
Server 106 can be to provide the server of various services.Server can store the data received,
The processing such as analysis can also send control command or request etc. to terminal device or other servers.Server can respond
Service is provided in the service request of user.It is appreciated that a server can provide one or more services, same clothes
Business can also be provided by multiple servers.
The application is described in detail below in conjunction with specific embodiments.
As shown in Fig. 2, Fig. 2 is the stream according to a kind of matching process for rideshare service shown in an exemplary embodiment
Cheng Tu, this method can be applied in server.This method includes the following steps：
In step 201, target group is determined based on the multiple rideshare service requests received, which is included on part
State the corresponding service requester of rideshare service request.
In the present embodiment, involved service can be the rideshare service of the vehicles, for example, the rideshare clothes of net about vehicle
Business etc..The corresponding service requester of rideshare service request can be the passenger for asking rideshare service, can be in rideshare service request
Carry the information such as start of a run, stroke end and passenger ID.It, can be first when server receives multiple rideshare service requests
First determine target group.Wherein, which can include the corresponding service requester of part rideshare service request.
Specifically, in one implementation, the start of a run that each rideshare service request carries can be obtained first.
Then, the corresponding service requester of rideshare service request is grouped according to the position of start of a run, to obtain target group, made
The mutual position relationship of the corresponding start of a run of service requester in same target group meets preset rules.
In another implementation, start of a run and the stroke end that each rideshare service request carries can also be obtained
Point.Then, target group is determined based on the trip starting point and stroke end, makes the corresponding row of service requester in same target group
Position relationship mutual Cheng Qidian meets preset start position rule, and the service requester in same target group is corresponding
The mutual position relationship in stroke end meets preset final position rule.
It is appreciated that target group can also be determined by other arbitrary reasonable manners, the application is to determining target group
It is not limited in terms of concrete mode.
In step 202, the similar parameter of the service requester interest between any two in target group is obtained.
In the present embodiment, the similar parameter of service requester in target group interest between any two can be obtained.Wherein,
The similar parameter of interest can be that can arbitrarily measure interest between the two service requesters between two service requesters
The parameter of degree of approximation, the similar parameter can be with the degree of approximation positive correlations of interest, i.e. the similar parameter is bigger, interest it is near
It is bigger (for example, the similar parameter can be similarity etc.) like degree.The similar parameter can also be born with the approximate degree of interest
Correlation, the i.e. similar parameter are bigger, the degree of approximation of interest it is smaller (for example, the similar parameter can be Euclidean distance, geneva away from
From or Minkowski Distance etc.).
Specifically, in one implementation, it is possible, firstly, to determine one or more target interest types.Then, it obtains
Interest characteristics vector of each service requester in target group for each target interest types is taken, and based on above-mentioned each clothes
It is engaged in interest characteristics vector of the requesting party for each target interest types, obtains service requester interest between any two in target group
Similar parameter.
In another implementation, the corresponding user's portrait of each service requester in target group can also be obtained, by
It can reflect the interest of service requester to a certain extent in user's portrait.It is consequently possible to calculate service requester two-by-two it
Between similar parameter of the similarity as interest drawn a portrait of user.
It it is appreciated that can also be by the service requester in other arbitrary reasonable manners acquisition target groups between any two
The similar parameter of interest, the application to not limiting in this respect.
In step 203, the service requester to match in target group is determined according to the similar parameter.
In the present embodiment, can mesh be determined according to the similar parameter of the interest between any two of the service requester in target group
The service requester to match in mark group.Specifically, for any pair of service requester in target group, if according to emerging
The similar parameter of interest determines that the similarity degree of the interest to service requester is more than preset similarity degree, then can determine this
Match to service requester.
In one implementation, if the degree of approximation positive correlation of the similar parameter of interest and interest, for target group
In any pair of service requester, if the similar parameter of the interest to service requester be greater than or equal to predetermined threshold value,
It is the service requester to match to service requester that can then determine this.
In another implementation, if the degree of approximation of the similar parameter of interest and interest is negatively correlated, for target
Any pair of service requester in group, if the similar parameter of the interest to service requester is less than or equal to default threshold
Value, then it is the service requester to match to service requester that can determine this.
The matching process for rideshare service that above-described embodiment of the application provides, by based on the multiple conjunctions received
Multiply service request and determine target group, which includes the corresponding service requester of part rideshare service request, obtains target group
In service requester interest between any two similar parameter, and the service for determining to match in target group according to the similar parameter
Requesting party.So as to which during rideshare service is provided, the close service requester of interest can be matched, so as to improve clothes
The business matched reasonability of requesting party, not only promotes the raising of efficiency of service, can also improve the utilization rate of Service Source.
As shown in figure 3, stream of another kinds of the Fig. 3 according to an exemplary embodiment for the matching process of rideshare service
Cheng Tu, This embodiment describes the process of the service requester similar parameter of interest between any two obtained in target group, the party
Method can be applied in server, include the following steps：
In step 301, target group is determined based on the multiple rideshare service requests received, which includes part and close
Multiply the corresponding service requester of service request.
In step 302, one or more target interest types are determined.
In the present embodiment, one or more interest types can be preset, for example, the interest types can include but
Cuisines are not limited to, video display are performed, travelling, music, sports, amusement etc..Then, in one implementation, can incite somebody to action
Preset whole interest types are determined as target interest types.In another implementation, it can also will preset
Interest types alternately interest types, target interest types are chosen from alternative interest types.
Specifically, target interest types can be chosen from alternative interest types in the following way：It is possible, firstly, to it obtains
Take the corresponding user behavior data of each service requester in target group.User behavior data can include but is not limited to user's
Search behavior data, navigation patterns data, trading activity data, collection data behavioral data etc..
Then, the corresponding user behavior data of each service requester can be based on and obtains each service requester for every
The liveness of the preset alternative interest types of kind.For any service requester, the data in terms of some target interest types
It is abundanter, then it is higher for the liveness of the target interest types.
Finally, the liveness of each preset alternative interest types can be directed to based on each service requester, from alternative
One or more target interest types are chosen in interest types.It is directed to for example, all service requesters in target group can be calculated
The sum of liveness of each preset alternative interest types, the alternative interest types that the sum of liveness is more than to predetermined threshold value determine
For target interest types.Alternatively, can also be according to the sequence of the sum of liveness from big to small, the alternative interest of predetermined number before taking
Type is as target interest types.
In step 303, each service requester obtained in target group is special for the interest of each target interest types
Sign vector.
In the present embodiment, it is possible, firstly, to obtain the corresponding user behavior data of each service requester in target group.
Then, preset topic model may be used and parse the user behavior data, obtain objective result.Optionally, the preset master
LDA (Latent Dirichlet Allocation, potential Di Li Crays distribution) topic model may be used in topic model.Gained
To objective result can include target group in each service requester be directed to each target interest types multiple interest marks
The weight of label and each interest tags.Wherein, can be in the target interest types for the interest tags of target interest types
Under interest branch.For example, if target interest types are cuisines, fiber crops are can include but is not limited to for the interest tags of cuisines
It is peppery to scald, chafing dish, barbecue, river Hunan cuisine, beefsteak, snack, dessert etc..In another example if target interest types are music, for sound
Happy interest tags can include but is not limited to classics, classic, rock and roll, folk rhyme, light music, jazz, campus etc..Interest tags
Weight can characterize fancy grade of the service requester to corresponding interest tags, weight is bigger to illustrate service requester to phase
The fancy grade for the interest tags answered is bigger.
It is then possible to based on objective result generation interest characteristics vector, for each service requester, can be directed to every
A target interest types generate a corresponding interest characteristics vector.If there are N number of target interest types, N number of phase can be generated
The interest characteristics vector answered.It specifically, can be by the interest tags under the target interest types for either objective interest types
As the base of interest characteristics vector, using the weight of interest tags as the coordinate of interest characteristics vector, so as to generate interest characteristics
Vector.
In step 304, the similar parameter of service requester interest between any two is obtained based on above-mentioned interest characteristics vector.
In the present embodiment, can the similar of service requester interest between any two be obtained based on above-mentioned interest characteristics vector
Parameter.In one implementation, the corresponding interest characteristics vector of above-mentioned each target interest types can be based on, calculates service
Requesting party is directed to the Euclidean distance of each target interest types between any two.Then, it for any pair of service requester, acquires
The average value or weighted average of the corresponding Euclidean distance of all target interest types, it is corresponding to service requester as this
The similar parameter of interest.
In another implementation, the corresponding interest characteristics vector of above-mentioned each target interest types is also based on,
Calculate the similarity that service requester is directed to each target interest types between any two.Then, for any pair of service request
The average value or weighted average of the corresponding similarity of all target interest types acquire, as this to service requester in side
The similar parameter of corresponding interest.
It is appreciated that the similar of service requesters interest between any two can also be obtained by other arbitrary reasonable manners
Parameter, the application to not limiting in this respect.
In step 305, the service requester to match in target group is determined according to the similar parameter.
It should be noted that for the step identical with Fig. 2 embodiments, no longer go to live in the household of one's in-laws on getting married in above-mentioned Fig. 3 embodiments
It states, related content can be found in Fig. 2 embodiments.
Although should be noted that in the embodiment of above-mentioned Fig. 3, the operation of the application method is described with particular order,
It is that this, which does not require that or implies, to perform these operations according to the particular order or have to carry out shown in whole
Operation could realize desired result.On the contrary, the step of describing in flow chart, which can change, performs sequence.For example, it can first hold
Row step 301 determines target group based on the multiple rideshare service requests received, then performs step 302 again, determine one or
Multiple target interest types.Step 302 can also be first carried out, then performs step 301, step 301 and step can also be performed simultaneously
Rapid 302.Additionally or alternatively, it is convenient to omit multiple steps are merged into step and performed and/or by one by certain steps
A step is decomposed into execution of multiple steps.
The matching process for rideshare service that above-described embodiment of the application provides, based on the multiple rideshares clothes received
Business request determines target group, which includes the corresponding service requester of part rideshare service request, determines one or more
Target interest types obtain interest characteristics vector of each service requester in target group for each target interest types,
The similar parameter of service requester interest between any two is obtained based on above-mentioned interest characteristics vector, and is determined according to the similar parameter
The service requester to match in target group.Therefore, the matched reasonability of service requester is further improved, and helps to carry
The utilization rate of high efficiency of service and Service Source.
As shown in figure 4, another kinds of the Fig. 4 according to an exemplary embodiment is used for the matched method stream of rideshare service
The process of determining target group is described in detail in Cheng Tu, the embodiment, and this method can be applied in server, including following step
Suddenly：
In step 401, start of a run and the stroke end that each rideshare service request received carries are obtained.
In step 402, target group is determined based on above-mentioned start of a run and stroke end, which includes part rideshare
The corresponding service requester of service request.
In one implementation, may be used preset clustering algorithm respectively to above-mentioned start of a run and stroke end into
Row cluster obtains starting point cluster set and terminal cluster set.So that start of a run in starting point cluster set is mutual
Apart from sufficiently small.Terminal cluster set in stroke end it is mutual distance it is sufficiently small.Then, it is clustered according to above-mentioned starting point
Set and terminal cluster set determine target group, the corresponding start of a run of all service requesters are made in target group to correspond to identical
Starting point cluster set, the corresponding stroke end of all service requesters corresponds to identical terminal cluster set in target group.
Target group is determined using aforesaid way, the corresponding starting point of all service requesters in target group can be made as close possible to eventually
Point is also as close possible to so as to reduce the unreasonable probability of service requester matching.
In another implementation, road network can also be in advance based on and the region division for providing rideshare service is gone out into multiple sons
Then region, determines target group according to above-mentioned subregion and above-mentioned start of a run and stroke end, makes all clothes in target group
The corresponding start of a run of business requesting party corresponds to identical subregion, the corresponding stroke end of all service requesters in target group
Also identical subregion is corresponded to.Target group is determined using aforesaid way, all service requesters in target group can be made corresponding
Starting point as close possible to and positioned at identical subregion, terminal is also as close possible to and positioned at identical subregion.So as to avoid conjunction
During multiplying service, when welcoming the emperor and being sent to, due to rideshare service requester is located at different subregions and caused by detour, into
One step improves the matched reasonability of service requester.
It is appreciated that target group can also be determined by other arbitrary reasonable manners, the application to not limiting in this respect.
In step 403, the similar parameter of the service requester interest between any two in target group is obtained.
In step 404, the service requester to match in target group is determined according to the similar parameter.
It should be noted that for the step identical with Fig. 2 and Fig. 3 embodiments, in above-mentioned Fig. 4 embodiments no longer into
Row repeats, and related content can be found in Fig. 2 and Fig. 3 embodiments.
The matching process for rideshare service that above-described embodiment of the application provides, by obtaining each conjunction received
Multiply the corresponding start of a run of service request and stroke end, target group is determined based on above-mentioned start of a run and stroke end, the mesh
Mark group includes the corresponding service requester of part rideshare service request, obtains the service requester interest between any two in target group
Similar parameter, and the service requester for determining to match in target group according to the similar parameter.Since the present embodiment is based on often
The corresponding start of a run of a rideshare service request and stroke end are tentatively grouped corresponding service requester, so as to
The more accurate preliminary screening more matched service requester of outbound path, and it is emerging between any two to be based further on service requester
The similar parameter of interest determines the service requester to match in target group.It is matched rationally that service requester can be further improved
Property, so as to further improve the utilization rate of efficiency of service and Service Source.
Corresponding with the matching process embodiment for being previously used for rideshare service, present invention also provides for rideshare service
The embodiment of coalignment.
It is filled as shown in figure 5, Fig. 5 is a kind of matching for rideshare service of the application according to an exemplary embodiment
Block diagram is put, which can include：First determining module 501,502 and second determining module 503 of acquisition module.
Wherein, the first determining module 501, for determining target group based on the multiple rideshare service requests received, the mesh
Mark group includes the corresponding service requester of part rideshare service request.
Acquisition module 502, for obtaining the similar parameter of the interest between any two of the service requester in target group.
Second determining module 503, for the service requester for determining to match in target group according to above-mentioned similar parameter.
As shown in fig. 6, Fig. 6 is the matching that another kind of the application according to an exemplary embodiment is used for rideshare service
Device block diagram, on the basis of aforementioned embodiment illustrated in fig. 5, acquisition module 502 can include the embodiment：Determination sub-module
601, the first acquisition submodule 602 and the second acquisition submodule 603.
Wherein it is determined that submodule 601, for determining one or more target interest types.
First acquisition submodule 602, it is special for the interest of each target interest types for obtaining each service requester
Sign vector.
Second acquisition submodule 603 obtains service requester interest between any two for being based on above-mentioned interest characteristics vector
Similar parameter.
In some optional embodiments, determination sub-module 601 is configured for：Each service requester is obtained for every
The liveness of the preset alternative interest types of kind, target interest types are chosen based on above-mentioned liveness from alternative interest types.
In other optional embodiments, above-mentioned liveness is based on the corresponding user behavior data of each service requester
It obtains.
In other optional embodiments, the first acquisition submodule 602 is configured for：Obtain each service requester
Corresponding user behavior data using the above-mentioned user behavior data of preset themes model analyzing, obtains objective result.The target knot
Fruit includes each service requester for multiple interest tags of each target interest types and the weight of each interest tags, base
Above-mentioned interest characteristics vector is generated in objective result.
In other optional embodiments, the second acquisition submodule 603 is configured for：Based on above-mentioned interest characteristics to
Amount calculates the Euclidean distance that service requester is directed to each target interest types between any two, and is obtained based on above-mentioned Euclidean distance
The interest similar parameter of service requester between any two.
In other optional embodiments, the first determining module 501 is configured for：Obtain each rideshare service request
The start of a run of carrying and stroke end, and target group is determined based on the trip starting point and stroke end.
It should be appreciated that above device can be pre-set in the server, can also be loaded by the modes such as downloading
In server.Corresponding module in above device can cooperate to realize for rideshare service with the module in server
Matching scheme.
For device embodiment, since it corresponds essentially to embodiment of the method, so related part is referring to method reality
Apply the part explanation of example.The apparatus embodiments described above are merely exemplary, wherein described be used as separating component
The unit of explanation may or may not be physically separate, and the component shown as unit can be or can also
It is not physical unit, you can be located at a place or can also be distributed in multiple network element.It can be according to reality
It needs that some or all of module therein is selected to realize the purpose of application scheme.Those of ordinary skill in the art are not paying
In the case of going out creative work, you can to understand and implement.
The embodiment of the present application additionally provides a kind of computer readable storage medium, which is stored with computer journey
Sequence, computer program can be used for performing the matching process for rideshare service that above-mentioned Fig. 2 is provided to Fig. 4 any embodiments.
Corresponding to the above-mentioned matching process for rideshare service, the embodiment of the present application also proposed basis shown in Fig. 7
The schematic configuration diagram of the electronic equipment of the exemplary embodiment of the application.Fig. 7 is please referred to, in hardware view, the electronic equipment
Including processor, internal bus, network interface, memory and nonvolatile memory, it is also possible that other business institutes certainly
The hardware needed.Processor reads in corresponding computer program to memory and then is run from nonvolatile memory, is patrolling
The coalignment for rideshare service is formed in the level of collecting.Certainly, other than software realization mode, it is not precluded in the application
His realization method, such as mode of logical device or software and hardware combining etc., that is to say, that the execution master of following process flow
Body is not limited to each logic unit or hardware or logical device.
Those skilled in the art will readily occur to the application its after considering specification and putting into practice invention disclosed herein
Its embodiment.This application is intended to cover any variations, uses, or adaptations of the application, these modifications, purposes or
Person's adaptive change follows the general principle of the application and including the undocumented common knowledge in the art of the application
Or conventional techniques.Description and embodiments are considered only as illustratively, and the true scope and spirit of the application are by following
Claim is pointed out.
It should be understood that the precision architecture that the application is not limited to be described above and be shown in the drawings, and
And various modifications and changes may be made without departing from the scope thereof.Scope of the present application is only limited by appended claim.
Claims (10)
1. a kind of matching process for rideshare service, which is characterized in that the method includes：
Target group is determined based on the multiple rideshare service requests received, and the target group includes the part rideshare service request
Corresponding service requester；
Obtain the similar parameter of service requester in target group interest between any two；
The service requester for determining to match in the target group according to the similar parameter.
2. according to the method described in claim 1, it is characterized in that, the service requester obtained in the target group two-by-two
Between interest similar parameter, including：
Determine one or more target interest types；
Obtain the interest characteristics vector that each service requester is directed to each target interest types；
The similar parameter of service requester interest between any two is obtained based on the interest characteristics vector.
3. according to the method described in claim 2, it is characterized in that, determining one or more target interest types, including：
Obtain the liveness that each service requester is directed to each preset alternative interest types；
The target interest types are chosen from the alternative interest types based on the liveness.
4. according to the method described in claim 3, it is characterized in that, the liveness is based on each service requester correspondence
User behavior data obtain.
5. according to the method described in claim 2, it is characterized in that, described obtain each service requester for each institute
The interest characteristics vector of target interest types is stated, including：
Obtain the corresponding user behavior data of each service requester；
The user behavior data is parsed using preset topic model, obtains objective result, the objective result includes each
The service requester is directed to each multiple interest tags of the target interest types and the weight of each interest tags；
The interest characteristics vector is generated based on the objective result.
6. according to the method described in claim 2, it is characterized in that, described obtain the service based on the interest characteristics vector
The similar parameter of requesting party's interest between any two, including：
The service requester is calculated between any two for each target interest types based on the interest characteristics vector
Euclidean distance；
The interest similar parameter of the service requester between any two is obtained based on the Euclidean distance.
7. according to the method any in claim 1-6, which is characterized in that described based on the multiple rideshare services received
Request determines target group, including：
Obtain start of a run and the stroke end that each rideshare service request carries；
The target group is determined based on the start of a run and stroke end.
8. a kind of coalignment for rideshare service, which is characterized in that described device includes：
First determining module, for determining target group based on the multiple rideshare service requests received, the target group includes portion
Divide the rideshare service request corresponding service requester；
Acquisition module, for obtaining the similar parameter of the interest between any two of the service requester in the target group；
Second determining module, for the service requester for determining to match in the target group according to the similar parameter.
9. a kind of computer readable storage medium, which is characterized in that the storage medium is stored with computer program, the calculating
Realize that the claims 1-7 any one of them is used for the matching process of rideshare service when machine program is executed by processor.
10. a kind of electronic equipment including memory, processor and stores the calculating that can be run on a memory and on a processor
Machine program, which is characterized in that the processor realizes the side described in any one of the claims 1-7 when performing described program
Method.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810039558.9A CN108229748B (en) | 2018-01-16 | 2018-01-16 | Matching method and device for carpooling service and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810039558.9A CN108229748B (en) | 2018-01-16 | 2018-01-16 | Matching method and device for carpooling service and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108229748A true CN108229748A (en) | 2018-06-29 |
| CN108229748B CN108229748B (en) | 2022-06-10 |
Family
ID=62640470
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810039558.9A Active CN108229748B (en) | 2018-01-16 | 2018-01-16 | Matching method and device for carpooling service and electronic equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108229748B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110581802A (en) * | 2019-08-27 | 2019-12-17 | 北京邮电大学 | fully-autonomous intelligent routing method and device based on deep belief network |
Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005250562A (en) * | 2004-03-01 | 2005-09-15 | Tama Tlo Kk | Discrimination analysis method, similar image search method, program for it, and device |
| CN102411596A (en) * | 2010-09-21 | 2012-04-11 | 阿里巴巴集团控股有限公司 | Information recommendation method and system |
| CN103325046A (en) * | 2012-03-19 | 2013-09-25 | 上海博路信息技术有限公司 | Real-time car-sharing system based on HTML5 |
| CN103778206A (en) * | 2014-01-14 | 2014-05-07 | 河南科技大学 | Method for providing network service resources |
| US20140129578A1 (en) * | 2012-11-08 | 2014-05-08 | Sap Ag | System and method for carpool matching |
| CN103886072A (en) * | 2014-03-24 | 2014-06-25 | 河南理工大学 | Retrieved result clustering system in coal mine search engine |
| US20140207375A1 (en) * | 2013-01-24 | 2014-07-24 | Sap Ag | Distribution of location and movement information of meeting participants |
| CN104881459A (en) * | 2015-05-22 | 2015-09-02 | 电子科技大学 | Friend recommendation method of mobile social network |
| CN105243562A (en) * | 2015-10-21 | 2016-01-13 | 北京小飞快充网络科技有限公司 | Method and system for enhancing content distribution effects of chauffeured cars |
| CN105468631A (en) * | 2014-09-04 | 2016-04-06 | 阿里巴巴集团控股有限公司 | Point-of-interest query method and apparatus |
| US20160138928A1 (en) * | 2014-11-18 | 2016-05-19 | International Business Machines Corporation | Dynamic real-time carpool matching |
| US20160364823A1 (en) * | 2015-06-11 | 2016-12-15 | Raymond Cao | Systems and methods for on-demand transportation |
| US20170034110A1 (en) * | 2015-07-30 | 2017-02-02 | Uber Technologies, Inc. | Social media integration for transport arrangement service |
| CN106447387A (en) * | 2016-08-31 | 2017-02-22 | 上海交通大学 | Air ticket personalized recommendation method based on shared account passenger prediction |
| WO2017075330A1 (en) * | 2015-10-30 | 2017-05-04 | Faraday&Future Inc. | System for determining common interests of vehicle occupants |
| CN107317688A (en) * | 2017-07-25 | 2017-11-03 | 薛江炜 | The device and method of communication group is created based on tag along sort |
| CN107527105A (en) * | 2017-08-11 | 2017-12-29 | 杨志伟 | Carpooling order combining method |
| CN107577682A (en) * | 2016-07-05 | 2018-01-12 | 上海交通大学 | Users' Interests Mining and user based on social picture recommend method and system |
-
2018
- 2018-01-16 CN CN201810039558.9A patent/CN108229748B/en active Active
Patent Citations (18)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005250562A (en) * | 2004-03-01 | 2005-09-15 | Tama Tlo Kk | Discrimination analysis method, similar image search method, program for it, and device |
| CN102411596A (en) * | 2010-09-21 | 2012-04-11 | 阿里巴巴集团控股有限公司 | Information recommendation method and system |
| CN103325046A (en) * | 2012-03-19 | 2013-09-25 | 上海博路信息技术有限公司 | Real-time car-sharing system based on HTML5 |
| US20140129578A1 (en) * | 2012-11-08 | 2014-05-08 | Sap Ag | System and method for carpool matching |
| US20140207375A1 (en) * | 2013-01-24 | 2014-07-24 | Sap Ag | Distribution of location and movement information of meeting participants |
| CN103778206A (en) * | 2014-01-14 | 2014-05-07 | 河南科技大学 | Method for providing network service resources |
| CN103886072A (en) * | 2014-03-24 | 2014-06-25 | 河南理工大学 | Retrieved result clustering system in coal mine search engine |
| CN105468631A (en) * | 2014-09-04 | 2016-04-06 | 阿里巴巴集团控股有限公司 | Point-of-interest query method and apparatus |
| US20160138928A1 (en) * | 2014-11-18 | 2016-05-19 | International Business Machines Corporation | Dynamic real-time carpool matching |
| CN104881459A (en) * | 2015-05-22 | 2015-09-02 | 电子科技大学 | Friend recommendation method of mobile social network |
| US20160364823A1 (en) * | 2015-06-11 | 2016-12-15 | Raymond Cao | Systems and methods for on-demand transportation |
| US20170034110A1 (en) * | 2015-07-30 | 2017-02-02 | Uber Technologies, Inc. | Social media integration for transport arrangement service |
| CN105243562A (en) * | 2015-10-21 | 2016-01-13 | 北京小飞快充网络科技有限公司 | Method and system for enhancing content distribution effects of chauffeured cars |
| WO2017075330A1 (en) * | 2015-10-30 | 2017-05-04 | Faraday&Future Inc. | System for determining common interests of vehicle occupants |
| CN107577682A (en) * | 2016-07-05 | 2018-01-12 | 上海交通大学 | Users' Interests Mining and user based on social picture recommend method and system |
| CN106447387A (en) * | 2016-08-31 | 2017-02-22 | 上海交通大学 | Air ticket personalized recommendation method based on shared account passenger prediction |
| CN107317688A (en) * | 2017-07-25 | 2017-11-03 | 薛江炜 | The device and method of communication group is created based on tag along sort |
| CN107527105A (en) * | 2017-08-11 | 2017-12-29 | 杨志伟 | Carpooling order combining method |
Non-Patent Citations (4)
| Title |
|---|
| RAHUL B. KHOT: "Pub-sub model based on preference matching for Carpooling framework", 《2016 INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT)》 * |
| 周雪妍，林泽鸿: "《在线社交网络关键用户挖掘方法研究》", 31 March 2017, 中国科学技术出版社 * |
| 李金发: "汽车共享的拼车合乘模式——以嘀嗒拼车为例", 《交通与港航》 * |
| 顾兆军等: "机上无线局域网用户行为分析", 《中国民航大学学报》 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110581802A (en) * | 2019-08-27 | 2019-12-17 | 北京邮电大学 | fully-autonomous intelligent routing method and device based on deep belief network |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108229748B (en) | 2022-06-10 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108197532B (en) | The method, apparatus and computer installation of recognition of face | |
| CN104243598B (en) | A kind of information recommendation method and device | |
| CN106791235B (en) | A kind of method, apparatus and system selecting service agent | |
| CN110659678B (en) | User behavior classification method, system and storage medium | |
| CN111506820B (en) | Recommendation model, recommendation method, recommendation device, recommendation equipment and recommendation storage medium | |
| KR102214422B1 (en) | Method and system of real-time graph-based embedding for personalized content recommendation | |
| CN108229864A (en) | Distribution method, device and the electronic equipment of order | |
| CN105354202B (en) | Data push method and device | |
| CN109214543B (en) | Data processing method and device | |
| CN110191183A (en) | Accurate intelligent method for pushing, system, device and computer readable storage medium | |
| CN109685805A (en) | A kind of image partition method and device | |
| CN113765993B (en) | Download speed prediction method, device and storage medium | |
| CN108229748A (en) | For the matching process, device and electronic equipment of rideshare service | |
| CN111552831B (en) | Music recommendation method and server | |
| CN108509179A (en) | Method and apparatus for generating model | |
| CN109062683A (en) | The method, apparatus and computer readable storage medium of host resource distribution | |
| CN110191362B (en) | Data transmission method and device, storage medium and electronic equipment | |
| CN111368060A (en) | Self-learning method, device and system for conversation robot, electronic equipment and medium | |
| CN114092162B (en) | Recommendation quality determination method, and training method and device of recommendation quality determination model | |
| CN114301907B (en) | Service processing method, system and device in cloud computing network and electronic equipment | |
| CN116367190A (en) | Digital twin function virtualization method for 6G mobile network | |
| CN109598344A (en) | Model generating method and device | |
| CN115130561A (en) | Processing method, device and equipment of pooling operator and storage medium | |
| CN114661887A (en) | Cross-domain data recommendation method and device, computer equipment and medium | |
| CN111836274B (en) | Service processing method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |