CN108882168B

CN108882168B - Travel track acquisition method and device and server

Info

Publication number: CN108882168B
Application number: CN201710326077.1A
Authority: CN
Inventors: 黄艺海; 叶佳木; 凌国惠; 李追日; 余传伟
Original assignee: Tencent Technology Shenzhen Co Ltd
Current assignee: Tencent Technology Shenzhen Co Ltd
Priority date: 2017-05-10
Filing date: 2017-05-10
Publication date: 2020-09-08
Anticipated expiration: 2037-05-10
Also published as: CN108882168A

Abstract

The embodiment of the invention provides a travel track obtaining method, a travel track obtaining device and a server, wherein a plurality of position data of a user are obtained, and the change trend of the geographical position according to time is obtained according to the geographical position corresponding to each time represented by the position data; determining interference position data from the plurality of position data according to the change trend and the confidence level of the geographic position corresponding to each time represented by the plurality of position data; the interference position data is eliminated, and the accurate travel track of the user can be obtained according to the target position data except the interference position data, so that the accuracy of obtaining the travel track is improved.

Description

Travel track acquisition method and device and server

Technical Field

The invention relates to the technical field of big data mining, in particular to a travel track obtaining method, a travel track obtaining device and a travel track obtaining server.

Background

The user travel information mining is to acquire the user travel information, such as transportation means adopted by the user for traveling, the consumption level of the user and the like, from the user travel track (the travel track comprises the origin, the departure time, the destination and the arrival time of the destination of the user) by adopting a data mining method.

At present, those skilled in the art are working on optimizing an acquisition method of a travel track so as to improve accuracy of travel information mined according to the travel track of a user.

Disclosure of Invention

In view of this, the invention provides a travel track acquiring method, a travel track acquiring device and a server, so as to overcome the problem of optimizing the travel track acquiring method in the prior art.

In order to achieve the purpose, the invention provides the following technical scheme:

a travel track acquisition method comprises the following steps:

obtaining a plurality of location data of a user, each location data including a geographic location corresponding to the user at a time and a confidence level for characterizing an accuracy of the geographic location;

obtaining the change trend of the geographic position according to the time according to the geographic position corresponding to each time represented by the plurality of position data;

determining interference position data from the plurality of position data according to the change trend and the confidence level of the geographic position corresponding to each time represented by the plurality of position data;

removing the interference position data from the plurality of position data to obtain target position data;

and obtaining the travel track of the user according to the target position data.

A travel trajectory acquisition apparatus comprising:

a first obtaining module, configured to obtain a plurality of location data of a user, where each location data includes a geographic location corresponding to the user at a time and a confidence level for characterizing an accuracy of the geographic location;

the second acquisition module is used for acquiring the change trend of the geographic position according to the time according to the geographic position corresponding to each time represented by the plurality of position data;

a first determining module, configured to determine interference location data from the plurality of location data according to the change trend and a confidence level of a geographic location corresponding to each time represented by the plurality of location data;

a third obtaining module, configured to remove the interference position data from the plurality of position data to obtain target position data;

and the fourth acquisition module is used for acquiring the travel track of the user according to the target position data.

A server, comprising:

a memory for storing a program;

a processor configured to execute the program, the program specifically configured to:

As can be seen from the foregoing technical solutions, compared with the prior art, an embodiment of the present invention provides a travel trajectory obtaining method, which obtains a plurality of location data of a user, and obtains a change trend of a geographic location according to time according to a geographic location corresponding to each time represented by the plurality of location data; determining interference position data from the plurality of position data according to the change trend and the confidence level of the geographic position corresponding to each time represented by the plurality of position data; the interference position data is eliminated, and the accurate travel track of the user can be obtained according to the target position data except the interference position data, so that the accuracy of obtaining the travel track is improved.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.

Fig. 1 is a structural diagram of a travel trajectory acquisition system according to an embodiment of the present invention;

fig. 2 is a flowchart of a travel trajectory acquisition method according to an embodiment of the present invention;

fig. 3 is a flowchart of another travel trajectory obtaining method according to an embodiment of the present invention;

fig. 4 is a structural diagram of a travel trajectory acquisition device according to an embodiment of the present invention;

fig. 5 is a block diagram of a server according to an embodiment of the present invention.

Detailed Description

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 travel trajectory acquisition method provided by the embodiment of the present invention may be applied to a travel trajectory acquisition system, and as shown in fig. 1, the travel trajectory acquisition system provided by the embodiment of the present invention is a structure diagram of the travel trajectory acquisition system, and the travel trajectory acquisition system may include at least one terminal device 11 and a server 12.

Each terminal device 11 may collect the user's location data and upload it to the server 12.

The terminal device 11 may be a mobile terminal such as a smart phone, a PAD, a notebook computer, etc. The terminal device 11 can locate the position of the user, so as to obtain the position data, and upload the position data to the server 12.

The server 12 may analyze a plurality of position data of each user to obtain a travel track of each user; preferably, the travel location preference of each user and/or the transportation used by each user can be obtained according to the travel track of each user, and/or the consumption capacity of each user can be mined according to the distance between the travel starting location and the travel destination of each user, the city grade of the travel destination, the grade of the transportation and the like.

The server 12 may also analyze urban tourism situations of each province of a major holiday (e.g. five-one, eleven, etc.) according to travel tracks of a plurality of users, and may even predict possible tourism situations of the major holiday to come. The flow condition of the people returning to the country in the spring festival can be analyzed according to the travel tracks of a plurality of users in the spring festival, even the flow condition of the people returning to the country in the future spring festival can be predicted, and the urban traffic planning and management can be optimized according to the predicted result.

The server can also mine specific crowds, such as crowds going back and forth from Shenzhen to hong Kong on the same day on weekends, according to travel tracks of multiple users.

Currently, a server may collect location data of a user collected by a terminal device, but the accuracy of a geographic location located by the terminal device is not high, for example, the accuracy of a geographic location located by using an IP (Internet Protocol Address) Address locating method and a WiFi (wireless fidelity) locating method is not high, and the accuracy of a geographic location obtained by using a GPS (Global positioning system) locating method is higher, but an error may also occur. In addition, in the process of uploading the location data of the user to the server by the terminal device, the location data is also limited by convenience of user privacy protection, for example, if some positioning software is set with access authority, the server cannot acquire the location data of the user obtained by the positioning software.

Based on the user position data with low accuracy, the server obtains a user travel track with relatively low accuracy, so that the server obtains the user travel track with relatively low accuracy and the mined information has relatively low accuracy. In order to solve the above problem, embodiments of the present invention provide a travel trajectory obtaining method, which can effectively remove interference position data, and a server can obtain a user travel trajectory with higher accuracy according to accurate position data.

The following description is given of a method for acquiring a travel track of a user by a server, and the specific steps are shown in fig. 2, where the travel track acquiring method includes:

step S201: a plurality of location data of a user is obtained, each location data including a geographic location corresponding to the user at a time and a confidence level for characterizing an accuracy of the geographic location.

The plurality of location data of the user may be collected by at least one terminal device 11 and uploaded to the server 12. Since the server 12 may receive the location data of a plurality of users, each location data further needs to include a user ID, which may be an IMEI (International Mobile Equipment Identity) of the terminal device, or a Mobile phone number of the user, or a login name of the user, etc.

In an application scene, a user always carries a mobile phone with the user for going out, so that a plurality of position data of the user can be obtained by using the mobile phone carried with the user, and the user identification ID can be the IMEI of terminal equipment or the mobile phone number of the user; in another application scenario, the user may have more than one terminal device, but the user uses a positioning software for positioning, and needs to input a login name and a password during the positioning software, and at this time, the user ID may also be the login name of the user. In different application scenarios, the user identification IDs may be the same and may be different, and this is not specifically limited in the embodiment of the present invention.

Each location data may comprise at least 4 elements, i.e. user identification ID, geographical location, time, confidence level, preferably, each location data may be in the format of: (user ID, geographic location, time, confidence level), the order of the 4 elements included in each location data may be arbitrary, and the embodiment of the present invention is not limited to this specifically. The geographic locations may include: country name, province name, city name, street name, etc., and the geographic location may also include the name of the cell in which the user is located.

In the embodiment of the invention, the data obtained by the terminal equipment in the process of positioning the user is called as original data; the terminal device may process each raw data to obtain the position data having the above format corresponding to each raw data, respectively. Or the terminal device sends the plurality of original data to the server, and the server processes each original data to obtain the position data with the format corresponding to each original data.

Step S202: and obtaining the change trend of the geographic position according to the time according to the geographic position corresponding to each time represented by the plurality of position data.

The change trend of the geographic position according to the time comprises the following steps: a user travel direction trend, and/or a user travel destination trend. The following describes a user travel direction trend and a user travel destination trend with a specific example. Assume that the geographic location includes a country name, a province name, and a city name, and a plurality of location data with a user ID of 10001 are as follows:

(10001, china, guangdong province, shenzhen city, 9/12 th 9:48, confidence level);

(10001, China, Guangdong province, Shenzhen City, 9/12 th day 13:48, confidence level);

(10001, china, south fluvial province, zheng city, 21:48 on 12 days 9 months, confidence level);

(10001, USA, California, san Francisco, 9 months 12 days 23:48, confidence level)

(10001, China, Shaanxi province, xi' an city, 13 months 9, 06:48, confidence level);

(10001, china, shanxi province, xi' an city, 9 months, 13 days, 10:48, confidence level);

(10001, China, Shaanxi province, xi' an city, 9 months, 14 days 15:48, confidence level).

In the plurality of location data, the change process of the geographic location with time is as follows: china, Guangdong province, Shenzhen City (9.12.48) → China, Guangdong province, Shenzhen City (9.12.13: 47) → China, Henan province, Zheng State City (9.12.21: 22) → USA, California, san Francisco (9.12.21: 22) → China, Shaanxi province, Xian City (9.13.06: 2) → China, Shaanxi province, Xian City (9.13.10: 22) → China, Shaanxi province, and Xian City (9.14.15: 22).

The user travel direction trend comprises the following steps: 8 hours from Shenzhen city of Guangdong province in China to Zhengzhou city of Henan province in China; from Zheng Zhou, Henan, China to san Francisco, California, USA for 2 hours; 7 hours from san Francisco, California, USA to Xian city, Shaanxi province, China.

Destination trends for a user's trip include: staying in Shenzhen city of Guangdong province in China for 4 hours; does not stay in Zhengzhou city of Henan province in China; not retained in san Francisco, California, USA; stay in Xian city of Shaanxi province in China for 33 hours.

Step S203: interference location data is determined from the plurality of location data based on the trend of change and a confidence level for characterizing accuracy of the geographic location.

The interference location data may include location data of a geographical location anomaly, which may be generated for a variety of reasons, and embodiments of the present invention provide, but are not limited to, the following:

first, the terminal device does not accurately locate the location of the user.

The position data obtained by the terminal device according to the IP address positioning method may cause a geographical position positioning error due to the following problems: firstly, the IP allocation of an operator is wrong, so that the geographic position corresponding to the IP address is inconsistent with the real geographic position corresponding to the IP address; secondly, the proxy server is used for IP address positioning, the geographical position of the proxy server is obtained, and the geographical position of the proxy server is not consistent with the geographical position of the user.

The position data obtained by the terminal device according to the WiFi positioning method may cause a geographical position positioning error due to the following problems: firstly, the position coordinates of the WiFi hotspots at fixed positions are wrong; and secondly, the number of WiFi hotspots at fixed positions near the terminal equipment is small.

Second, multiple users at different geographic locations log into the location software using the same account.

Assuming that the user identifier is a login name of the user, the user needs to log in a positioning software by using the login name to obtain the geographical location of the user through the positioning software, and if the user (assumed to be located in Beijing) borrows an account number to other users (assumed to be located in the United states) at a certain time (assumed to be a first time), the position data of the user in the United states at the first time is obtained, and although the position data is correctly positioned, the position data is interference position data for the user.

Location data of geographic location anomalies may result in user travel direction trends including anomalous travel direction trends, for example, 2 hours from zheng city, han, huinan, china, and 7 hours from san kan, han, california, usa, to seian, shaxi, china, shaxi.

In a preferred embodiment, the interference location data may further include: the user temporarily stays at the location data corresponding to the geographical location.

Since the geographical location where the user stays for a short time is not a destination to which the user needs to reach but a place to pass, and the location data may interfere with the destination in acquiring the travel trajectory of the user, it is preferable that the interference location data include location data corresponding to the geographical location where the user stays for a short time.

For example, in the above specific example, the interference location data includes: (10001, U.S., California, san Francisco, 9.12 days 23:48) and (10001, China, Henan province, Zheng city, 9.12 days 21: 48).

Step S204: and removing the interference position data from the plurality of position data to obtain target position data.

Step S205: and obtaining the travel track of the user according to the target position data.

The travel track obtaining method provided by the embodiment of the invention comprises the steps of obtaining a plurality of position data of a user, and obtaining the change trend of the geographic position according to time according to the geographic position corresponding to each time represented by the position data; determining interference position data from the plurality of position data according to the change trend and the confidence level of the geographic position corresponding to each time represented by the plurality of position data; the interference position data is eliminated, and the accurate travel track of the user can be obtained according to the target position data except the interference position data, so that the accuracy of obtaining the travel track is improved.

There are various methods for obtaining the change trend of the geographic location according to the time according to the geographic location corresponding to each time represented by the plurality of location data, which are provided by the embodiments of the present invention, but not limited to the following methods:

first, the user's travel direction trend.

Due to the limitation of the running speed of the transportation means, the jumping speed of each geographic position has certain speed limitation, and the running speed of users using different transportation means passing through each geographic position is not used, namely, the jumping speed of each geographic position is different by using different transportation means.

For example, if the vehicle is an aircraft and the travel speed of the aircraft may be greater than or equal to a first speed and less than or equal to a second speed, the jump speed for the geographic location may be greater than or equal to the first speed and less than or equal to the second speed; if the vehicle is a high-speed rail, and the running speed of the high-speed rail may be greater than or equal to the third speed and less than or equal to the fourth speed, the jump speed of the geographic position may be greater than or equal to the third speed and less than or equal to the fourth speed; if the vehicle is a motor car and the running speed of the motor car is greater than or equal to the fifth speed and less than or equal to the sixth speed, the jump speed of the geographic position may be greater than or equal to the fifth speed and less than or equal to the sixth speed.

In summary, each vehicle has its own driving speed range, and the jumping speed of the geographic location belongs to different speed ranges when different vehicles are used.

Specifically, "obtaining a time-dependent change trend of the geographic location according to the geographic location corresponding to each time represented by the plurality of location data" includes:

and dividing the plurality of position data into at least one group of travel data set, wherein one travel data set comprises at least two position data adjacent in time. And respectively determining the geographic position jump speed corresponding to each group of travel data sets according to the geographic position corresponding to each group of travel data sets.

Still referring to the above example for the time-adjacency, the position data time-adjacency to the position data (10001, china, shaanxi province, xi' an city, 13 th 9 th 06:48, confidence level) includes: (10001, san Francisco, Calif., 23:48, confidence level 12 months 9) and (10001, China, Shaanxi, Xian, 10:48 months 9, 13, confidence level).

Still taking the example that the geographic location jumps from san francisco, california, usa to shaxi province, west ampere, china, and the time spent is 7 hours, the jump speeds of the two geographic locations are: distance between san Francisco, California, USA and Xian city, Shaanxi province, China/7 hours.

Correspondingly, the determining interference location data from the plurality of location data according to the change trend and the confidence level of the geographic location corresponding to each time represented by the plurality of location data comprises: and determining the interference position data according to the geographic position jump speed corresponding to each group of travel data sets and the confidence level of the geographic position corresponding to each time represented by the plurality of position data.

There are various implementation manners of "determining the interference location data according to the geographic location jump speed corresponding to each group of travel data sets and the confidence level of the geographic location corresponding to each time represented by the plurality of location data", and the embodiments of the present invention provide, but are not limited to, the following.

If the server only needs to obtain the position data of a certain vehicle, the position data in the process of traveling by using the vehicle can be obtained according to the speed range corresponding to the vehicle, and the position data in the process of traveling by using other vehicles is determined as the interference position data.

Specifically, the confidence level in the location data during traveling using another vehicle is set as a preset level, and the preset level may be smaller than any confidence level of the geographic location corresponding to each time represented by the plurality of location data.

And determining the position data with the confidence level less than or equal to the preset level as interference position data, wherein the position data with the confidence level less than or equal to the preset level comprises position data in the process of travelling by using other vehicles.

And secondly, determining error position data according to the jump speed of the geographic position, assuming that the running speed of the vehicle with the highest current speed is the speed A, and if the jump speed of the geographic position is higher than the speed A, obviously having position data with the wrong geographic position because the running speed of the user cannot exceed the speed A in real life.

Specifically, the determining the interference location data according to the geographic location jump speed corresponding to each group of travel data sets and the confidence level of the geographic location corresponding to each time represented by the plurality of location data "includes:

determining a target travel data set with the geographic position jump speed being greater than or equal to a speed threshold value from each group of travel data sets;

and determining the position data with the minimum confidence level in the target trip data set as the interference position data, or determining all the position data in the target trip data set as the interference position data when the confidence levels of all the position data in the target trip data set are the same.

Since the positioning method of each location data may be different, and the accuracy of the geographic location determined by different positioning methods is different, in a preferred embodiment, the server or the mobile terminal may determine the confidence level corresponding to each location data according to the data source of each location data. The data source refers to a positioning method for acquiring corresponding position data; a higher confidence level indicates a higher accuracy of the geographic position fix in the location data. Preferably, the accuracy of the geographical position of the GPS positioning is higher than the accuracy of the geographical position of the WiFi positioning and the geographical position of the IP address positioning; the accuracy of the geographical location of the WiFi positioning and the geographical location of the IP address positioning may be determined according to actual situations. For example, in an application scenario where fixed-location WiFi hotspots are more, the accuracy of the geographical location of the WiFi location is higher than that of the IP address location, i.e. the confidence level of the geographical location of the WiFi location is several times higher than that of the geographical location of the IP address location.

The confidence level may be represented by a number and/or a letter, which is not particularly limited by the embodiment of the present invention. For example, the confidence level of the location data of the GPS positioning is 1, the confidence level of the location data of the WiFi positioning is 0.5, and the confidence level of the location data of the IP address positioning is 0.3. If there is only one data source of the position data, the confidence level may not be set, and if there are two data sources of the position data, the confidence level may be simply set, for example, the confidence level includes an accuracy level and a fuzzy level, where the value of the accuracy level is greater than the value of the fuzzy level, for example, the value of the accuracy level is 1, and the value of the fuzzy level is 0.

The confidence level of each geographic location may be obtained by the mobile terminal and then sent to the server; the mobile terminal can also identify data sources of each geographic position and mark each geographic position, the identifiers of the geographic positions corresponding to different data sources are different, and the server can respectively determine the confidence level of each geographic position according to the corresponding identifier of each geographic position.

Second, the destination trend of the user's trip.

If the geographic position is the destination of the user for going out, the time of the user staying at the geographic position is longer than or equal to the preset time, and if the time of the user staying at one geographic position is shorter than the preset time, the geographic position is a place which the user passes by and is not the destination which the user wants to reach.

"obtaining a time-dependent change trend of the geographic location according to the geographic location corresponding to each time represented by the plurality of location data" includes:

dividing the plurality of position data into at least one group of travel data sets, wherein one travel data set comprises at least two position data adjacent in time; and respectively determining the residence time of the geographic position corresponding to each group of travel data sets according to the geographic position corresponding to each group of travel data sets.

Correspondingly, the determining interference location data from the plurality of location data according to the change trend and the confidence level of the geographic location corresponding to each time represented by the plurality of location data comprises: and determining the interference position data according to the residence time of the geographic position corresponding to each group of travel data sets and the confidence level of the geographic position corresponding to each time represented by the plurality of position data.

Specifically, the determining the interference position data according to the stay time of the geographic position corresponding to each group of travel data sets and the confidence level of the geographic position corresponding to each time represented by the plurality of position data includes:

determining a target travel data set with retention time less than or equal to preset time from each group of travel data sets;

setting the confidence level of the geographic position corresponding to each time represented by each position data in the target trip data set as a preset level;

and determining the position data with the confidence level smaller than or equal to the preset level in the plurality of position data as the interference position data.

Or, the interference location data is determined directly according to the corresponding geographic location dwell time of each group of travel data sets, specifically:

determining a target travel data set with retention time less than or equal to preset time from each group of travel data sets; and determining all position data in the target data set as the interference position data.

Thirdly, determining the interference position data by combining the first mode and the second mode, namely determining the interference position data according to the jump speed of the geographic position corresponding to each group of travel data sets and the confidence level of the geographic position corresponding to each time represented by the plurality of position data; and determining the interference position data according to the residence time of the geographic position corresponding to each group of travel data sets and the confidence level of the geographic position corresponding to each time represented by the plurality of position data.

In summary, the three methods provided by the embodiment of the invention mainly utilize the principle that the geographic position jump speed is normal and the principle that the geographic position stops valuably to filter the interference position data. And preferably, the position data with higher confidence level is reserved in the process of filtering the interference position data.

It can be understood that, in the process of "dividing the plurality of location data into at least one set of travel data sets", two location data which are adjacent in time and have the same geographic location may be divided into one set of travel data sets, and obviously, the jump speed of the geographic location corresponding to the set of travel data sets is zero, and this calculation is meaningless; although the stay time corresponding to the set of travel data sets is less than or equal to the preset time, it cannot be guaranteed that the geographic location is not the destination because there may be location data that is temporally adjacent to the two location data and has the same geographic location that is not included in the set of travel data sets.

It is preferable to combine a plurality of location data that are adjacent in time and have the same geographical location in order to reduce such meaningless and possibly erroneous calculations. And then, collecting the combined position data and the position data which does not need to be combined, dividing the collected position data into at least one group of travel data sets, determining interference position data, and removing the interference position data.

It can be understood that the position data which is not adjacent to the interference position data before the interference position data is removed may become position data which is adjacent to the interference position data after the interference position data is removed, because the two position data which are adjacent to the interference position data before are changed into position data which are adjacent to each other, if the two position data have the same geographical position, the two position data need to be merged again, and then the interference position data is removed, so the process of acquiring the target position data includes: merging → de-interference location data → merging → a cyclic process of de-interference location data.

As shown in fig. 3, a flowchart of another travel trajectory obtaining method provided in the embodiment of the present invention is shown, where the method includes:

step S301: a plurality of location data of a user is obtained, each location data including a geographic location corresponding to the user at a time and a confidence level for characterizing an accuracy of the geographic location.

Assuming that the geographic location includes a country, a province, and a city, assuming that there are two data sources of the plurality of location data in step S301, that is, the location data for positioning by using the IP address and the location data for positioning by using the GPS, and that the confidence level of the location data for positioning by using the IP address is 0, and the confidence level of the location data for positioning by using the GPS is 1, it is assumed that the format of each location data may be: (user ID, country, province, city, time, confidence level), assuming that the user ID is 10001, the user's multiple location data is as follows:

(10001, China, Guangdong province, Shenzhen City, 9/12 th month 9:48, 1);

(10001, China, Guangdong province, Shenzhen City, 9/12 th day 13:47, 0);

(10001, china, guangdong province, unknown city, 9 months, 12 days 14:32, 0);

(10001, China, Henan province, unknown City, 9 months, 12 days 20:45, 0);

(10001, China, Henan province, Zheng City, 9 months, 12 days 21:22, 1);

(10001, China, Shaanxi province, xi' an city, 9 months 13 days 06:22, 1);

(10001, China, Shaanxi province, xi' an city, 9 months, 13 days 10:22, 0);

(10001, China, Shaanxi province, xi' an city, 9 months, 13 days 15:22, 1);

(10001, U.S., unknown province, unknown city, 9 months 13 days 17:22, 0);

(10001, China, Beijing, 9 months, 13 days 20:22, 0);

(10001, China, Beijing, 9 months, 14 days 09:45, 1).

Step S302: and determining at least one group of position data to be merged from the plurality of position data, wherein the group of position data to be merged comprises a plurality of position data which are adjacent in time and have the same geographic position.

It can be understood that, due to different data sources of geographic locations, the geographic locations may be located with higher precision, for example, the geographic locations may be located in cities, even streets or cells; since the position data missing from the geographic position field cannot be determined whether the geographic position of the position data adjacent to the geographic position field is the same or not, it is preferable to complete the position data missing from the geographic position field in the process of determining at least one group of position data to be combined in the step S302.

If the completion is not performed in step S302, step S302 can only perform data merging on the location data with complete geographic location fields, for example, in the above example, the location data includes 3 sets of location data to be merged, where a set of location data to be merged includes: (10001, China, Guangdong province, Shenzhen city, 9.12.9: 48, 1) and (10001, China, Guangdong province, Shenzhen city, 9.12.13: 47), 0; the set of location data to be merged includes: (10001, china, shanxi province, xi ' an city, 13 th 9 th month 06:22, 1), (10001, china, shanxi province, xi ' an city, 13 th 9 th month 10:22, 0), (10001, china, shanxi province, xi ' an city, 13 th 9 th month 15:22, 1); the set of location data to be merged includes: (10001, China, Beijing, 9.13 days 20:22, 0), (10001, China, Beijing, 9.14 days 09:45, 1).

Step S303: and respectively carrying out data merging on each group of position data to be merged to obtain merged position data corresponding to each group of position data to be merged, wherein the starting time of the merged position data is the minimum time of the position data in the corresponding position data group to be merged, and the ending time of the merged position data is the maximum time of the position data in the corresponding position data group to be merged.

Since the merged location data includes the start time and the end time, it is preferable that the respective location data be converted into location data (user identification ID, country, province, city, start time, end time, confidence level) in the following format, and since the respective location data are not merged, the start time and the end time of each location data are the same. The results of the changes to the position data are as follows:

(10001, China, Guangdong province, Shenzhen city, 9/12/9/48/9/12/48/1);

(10001, China, Guangdong province, Shenzhen city, 12 th 9 th 13:47, 0);

(10001, china, guangdong province, unknown city, 9 months, 12 days, 14:32, 0);

(10001, China, Henan province, unknown City, 9 months, 12 days 20:45, 0);

(10001, China, Henan province, Zheng City, 21:22 at 12 days 9 and 21:22, 1 at 12 days 9);

(10001, China, Shaanxi province, xi' an city, 06:22 on 13 th month 9, 06:22, 1 on 13 th month 9);

(10001, China, Shaanxi province, xi' an city, 9 months 13 days 10:22, 0);

(10001, China, Shaanxi province, xi' an city, 13 months at 9 days 15:22, 1);

(10001, USA, unknown province, unknown City, 9 months 13 days 17:22, 0);

(10001, China, Beijing, 9/13/20/22, 0);

(10001, China, Beijing, 9 months 14 days 09:45, 1).

The data merging is performed on each group of position data to be merged, and the merged position data can be obtained as follows:

(10001, China, Guangdong province, Shenzhen city, 9/12/9/48/09/12/13/47, 1);

(10001, China, Shaanxi province, xi' an city, 06:22 on 13 th month 9, 15:22, 1 on 13 th month 9);

(10001, China, Beijing, 9.13.20: 22, 9.14.09: 45, 1).

Preferably, the confidence level of each merged position data in the embodiment of the present invention is the maximum confidence level of the position data in the corresponding position data group to be merged.

The confidence level of the merged position data indicates that: location data with a higher confidence level will support location data with a lower confidence level with a confidence level. That is, if there is position data with a higher confidence level in the vicinity of position data with a lower confidence level, the position data with the lower confidence level is authenticated as position data with a higher confidence level. It is therefore an object of the present invention to improve the confidence level of fuzzy data (i.e., position data with a lower confidence level) when the accurate data (i.e., position data with a higher confidence level) is used, and to make the overall data more comprehensive when the fuzzy data is considered as accurate data.

Step S304: collecting each combined position data with the position data which are not combined in the plurality of position data to obtain the collected position data; and determining the position data adjacent to time in the collected position data as a group of travel data sets.

Still taking the above as an example, the collected location data includes:

(10001, China, Guangdong province, Shenzhen city, 9/12/9/48/09/12/13/47, 1);

(10001, china, guangdong province, unknown city, 9 months, 12 days, 14:32, 0);

(10001, China, Henan province, unknown City, 9 months, 12 days 20:45, 0);

(10001, USA, unknown province, unknown City, 9 months 13 days 17:22, 0);

(10001, China, Beijing, 9.13.20: 22, 9.14.09: 45, 1).

For the position data after the aggregation, if the position data are sorted from small to large according to the start time, the end time of one position data is the start time of the next position data, and the start time of one position data is the end time of the previous position data.

If the position data with the missing geographic position field is completed in step S302, this completion step is not needed here; if the position data with the missing geographic position field is not completed in step S302, the position data with the missing geographic position field also needs to be completed in step S304.

Whether in step S302 or step S304, the method for completing the location data with the missing geographic location field includes:

determining position data with missing geographic position fields from the position data to be processed;

completing the position data missing from the geographic position field according to the position data with complete geographic positions adjacent to the position data time missing from the geographic position field;

at least one set of location data to be merged is determined from the location data with complete geographic location fields.

For step S302, the position data to be processed is the plurality of position data; in step S304, the to-be-processed position data is the collected position data.

The following illustrates a method of complementing the location data missing in the geographic location field based on location data having complete geographic locations temporally adjacent to the location data missing in the geographic location field.

Specifically, all the position data of the user may be sorted from small to large according to the starting time, so that the position data adjacent in time are also adjacent in position. If the field of the city with the missing geographic position is found after the sorting, the completion is carried out according to the following mode.

When the provinces of two position data (namely, the front and rear position data) which are adjacent to the position data with the missing geographic position field in time are the same and the cities are different, the position data with the missing geographic position is not completed. When two position data time-adjacent to the position data time-missing of the geographic position field have the same province and the same city, completing the position data time-missing of the geographic position field according to any position data time-adjacent to the position data time-missing of the geographic position field; and when the two provinces of the position data which are adjacent to the time of the position data which are missing from the geographic position field are different, the position data which are missing from the geographic position field are supplemented according to the position data which are the same as the provinces in the position data which are missing from the geographic position field and are adjacent to the time.

The logics of the provinces, cities, streets, cells, etc. are similar and will not be described herein.

For example, the position data obtained by complementing the collected position data is as follows:

(10001, China, Guangdong province, Shenzhen city, 9/12/9/48/09/12/13/47, 1);

(10001, China, Guangdong province, Shenzhen city, 9/12/14/32/9/12/14/32, 1);

(10001, China, Henan province, Zheng City, 9 months 12 days 20:45, 1);

(10001, USA, unknown province, unknown City, 9 months 13 days 17:22, 0);

(10001, China, Beijing, 9.13.20: 22, 9.14.09: 45, 1).

Preferably, in the embodiment of the present invention, the confidence level of the location data with the missing geographic location field may be determined according to the confidence level of the location data with complete geographic locations that are temporally adjacent to the location data with the missing geographic location field.

Specifically, when the geographic positions of the pieces of location data temporally adjacent to the missing location data of the geographic location field are the same, determining the maximum confidence level of the pieces of location data temporally adjacent to the missing location data of the geographic location field as the confidence level of the piece of location data of the missing location field;

and when the second field of the geographic position of each position data which is adjacent to the position data with the missing geographic position field in time is not the same, determining the confidence level of the position data which is adjacent to the position data with the same second field and is adjacent to the position data with the missing geographic position field in time as the confidence level of the position data with the missing geographic position.

In summary, location data with a higher confidence level may provide a confidence support for location data with a lower confidence level. That is, if there is position data with a higher confidence level in the vicinity of position data with a lower confidence level, the position data with the lower confidence level is authenticated as position data with a higher confidence level. It is therefore an object of the present invention to improve the confidence level of fuzzy data (i.e., position data with a lower confidence level) when the accurate data (i.e., position data with a higher confidence level) is used, and to make the overall data more comprehensive when the fuzzy data is considered as accurate data.

By the above example, it is found that the complemented position data may be further subjected to data merging, and the position data after data merging again is as follows:

(10001, China, Guangdong province, Shenzhen city, 09:48 on 12 th month 9, 14:32 on 12 th month 9, 1);

(10001, China, Henan province, Zheng City, 20:45 at 12 days 9 and 21:22 at 12 days 9 and 1);

(10001, USA, unknown province, unknown City, 9 months 13 days 17:22, 0);

(10001, China, Beijing, 9.13.20: 22, 9.14.09: 45, 1).

In summary, for convenience of description, the field missing from the geographic location in the location data is referred to as a first field, and the field not missing from the geographic location is referred to as a second field.

The "complementing the location data with the missing geographic location field according to the location data with complete geographic locations adjacent to the location data with the missing geographic location field in time" may include:

when the geographic position of each piece of position data adjacent to the position data time with the missing geographic position field is the same, completing the position data with the missing geographic position field according to the geographic position of any piece of position data adjacent to the position data time with the missing geographic position field;

when the second field of the geographic position of each piece of position data which is adjacent to the time of the position data with the missing geographic position field is the same and the first field is different, the position data with the missing geographic position field is not completed;

and when the second field of the geographic position of each piece of position data which is adjacent to the time of the position data which is missing from the geographic position field is different, completing the position data which is missing from the geographic position field according to the position data which is adjacent to the time and has the same second field as the position data which is missing from the geographic position field.

Step S305: respectively determining the geographic position jump speed corresponding to each group of travel data sets according to the geographic position corresponding to each group of travel data sets; and/or respectively determining the residence time of the geographic position corresponding to each group of travel data sets according to the geographic position corresponding to each group of travel data sets.

Step S306: determining the interference position data according to the geographic position jump speed corresponding to each group of travel data sets and the confidence level of the geographic position corresponding to each time represented by the plurality of position data; and/or determining the interference position data according to the residence time of the geographic position corresponding to each group of travel data sets and the confidence level of the geographic position corresponding to each time represented by the plurality of position data.

Step S307: removing interference position data in the collected position data determined in the step S304; judging whether the position data after the interference-removed position data set has a plurality of position data with adjacent time and the same geographical position, if so, executing step S308; if not, go to step S309.

Still taking the above as an example, the position data after removing the interference position data includes:

(10001, China, Beijing, 9.13.20: 22, 9.14.09: 45, 1).

Step S308: determining at least one group of position data to be merged from the position data determined in step S307 after the set of interference-removed position data is collected, wherein the group of position data to be merged includes a plurality of position data which are adjacent in time and have the same geographical position, and returning to step S303.

Step S309: and determining the position data after removing the set of the interference position data as the target position data.

It can be understood that through continuous data merging, interference position data removal and completion, the still-retained position data is the correct stay information of a user in a certain city, street or cell within a period of time, and then the position data adjacent to the time is represented as a trip of the user.

In summary, the process of acquiring the target position data is denoted as a cyclic process of merging → complementing → merging → removing the interference position data, or a cyclic process of complementing → merging → removing the interference position data.

Still taking the above as an example, the target location data includes:

(10001, China, Beijing, 9.13.20: 22, 9.14.09: 45, 1).

According to the target position data, the obtained travel track of the user comprises the following steps:

shenzhen to xi 'an, departs from 14:32 on 12 th month and 9 th month, arrives 06:22 on 13 th month, judges as a train or a car according to the speed per hour, and stays at 15:22 on 13 th month and 9 th month on xi' an;

when the train arrives at Beijing in Xian, the train departs from 15:22 on 13 th days 9 months, and arrives at 20:22 on 13 th days 9 months, and the train is judged to be high-speed train or motor train according to the speed per hour, and the stay time is not finished in the Beijing (because the following data are not seen yet).

The embodiment of the invention also provides a travel track acquisition device corresponding to the travel track acquisition method, and the two embodiments can be referred to each other and are not described herein again.

As shown in fig. 4, a structure diagram of a travel trajectory obtaining apparatus provided in an embodiment of the present invention includes:

a first obtaining module 41, configured to obtain a plurality of location data of a user, where each location data includes a geographic location corresponding to the user at a time and a confidence level for characterizing an accuracy of the geographic location;

a second obtaining module 42, configured to obtain a change trend of the geographic location according to time according to the geographic location corresponding to each time represented by the plurality of location data;

a first determining module 43, configured to determine interference location data from the plurality of location data according to the change trend and the confidence level of the geographic location corresponding to each time represented by the plurality of location data;

a third obtaining module 44, configured to remove the interference position data from the multiple position data to obtain target position data;

a fourth obtaining module 45, configured to obtain the travel track of the user according to the target position data.

Optionally, the second obtaining module 42 includes:

the dividing unit is used for dividing the plurality of position data into at least one group of trip data sets, and each trip data set comprises at least two position data adjacent in time;

and the first determining unit is used for respectively determining the geographic position jump speed corresponding to each group of travel data sets according to the geographic position corresponding to each group of travel data sets.

Optionally, the first determining module includes:

a third determining unit, configured to determine the interference location data according to the geographic location jump speed corresponding to each group of travel data sets and the confidence level of the geographic location corresponding to each time represented by the multiple location data.

Optionally, the third determining unit includes:

the second determining subunit is used for determining a target trip data set with the geographic position jump speed greater than or equal to the speed threshold from each group of trip data sets;

a third determining subunit, configured to determine, as the interference location data, the location data in the target trip data set with the smallest confidence level, or determine, as the interference location data, all the location data in the target trip data set when the confidence levels of all the location data in the target trip data set are the same.

Optionally, the second obtaining module 42 further includes:

and the second determining unit is used for respectively determining the residence time of the geographic position corresponding to each group of travel data sets according to the geographic position corresponding to each group of travel data sets.

Optionally, the second obtaining module 42 includes:

and the fourth determining unit is used for respectively determining the residence time of the geographic position corresponding to each group of travel data sets according to the geographic position corresponding to each group of travel data sets.

Optionally, the first determining module 43 includes:

a fifth determining unit, configured to determine the interference location data according to the staying time at the geographic location corresponding to each group of travel data sets and the confidence level of the geographic location corresponding to each time represented by the plurality of location data.

Optionally, the fifth determining unit includes:

a fourth determining subunit, configured to determine, from each group of travel data sets, a target travel data set with a retention time less than or equal to a preset time;

a setting subunit, configured to set, as a preset level, a confidence level of a geographic position corresponding to each time represented by each piece of position data in the target trip data set;

a fifth determining subunit, configured to determine, as the interference location data, location data whose confidence level is less than or equal to the preset level among the plurality of location data.

Optionally, the dividing unit includes:

a sixth determining subunit, configured to determine at least one set of location data to be merged from the location data to be processed, where the set of location data to be merged includes multiple location data that are adjacent in time and have the same geographic location;

the first acquiring subunit is configured to perform data merging on each group of position data to be merged, respectively, to obtain merged position data corresponding to each group of position data to be merged, where a start time of the merged position data is a minimum time of the position data in the corresponding position data group to be merged, and an end time of the merged position data is a maximum time of the position data in the corresponding position data group to be merged;

a second obtaining subunit, configured to aggregate each merged position data with non-merged position data in the plurality of position data to obtain aggregated position data; and determining the position data adjacent to time in the collected position data as a group of travel data sets.

Optionally, the to-be-processed location data includes the multiple location data, or location data after multiple sets of location data with time-adjacent and same geographic locations, and the third obtaining module 44 includes:

a deleting unit configured to remove interference position data from the collected position data;

a sixth determining unit, configured to determine the aggregated location data as the target location data if the aggregated location data does not have location data of temporally adjacent and same geographic locations.

Optionally, each geographic location includes a plurality of fields, and the sixth determining subunit includes:

the first determining submodule is used for determining the position data with missing geographic position fields from the position data to be processed;

the completion submodule is used for completing the position data missing from the geographic position field according to the position data with complete geographic positions adjacent to the position data missing from the geographic position field in time;

and the second determining submodule is used for determining at least one group of position data to be combined from the position data with complete geographic position fields.

Optionally, the confidence level of the merged position data is the maximum confidence level of the position data in the corresponding position data group to be merged;

and/or, further comprising: a second determination module to:

determining a confidence level for the missing location data for the geographic location field based on the confidence level for the location data having complete geographic locations that are temporally adjacent to the missing location data for the geographic location field.

An embodiment of the present invention further provides a server, as shown in fig. 5, which is a structural diagram of the server provided in the embodiment of the present invention, and the server includes:

a memory 51 for storing a program;

the program may include program code including computer operating instructions.

A processor 52 for executing the program.

The memory 51 may comprise high-speed RAM memory, and may also include non-volatile memory (non-volatile memory), such as at least one disk memory.

The processor 52 may be a central processing unit CPU or an application specific Integrated circuit asic or one or more Integrated circuits configured to implement embodiments of the present invention.

Wherein the program is specifically for:

Optionally, the electronic device may further include a communication bus 53 and a communication interface 54, wherein the memory 51, the processor 52, and the communication interface 54 complete communication with each other through the communication bus 53;

alternatively, the communication interface 54 may be an interface of a communication module, such as an interface of a GSM module.

Finally, it should also be noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.

The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A travel track acquisition method is characterized by comprising the following steps:

obtaining a plurality of location data of a user, each location data including a geographic location corresponding to the user at a time and a confidence level for characterizing an accuracy of the geographic location; the confidence level of the geographic location is determined from a data source of the geographic location;

obtaining the change trend of the geographic position according to the time according to the geographic position corresponding to each time represented by the plurality of position data; the time-dependent change trend of the geographic position comprises the following steps: the travel direction trend of the user and/or the travel destination trend of the user;

2. A travel trajectory acquisition method according to claim 1, wherein the obtaining a time-dependent trend of the geographic location from the geographic location corresponding to each time represented by the plurality of location data comprises:

dividing the plurality of position data into at least one group of travel data sets, wherein one travel data set comprises at least two position data adjacent in time;

and respectively determining the geographic position jump speed corresponding to each group of travel data sets according to the geographic position corresponding to each group of travel data sets.

3. The travel trajectory acquisition method according to claim 2, wherein the determining, from the plurality of location data, the interference location data according to the change trend and the confidence level of the geographic location corresponding to each time represented by the plurality of location data comprises:

and determining the interference position data according to the geographic position jump speed corresponding to each group of travel data sets and the confidence level of the geographic position corresponding to each time represented by the plurality of position data.

4. The travel trajectory acquisition method according to claim 3, wherein the determining the interference location data according to the geographic location jump speed corresponding to each set of travel data sets and the confidence level of the geographic location corresponding to each time represented by the plurality of location data sets comprises:

determining a target travel data set with the geographic position jump speed greater than or equal to a speed threshold value from each group of travel data sets;

5. A travel trajectory acquisition method according to claim 2, wherein obtaining a time-dependent trend of geographic locations based on the geographic locations corresponding to the respective times represented by the plurality of location data further comprises:

and respectively determining the residence time of the geographic position corresponding to each group of travel data sets according to the geographic position corresponding to each group of travel data sets.

6. A travel trajectory acquisition method according to claim 1, wherein the obtaining a time-dependent trend of the geographic location from the geographic location corresponding to each time represented by the plurality of location data comprises:

7. The travel trajectory acquisition method according to claim 6, wherein the determining, from the plurality of location data, the interference location data according to the change trend and the confidence level of the geographic location corresponding to each time represented by the plurality of location data comprises:

and determining the interference position data according to the residence time of the geographic position corresponding to each group of travel data sets and the confidence level of the geographic position corresponding to each time represented by the plurality of position data.

8. The travel trajectory acquisition method according to claim 7, wherein the determining the interference location data according to the respective geographic location dwell times of the sets of travel data and the confidence levels of the respective geographic locations at the respective times represented by the plurality of location data includes:

9. The method for acquiring a travel trajectory according to any one of claims 2 to 8, wherein the dividing the plurality of location data into at least one set of travel data includes:

determining at least one group of position data to be merged from the position data to be processed, wherein the group of position data to be merged comprises a plurality of position data which are adjacent in time and have the same geographic position;

respectively carrying out data merging on each group of position data to be merged to obtain merged position data corresponding to each group of position data to be merged, wherein the starting time of the merged position data is the minimum time of the position data in the corresponding position data group to be merged, and the ending time of the merged position data is the maximum time of the position data in the corresponding position data group to be merged;

collecting each combined position data with the position data which are not combined in the plurality of position data to obtain the collected position data; and determining the position data adjacent to time in the collected position data as a group of travel data sets.

10. The method according to claim 9, wherein the to-be-processed location data includes the plurality of location data, or location data after a plurality of location data sets having time-adjacent and same geographic locations, and the removing the interference location data from the plurality of location data to obtain target location data includes:

removing interference position data in the collected position data;

and if the position data after the collection does not have the position data which are adjacent in time and have the same geographic position, determining the position data after the collection as the target position data.

11. A travel trajectory acquisition method according to claim 10, wherein each geographical location comprises a plurality of fields, and said determining at least one set of location data to be merged from the location data to be processed comprises:

complementing the position data missing from the geographic position field according to the position data which is adjacent to the position data missing from the geographic position field in time and complete in geographic position;

12. The travel trajectory acquisition method according to claim 11, wherein the confidence level of a merged location data is the maximum confidence level of the location data in the corresponding location data group to be merged;

and/or the presence of a gas in the gas,

and determining the confidence level of the position data missing from the geographic position field according to the confidence level of the position data which is adjacent to the position data missing from the geographic position field in time and has complete geographic positions.

13. A travel trajectory acquisition device, characterized by comprising:

a first obtaining module, configured to obtain a plurality of location data of a user, where each location data includes a geographic location corresponding to the user at a time and a confidence level for characterizing an accuracy of the geographic location; the confidence level of the geographic location is determined from a data source of the geographic location;

the second acquisition module is used for acquiring the change trend of the geographic position according to the time according to the geographic position corresponding to each time represented by the plurality of position data; the time-dependent change trend of the geographic position comprises the following steps: the travel direction trend of the user and/or the travel destination trend of the user;

14. The travel trajectory acquisition device according to claim 13, wherein the second acquisition module comprises:

the first determining unit is used for respectively determining the geographic position jump speed corresponding to each group of travel data sets according to the geographic position corresponding to each group of travel data sets; and/or the second determining unit is used for respectively determining the residence time of the geographic position corresponding to each group of travel data sets according to the geographic position corresponding to each group of travel data sets.

15. A server, comprising:

a memory for storing a program;