CN112765284A - Method and device for determining relevant location of user - Google Patents

Method and device for determining relevant location of user Download PDF

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CN112765284A
CN112765284A CN202110078852.2A CN202110078852A CN112765284A CN 112765284 A CN112765284 A CN 112765284A CN 202110078852 A CN202110078852 A CN 202110078852A CN 112765284 A CN112765284 A CN 112765284A
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user
area
station
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CN112765284B (en
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邹大毕
何子登
杜星
程世勇
温晓丽
宋秉麟
周龙涛
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Guangzhou Yang Cheng Tong Co ltd
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    • G06F16/284—Relational databases
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    • G06F16/245—Query processing
    • G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
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Abstract

The invention discloses a method and a device for determining relevant places of a user, wherein after travel records of the user in the same time period every day in a plurality of days are collected, the method acquires boarding sites corresponding to the earliest travel records in the same time period every day from all the travel records, and performs clustering operation on the boarding sites corresponding to all the earliest travel records, so that the accurate central point position of the residence or working place of the user can be acquired, more accurate reference basis is provided for improving operation service of urban public transport, the layout accuracy of an urban public transport network is improved, the travel efficiency of people is improved, and traffic jam is relieved.

Description

Method and device for determining relevant location of user
Technical Field
The invention relates to the technical field of internet, in particular to a method and a device for determining a relevant place of a user.
Background
Based on the advantages of convenience in travelling, environmental protection and the like, public transport means are more and more favored by people.
In recent years, with the accelerated development of urbanization, urban public transportation networks are under greater pressure, and research on how to improve the operation service of urban public transportation becomes a focus of attention in the industry. At present, an in-and-out monitoring system and a vehicle-mounted GPS navigation positioning device are generally installed, in-and-out information of public transport means (particularly buses) and GPS driving track data are recorded according to time sequence, and urban public transport operation and passenger trip big data are formed by all continuously running buses and numerous passenger card swiping transactions. However, practice finds that, because public transportation charging mostly adopts a 'one-ticket system', only the boarding travel data (such as boarding times and boarding time) are available, so that the operation condition of the urban public transportation can be estimated only through the boarding travel data, and the operation service of the urban public transportation can still not be improved well by laying out the urban public transportation network according to the boarding travel data.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a method and a device for determining a relevant place of a user, which can provide a more comprehensive reference basis for improving the operation service of urban public transport, thereby improving the layout accuracy of an urban public transport network.
In order to solve the above technical problem, a first aspect of an embodiment of the present invention discloses a method for determining a relevant location of a user, where the method includes:
collecting travel records of a certain target user in a target time period of a plurality of days each day, and determining a boarding station corresponding to the earliest travel record in the target time period in the plurality of days according to all the collected travel records to obtain a plurality of target boarding stations;
performing clustering operation on all the target getting-on stations based on the determined clustering algorithm to obtain the position of the central point of the area where the place matched with the target user is located;
the area where the place matched with the target user is located comprises the area where the place where the target user is located or the area where the place where the target user is located.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the clustering algorithm includes a Mean Shift clustering algorithm;
the clustering operation is executed on all the target getting-on sites based on the determined clustering algorithm to obtain the central point position of the area where the place matched with the target user is located, and the method comprises the following steps:
selecting the position of any one target boarding station from all the target boarding stations as a circle center, and determining a target circular area based on the circle center and the radius which is a preset distance value;
calculating mean vehicle-entering station vectors corresponding to all the target vehicle-entering stations in the target circular area, and judging whether the mean vehicle-entering station vectors meet the determined convergence condition;
when the mean vehicle-entering station vector is judged to meet the convergence condition, determining that the position corresponding to the mean vehicle-entering station vector is the central point position of the area where the point matched with the target user is located;
when the average vehicle-mounted station vector is judged not to meet the convergence condition, taking the vector end point of the average vehicle-mounted station vector as a new circle center, and repeatedly executing the steps of determining a target circular area based on the circle center and taking a preset distance value as a radius; and calculating the mean vehicle-entering station vectors corresponding to all the target vehicle-entering stations in the target circular area, and judging whether the mean vehicle-entering station vectors meet the determined convergence condition.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the calculating a mean boarding station vector corresponding to all the target boarding stations in the target circular region includes:
determining a boarding station vector corresponding to each target boarding station in the target circular area by taking the position of the circle center as a vector starting point and the position of each target boarding station in the target circular area as a vector terminal point;
and calculating the mean value of all the boarding station vectors in the target circular area, and taking the mean value as the mean value boarding station vector corresponding to all the target boarding stations in the target circular area.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, the target time period includes a first time period or a second time period, where a time of the first time period is earlier than a time of the second time period;
when the target time period is the first time period, the area where the place matched with the target user is located is the area where the target user is located; and when the target time period is the second time period, the area where the place matched with the target user is located is the area where the target user works.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, when the central point position of the area where the location matched with the target user is located includes a first central point position of the area where the place where the target user is located and a second central point position of the area where the place where the target user is located, and the clustering operation is performed on all the target pick-up sites based on the determined clustering algorithm, and after the central point position of the area where the location matched with the target user is located is obtained, the method further includes:
determining all travel route schemes matched with the first central point position and the second central point position according to the first central point position and the second central point position;
the method further comprises the following steps:
determining the travel demand of the target user, wherein the travel demand of the target user comprises the travel time saving demand of the target user or the travel cost saving demand of the target user;
and screening a target travel route scheme matched with the travel demand of the target user from all the travel route schemes, and pushing the target travel route scheme to a user terminal corresponding to the target user.
As an optional implementation manner, in the first aspect of the embodiment of the present invention, after determining, according to all the collected travel records, a boarding station corresponding to an earliest travel record in the several days in the target time period to obtain several target boarding stations, and performing a clustering operation on all the target boarding stations based on the determined clustering algorithm to obtain a center point position of an area where a place matched with the target user is located, the method further includes:
inquiring the geographical position of each target getting-on station, and calculating the position relative density of the geographical position of each target getting-on station;
performing sorting operation on the position relative densities of the geographic positions of all the target boarding stations from small to large to obtain the sorted position relative densities;
and deleting the target getting-on stations with the relative position densities ranked before a preset name from all the target getting-on stations according to the ranked relative position densities to obtain the deleted target getting-on stations, and triggering and executing the determined clustering algorithm to perform clustering operation on all the target getting-on stations to obtain the operation of the central point position of the area where the place matched with the target user is located.
The second aspect of the embodiments of the present invention discloses a device for determining a relevant location of a user, where the device includes:
the system comprises an acquisition module, a storage module and a display module, wherein the acquisition module is used for acquiring travel records of a certain target user in a target time period of each day in a plurality of days;
the determining module is used for determining the getting-on station corresponding to the earliest travel record in the target time period in the plurality of days according to all the collected travel records to obtain a plurality of target getting-on stations;
the clustering module is used for performing clustering operation on all the target getting-on sites based on the determined clustering algorithm to obtain the central point position of the area where the place matched with the target user is located;
the area where the place matched with the target user is located comprises the area where the place where the target user is located or the area where the place where the target user is located.
As an optional implementation manner, in the second aspect of the embodiment of the present invention, the clustering algorithm includes a Mean Shift clustering algorithm;
the clustering module performs clustering operation on all the target getting-on stations based on the determined clustering algorithm, and a mode of obtaining the central point position of the area where the place matched with the target user is located is specifically as follows:
selecting the position of any one target boarding station from all the target boarding stations as a circle center, and determining a target circular area based on the circle center and the radius which is a preset distance value;
calculating mean vehicle-entering station vectors corresponding to all the target vehicle-entering stations in the target circular area, and judging whether the mean vehicle-entering station vectors meet the determined convergence condition;
when the mean vehicle-entering station vector is judged to meet the convergence condition, determining that the position corresponding to the mean vehicle-entering station vector is the central point position of the area where the point matched with the target user is located;
when the average vehicle-mounted station vector is judged not to meet the convergence condition, taking the vector end point of the average vehicle-mounted station vector as a new circle center, and repeatedly executing the steps of determining a target circular area based on the circle center and taking a preset distance value as a radius; and calculating the mean vehicle-entering station vectors corresponding to all the target vehicle-entering stations in the target circular area, and judging whether the mean vehicle-entering station vectors meet the determined convergence condition.
As an optional implementation manner, in the second aspect of the embodiment of the present invention, the specific manner of calculating the mean boarding station vector corresponding to all the target boarding stations in the target circular region by the clustering module is as follows:
determining a boarding station vector corresponding to each target boarding station in the target circular area by taking the position of the circle center as a vector starting point and the position of each target boarding station in the target circular area as a vector terminal point;
and calculating the mean value of all the boarding station vectors in the target circular area, and taking the mean value as the mean value boarding station vector corresponding to all the target boarding stations in the target circular area.
As an optional implementation manner, in the second aspect of the embodiment of the present invention, the target time period includes a first time period or a second time period, where the time of the first time period is earlier than the time of the second time period;
when the target time period is the first time period, the area where the place matched with the target user is located is the area where the target user is located; and when the target time period is the second time period, the area where the place matched with the target user is located is the area where the target user works.
As an optional implementation manner, in the second aspect of the embodiment of the present invention, the determining module is further configured to, when the central point position of the area where the location matched with the target user is located includes a first central point position of the area where the place where the target user is located and a second central point position of the area where the place where the target user is located, and after the clustering module performs a clustering operation on all the target boarding sites based on the determined clustering algorithm to obtain the central point positions of the area where the location matched with the target user is located, determine all the travel route plans matched with the first central point position and the second central point position according to the first central point position and the second central point position;
the determining module is further configured to determine a travel demand of the target user, where the travel demand of the target user includes a travel time saving demand of the target user or a travel cost saving demand of the target user;
and, the apparatus further comprises:
the screening module is used for screening a target trip route scheme matched with the trip demand of the target user from all the trip route schemes;
and the pushing module is used for pushing the target trip route scheme to the user terminal corresponding to the target user.
As an optional implementation manner, in the second aspect of the embodiment of the present invention, the apparatus further includes:
the query module is used for querying the geographical position of each target getting-on station before the determining module determines the getting-on station corresponding to the earliest travel record in the plurality of days in the target time period according to all the collected travel records to obtain a plurality of target getting-on stations and the clustering module performs clustering operation on all the target getting-on stations based on the determined clustering algorithm to obtain the position of the central point of the area where the place matched with the target user is located;
the calculation module is used for calculating the position relative density of the geographical position of each target boarding station;
the sorting module is used for performing sorting operation on the position relative densities of the geographic positions of all the target boarding stations from small to large to obtain the sorted position relative densities;
and the optimization module is used for deleting the target getting-on stations with the relative position densities ordered before a preset name from all the target getting-on stations according to the ordered relative position densities to obtain the deleted target getting-on stations, and triggering the clustering module to execute the clustering operation on all the target getting-on stations based on the determined clustering algorithm to obtain the operation of the central point position of the area where the place matched with the target user is located.
A third aspect of the present invention discloses another user's relevant location determination apparatus, the apparatus comprising:
a memory storing executable program code;
a processor coupled with the memory;
the processor calls the executable program code stored in the memory to execute the relevant location determining method of the user disclosed by the first aspect of the invention.
In a fourth aspect, the present invention discloses a computer-readable storage medium storing computer instructions for executing the method for determining a relevant location of a user disclosed in the first aspect of the present invention when the computer instructions are called.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
the embodiment of the invention discloses a method and a device for determining a relevant place of a user, wherein the method comprises the following steps: collecting travel records of a certain target user in a target time period of a plurality of days each day, and determining a boarding station corresponding to the earliest travel record in the target time period in the plurality of days according to all the collected travel records to obtain a plurality of target boarding stations; performing clustering operation on all target getting-on sites based on the determined clustering algorithm to obtain the central point position of the area where the place matched with the target user is located; the area where the place matched with the target user is located comprises the area where the place where the target user is located or the area where the place where the target user is located. Therefore, after the travel records of the user in the same time period every day in a plurality of days are acquired, the boarding sites corresponding to the earliest travel records in the same time period every day are acquired from all the travel records, and the clustering operation is performed on the boarding sites corresponding to all the earliest travel records, so that the central point position of the residence or working place of the accurate user can be acquired, and the method and the device are favorable for providing more accurate reference basis for improving the operation service of urban public transport, thereby improving the layout accuracy of the urban public transport network, improving the travel efficiency of people and relieving traffic congestion.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1 is a schematic flow chart of a method for determining a relevant location of a user according to an embodiment of the present invention;
FIG. 2 is a flow chart illustrating another method for determining a relevant location of a user according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a relevant location determining apparatus for a user according to an embodiment of the present invention;
FIG. 4 is a schematic structural diagram of another user relevant location determining apparatus according to an embodiment of the present invention;
fig. 5 is a schematic structural diagram of another related location determining apparatus for a user according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," and the like in the description and claims of the present invention and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, apparatus, product, or apparatus that comprises a list of steps or elements is not limited to those listed but may alternatively include other steps or elements not listed or inherent to such process, method, product, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The invention discloses a method and a device for determining relevant places of a user, which can acquire boarding sites corresponding to earliest travel records in the same time period every day from all the travel records after the travel records of the user in the same time period every day are acquired for a plurality of days, perform clustering operation on the boarding sites corresponding to the earliest travel records every day, acquire the central point position of a precise residence or working place of the user, and are beneficial to providing more accurate reference basis for improving the operation service of urban public transport, thereby improving the layout accuracy of an urban public transport network, improving the travel efficiency of people and relieving traffic jam. The following are detailed below.
Example one
Referring to fig. 1, fig. 1 is a flowchart illustrating a method for determining a relevant location of a user according to an embodiment of the present invention. The method for determining the relevant location of the user described in fig. 1 can be applied to urban public transport layout terminal equipment. As shown in fig. 1, the method for determining a relevant location of a user may include the steps of:
101. travel records of a certain target user in a target time period of several days are collected.
In the embodiment of the invention, the target user is any user who travels at ordinary times.
In this embodiment of the present invention, optionally, the target time period includes a first time period or a second time period, where the time of the first time period is earlier than the time of the second time period, for example: the target time period includes a morning time period (8:00-11:00) or an afternoon time period (14:00-18: 00).
In the embodiment of the invention, the plurality of days can be continuous days or discontinuous days.
In the embodiment of the invention, the travel record comprises the boarding station of the target user, and further comprises the boarding time of the target user. Still further optionally, the travel record further includes a boarding frequency of each boarding station of all boarding stations for several days.
102. And determining the getting-on station corresponding to the earliest travel record in the target time period in a plurality of days according to all the collected travel records to obtain a plurality of target getting-on stations.
103. And performing clustering operation on all target getting-on sites based on the determined clustering algorithm to obtain the position of the central point of the area where the place matched with the target user is located.
In this embodiment of the present invention, optionally, the clustering algorithm includes at least one of a Mean Shift clustering algorithm, a density-based clustering algorithm, and a coacervation hierarchical clustering algorithm, or a combination of multiple algorithms.
In the embodiment of the invention, the area where the place matched with the target user is located comprises the area where the place where the target user is located or the area where the place where the target user is located.
In the embodiment of the present invention, optionally, when the target time period is the first time period, the area where the place matched with the target user is located is the area where the place where the target user is located; and when the target time period is the second time period, the area where the place matched with the target user is located is the area where the work place of the target user is located.
It can be seen that, by implementing the method for determining relevant places of the user described in fig. 1, after the travel records of the user in the same time period every day are collected for several days, the boarding sites corresponding to the earliest travel records in the same time period every day are obtained from all the travel records, and the clustering operation is performed on the boarding sites corresponding to all the earliest travel records, so that the central point position of the accurate residence or working place of the user can be obtained, which is beneficial to providing a more accurate reference for improving the operation service of urban public transportation, thereby improving the layout accuracy of the urban public transportation network, improving the travel efficiency of people, and alleviating traffic congestion.
In an alternative embodiment, the clustering algorithm comprises a Mean Shift clustering algorithm; optionally, performing a clustering operation on all target boarding stations based on the determined clustering algorithm to obtain a central point position of an area where a place matched with the target user is located, including:
selecting the position of any one target boarding station from all target boarding stations as a circle center, and determining a target circular area based on the circle center and the radius of the preset distance value (for example, 100 meters);
calculating mean boarding station vectors corresponding to all target boarding stations in the target circular area based on the circle center, and judging whether the mean boarding station vectors meet the determined convergence condition;
and when the mean vehicle-entering station vector meets the convergence condition, determining the position corresponding to the mean vehicle-entering station vector as the position of the central point of the area where the point matched with the target user is located.
In the optional embodiment, optionally, when it is determined that the average vehicle station vector does not satisfy the convergence condition, determining a target circular area by taking a vector endpoint of the average vehicle station vector as a new circle center and repeatedly executing the process based on the circle center and the preset distance value as a radius; and calculating the average vehicle-entering station vectors corresponding to all target vehicle-entering stations in the target circular area, and judging whether the average vehicle-entering station vectors meet the determined convergence condition.
In this optional embodiment, optionally, when the absolute value of the station vector on the average is less than or equal to the determined value, for example: and 30 meters, which means that the average station-on-vehicle vector meets the convergence condition.
In this optional embodiment, it should be noted that, when the absolute value of the average boarding station vector obtained by the last iteration is still not smaller than the determined value, the position corresponding to the average boarding station vector obtained by the last iteration is determined to be the position of the center point of the area where the location matched with the target user is located. This ensures that the location of the centre point of the area in which the user's place of residence or work is located is determined.
Therefore, in the optional embodiment, whether the mean vehicle-loading station vector corresponding to all vehicle-loading stations in the circular area meets the convergence condition is judged, if yes, the terminal point corresponding to the mean vehicle-loading station vector is directly determined to be the position of the central point of the area where the user resides or works, the accuracy and the reliability of determining the position of the central point of the area where the user resides or works can be improved, and therefore more accurate reference basis is further provided for improving the operation service of urban public transport; if the average value does not meet the requirement, the end point corresponding to the vehicle station vector on the average value is taken as a new circle center, the determination of the position of the central point of the area where the user resides or the work place is located is continuously carried out, and the determination probability of the position of the central point of the area where the user resides or the work place is located can be improved.
In another optional embodiment, calculating a mean boarding station vector corresponding to all target boarding stations in the target circular region based on the circle center includes:
determining a boarding station vector corresponding to each target boarding station in the target circular area by taking the position of the circle center as a vector starting point and the position of each target boarding station in the target circular area as a vector terminal point;
and calculating the mean value of all boarding station vectors in the target circular area, and taking the mean value as the mean value boarding station vector corresponding to all target boarding stations in the target circular area.
In this optional embodiment, optionally, the mean boarding station vector corresponding to all target boarding stations in the target circular region may be calculated by the following formula:
Figure BDA0002908424450000101
Figure BDA0002908424450000102
in the formula, MhA mean pick-up station vector, S, corresponding to all the pick-up stations of the target in the circular area of the targeth(x) Is a target circular area, h is the radius of the target circular area, k is the number of target boarding stations falling into the target circular area among all the target boarding stations, xiThe ith target getting-on station is defined, and x is the circle center of the target circular area; y is the set of target pick-up stations that fall within the target circular area.
It can be seen that, in the alternative embodiment, after the circular area is determined, the position of the circle center is used as a vector starting point, the position of the boarding station in the circular area is used as a vector terminal, and the mean value of the boarding station vectors corresponding to each boarding station is calculated as the mean value boarding station vector corresponding to all the boarding stations in the circular area, so that the determination of the mean value boarding station vector can be realized, the determination accuracy of the mean value boarding station vector is improved, and the determination accuracy of the position of the central point of the area where the user resides or works is further improved.
In this optional embodiment, optionally, the boarding frequency of each target boarding station in the plurality of target boarding stations is calculated, and the weight value of each target boarding station is determined according to the boarding frequency of each target boarding station. At this time, optionally, determining a boarding station vector corresponding to each target boarding station in the target circular region includes:
and determining a boarding station vector corresponding to each target boarding station in the target circular area according to the weight value of each target boarding station.
In this alternative embodiment, M is as described abovehThe calculation formula of (a) is as follows:
Figure BDA0002908424450000111
in the formula, miIs the weighted value of the ith target getting-on station, and miAnd the sum of the weight values of all the target boarding stations is equal to or more than 0, and the sum of the weight values of all the target boarding stations is equal to 1.
Therefore, in the optional embodiment, the weight value of each boarding station in the circular area can be calculated, and the boarding station vector corresponding to each boarding station is calculated by combining the corresponding weight values, so that the calculation accuracy and reliability of the boarding station vector corresponding to each boarding station can be improved, the calculation accuracy and reliability of the mean boarding station vector corresponding to all the boarding stations in the circular area can be improved, and the determination accuracy of the central point position of the area where the user resides or works is further improved.
In yet another alternative embodiment, when the center point position of the area where the location matched with the target user is located includes a first center point position of the area where the target user's residence is located and a second center point position of the area where the target user's workplace is located, and after the determined clustering operation is performed on all target boarding sites based on the determined clustering algorithm, and the center point position of the area where the location matched with the target user is located is obtained, the method for determining the relevant location of the user may further include the following steps:
determining all travel route schemes matched with the first central point position and the second central point position according to the first central point position and the second central point position;
the relevant location determination method of the user may further include the steps of:
determining the travel demand of a target user, wherein the travel demand of the target user comprises the travel time saving demand of the target user or the travel cost saving demand of the target user;
and screening a target trip route scheme matched with the trip demand of the target user from all trip route schemes, and pushing the target trip route scheme to a user terminal corresponding to the target user.
Therefore, after the central point position of the area where the user resides and the central point position of the place where the user resides are determined, the alternative embodiment can determine the travel route scheme between the user residence place and the place where the user resides; furthermore, the travel route scheme required by the user is matched for the user according to the travel time-saving or cost-saving requirement of the user, the user does not need to manually inquire, the personalized travel route scheme can be matched for the user, the matching accuracy and efficiency of the travel route scheme required by the user are improved, and the travel convenience of the user is further improved.
In yet another optional embodiment, before the target travel route scheme matched with the travel demand of the target user is screened from all travel route schemes, the method for determining the relevant location of the user may further include the following steps:
positioning the geographical position of a target user;
the method for screening the target travel route schemes matched with the travel demands of the target users from all the travel route schemes comprises the following steps:
and screening a target travel route scheme matched with the travel demand of the target user from all the travel route schemes according to the geographical position of the target user.
Therefore, in the optional embodiment, the geographical position of the user is located, and the trip route scheme matched with the trip demand of the user is matched for the user by combining the geographical position of the user, so that the accuracy and efficiency of matching the trip route scheme required by the user can be further improved.
Example two
Referring to fig. 2, fig. 2 is a schematic flowchart illustrating another method for determining a relevant location of a user according to an embodiment of the present invention. The method for determining the relevant location of the user described in fig. 2 can be applied to the urban public transport layout terminal device. As shown in fig. 2, the method for determining a relevant location of a user may include the steps of:
201. travel records of a certain target user in a target time period of several days are collected.
202. And determining the getting-on station corresponding to the earliest travel record in the target time period in a plurality of days according to all the collected travel records to obtain a plurality of target getting-on stations.
203. And inquiring the geographical position of each target boarding station, and calculating the position relative density of the geographical position of each target boarding station.
204. And performing sorting operation on the position relative densities of the geographic positions of all the target boarding stations from small to large to obtain the sorted position relative densities.
205. And according to the sorted relative densities of all the positions, deleting the target boarding stations with the relative densities sorted before the preset name (for example, the boarding stations sorted at the top 3) from all the target boarding stations to obtain the deleted target boarding stations.
206. And performing clustering operation on all the deleted target getting-on stations based on the determined clustering algorithm to obtain the central point position of the area where the point matched with the target user is located.
Therefore, according to the embodiment of the invention, after the boarding station corresponding to the earliest travel record in a plurality of days is obtained, the boarding station with a smaller relative position density is further deleted from the boarding station corresponding to the earliest travel record, so that the calculation amount of the irrelevant boarding station can be reduced, the clustering operation is performed on the remaining boarding stations, the calculation amount of the clustering operation can be reduced, and the calculation efficiency of the clustering operation is improved under the condition of ensuring the calculation accuracy of the clustering operation, so that the determination efficiency of the position of the central point of the position of the area where the user residence or work place is located is improved under the condition of ensuring the determination accuracy of the position of the central point of the position of the area where the user residence or work place is located.
In the embodiment of the present invention, please refer to the detailed description of steps 101 to 103 in the first embodiment for the related description of steps 201, 202, and 206, which is not repeated herein.
It can be seen that, by implementing the method for determining relevant places of the user described in fig. 2, after travel records of the user in the same time period every day are collected for a plurality of days, getting a boarding site corresponding to an earliest travel record in the same time period every day from all the travel records, and performing clustering operation on the boarding sites corresponding to all the earliest travel records, so that a central point position of a precise residence or working place of the user can be obtained, and a more accurate reference basis is provided for improving operation services of urban public transportation, thereby improving layout accuracy of an urban public transportation network, improving travel efficiency of people, and alleviating traffic congestion; the calculation amount of the boarding station which is irrelevant can be reduced, the calculation amount of the clustering operation can be reduced, and the calculation efficiency of the clustering operation is improved under the condition that the calculation accuracy of the clustering operation is ensured, so that the determination efficiency of the central point position of the area where the user inhabitation place or the work place is located is improved under the condition that the determination accuracy of the central point position of the position where the user inhabitation place or the work place is located is ensured.
In an optional embodiment, the method for determining the relevant location of the user may further include the steps of:
in the process of deleting the target getting-on station before the preset name, judging whether the getting-on frequency of the target getting-on station before the preset name is less than or equal to the determined getting-on frequency threshold value or not;
when the number of the boarding frequency thresholds is judged to be less than or equal to the boarding frequency threshold, triggering and executing the determined clustering algorithm to perform clustering operation on all deleted target boarding stations to obtain the operation of the central point position of the area where the place matched with the target user is located;
in this optional embodiment, optionally, when it is determined that the number of boarding frequency is not less than or equal to the threshold value of boarding frequency, the operation of performing the clustering operation on all target boarding stations based on the determined clustering algorithm is triggered to obtain the center point position of the area where the point matched with the target user is located.
Therefore, in the optional embodiment, by judging whether the boarding station with the smaller relative position density is smaller, if so, deleting the boarding station with the smaller relative position density, and if not, directly performing clustering operation on all the boarding stations recorded at the earliest trip, the calculation accuracy and reliability of the clustering operation can be further improved, so that the determination accuracy and reliability of the position of the central point of the area where the user resides or the work place is located can be further improved.
EXAMPLE III
Referring to fig. 3, fig. 3 is a schematic structural diagram of a device for determining a relevant location of a user according to an embodiment of the present invention. The relevant location determining apparatus of the user described in fig. 3 may be applied to an urban public transportation layout terminal device, and the embodiment of the present invention is not limited thereto. As shown in fig. 3, the relevant location determining apparatus of the user may include an acquisition module 301, a determination module 302, and a clustering module 303, wherein:
the collection module 301 is configured to collect travel records of a certain target user in a target time period of each day.
The determining module 302 is configured to determine, according to all the collected travel records, a boarding station corresponding to the earliest travel record in the target time period in several days, so as to obtain several target boarding stations.
And the clustering module 303 is configured to perform clustering operation on all target boarding stations based on the determined clustering algorithm to obtain a center point position of an area where a place matched with the target user is located.
In the embodiment of the invention, the area where the place matched with the target user is located comprises the area where the place where the target user is located or the area where the place where the target user is located.
The target time period includes a first time period or a second time period, wherein the time of the first time period is earlier than the time of the second time period.
In the embodiment of the present invention, optionally, when the target time period is the first time period, the area where the place matched with the target user is located is the area where the place where the target user is located; and when the target time period is the second time period, the area where the place matched with the target user is located is the area where the work place of the target user is located.
It can be seen that, by implementing the device for determining relevant places of the user described in fig. 3, after the travel records of the user in the same time period every day are collected for a plurality of days, the boarding sites corresponding to the earliest travel records in the same time period every day are obtained from all the travel records, and the clustering operation is performed on the boarding sites corresponding to all the earliest travel records, so that the central point position of the residence or working place of the accurate user can be obtained, which is beneficial to providing a more accurate reference for improving the operation service of urban public transportation, thereby improving the layout accuracy of the urban public transportation network, improving the travel efficiency of people, and alleviating traffic congestion.
In an optional embodiment, the clustering algorithm includes a Mean Shift clustering algorithm, and as shown in fig. 3, the clustering module 303 performs a clustering operation on all target boarding stations based on the determined clustering algorithm, and a manner of obtaining a central point position of an area where a place matched with the target user is located is specifically as follows:
selecting the position of any target boarding station from all target boarding stations as a circle center, and determining a target circular area based on the circle center and the radius of the preset distance value;
calculating mean vehicle-entering station vectors corresponding to all target vehicle-entering stations in the target circular area, and judging whether the mean vehicle-entering station vectors meet the determined convergence condition;
when the mean vehicle-entering station vector is judged to meet the convergence condition, determining that the position corresponding to the mean vehicle-entering station vector is the position of the central point of the area where the point matched with the target user is located;
when the average vehicle-mounted station vector does not meet the convergence condition, taking the vector end point of the average vehicle-mounted station vector as a new circle center, and repeatedly executing the steps of determining a target circular area based on the circle center and taking a preset distance value as a radius; and calculating the average vehicle-entering station vectors corresponding to all target vehicle-entering stations in the target circular area, and judging whether the average vehicle-entering station vectors meet the determined convergence condition.
It can be seen that, by implementing the device for determining relevant places of a user described in fig. 3, whether the mean boarding station vector corresponding to all boarding stations in the circular area meets the convergence condition can be judged, and if so, the terminal point corresponding to the mean boarding station vector is directly determined to be the central point position of the area where the user resides or works, so that the accuracy and reliability of determining the central point position of the area where the user resides or works can be improved, and further, the device is favorable for providing a more accurate reference basis for improving the operation service of urban public transport; if the average value does not meet the requirement, the end point corresponding to the vehicle station vector on the average value is taken as a new circle center, the determination of the position of the central point of the area where the user resides or the work place is located is continuously carried out, and the determination probability of the position of the central point of the area where the user resides or the work place is located can be improved.
In another alternative embodiment, as shown in fig. 3, the specific way for the clustering module 303 to calculate the mean boarding station vector corresponding to all the target boarding stations in the target circular region is as follows:
determining a boarding station vector corresponding to each target boarding station in the target circular area by taking the position of the circle center as a vector starting point and the position of each target boarding station in the target circular area as a vector terminal point;
and calculating the mean value of all boarding station vectors in the target circular area, and taking the mean value as the mean value boarding station vector corresponding to all target boarding stations in the target circular area.
It can be seen that, by implementing the relevant location determining apparatus for the user described in fig. 3, after the circular area is determined, the location of the circle center is used as a vector starting point, the location of the boarding station in the circular area is used as a vector ending point, and the mean value of the boarding station vectors corresponding to each boarding station is calculated as the mean value boarding station vector corresponding to all the boarding stations in the circular area, so that the determination of the mean value boarding station vector can be achieved, and the determination accuracy of the mean value boarding station vector is improved, thereby further improving the determination accuracy of the location of the central point of the area where the user resides or works.
In yet another alternative embodiment, as shown in fig. 4, the relevant location determining apparatus of the user may further include: a filtering module 304 and a pushing module 305, wherein:
the determining module 302 is further configured to, when the center point position of the area where the location matched with the target user is located includes a first center point position of the area where the target user is located and a second center point position of the area where the target user is located, perform, at the clustering module, clustering operation on all target boarding sites based on the determined clustering algorithm to obtain the center point position of the area where the location matched with the target user is located, and then determine all travel route schemes matched with the first center point position and the second center point position according to the first center point position and the second center point position.
The determining module 302 is further configured to determine a travel demand of the target user, where the travel demand of the target user includes a travel time saving demand of the target user or a travel cost saving demand of the target user.
And a screening module 304, configured to screen a target travel route plan matching the travel demand of the target user from all travel route plans.
The pushing module 305 is configured to push the target trip route scheme to the user terminal corresponding to the target user.
It can be seen that, implementing the relevant location determining apparatus for the user described in fig. 4 can also determine the travel route plan between the user's residence and the work place after determining the central point position of the area where the user resides and the central point position of the work place; furthermore, the travel route scheme required by the user is matched for the user according to the travel time-saving or cost-saving requirement of the user, the user does not need to manually inquire, the personalized travel route scheme can be matched for the user, the matching accuracy and efficiency of the travel route scheme required by the user are improved, and the travel convenience of the user is further improved.
In yet another alternative embodiment, as shown in fig. 4, the relevant location determining apparatus of the user may further include: a filtering module 304 and a pushing module 305, wherein:
the query module 306 is configured to query the geographical location of each target boarding station before the determining module 302 determines the boarding station corresponding to the earliest travel record in the target time period in several days according to all the collected travel records to obtain several target boarding stations, and the clustering module 303 performs clustering operation on all the target boarding stations based on the determined clustering algorithm to obtain the central point location of the area where the place matched with the target user is located.
And the calculating module 307 is configured to calculate a position relative density of the geographic position where each target boarding station is located.
And the sorting module 308 is configured to perform a sorting operation on the position relative densities of the geographic positions where all the target boarding stations are located according to the sequence from small to large, so as to obtain the sorted position relative densities.
And the optimizing module 309 is configured to delete the target getting-on station with the position relative density ranked before the preset rank from all the target getting-on stations according to the sorted all the position relative densities, to obtain a deleted target getting-on station, and trigger the clustering module 303 to perform the clustering operation on all the target getting-on stations based on the determined clustering algorithm, to obtain an operation on a center point position of an area where a place matched with the target user is located. At this time, the clustering operation performed on all the target boarding stations is to perform the clustering operation on the boarding stations with low relative density of deletion positions.
It can be seen that, by implementing the device for determining a relevant location of a user described in fig. 4, after the boarding station corresponding to the earliest travel record in a period of several days is obtained, the boarding station with a relatively low relative density of locations is further deleted from the boarding station corresponding to the earliest travel record, so that the amount of computation of the insignificant boarding stations can be reduced, then the clustering operation is performed on the remaining boarding stations, the amount of computation of the clustering operation can be reduced, and the computation efficiency of the clustering operation is improved under the condition that the computation accuracy of the clustering operation is ensured, so that the determination efficiency of the location of the central point of the location of the user residence or work place area is improved under the condition that the determination accuracy of the location of the central point of the location of the residence or work place area of the user is ensured.
Example four
Referring to fig. 5, fig. 5 is a related location determining apparatus for a user according to another embodiment of the disclosure. Among them, the relevant location determining apparatus of the user described in fig. 5 can be applied to the urban public transportation layout terminal device. As shown in fig. 5, the relevant location determining apparatus of the user may include:
a memory 501 in which executable program code is stored;
a processor 502 coupled to a memory 501;
the processor 502 calls the executable program code stored in the memory 501 for performing the operations of the relevant location determination method of the user described in the first embodiment or the second embodiment.
EXAMPLE five
An embodiment of the present invention discloses a computer-readable storage medium storing a computer program for electronic data exchange, wherein the computer program causes a computer to execute the operations of the relevant location determination method for a user described in the first or second embodiment.
EXAMPLE six
An embodiment of the present invention discloses a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to perform the operations of the relevant location determination method for a user described in the first or second embodiment.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above detailed description of the embodiments, those skilled in the art will clearly understand that the embodiments may be implemented by software plus a necessary general hardware platform, and may also be implemented by hardware. Based on such understanding, the above technical solutions may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, where the storage medium includes a Read-Only Memory (ROM), a Random Access Memory (RAM), a Programmable Read-Only Memory (PROM), an Erasable Programmable Read-Only Memory (EPROM), a One-time Programmable Read-Only Memory (OTPROM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a Compact Disc-Read-Only Memory (CD-ROM), or other disk memories, CD-ROMs, or other magnetic disks, A tape memory, or any other medium readable by a computer that can be used to carry or store data.
Finally, it should be noted that: the method and apparatus for determining a location associated with a user disclosed in the embodiments of the present invention are only preferred embodiments of the present invention, and are only used for illustrating the technical solutions of the present invention, rather than limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those skilled in the art; the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (10)

1. A method for determining a location of interest of a user, the method comprising:
collecting travel records of a certain target user in a target time period of a plurality of days each day, and determining a boarding station corresponding to the earliest travel record in the target time period in the plurality of days according to all the collected travel records to obtain a plurality of target boarding stations;
performing clustering operation on all the target getting-on stations based on the determined clustering algorithm to obtain the position of the central point of the area where the place matched with the target user is located;
the area where the place matched with the target user is located comprises the area where the place where the target user is located or the area where the place where the target user is located.
2. The method of claim 1, wherein the clustering algorithm comprises a Mean Shift clustering algorithm;
the clustering operation is executed on all the target getting-on sites based on the determined clustering algorithm to obtain the central point position of the area where the place matched with the target user is located, and the method comprises the following steps:
selecting the position of any one target boarding station from all the target boarding stations as a circle center, and determining a target circular area based on the circle center and the radius which is a preset distance value;
calculating mean vehicle-entering station vectors corresponding to all the target vehicle-entering stations in the target circular area, and judging whether the mean vehicle-entering station vectors meet the determined convergence condition;
when the mean vehicle-entering station vector is judged to meet the convergence condition, determining that the position corresponding to the mean vehicle-entering station vector is the central point position of the area where the point matched with the target user is located;
when the average vehicle-mounted station vector is judged not to meet the convergence condition, taking the vector end point of the average vehicle-mounted station vector as a new circle center, and repeatedly executing the steps of determining a target circular area based on the circle center and taking a preset distance value as a radius; and calculating the mean vehicle-entering station vectors corresponding to all the target vehicle-entering stations in the target circular area, and judging whether the mean vehicle-entering station vectors meet the determined convergence condition.
3. The method according to claim 2, wherein the calculating a mean boarding station vector corresponding to all the target boarding stations in the target circular region comprises:
determining a boarding station vector corresponding to each target boarding station in the target circular area by taking the position of the circle center as a vector starting point and the position of each target boarding station in the target circular area as a vector terminal point;
and calculating the mean value of all the boarding station vectors in the target circular area, and taking the mean value as the mean value boarding station vector corresponding to all the target boarding stations in the target circular area.
4. The method according to any one of claims 1 to 3, wherein the target time period comprises a first time period or a second time period, wherein the time of the first time period is earlier than the time of the second time period;
when the target time period is the first time period, the area where the place matched with the target user is located is the area where the target user is located; and when the target time period is the second time period, the area where the place matched with the target user is located is the area where the target user works.
5. The method according to claim 4, wherein when the center point position of the area where the location matched with the target user is located includes a first center point position of the area where the target user's residence is located and a second center point position of the area where the target user's workplace is located, and the clustering operation is performed on all the target pick-up sites based on the determined clustering algorithm, after the center point position of the area where the location matched with the target user is located is obtained, the method further comprises:
determining all travel route schemes matched with the first central point position and the second central point position according to the first central point position and the second central point position;
the method further comprises the following steps:
determining the travel demand of the target user, wherein the travel demand of the target user comprises the travel time saving demand of the target user or the travel cost saving demand of the target user;
and screening a target travel route scheme matched with the travel demand of the target user from all the travel route schemes, and pushing the target travel route scheme to a user terminal corresponding to the target user.
6. The method according to claim 1, 2, 3 or 5, wherein after the boarding station corresponding to the earliest travel record in the plurality of days in the target time period is determined according to all the collected travel records, and a plurality of target boarding stations are obtained, and the clustering operation is performed on all the target boarding stations based on the determined clustering algorithm, before the central point position of the area where the location matched with the target user is obtained, the method further comprises:
inquiring the geographical position of each target getting-on station, and calculating the position relative density of the geographical position of each target getting-on station;
performing sorting operation on the position relative densities of the geographic positions of all the target boarding stations from small to large to obtain the sorted position relative densities;
and deleting the target getting-on stations with the relative position densities ranked before a preset name from all the target getting-on stations according to the ranked relative position densities to obtain the deleted target getting-on stations, and triggering and executing the determined clustering algorithm to perform clustering operation on all the target getting-on stations to obtain the operation of the central point position of the area where the place matched with the target user is located.
7. A user's location-of-relevance determining apparatus, the apparatus comprising:
the system comprises an acquisition module, a storage module and a display module, wherein the acquisition module is used for acquiring travel records of a certain target user in a target time period of each day in a plurality of days;
the determining module is used for determining the getting-on station corresponding to the earliest travel record in the target time period in the plurality of days according to all the collected travel records to obtain a plurality of target getting-on stations;
the clustering module is used for performing clustering operation on all the target getting-on sites based on the determined clustering algorithm to obtain the central point position of the area where the place matched with the target user is located;
the area where the place matched with the target user is located comprises the area where the place where the target user is located or the area where the place where the target user is located.
8. The user's relevant location determining apparatus according to claim 7, wherein the clustering algorithm comprises a Mean Shift clustering algorithm;
the clustering module performs clustering operation on all the target getting-on stations based on the determined clustering algorithm, and a mode of obtaining the central point position of the area where the place matched with the target user is located is specifically as follows:
selecting the position of any one target boarding station from all the target boarding stations as a circle center, and determining a target circular area based on the circle center and the radius which is a preset distance value;
calculating mean vehicle-entering station vectors corresponding to all the target vehicle-entering stations in the target circular area, and judging whether the mean vehicle-entering station vectors meet the determined convergence condition;
when the mean vehicle-entering station vector is judged to meet the convergence condition, determining that the position corresponding to the mean vehicle-entering station vector is the central point position of the area where the point matched with the target user is located;
when the average vehicle-mounted station vector is judged not to meet the convergence condition, taking the vector end point of the average vehicle-mounted station vector as a new circle center, and repeatedly executing the steps of determining a target circular area based on the circle center and taking a preset distance value as a radius; and calculating the mean vehicle-entering station vectors corresponding to all the target vehicle-entering stations in the target circular area, and judging whether the mean vehicle-entering station vectors meet the determined convergence condition.
9. A user's location-of-relevance determining apparatus, the apparatus comprising:
a memory storing executable program code;
a processor coupled with the memory;
the processor calls the executable program code stored in the memory to execute the user's place of relevance determination method according to any of claims 1-6.
10. A computer-storable medium that stores computer instructions that, when invoked, perform a user location-of-relevance determination method according to any one of claims 1-6.
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