CN113590674A - Travel purpose identification method, device, equipment and storage medium - Google Patents
Travel purpose identification method, device, equipment and storage medium Download PDFInfo
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Abstract
The application discloses a travel purpose identification method, a travel purpose identification device, travel purpose identification equipment and a storage medium, and relates to the field of big data. The specific implementation scheme is as follows: the method comprises the steps of obtaining travel time and a destination in travel information, obtaining positioning information closest to the destination, determining a plurality of POIs (point of interest) located in a preset range of the positioning information according to the positioning information, and determining a travel purpose from the POIs according to weight information of the POIs at the travel time. Therefore, the travel purpose is determined based on the weight information of the POIs determined by the positioning information closest to the travel destination of the resident, the technical problem that the travel purpose of the resident cannot be accurately determined due to the fact that the destination is a mixed land is solved, and the accuracy of identifying the travel purpose of the resident is improved.
Description
Technical Field
The application discloses a travel purpose identification method, a travel purpose identification device, travel purpose identification equipment and a storage medium, and relates to the technical field of data processing, in particular to the field of big data.
Background
Urban resident trip analysis is one of important research topics in the urban planning field. The reasonable degree of urban resource allocation is directly reflected by the travel behaviors of residents, and urban night life analysis is carried out; analyzing the park service radius; airport (station) passenger source analysis is an important content of travel behavior analysis. The aforesaid problems can be solved by analyzing the travel distance, travel time, and travel purpose of the resident.
Disclosure of Invention
The application provides a travel purpose identification method, a travel purpose identification device, travel purpose identification equipment and a storage medium.
According to an aspect of the present application, there is provided a travel purpose identification method, including:
acquiring travel information; wherein the travel information comprises travel time and destination;
obtaining positioning information closest to the destination;
determining a plurality of POIs (points of interest) positioned in a preset range of the positioning information according to the positioning information;
and determining a travel purpose from the POIs according to the weight information of the POIs at the travel time.
According to another aspect of the present application, there is provided a travel purpose identifying apparatus including:
the first acquisition module is used for acquiring travel information; wherein the travel information comprises travel time and destination;
the second acquisition module is used for acquiring the positioning information closest to the destination;
the first determining module is used for determining a plurality of POIs (points of interest) located in a preset range of the positioning information according to the positioning information;
and the second determining module is used for determining a travel purpose from the POIs according to the weight information of the POIs at the travel time.
According to another aspect of the present application, there is provided an electronic device including:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of one aspect.
According to another aspect of the present application, there is provided a non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of the above one aspect.
According to another aspect of the application, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the method of the above-mentioned aspect.
According to the technology of the application, the accuracy rate of travel purpose identification is improved.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present application, nor do they limit the scope of the present application. Other features of the present application will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not intended to limit the present application. Wherein:
fig. 1 is a schematic flow chart of a travel purpose identification method according to an embodiment of the present application;
fig. 2 is a schematic flowchart of another travel purpose identification method according to an embodiment of the present application;
FIG. 3 is a diagram illustrating an example of a prior rasterization provided by an embodiment of the present application;
FIG. 4 is a diagram illustrating an example of rasterization provided by an embodiment of the present application;
fig. 5 is a schematic flowchart of another travel purpose identification method according to an embodiment of the present application;
fig. 6 is an exemplary diagram of determining a grid in which positioning information is located according to an embodiment of the present application;
FIG. 7 is an example process of improved rasterization provided by embodiments of the present application;
fig. 8 is a schematic flowchart of another travel purpose identification method according to an embodiment of the present application;
fig. 9 is a flowchart illustrating a travel purpose identification method according to an embodiment of the present application;
FIG. 10 is a diagram illustrating the ratio of travel in a certain city;
FIG. 11 is a diagram illustrating the ratio of travel at a station;
FIG. 12 is a comparison of travel objectives in a city;
fig. 13 is a schematic structural diagram of an apparatus for identifying travel destinations according to an embodiment of the present application;
fig. 14 is a block diagram of an electronic device of a travel purpose identification method according to an embodiment of the present application.
Detailed Description
The following description of the exemplary embodiments of the present application, taken in conjunction with the accompanying drawings, includes various details of the embodiments of the application for the understanding of the same, which are to be considered exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present application. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
The travel purpose is mined as a more popular topic, most of the traditional methods are carried out based on an questionnaire mode, and the method has high precision, but the cost is high, only sampling can be carried out, and large-scale popularization cannot be carried out.
In the related art, POI is the most important factor for determining a travel purpose. For POI with single attribute, such as scenic spot, hospital, etc. As long as the resident's location points fall within these areas, it can be determined that the purpose of travel is travel or hospitalization. Most POI peripheral attributes are not unique, which poses difficulties in giving row-purpose decisions.
In order to improve accuracy of identifying travel purposes of residents, the travel purpose identification method comprises the steps of obtaining travel time and a destination in travel information, obtaining positioning information closest to the destination, determining a plurality of POIs (points of interest) located within a preset range of the positioning information according to the positioning information, and determining the travel purpose from the POIs according to weight information of the POIs at the travel time.
Travel purpose identification methods, apparatuses, devices, and storage media according to embodiments of the present application are described below with reference to the accompanying drawings.
Fig. 1 is a schematic flow chart of a travel purpose identification method provided in an embodiment of the present application.
The embodiment of the present application is exemplified in that the travel purpose identification method is configured in a travel purpose identification apparatus, and the travel purpose identification apparatus may be applied to any electronic device, so that the electronic device may perform a travel purpose identification function.
The electronic device can be a cloud device, a mobile device, a smart sound box and the like, and the mobile device can be a hardware device with various operating systems, such as a mobile phone, a tablet computer, a personal digital assistant, a wearable device, a vehicle-mounted device and the like.
As shown in fig. 1, the travel purpose identification method may include the steps of:
In the embodiment of the present application, the travel information is not limited to the travel event and the destination, and may further include a departure place, a travel distance, and the like, which are not limited herein.
For example, a certain resident goes from home to a company ten kilometers away in the morning, and it is seen that the travel information of the resident includes travel time, departure place, destination, and travel distance.
As a possible implementation manner, the positioning data of the residents may be acquired, and the acquired positioning data is spatially clustered according to a time sequence to obtain the travel information of the corresponding residents.
According to the technical scheme, the acquisition, storage, application and the like of the personal information of the related user are all in accordance with the regulations of related laws and regulations, and the customs of the public order is not violated.
In the embodiment of the application, the real-time positioning information of the equipment when a resident goes out can be obtained, so that the positioning information closest to the destination can be determined according to the real-time positioning information of the equipment.
The device when the resident goes out is a device accompanying the resident when the resident goes out, such as a mobile phone, an intelligent bracelet, a vehicle and the like.
Optionally, the device during traveling is equipped with an electronic map and has a positioning function, and a plurality of positioning data generated by the device can be acquired according to a set frequency when the positioning function is started. Illustratively, the positioning data includes time information of the track points, spatial information (e.g., position latitude and longitude), and other positioning attributes.
Alternatively, the positioning Information of the resident when the resident goes out may be determined by a GIS (Geographic Information System) so as to determine the positioning Information closest to the destination according to the positioning Information of the resident when the resident goes out.
And 103, determining a plurality of POIs (points of interest) within a preset range of the positioning information according to the positioning information.
Where a POI (Point of interest) is any non-geographically meaningful Point on a map, such as a shop, a bar, a gas station, a hospital, a station, a park, etc. Each POI contains four-sided information, respectively name, category, longitude, latitude.
Since the POI categories are various and the common types of travel orders are preferred, the POI categories need to be classified according to their own attributes. For example, shopping, catenaries, companies, residences, living services, cross-city transportation hubs, transportation facilities, educational training, medical, recreational, travel, primary and secondary schools, colleges, and others may be classified.
In order to solve the problem that the travel destination of a resident cannot be accurately determined due to the fact that the travel destination of the resident is a mixed land attribute area, such as eating, fitness, shopping and the like in a shopping mall, in the embodiment of the application, after the positioning information closest to the travel destination of the resident is determined, a plurality of POI (point of interest) located in a preset positioning information range are determined.
As an example, assuming that the destination of a certain resident who travels at 12 pm is a shopping mall, after the positioning information closest to the shopping mall is determined, all POIs within a range of 50 meters of the positioning information can be acquired.
In the present application, the preset range may be set according to a travel destination, for example, when the destination is a shopping mall, the preset range may be 50 meters, and when the destination is a cell, the preset range may be 100 meters, which is not limited herein.
And step 104, determining a travel purpose from the POIs according to the weight information of the POIs at the travel time.
In order to improve the accuracy of determining the travel purpose of the resident, after the plurality of POIs located within the preset range of the positioning information of the resident are determined, the weight information of the plurality of POIs at the travel time can be further determined, so that the travel purpose of the resident can be determined according to the POI with the largest weight information of the plurality of POIs at the travel time.
Continuing with the example in step 103, determining that the POIs located within 50 meters of the shopping mall are respectively a restaurant a, a gymnasium B and a supermarket C, and determining that the POI with the largest weight information is the restaurant a according to the weight information of the 3 POIs at the travel time, so that the travel purpose of the resident can be determined to be dining.
In the embodiment of the application, after the travel purpose of the resident is determined, deep research can be carried out on the travel condition of the urban population corresponding to the travel purpose of the resident in a certain city, if the urban public resource allocation is judged to be reasonable, the tourist population is analyzed, the city-crossing hospitalizing behavior, the travel behavior changes around the epidemic situation and the like.
According to the travel destination identification method, travel time and a destination in travel information are obtained, positioning information closest to the destination is obtained, a plurality of POIs (points of interest) located in a preset range of the positioning information are determined according to the positioning information, and a travel destination is determined from the POIs according to weight information of the POIs at the travel time. Therefore, the travel purpose is determined based on the weight information of the POIs determined by the positioning information closest to the travel destination of the resident, the technical problem that the travel purpose of the resident cannot be accurately determined due to the fact that the destination is a mixed land is solved, and the accuracy of identifying the travel purpose of the resident is improved.
In order to determine the occurrence purpose from a plurality of POIs according to the weight information of the plurality of POIs at the travel time in the foregoing embodiment, how to determine the weight information of the plurality of POIs at the travel time is described in detail below with reference to fig. 2, and fig. 2 is a schematic flow chart of another travel purpose identification method provided in the embodiment of the present application.
As shown in fig. 2, the travel purpose identification method may include the following steps:
In the embodiment of the present application, the implementation process of step 201 to step 203 may refer to the implementation process of step 101 to step 103 in the above embodiment, and details are not described here.
At step 204, a first frequency of POI being retrieved at travel time is determined.
In the embodiment of the present application, the average monthly retrieval number of each POI in a certain time period may be calculated, for example, the average monthly retrieval number of each POI between ten am and eleven am is determined. In addition, the total number of monthly searches for all POIs can also be determined.
Further, according to the average monthly retrieval number of each POI at the travel time and the total monthly retrieval number of all POIs, determining the first frequency of retrieval of each POI at the travel time.
The first Frequency may be TF (Term Frequency). The TF of each POI may be a ratio of the average number of searches per month of the POI at the time of travel to the total number of searches per month of the total POI.
As a possible implementation manner, for any POI, a central grid centered around the POI may be determined from a plurality of candidate grids divided by the map, and a plurality of grids corresponding to the POI may be determined according to the central grid and a peripheral grid surrounding the central grid.
Rasterization is a common means of processing spatiotemporal data. The related papers of travel purpose mining also basically calculate travel purposes of areas based on a rasterization method. However, the traditional calculation method based on the rectangular grid has some problems, for example, the large rectangular grid (1km/500m) can not truly reflect the distance relation between the positions. For example, fig. 3 is a grid with a side length of 1km, the upper point is a positioning point of a resident, the lower point is a POI, and it is obvious that the point location is closer to the grid where the POI is located, but the large rectangular grid algorithm divides the positioning point into grids of the POI area. In view of this, the grid can be divided into smaller areas, for example 20m, and then expanded based on the grid, as shown in the left diagram of fig. 4, which can solve the problem presented in fig. 3, in fact, simulating a circular area with a rectangle (square). However, in the rectangle at the center of the left image in fig. 4, the distance from the center point of the peripheral rectangle is not equal, and in order to solve this problem, the rectangle is replaced by a regular hexagon in the present application. The distances from the central regular hexagon to the central points of the peripheral hexagons are equal, the regular hexagon is closer to a circle, and the method has greater advantages in calculating the peripheral POI of the trip.
As an example, as shown in fig. 4, for any POI, the POI is expanded by a regular hexagon with the POI as the center, for example, the circumscribed circle of the regular hexagon has a radius of 20m, and as shown in the right side of fig. 4, the circle with an approximate circle radius of 100 m can be obtained by two circles.
At step 206, a second frequency of occurrence of each POI in the corresponding plurality of grids is determined.
Wherein, the second Frequency may be an IDF (Inverse text Frequency index).
In this embodiment of the application, after determining the multiple grids corresponding to each POI, a logarithm of a ratio of the total grid number to the grid number corresponding to each POI may be used as the second frequency.
And step 207, determining weight information of each POI in travel time according to the first frequency and the second frequency of each POI.
In this embodiment of the application, after the first frequency and the second frequency of each POI are determined, a product of the first frequency and the second frequency may be calculated to determine weight information of each POI at travel time.
It should be noted that, in the present application, the retrieval heat is used to calculate the weight information of each POI at the travel time, so that the accuracy of determining the weight information of each POI at the travel time is improved.
And step 208, determining a travel purpose from the POIs according to the weight information of the POIs at the travel time.
In the embodiment of the present application, the implementation process of step 208 may refer to the implementation process of step 104 in the foregoing embodiment, and is not described herein again.
In the embodiment of the application, after travel time and a destination included in travel information are acquired, positioning information closest to the destination is acquired, a plurality of POIs located within a preset range of the positioning information are determined according to the positioning information, a first frequency of each POI retrieved at the travel time, a plurality of grids corresponding to each POI and a second frequency of each POI appearing in the corresponding grids are determined, and weight information of each POI at the travel time is determined according to the first frequency and the second frequency of each POI, so that a travel purpose is determined from the POIs. Therefore, the weight information of each POI at the travel time is determined based on the searched heat degree of each POI at the travel time and the occurrence frequency of each POI in the corresponding grid, and the accuracy of the judgment of the travel purpose of the residents is improved.
In any of the above embodiments, when determining a plurality of POIs located within a preset range of the positioning information, the POIs included in each grid near the grid where the positioning information is located may be determined based on the POIs, which is described in detail below with reference to fig. 5, where fig. 5 is a flowchart of another travel purpose identification method provided in this embodiment of the present application.
As shown in fig. 5, the travel purpose identification method may include the following steps:
In the embodiment of the application, the map may be divided into a plurality of candidate grids, so that the grid where the positioning information is located is determined from the plurality of candidate grids according to the longitude and latitude included in the positioning information.
As an example, as shown in fig. 6, after the positioning information closest to the destination is obtained, it is determined that the resident is located at the positioning point L according to the positioning information, and the grid where the positioning point L is located is the grid where the positioning information is located.
In the embodiment of the application, for convenience of use of subsequent processes, the grids corresponding to each POI may be grouped and aggregated, and the aggregation value stores the weight information of the current grid and the weight information of the grid to which the current grid belongs.
For example, the grid of the positioning information in fig. 6 stores the weight information of POI components of p1-p5 contained in the self-extension. Since the grid in which the positioning information is located is in the grid after the grid in which p5 is located is expanded, the grid in which the positioning information is located also includes the weight information of the grid range with p5 as the center. Similarly, the weight information of p1-p4 is also included.
In the embodiment of the application, after the grid where the positioning information is located is determined, POIs included in each grid within a preset range of the grid where the positioning information is located can be determined as a plurality of POIs within the preset range of the positioning information.
As an example, as shown in fig. 6, after the grid where the positioning information is located is determined, the POIs included in each grid within two circles of the grid where the positioning information is located are determined to be p1 to p5, and then the 5 POIs p1 to p5 may be determined to be POIs within the preset range of the positioning information.
In the related technology, when the POI around the positioning point of the resident is determined, the travel purpose of the resident is determined by calculating the POI in the preset range around the positioning point and further searching information in time division by combining the POI.
As an example, as shown in fig. 7, POIs within a range of 100 meters around the positioning point L in fig. 7 are calculated to determine the purpose of travel from the POIs.
Because of the complex computation of KNN (k-Nearest Neighbor, proximity algorithm), the original problem has been engineered in this application to approximate a replacement circle using a hexagonal grid. In order to reduce the calculation amount, the problem of calculating the POI around the positioning point (4.5 hundred million) can be converted into the calculation of the positioning point of the trip around the POI (6000 million). And meanwhile, the POI transformation problem is further transformed, and a hexagon is used for replacing a circle as a final problem. In the final question, it may be convenient to calculate that p1 is closest to anchor point L. The grid included in p1 actually covers p1-p5, and thus, the purpose of travel is determined by integrating a plurality of POIs in the periphery, instead of considering only the nearest p 1.
In the embodiment of the application, a grid where positioning information is located is determined from a plurality of candidate grids divided by a map, and POIs included in each grid within a preset grid range from the positioning information are determined as a plurality of POIs within the preset positioning information range. Therefore, by determining the POIs around the positioning information and determining the travel purpose of the resident based on the weight information of the POIs at the travel time, the accuracy of travel purpose identification is improved.
In any of the above embodiments, when determining the positioning information closest to the destination, the positioning information may also be determined based on the resident information and the real-time positioning, which is described in detail below with reference to fig. 8, where fig. 8 is a flowchart illustrating a further travel purpose identification method provided in this embodiment of the present application.
As shown in fig. 8, the trip purpose identification method may further include the following steps:
In this embodiment of the present application, the implementation process of step 801 may participate in the implementation process of step 101 in the foregoing embodiment, and details are not described here.
In the embodiment of the present application, the resident information may be residence information, work place information, or the like.
Alternatively, resident information of the resident can be acquired by locating the resident for a long period of time. For example, assuming that a certain resident is located in a certain cell at night mostly, it can be determined that the cell is a resident address of the resident. Assuming that the location address of the working time of a certain resident is mostly at company a, it is possible to determine that company a is the information of the working place of the resident.
In the embodiment of the application, when the positioning information closest to the travel destination of the resident is obtained, the positioning information closest to the destination can be determined according to at least one of resident information and real-time positioning of the resident.
In a possible situation, during the travel of the resident, the real-time location of the resident can be obtained, and the real-time location closest to the destination is determined as the location information closest to the destination.
As an example, assuming that a resident goes from an origin a to a destination B, positioning information may be acquired in real time during travel of the resident, and a real-time positioning closest to the destination B is determined as the positioning information closest to the destination.
In another possible case, the positioning information closest to the destination may also be determined based on resident information of the resident.
In yet another possible case, during the travel of the resident, the real-time location closest to the destination may also be compared with the resident's resident information to simultaneously determine the location information closest to the destination from the resident's resident information and the real-time location.
As an example, assuming that the real-time location of the resident is located near the home, it may be determined that the location information closest to the destination is the home of the resident whose travel purpose is going home.
And 803, determining a plurality of POIs (points of interest) within a preset range of the positioning information according to the positioning information.
And step 804, determining a travel purpose from the multiple POIs according to the weight information of the multiple POIs at the travel time.
In this embodiment of the application, the implementation processes of step 803 and step 804 may participate in the implementation processes of step 103 and step 104 in the foregoing embodiments, and are not described herein again.
According to the travel destination identification method, after travel time and a destination of a resident are obtained, positioning information closest to the destination is determined according to at least one of resident information and real-time positioning, a plurality of POIs (points of interest) located within a preset range of the positioning information are determined according to the positioning information, and the travel destination is determined from the POIs according to weight information of the POIs at the travel time. Therefore, when the positioning information closest to the destination is determined to be resident information, the travel purpose of the resident can be directly determined, and when the positioning information closest to the destination is determined to be real-time positioning, the travel purpose can be determined based on the weight information of the POI determined by the positioning information closest to the travel destination of the resident, so that the technical problem that the travel purpose of the resident cannot be accurately determined due to the fact that the destination is a mixed land is solved, and the accuracy of identifying the travel purpose of the resident is improved.
As an example, as shown in fig. 9, fig. 9 is a flowchart illustrating a travel purpose identification method according to an embodiment of the present application. When judging the appearance purpose of a resident, the prepositive data is firstly acquired, wherein the prepositive data can comprise resident information and travel information. The resident information may be residence information, workplace information, and the like. The travel information may include a travel time, a travel distance, a departure place, and a destination. Further, the POIs in the map are classified into categories, such as shopping, cate, company, house, living service, cross-city traffic hub, transportation facility, education and training, medical treatment, entertainment, tourism, primary and secondary schools, colleges, and others. After the POIs are classified, one type of POIs own boundary number, the areas corresponding to the POIs are single, such as scenic spots, hospitals and the like, and the POIs do not need to participate in a grid expansion process.
Further, for each POI, calculating weight information corresponding to all categories of POI covered by the grid so as to determine a travel purpose from the POIs according to the weight information of each POI at travel time.
If the travel destination is the resident information, the travel destination of the resident can be directly judged according to the resident information. If the travel destination is not resident information, the travel destination can be determined according to the weight information of a plurality of POIs near the positioning information nearest to the travel destination at the travel time.
As an example, as shown in fig. 10, the trip-purpose data is mainly used to evaluate the trip-purpose proportion of the area, and the effects on the typical area and the city a are listed in fig. 10. As shown in fig. 10, the left side of the graph is the proportion of the number of the residents who go out for the purpose of travel on the working day of a certain technology park, the number of the residents who go out for the purpose of travel is the first, the number of the residents who go out for the purpose of travel is the second, and the like. In fig. 10, the middle graph is the proportion of the travel purpose of the same science and technology park on weekends, and it can be seen that the number of the residents on duty for the travel purpose is the first, the number of the residents on business for the travel purpose is the second, and the like. The right graph in fig. 10 is the proportion of eleven trips in the same science and technology park for trip purposes, and it can be seen that the number of residents on duty for trip purposes is the first, the number of residents on business for trip purposes is the second, and the like. It can be seen from fig. 10 that residents who travel to work and business in the scientific park have the most proportion.
For example, the occupancy of the residents for travel at a certain station is listed in fig. 11, and as can be seen from the left-hand graph in fig. 11, the occupancy of the residents for travel on working days at a certain station is the largest, and the occupancy of the travel for work is the second. As can be seen from the middle diagram in fig. 11, the percentage of residents who travel on weekends for the purpose of urban traffic is the largest, and the percentage of residents who travel home for the purpose of traveling is the second. As can be seen from the right-hand graph of fig. 11, the proportion of the number of residents who travel across cities is the largest for the eleven trip destinations at the same station, and the proportion of the number of residents who travel to work is the second. As can be seen from fig. 11, the number of residents who travel to cross city traffic in the station is the largest, and the number of people on holidays is more than on weekends and weekdays.
As an example, as shown in fig. 12, fig. 12 is a comparison graph of travel purposes of a certain city, namely comparison of travel purposes in 2014 and 2018, respectively, wherein as can be seen from fig. 12, the travel purpose of the city is that residents who go to and from work are most occupied.
In order to achieve the above embodiments, the present application provides an identification device for trip purposes.
Fig. 13 is a schematic structural diagram of an identification device for trip purposes according to an embodiment of the present application.
As shown in fig. 13, the trip purpose identifying apparatus 1300 may include: a first obtaining module 1301, a second obtaining module 1302, a first determining module 1303, and a second determining module 1304.
The first obtaining module 1301 is configured to obtain travel information; the travel information comprises travel time and a destination;
a second obtaining module 1302, configured to obtain positioning information closest to the destination;
the first determining module 1303 is configured to determine, according to the positioning information, a plurality of POI located within a preset range of the positioning information;
the second determining module 1304 is configured to determine a travel purpose from the multiple POIs according to weight information of the multiple POIs at a travel time.
Optionally, the travel purpose identifying apparatus 1300 may further include:
the third determining module is used for determining the first frequency of the POI to be retrieved at the travel time;
the fourth determining module is used for determining a plurality of grids corresponding to each POI;
a fifth determining module, configured to determine a second frequency of occurrence of each POI in the corresponding plurality of grids;
and the sixth determining module is used for determining the weight information of each POI in the travel time according to the first frequency and the second frequency of each POI.
Optionally, the fourth determining module may be further configured to:
for any POI, determining a central grid taking a POI as a center from a plurality of candidate grids divided by a map; and determining a plurality of grids corresponding to a POI according to the central grid and the peripheral grid surrounding the central grid.
Optionally, the first determining module 1303 may be further configured to:
determining a grid where the positioning information is located from a plurality of candidate grids divided by a map; and determining POIs included in each grid within the preset range of the grid where the distance positioning information is located as a plurality of POIs within the preset range of the positioning information.
Optionally, the second obtaining module 1302 may be further configured to:
and determining positioning information closest to the destination according to at least one of the resident information and the real-time positioning.
It should be noted that the foregoing explanation of the travel purpose identification method embodiment is also applicable to the travel purpose identification apparatus of this embodiment, and details are not repeated here.
The travel destination identification device acquires travel time and a destination in travel information, acquires positioning information closest to the destination, determines a plurality of POIs (points of interest) within a preset range of the positioning information according to the positioning information, and determines a travel destination from the POIs according to weight information of the POIs at the travel time. Therefore, the travel purpose is determined based on the weight information of the POIs determined by the positioning information closest to the travel destination of the resident, the technical problem that the travel purpose of the resident cannot be accurately determined due to the fact that the destination is a mixed land is solved, and the accuracy of identifying the travel purpose of the resident is improved.
In order to achieve the above embodiments, the present application proposes an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any of the above embodiments.
To achieve the above embodiments, the present application proposes a non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the method described in any of the above embodiments.
In order to implement the above embodiments, the present application proposes a computer program product comprising a computer program which, when executed by a processor, implements the method described in any of the above embodiments.
According to an embodiment of the present application, an electronic device and a readable storage medium are also provided.
Fig. 14 is a block diagram of an electronic device according to a travel purpose identification method according to an embodiment of the present application. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the present application that are described and/or claimed herein.
As shown in fig. 14, the electronic apparatus includes: one or more processors 1401, a memory 1402, and interfaces for connecting the various components, including a high-speed interface and a low-speed interface. The various components are interconnected using different buses and may be mounted on a common motherboard or in other manners as desired. The processor may process instructions for execution within the electronic device, including instructions stored in or on the memory to display graphical information of a GUI on an external input/output apparatus (such as a display device coupled to the interface). In other embodiments, multiple processors and/or multiple buses may be used, along with multiple memories and multiple memories, as desired. Also, multiple electronic devices may be connected, with each device providing portions of the necessary operations (e.g., as a server array, a group of blade servers, or a multi-processor system). Fig. 14 illustrates an example of a processor 1401.
The memory 1402, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs, non-transitory computer executable programs, and modules, such as program instructions/modules corresponding to the travel purpose identification method in the embodiment of the present application (for example, the first obtaining module 1301, the second obtaining module 1302, the first determining module 1303, and the second determining module 1304 shown in fig. 13). The processor 1401 executes various functional applications of the server and data processing, i.e., implements the trip purpose identification method in the above-described method embodiment, by running non-transitory software programs, instructions, and modules stored in the memory 1402.
The memory 1402 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the electronic device, and the like. Further, the memory 1402 may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, memory 1402 may optionally include memory located remotely from processor 1401, which may be connected to an electronic device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The electronic device may further include: an input device 1403 and an output device 1404. The processor 1401, the memory 1402, the input device 1403, and the output device 1404 may be connected by a bus or other means, as exemplified by the bus connection in fig. 14.
The input device 1403 may receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic device, such as an input device like a touch screen, keypad, mouse, track pad, touch pad, pointer stick, one or more mouse buttons, track ball, joystick, etc. The output devices 1404 may include a display device, auxiliary lighting devices (e.g., LEDs), and tactile feedback devices (e.g., vibrating motors), among others. The display device may include, but is not limited to, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, and a plasma display. In some implementations, the display device can be a touch screen.
Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, application specific ASICs (application specific integrated circuits), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
These computer programs (also known as programs, software applications, or code) include machine instructions for a programmable processor, and may be implemented using high-level procedural and/or object-oriented programming languages, and/or assembly/machine languages. As used herein, the terms "machine-readable medium" and "computer-readable medium" refer to any computer program product, apparatus, and/or device (e.g., magnetic discs, optical disks, memory, Programmable Logic Devices (PLDs)) used to provide machine instructions and/or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term "machine-readable signal" refers to any signal used to provide machine instructions and/or data to a programmable processor.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), the internet, and blockchain networks.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The Server may be a cloud Server, which is also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service extensibility in a conventional physical host and a Virtual Private Server (VPS). The server may also be a server of a distributed system, or a server incorporating a blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present application may be executed in parallel, sequentially, or in different orders, and the present invention is not limited thereto as long as the desired results of the technical solutions disclosed in the present application can be achieved.
The above-described embodiments should not be construed as limiting the scope of the present application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (13)
1. A travel purpose identification method comprises the following steps:
acquiring travel information; wherein the travel information comprises travel time and destination;
obtaining positioning information closest to the destination;
determining a plurality of POIs (points of interest) positioned in a preset range of the positioning information according to the positioning information;
and determining a travel purpose from the POIs according to the weight information of the POIs at the travel time.
2. The method of claim 1, wherein before determining the travel purpose from the POIs according to the weight information of the POIs at the travel time, the method further comprises:
determining a first frequency with which each POI is retrieved at the travel time;
determining a plurality of grids corresponding to the POIs;
determining a second frequency of occurrence of each of the POIs in the corresponding plurality of grids;
and determining the weight information of each POI in the travel time according to the first frequency and the second frequency of each POI.
3. The method of claim 2, wherein said determining a plurality of grids corresponding to each of said POIs comprises:
for any POI, determining a central grid taking the POI as a center from a plurality of candidate grids divided by a map;
and determining a plurality of grids corresponding to the POI according to the central grid and the peripheral grid surrounding the central grid.
4. The method of claim 1, wherein the determining, according to the positioning information, a plurality of POIs (points of interest) located within a preset range of the positioning information comprises:
determining a grid where the positioning information is located from a plurality of candidate grids divided by a map;
and determining POIs included in each grid within a preset range of the grid where the positioning information is located as a plurality of POIs within the preset range of the positioning information.
5. The method of any of claims 1-4, wherein the obtaining of the location information closest to the destination comprises:
and determining positioning information closest to the destination according to at least one of resident information and real-time positioning.
6. An identification device for travel purposes, comprising:
the first acquisition module is used for acquiring travel information; wherein the travel information comprises travel time and destination;
the second acquisition module is used for acquiring the positioning information closest to the destination;
the first determining module is used for determining a plurality of POIs (points of interest) located in a preset range of the positioning information according to the positioning information;
and the second determining module is used for determining a travel purpose from the POIs according to the weight information of the POIs at the travel time.
7. The apparatus of claim 6, wherein the apparatus comprises:
a third determining module, configured to determine a first frequency at which each POI is retrieved at the travel time;
a fourth determining module, configured to determine a plurality of grids corresponding to the POIs;
a fifth determining module, configured to determine a second frequency of occurrence of each POI in the corresponding plurality of grids;
a sixth determining module, configured to determine, according to the first frequency and the second frequency of each POI, weight information of each POI in the travel time.
8. The apparatus of claim 7, wherein the fourth determining means is further configured to:
for any POI, determining a central grid taking the POI as a center from a plurality of candidate grids divided by a map;
and determining a plurality of grids corresponding to the POI according to the central grid and the peripheral grid surrounding the central grid.
9. The apparatus of claim 6, wherein the first determining module is further configured to:
determining a grid where the positioning information is located from a plurality of candidate grids divided by a map;
and determining POIs included in each grid within a preset range of the grid where the positioning information is located as a plurality of POIs within the preset range of the positioning information.
10. The apparatus of any of claims 6-9, wherein the second obtaining means is further configured to:
and determining positioning information closest to the destination according to at least one of resident information and real-time positioning.
11. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.
12. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-5.
13. A computer program product comprising a computer program which, when executed by a processor, implements the method of any one of claims 1-5.
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