CN105674995A - Method for acquiring commuting route based on user's travel locus, and apparatus thereof - Google Patents
Method for acquiring commuting route based on user's travel locus, and apparatus thereof Download PDFInfo
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Abstract
The invention discloses a method for acquiring a commuting route based on a user's travel locus, and an apparatus thereof. The method for acquiring a commuting route based on a user's travel locus comprises the following steps: acquiring the historical travel locus data of an unknown commuting route user; determining the dwelling house position, the company position and the commuting travel road of the unknown commuting route user according to the historical travel locus data; and determining the commuting route of the unknown commuting route user according to the dwelling house position, the company position, the commuting travel road and the historical travel locus data. The method provided in the technical scheme in the embodiment of the invention is a method for acquiring the commuting route having a high matching degree with a user's practical commuting route.
Description
Technical field
The present invention relates to intelligent identification technology field, particularly relate to and a kind of obtain the method for commute route and device based on user's track of going on a journey.
Background technology
In all kinds of car business, in the such as business such as windward driving or share-car, the demand of travelling frequently of user occupies the very important market share. Pushing to user travels frequently with before car order, it is necessary to according to the matching degree of the actual traffic path of order traffic path and user determines whether push order to user. But, in existing accreditation process, the commute route that user provides complete can not be allowed, wherein part user can provide home address and company address. Another part user can not provide home address and company address usually. In order to better meet the demand of travelling frequently of user, before order is travelled frequently in propelling movement, it is necessary to obtain the commute route that user is on and off duty.
Prior art does not provide the method that can automatically and accurately obtain user's commute route on and off duty so that the commute route that the actual commute route of user and order push is widely different so that the order of travelling frequently of propelling movement can not meet the actual needs of user.
Summary of the invention
In view of this, the embodiment of the present invention provides a kind of and obtains the method for commute route and device based on user's track of going on a journey, to improve the accuracy determining the actual commute route of user.
First aspect, embodiments provides a kind of method of track acquisition commute route of going on a journey based on user, and described method comprises:
Obtain the history trip track data of unknown commute route user;
Determine home location, the company position of described unknown commute route user according to described history trip track data and travel frequently by way of section;
According to described home location, company position, travel frequently and determine the commute route of described unknown commute route user by way of section and described history trip track data.
Second aspect, the embodiment of the present invention additionally provides the device of a kind of track acquisition commute route of going on a journey based on user, and described device comprises:
Data acquisition module, for obtaining the history trip track data of unknown commute route user;
Critical data determination module, for determining home location, the company position of described unknown commute route user according to described history trip track data and travel frequently by way of section;
Commute route determination module, for according to described home location, company position, travel frequently and determine the commute route of described unknown commute route user by way of section and described history trip track data.
What the embodiment of the present invention provided obtains the method for commute route and device based on user's track of going on a journey; the history trip track data of user is utilized to obtain the commute route of user; the commute route of commute route and the user's reality obtained is coincide, and degree is better, matching degree is higher; using the commute route that obtains as order route, it is to increase push the success ratio of order to user by car class application program.
Accompanying drawing explanation
By reading with reference to detailed description non-limiting example done that the following drawings is done, the other features, objects and advantages of the present invention will become more obvious:
Fig. 1 a kind of obtains the schema of method of commute route based on user's track of going on a journey for what the embodiment of the present invention one provided;
The schema of the method for the process history trip track data that Fig. 2 provides for the embodiment of the present invention one;
Fig. 3 a kind of obtains the schema of method of commute route based on user's track of going on a journey for what the embodiment of the present invention two provided;
Fig. 4 a kind of obtains the schema of method of commute route based on user's track of going on a journey for what the embodiment of the present invention three provided;
Fig. 5 a kind of obtains the schema of method of commute route based on user's track of going on a journey for what the embodiment of the present invention four provided;
The track street that is not connected that Fig. 6 provides for the embodiment of the present invention four is connected schematic diagram;
Fig. 7 a kind of obtains the schema of method of commute route based on user's track of going on a journey for what the embodiment of the present invention five provided;
Fig. 8 a kind of obtains the structure iron of device of commute route based on user's track of going on a journey for what the embodiment of the present invention six provided.
Embodiment
Below in conjunction with drawings and Examples, the present invention is described in further detail. It should be appreciated that specific embodiment described herein is only for explaining the present invention, but not limitation of the invention. It also should be noted that, for convenience of description, accompanying drawing illustrate only part related to the present invention and not all content.
Embodiment one
Fig. 1 a kind of obtains the schema of method of commute route based on user's track of going on a journey for what the embodiment of the present invention one provided. The present embodiment is applicable in the situation wanting to obtain the commute route of unknown commute route user. Commute route is generally the route between the family of user and company, or can also be interpreted as it is the route that user frequently uses a certain period (several months). The method can by based on user go on a journey track obtain commute route device perform, wherein this device can be realized by software and/or hardware, and this device is usually in the server configurable. With reference to figure 1, the present embodiment provide based on user go on a journey track obtain commute route method specifically can comprise as follows:
S110, the history trip track data obtaining unknown commute route user.
Wherein, history trip track data is gather, by user's historical position information of internet or each application client end collection, the data obtained. Such as, user uses shopping client terminal to carry out the position data of self location, it may also be useful to map client terminal carries out the navigation way etc. navigated, and all can be used as history trip track data; User carries out the position data filled in when account is registered in internet. Obtaining history trip track data can be obtain unknown commute route user history trip track data within a preset time interval or obtain the history trip track data of unknown commute route user in default trip number of times, concrete prefixed time interval and preset trip number of times and can limit according to practical situation.
S120, track data of going on a journey according to described history are determined home location, the company position of described unknown commute route user and travel frequently by way of section.
Exemplary, home location is the positional information of the user's house directly or indirectly obtained by history trip track data, it is preferable to a coordinate point in map; Company position is the positional information of the user company directly or indirectly obtained by history trip track data, it is preferable to a coordinate point in map. In fact frequent two end points using route are for the route that user frequently uses, home location and company position. For the user having specific rule of life, frequent more than one of the route possibility used, then home location and company position can also be more than one. Travelling frequently is the fragment position information through commute route directly or indirectly obtained by history trip track data by way of section, it is preferably in map the section between two crossings, or being section vector units minimum in electronics map, each unknown commute route user can have multiple travelling frequently by way of section.
S130, according to described home location, company position, travel frequently and determine the commute route of described unknown commute route user by way of section and described history trip track data.
Exemplary, commute route determines that mode can be the whole communication paths obtaining between home location and company position in history goes on a journey track data, determines that route that probability is big is as commute route according to setting strategy from communication path.
The method of the track acquisition commute route of going on a journey based on user that the embodiment of the present invention one provides; by utilizing the history trip track data of unknown commute route user determine home location, the company position of unknown commute route user and travel frequently by way of section; and then determine the commute route of unknown commute route user; using the commute route determined as the order route by car class application program; make the actual commute route matching degree height of order route and user, it is to increase push the success ratio of order.
In technique scheme, determine home location, the company position of described unknown commute route user according to described history trip track data and travel frequently preferably to perform following method by way of section, see Fig. 2, comprising:
S121, track data of described history being gone on a journey are divided into path locus data and non-rice habitats track data.
Concrete, path locus data are the position data acquisition on road in history trip track data, can characterize the track route of unknown commute route user trip. Non-rice habitats track data is remove path locus remaining position data acquisition outer in history trip track data, can characterize the positional information of unknown commute route user in buildings or on the non-rice habitats such as outdoor place. So-called road, the section concept being in electronics map.
S122, travelling frequently by way of section of determining described unknown commute route user according to described path locus data.
Exemplary, can determine that unknown commute route user's respectively travels frequently by way of section by path locus data. Determining that mode can be utilize to travel frequently to identify by way of section recognizer, wherein travelling frequently is utilize machine learning system model travelling frequently of known commute route user to be obtained by way of section and the non-training by way of section of travelling frequently by way of section recognizer. Determine mode can also be according to path locus data by way of the time, be chosen at work hours section and/or quitting time section by way of section as travelling frequently by way of section.
S123, home location and the company position of determining described unknown commute route user according to described non-rice habitats track data.
Exemplary, home location and the company position of unknown commute route user can be determined by non-rice habitats track data. Determine that mode can be obtain home location and the company position that unknown commute route user provides. Determine that mode can also be utilize location indentifier to identify, wherein location indentifier is utilize machine learning system model the home location bunch of known home location and company position user, company position bunch and idle position bunch to be trained to obtain, and wherein said home location bunch, company position bunch and idle position bunch are by the non-rice habitats track data cluster of known home location and company position user being obtained. Determine mode can also be obtain user operationally between the region of the intensive appearance of section, it is company position by the most intensive position mark in commercial zone, obtain user in the region of the intensive appearance of non-working time section, it is home location by the most intensive position mark in Residential areas.
Embodiment two
The present embodiment provides a kind of method of track acquisition commute route of going on a journey based on user based on above-described embodiment. Fig. 3 a kind of obtains the schema of method of commute route based on user's track of going on a journey for what the embodiment of the present invention two provided. With reference to figure 3, the embodiment of the present invention provide based on user go on a journey track obtain commute route method can comprise as follows:
S210, the history trip track data obtaining unknown commute route user.
S220, track data of described history being gone on a journey are divided into path locus data and non-rice habitats track data.
S230, travelling frequently by way of section of determining described unknown commute route user according to described path locus data.
S240, described non-rice habitats track data is carried out cluster, obtain at least two points bunch.
Concrete, with cluster algorithm, described non-rice habitats track data can be carried out cluster, cluster algorithm can be dividing method (as: Kmeans), density based cluster algorithm (as: dbscan), based on grid cluster algorithm (as: wavecluster) etc. Can obtaining at least two points bunch after cluster, each point bunch comprises some amount or the location data of certain density, and the quantity of the position data comprised between each point bunch or density can be different.
S250, location indentifier is utilized to be identified by each described point bunch, to determine home location bunch, company position bunch and idle position bunch, and determine home location and company position, described location indentifier is utilize machine learning system model the home location bunch of known home location and company position user, company position bunch and idle position bunch to be trained to obtain, and wherein said home location bunch, company position bunch and idle position bunch are by the non-rice habitats track data cluster of known home location and company position user being obtained.
Exemplary, before utilizing location indentifier to be identified by each described point bunch, it needs to be determined that location indentifier, determining step specifically comprises: obtain the known home location of some amount and the history trip track data of company position user, each history is gone on a journey track data according to whether being divided into path locus data and non-rice habitats track data on road, with cluster algorithm, each non-rice habitats track data is carried out cluster, obtain multiple track point bunch, the point bunch comprising home location is labeled as home location (home) bunch, the point bunch comprising company position is labeled as company position (company) bunch, the point bunch of all the other positions is labeled as idle position (useless) bunch.The each bunch of training data as location indentifier that will obtain, utilizes machine learning system model to be trained by location indentifier according to preset attribute, confirms location indentifier. Wherein preset attribute is the attribute that can determine customer position information, can set manually, it is also possible to determine based on model training. Preset attribute can for the ratio of number of days, the user ratio that daytime and night occur in each bunch occurs in each bunch in user, each WLAN (wireless local area network) (WirelessFidelity, wifi) occurs in each bunch probability calculation wifi entropy out, user in one day each period bunch in occur ratio, user bunch at least one item such as the number of times that occurs.
After determining location indentifier, location indentifier is utilized to be identified by each point bunch of unknown commute route user, it is determined that home location bunch, company position bunch and idle position bunch. The home location that the center point coordinate of home location bunch is designated as unknown commute route user, is designated as the company position of unknown commute route user by the center point coordinate of company position bunch.
S260, according to described home location, company position, travel frequently and determine the commute route of described unknown commute route user by way of section and described history trip track data.
The method of a kind of track acquisition commute route of going on a journey based on user that the embodiment of the present invention two provides; by the history trip track data of unknown commute route user is divided into path locus data and non-rice habitats track data; determine to travel frequently by way of section according to path locus data; utilize cluster algorithm and location indentifier that non-rice habitats track data carries out cluster and identification; determine home location and the company position of user, then according to home location, company position with travel frequently to go on a journey in history by way of section track data is determined the commute route of unknown commute route user. The method can accurately determine home location and the company position of unknown commute route user, and then accurately determines commute route so that the commute route determined and the commute route matching degree of user's reality are higher.
Embodiment three
The present embodiment provides a kind of method of track acquisition commute route of going on a journey based on user based on above-described embodiment. Fig. 4 a kind of obtains the schema of method of commute route based on user's track of going on a journey for what the embodiment of the present invention three provided. With reference to figure 4, the embodiment of the present invention provide based on user go on a journey track obtain commute route method can comprise as follows:
S310, the history trip track data obtaining unknown commute route user.
S320, track data of described history being gone on a journey are divided into path locus data and non-rice habitats track data.
S330, travelling frequently by way of section of determining described unknown commute route user according to described path locus data.
S340, obtain in described non-rice habitats track data the home location and company position that provide by described unknown commute route user.
Exemplary, home location and company position can be that the unknown commute route user of prompting provides home location and company position when registering, or utilize the paid unknown commute route user of method excitation rewarded to provide home location and company position. Unknown commute route user can directly obtain home location and company position after providing home location and company position.
S350, according to described home location, company position, travel frequently and determine the commute route of described unknown commute route user by way of section and described history trip track data.
The method of the track acquisition commute route of going on a journey based on user that the embodiment of the present invention three provides; obtain home location and company position that unknown commute route user provides; and obtain according to path locus data and travel frequently by way of section, by home location, company position, travel frequently in history goes on a journey track data, determine the commute route of unknown commute route user by way of section.The method can directly obtain home location and the company position of unknown commute route user, simplify the step that commute route is determined, the commute route simultaneously making to determine is higher with actual commute route matching degree, it is to increase push the success ratio of order of travelling frequently to user by car class application program.
Embodiment four
The present embodiment provides a kind of method of track acquisition commute route of going on a journey based on user based on above-described embodiment. Fig. 5 a kind of obtains the schema of method of commute route based on user's track of going on a journey for what the embodiment of the present invention four provided. With reference to figure 5, the embodiment of the present invention provide based on user go on a journey track obtain commute route method can comprise as follows:
S410, the history trip track data obtaining unknown commute route user.
S420, track data of described history being gone on a journey are divided into path locus data and non-rice habitats track data.
S430, described path locus data are divided in units of street, obtain whole track streets, be designated as the set of track street.
Exemplary, path locus data are divided, it is possible to for dividing in units of street, it is possible to think and divide in units of preset length, it is preferable to divide in units of street. Described street is one section of street between two crossings. After path locus data being divided in units of street, obtain the set of track street.
Each track street that S440, utilization are travelled frequently in described track street is gathered by section recognizer identifies, what obtain unknown commute route user travels frequently by way of section, and each track street is identified as the probable value travelled frequently by way of section, described in travel frequently be utilize machine learning system model travelling frequently of known commute route user to be obtained by way of section and the non-training by way of section of travelling frequently by way of section recognizer.
Exemplary, a corresponding track street by way of section of travelling frequently. Before utilizing each track street travelled frequently in described track street is gathered by section recognizer to identify, first to be determined to travel frequently by way of section recognizer, determining step specifically comprises: the track street set obtaining the known commute route user of some amount, by each track street sign of commute route for travelling frequently by way of section, remaining track street sign is non-travelling frequently by way of section. Respectively travelling frequently of obtaining is travelled frequently by way of section and Ge Fei by way of section as the training data by way of section recognizer of travelling frequently, utilize machine learning system model to train by way of section recognizer travelling frequently according to preset attribute, confirm to travel frequently by way of section recognizer. Wherein preset attribute to determine that user travels frequently by way of the attribute in section, can set manually, it is also possible to determine based on model training. Preset attribute the ratio of minimum number of days can occurs for number of days and this user trajectory street set of number of days that the set of user trajectory street occurs, appearance, occur on daytime and night ratio and number of times, daytime and night occurrence number and the track street of this user be integrated into daytime and the ratio of minimum number occurs night, at least one item such as the ratio of each period appearance in a day and number of times.
Travel frequently after the recognizer of section in confirmation, utilizing travels frequently identifies the track street set of unknown commute route user by way of section recognizer, obtain travelling frequently by way of section of unknown commute route user, and each track street is identified as the probable value travelled frequently by way of section. Such as, the probable value that track street is identified as travelling frequently by way of section is R, and being identified as the non-probable value by way of section of travelling frequently is r, then R+r=1.Preferably, when track street be identified as travelling frequently be greater than preset value by way of the probable value in section time, this track street is identified as and travels frequently by way of section, the size of preset value can set according to practical situation.
S450, home location and the company position of determining described unknown commute route user according to described non-rice habitats track data.
S460, according to described home location, company position, travel frequently and determine the commute route of described unknown commute route user by way of section and described history trip track data.
The method of the track acquisition commute route of going on a journey based on user that the embodiment of the present invention four provides; by the history trip track data of unknown commute route user is divided into path locus data and non-rice habitats track data; utilizing travels frequently travels frequently by way of section in the recognizer identification path locus data of section; utilize non-rice habitats track data to determine home location and the company position of user, and then determine the commute route of unknown commute route user. The method can determine that unknown commute route user's travels frequently by way of section accurately so that the commute route finally determined and the commute route matching degree of user's reality are higher, it is to increase push the success ratio of order of travelling frequently to user by car class application program.
Technical scheme in the embodiment of the present invention can be preferably according to described home location, company position, travelled frequently before the commute route of described unknown commute route user is determined in section and described history trip track data, also comprise: check described history trip track data to be connected situation; It is not connected track street if having, then the described track street that is not connected is connected with the track street not being connected track street minimum described in described history trip track data middle distance, the path being connected is designated as and newly adds track street, and newly add track street travel frequently by way of section probable value be the travelling frequently by way of the half of section probable value sum of adjacent both ends track street.
Even there is situation about not being connected with other track streets in the track street in history trip track data. Now being connected not being connected track street with the track street not being connected track street distance value minimum, the path being connected, on road, is designated as and newly adds path, track street. The track street that is not connected that Fig. 6 provides for the embodiment of the present invention four is connected schematic diagram. As shown in Figure 6, history trip track data in be not connected track street 601, distance be not connected minimum track street 602, track street 601, track street 601 will be connected and will be connected with track street 602, and be designated as and newly add track street 603. Wherein, what newly add track street 603 travels frequently by way of the method for calculation of section probable value, it is preferable to adjacent both ends track street, is not namely connected travelling frequently by way of the half of section probable value sum of track street 601 and track street 602.
Embodiment five
The present embodiment provides a kind of method of track acquisition commute route of going on a journey based on user based on above-described embodiment. Fig. 7 a kind of obtains the schema of method of commute route based on user's track of going on a journey for what the embodiment of the present invention five provided. With reference to figure 7, the embodiment of the present invention provide based on user go on a journey track obtain commute route method can comprise as follows:
S510, the history trip track data obtaining unknown commute route user.
S520, track data of going on a journey according to described history are determined home location, the company position of described unknown commute route user and travel frequently by way of section.
S530, travel frequently by way of section based on described, it is determined that communication path between home location and described company position described in described history trip track data.
Exemplary, obtain the whole communication paths between home location and company position in history trip track data, wherein communication path is at least to travel frequently by way of section through one, and the trajectory path being connected on road.
Preferably, the described probable value obtaining described unknown commute route user from high to low N number of travels frequently by way of section, and N is at least 2; Calculate N number of described in travel frequently by way of section correspondence set each subset, subset described in each comprises travels frequently by way of section described at least one; Determine the shortest communication path that each described subset is corresponding, the shortest described communication path between described home location and described company position and by way of described subset comprise whole described in travel frequently by way of section.
Exemplary, obtain N number of probable value the highest travel frequently by way of section, wherein N is at least 2, and is the bigger the better. What obtain N number of travels frequently that being designated as by way of section travels frequently gathers by way of section, calculate each subset travelled frequently by way of section set correspondence, comprising at least one in each subset travels frequently by way of section, determine whole communication paths that each subset is corresponding between home location and company position, what each communication path comprised in corresponding subset whole travels frequently by way of section, preferably, it is determined that the shortest communication path in the whole communication path of each subset. Such as, when N gets 3, travel frequently and it is respectively the highest section of probable value 1 by way of section, section 2 and section 3. The subset gathering (section 1, section 2, section 3) corresponding by way of section of then travelling frequently is (section 1), (section 2), (section 3), (section 1, section 2), (section 1, section, 3), (section 2, section 3), (section 1, section 2, section 3). 5 are had by way of the communication path in (section 1) between home location and company position, the communication path getting shortest distance is designated as the shortest communication path 1,3 are had by way of the communication path in (section 2) between home location and company position, the communication path getting shortest distance is designated as the shortest communication path 2, analogize successively, finally obtain the shortest communication path 1 to the shortest communication path 7.
S540, travel frequently by way of the probable value in section based on described, calculate the commute route probable value of described communication path.
Exemplary, confirm unknown commute route user each track street travel frequently after the probable value in section, can by the commute route probable value travelled frequently and calculate each communication path by way of section probable value. Calculate the method for the commute route probable value of communication path, it is preferable to each track street obtained in communication path is the probable value travelled frequently by way of section, is multiplied each probable value as the commute route probable value of this communication path. Such as, article 1, communication path comprises 6 track streets, the probable value by way of section of travelling frequently in each track street is respectively 0.23,0.51,0.24,0.78,0.65,0.71, each probable value be multiplied and obtain 0.01013387544, then the commute route probable value of this communication path is 0.01013387544.
S550, the commute route determining described unknown commute route user according to described commute route probable value.
Exemplary, after calculating the commute route probable value of each communication path, get the commute route of the maximum communication path of probable value as unknown commute route user. If most probable value correspondence at least two communication paths, then get communication path that in communication path corresponding to most probable value, total path the is the shortest commute route as unknown commute route user.Such as, the probable value calculating 8 communication paths is respectively 0.0145,0.756,0.207,0.0597,0.0147,0.0451,0.0023,0.367, then get the commute route of communication path as unknown commute route user of 0.756 correspondence. If 8 the probable value of communication path is respectively 0.0145,0.756,0.207,0.0597,0.756,0.0147,0.0023,0.367, the probable value having two communication paths is 0.756, Article 1, the total path of communication path is 3.4 kilometers, the total path of Article 2 communication path is 3.1 kilometers, then get the commute route of Article 2 communication path as unknown commute route user.
The method of the track acquisition commute route of going on a journey based on user that the embodiment of the present invention five provides; determine home location, company position by obtaining the history trip track data of unknown commute route user and travel frequently by way of section; according to travelling frequently by way of section and probable value thereof; determine the communication path between home location and company position and probable value thereof, and then determine the commute route of unknown commute route user. The commute route of the unknown commute route user that the method is determined is higher with actual commute route matching degree, using the commute route of acquisition as the order route pushed by car class application program, it is possible to improve the success ratio pushing order.
Embodiment six
Fig. 8 a kind of obtains the structure iron of device of commute route based on user's track of going on a journey for what the embodiment of the present invention six provided. The present embodiment is applicable in the situation wanting to obtain the commute route of unknown commute route user. With reference to figure 8, the present embodiment provide based on user go on a journey track obtain commute route device specifically can comprise as follows:
Data acquisition module 801, for obtaining the history trip track data of unknown commute route user;
Critical data determination module 802, for determining home location, the company position of described unknown commute route user according to described history trip track data and travel frequently by way of section;
Commute route determination module 803, for according to described home location, company position, travel frequently and determine the commute route of described unknown commute route user by way of section and described history trip track data.
Further, described critical data determination module 802 can comprise:
Data Placement submodule block, is divided into path locus data and non-rice habitats track data for track data of described history being gone on a journey;
Travel frequently the true stator modules by way of section, for determining that described unknown commute route user's travels frequently by way of section according to described path locus data;
The true stator modules in position, for determining home location and the company position of described unknown commute route user according to described non-rice habitats track data.
Preferably, the true stator modules in described position can comprise:
Data clusters unit, for described non-rice habitats track data is carried out cluster, obtains at least two points bunch;
Point bunch determining unit, for utilizing location indentifier to be identified by each described point bunch, to determine home location bunch, company position bunch and idle position bunch, and determine home location and company position, described location indentifier is utilize machine learning system model the home location bunch of known home location and company position user, company position bunch and idle position bunch to be trained to obtain, and wherein said home location bunch, company position bunch and idle position bunch are by the non-rice habitats track data cluster of known home location and company position user being obtained.
Preferably, the true stator modules in described position specifically may be used for:
The home location and company position that there is provided by described unknown commute route user are provided in described non-rice habitats track data.
Further, described in the true stator modules by way of section of travelling frequently can comprise:
Track street determining unit, for described path locus data being divided in units of street, obtains whole track streets, is designated as the set of track street;
Travel frequently by way of section determining unit, the each track street travelled frequently in described track street is gathered by section recognizer for utilizing identifies, what obtain unknown commute route user travels frequently by way of section, and each track street is identified as the probable value travelled frequently by way of section, described in travel frequently be utilize machine learning system model travelling frequently of the known path user that travels frequently to be obtained by way of section and the non-training by way of section of travelling frequently by way of section recognizer.
Further, described commute route determination module 803 can comprise:
The true stator modules of communication path, for travelling frequently by way of section based on described, it is determined that communication path between home location and described company position described in described history trip track data;
Probable value calculating sub module, for travelling frequently by way of the probable value in section based on described, calculates the commute route probable value of described communication path;
The true stator modules of commute route, for determining the commute route of described unknown commute route user according to described commute route probable value.
Preferably, the true stator modules of described communication path can comprise:
Travelling frequently by way of section acquiring unit, travel frequently by way of section for described probable value from high to low N number of obtaining described unknown commute route user, N is at least 2;
Subset determing unit, for calculate N number of described in travel frequently by way of section correspondence set each subset, subset described in each comprises travels frequently by way of section described at least one;
The shortest communication path determining unit, for determining the shortest communication path that each described subset is corresponding, the shortest described communication path between described home location and described company position and by way of described subset comprise whole described in travel frequently by way of section.
Further, described device can also comprise:
Detection module, for checking described history trip track data to be connected situation;
Adjacent modules, if when not being connected track street for having, the described track street that is not connected is connected with the track street not being connected track street minimum described in described history trip track data middle distance, the path being connected is designated as and newly adds track street, and newly add track street travel frequently by way of section probable value be the travelling frequently by way of the half of section probable value sum of adjacent both ends track street.
The device of the track acquisition commute route of going on a journey based on user that the embodiment of the present invention six provides; with any embodiment of the present invention provide based on user go on a journey track obtain commute route method belong to same invention conceive; what can perform that any embodiment of the present invention provides obtains the method for commute route based on user's track of going on a journey, and possesses and performs to obtain the method corresponding function module of commute route and useful effect based on user's track of going on a journey. The not technology details of detailed description in the present embodiment, the method for the track acquisition commute route of going on a journey based on user that can provide see any embodiment of the present invention.
Note, above are only the better embodiment of the present invention and institute's application technology principle. It is understood by those skilled in the art that and the invention is not restricted to specific embodiment described here, various obvious change can be carried out for a person skilled in the art, readjust and substitute and protection scope of the present invention can not be departed from.Therefore, although being described in further detail invention has been by above embodiment, but the present invention is not limited only to above embodiment, when not departing from present inventive concept, other equivalence embodiments more can also be comprised, and the scope of the present invention is determined by appended right.
Claims (16)
1. one kind based on user go on a journey track obtain commute route method, it is characterised in that, comprising:
Obtain the history trip track data of unknown commute route user;
Determine home location, the company position of described unknown commute route user according to described history trip track data and travel frequently by way of section;
According to described home location, company position, travel frequently and determine the commute route of described unknown commute route user by way of section and described history trip track data.
2. method according to claim 1, it is characterised in that, determine home location, the company position of described unknown commute route user according to described history trip track data and travel frequently to comprise by way of section:
Track data of described history being gone on a journey is divided into path locus data and non-rice habitats track data;
Determine that described unknown commute route user's travels frequently by way of section according to described path locus data;
Home location and the company position of described unknown commute route user is determined according to described non-rice habitats track data.
3. method according to claim 2, it is characterised in that, determine that the home location of described unknown commute route user and company position comprise according to described non-rice habitats track data:
Described non-rice habitats track data is carried out cluster, obtains at least two points bunch;
Location indentifier is utilized to be identified by each described point bunch, to determine home location bunch, company position bunch and idle position bunch, and determine home location and company position, described location indentifier is utilize machine learning system model the home location bunch of known home location and company position user, company position bunch and idle position bunch to be trained to obtain, and wherein said home location bunch, company position bunch and idle position bunch are by the non-rice habitats track data cluster of known home location and company position user being obtained.
4. method according to claim 2, it is characterised in that, determine that the home location of described unknown commute route user and company position comprise according to described non-rice habitats track data:
The home location and company position that there is provided by described unknown commute route user are provided in described non-rice habitats track data.
5. method according to claim 3 or 4, it is characterised in that, determine that described unknown travelling frequently of commute route user comprises by way of section according to described path locus data:
Described path locus data are divided in units of street, obtains whole track streets, be designated as the set of track street;
The each track street travelled frequently in described track street is gathered by section recognizer is utilized to identify, what obtain unknown commute route user travels frequently by way of section, and each track street is identified as the probable value travelled frequently by way of section, described in travel frequently be utilize machine learning system model travelling frequently of known commute route user to be obtained by way of section and the non-training by way of section of travelling frequently by way of section recognizer.
6. method according to claim 5, it is characterised in that, according to described home location, company position, travel frequently and determine that the commute route of described unknown commute route user comprises by way of section and described history trip track data:
Travel frequently by way of section based on described, it is determined that communication path between home location and described company position described in described history trip track data;
Travel frequently by way of the probable value in section based on described, calculate the commute route probable value of described communication path;
The commute route of described unknown commute route user is determined according to described commute route probable value.
7. method according to claim 6, it is characterised in that, travel frequently by way of section based on described, it is determined that communication path between home location and described company position described in described history trip track data comprises:
The described probable value obtaining described unknown commute route user from high to low N number of travels frequently by way of section, and N is at least 2;
Calculate N number of described in travel frequently by way of section correspondence set each subset, subset described in each comprises travels frequently by way of section described at least one;
Determine the shortest communication path that each described subset is corresponding, the shortest described communication path between described home location and described company position and by way of described subset comprise whole described in travel frequently by way of section.
8. method according to claim 5, it is characterised in that, according to described home location, company position, travelled frequently before the commute route of described unknown commute route user is determined in section and described history trip track data, also comprise:
Described history trip track data is checked to be connected situation;
It is not connected track street if having, then the described track street that is not connected is connected with the track street not being connected track street minimum described in described history trip track data middle distance, the path being connected is designated as and newly adds track street, and newly add track street travel frequently by way of section probable value be the travelling frequently by way of the half of section probable value sum of adjacent both ends track street.
9. one kind based on user go on a journey track obtain commute route device, it is characterised in that, comprising:
Data acquisition module, for obtaining the history trip track data of unknown commute route user;
Critical data determination module, for determining home location, the company position of described unknown commute route user according to described history trip track data and travel frequently by way of section;
Commute route determination module, for according to described home location, company position, travel frequently and determine the commute route of described unknown commute route user by way of section and described history trip track data.
10. device according to claim 9, it is characterised in that, described critical data determination module comprises:
Data Placement submodule block, is divided into path locus data and non-rice habitats track data for track data of described history being gone on a journey;
Travel frequently the true stator modules by way of section, for determining that described unknown commute route user's travels frequently by way of section according to described path locus data;
The true stator modules in position, for determining home location and the company position of described unknown commute route user according to described non-rice habitats track data.
11. devices according to claim 10, it is characterised in that, the true stator modules in described position comprises:
Data clusters unit, for described non-rice habitats track data is carried out cluster, obtains at least two points bunch;
Point bunch determining unit, for utilizing location indentifier to be identified by each described point bunch, to determine home location bunch, company position bunch and idle position bunch, and determine home location and company position, described location indentifier is utilize machine learning system model the home location bunch of known home location and company position user, company position bunch and idle position bunch to be trained to obtain, and wherein said home location bunch, company position bunch and idle position bunch are by the non-rice habitats track data cluster of known home location and company position user being obtained.
12. devices according to claim 10, it is characterised in that, the true stator modules in described position specifically for:
The home location and company position that there is provided by described unknown commute route user are provided in described non-rice habitats track data.
13. devices according to claim 11 or 12, it is characterised in that, described in the true stator modules by way of section of travelling frequently comprise:
Track street determining unit, for described path locus data being divided in units of street, obtains whole track streets, is designated as the set of track street;
Travel frequently by way of section determining unit, the each track street travelled frequently in described track street is gathered by section recognizer for utilizing identifies, what obtain unknown commute route user travels frequently by way of section, and each track street is identified as the probable value travelled frequently by way of section, described in travel frequently be utilize machine learning system model travelling frequently of the known path user that travels frequently to be obtained by way of section and the non-training by way of section of travelling frequently by way of section recognizer.
14. devices according to claim 13, it is characterised in that, described commute route determination module comprises:
The true stator modules of communication path, for travelling frequently by way of section based on described, it is determined that communication path between home location and described company position described in described history trip track data;
Probable value calculating sub module, for travelling frequently by way of the probable value in section based on described, calculates the commute route probable value of described communication path;
The true stator modules of commute route, for determining the commute route of described unknown commute route user according to described commute route probable value.
15. devices according to claim 14, it is characterised in that, the true stator modules of described communication path comprises:
Travelling frequently by way of section acquiring unit, travel frequently by way of section for described probable value from high to low N number of obtaining described unknown commute route user, N is at least 2;
Subset determing unit, for calculate N number of described in travel frequently by way of section correspondence set each subset, subset described in each comprises travels frequently by way of section described at least one;
The shortest communication path determining unit, for determining the shortest communication path that each described subset is corresponding, the shortest described communication path between described home location and described company position and by way of described subset comprise whole described in travel frequently by way of section.
16. devices according to claim 13, it is characterised in that, also comprise:
Inspection module, for checking described history trip track data to be connected situation;
Adjacent modules, if when not being connected track street for having, the described track street that is not connected is connected with the track street not being connected track street minimum described in described history trip track data middle distance, the path being connected is designated as and newly adds track street, and newly add track street travel frequently by way of section probable value be the travelling frequently by way of the half of section probable value sum of adjacent both ends track street.
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| CN106931974A (en) * | 2017-03-29 | 2017-07-07 | 清华大学 | The method that personal Commuting Distance is calculated based on mobile terminal GPS location data record |
| CN107038858A (en) * | 2017-05-25 | 2017-08-11 | 厦门大学 | Method is recommended in the dynamic share-car of the private car that commutes |
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