CN108882168A - Trip track acquisition methods, device and server - Google Patents

Abstract

The embodiment of the invention provides a kind of trip track acquisition methods, device and servers, obtain multiple position datas of user, according to the corresponding geographical location of each time that the multiple position data indicates, obtain variation tendency of the geographical location according to the time；According to the confidence level in the corresponding geographical location of each time that the variation tendency and the multiple position data indicate, interference position data are determined from the multiple position data；Interference position data are excluded, according to the target position data in addition to interference position data, the trip track of accurate user can be obtained, to improve the accuracy for obtaining trip track.

Description

Trip track acquisition methods, device and server

Technical field

The present invention relates to big data digging technology fields, more particularly relate to trip track acquisition methods, device and service Device.

Background technique

It is the trip track according to user (when trip track includes the origin of user, sets out that user's trip information, which excavates, Between, destination and the time arrived at the destination), therefrom obtain the trip information of user using data digging method, for example, with The vehicles that family trip uses, level of consumption of user etc..

Currently, those skilled in the art are being dedicated to the acquisition methods of optimization trip track, to improve according to user The accuracy of trip information excavated of trip track.

Summary of the invention

In view of this, the present invention provides a kind of trip track acquisition methods, device and servers, to overcome the prior art The problem of acquisition methods of middle optimization trip track.

To achieve the above object, the present invention provides the following technical solutions：

A kind of trip track acquisition methods, including：

Multiple position datas of user are obtained, each position data include the user in a time corresponding geographical location And the confidence level of the accuracy for characterizing geographical location；

According to the corresponding geographical location of each time that the multiple position data indicates, geographical location is obtained according to the time Variation tendency；

According to the confidence in the corresponding geographical location of each time that the variation tendency and the multiple position data indicate Rank is spent, interference position data are determined from the multiple position data；

The interference position data are removed from the multiple position data, obtain target position data；

According to the target position data, the trip track of the user is obtained.

A kind of trip track acquisition device, including：

First obtains module, and for obtaining multiple position datas of user, each position data include the user one Time corresponding geographical location and the accuracy for characterizing geographical location confidence level；

Second obtains module, and the corresponding geographical location of each time for indicating according to the multiple position data obtains Variation tendency of the geographical location according to the time；

First determining module is corresponding for each time according to the variation tendency and the expression of the multiple position data Geographical location confidence level, from the multiple position data determine interference position data；

Third obtains module and obtains target position for removing the interference position data from the multiple position data Set data；

4th obtains module, for obtaining the trip track of the user according to the target position data.

A kind of server, which is characterized in that including：

Memory, for storing program；

Processor, for executing described program, described program is specifically used for：

Multiple position datas of user are obtained, each position data include the user in a time corresponding geographical location And the confidence level of the accuracy for characterizing geographical location；

According to the corresponding geographical location of each time that the multiple position data indicates, geographical location is obtained according to the time Variation tendency；

According to the confidence in the corresponding geographical location of each time that the variation tendency and the multiple position data indicate Rank is spent, interference position data are determined from the multiple position data；

The interference position data are removed from the multiple position data, obtain target position data；

According to the target position data, the trip track of the user is obtained.

It can be seen via above technical scheme that compared with prior art, the embodiment of the invention provides a kind of trip tracks Acquisition methods obtain multiple position datas of user, geographical position accordingly of each time indicated according to the multiple position data It sets, obtains variation tendency of the geographical location according to the time；It is indicated according to the variation tendency and the multiple position data The confidence level in each time corresponding geographical location determines interference position data from the multiple position data；It will interference Position data excludes, and according to the target position data in addition to interference position data, can obtain the trip track of accurate user, To improve the accuracy for obtaining trip track.

Detailed description of the invention

In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is only this The embodiment of invention for those of ordinary skill in the art without creative efforts, can also basis The attached drawing of offer obtains other attached drawings.

Fig. 1 is the structure chart that a kind of trip track provided in an embodiment of the present invention obtains system；

Fig. 2 is a kind of flow chart of track acquisition methods of going on a journey provided in an embodiment of the present invention；

Fig. 3 is the flow chart of another trip track acquisition methods provided in an embodiment of the present invention；

Fig. 4 is a kind of structure chart of track acquisition device of going on a journey provided in an embodiment of the present invention；

Fig. 5 is a kind of structure chart of server provided in an embodiment of the present invention.

Specific embodiment

Following will be combined with the drawings in the embodiments of the present invention, and technical solution in the embodiment of the present invention carries out clear, complete Site preparation description, it is clear that described embodiments are only a part of the embodiments of the present invention, instead of all the embodiments.It is based on Embodiment in the present invention, it is obtained by those of ordinary skill in the art without making creative efforts every other Embodiment shall fall within the protection scope of the present invention.

Trip track provided in an embodiment of the present invention acquisition methods can be applied in trip track acquisition system, such as Fig. 1 It is shown the structure chart that a kind of trip track provided in an embodiment of the present invention obtains system, trip track obtains system and may include At least one terminal device 11 and server 12.

Each terminal device 11 can acquire the position data of user, and be uploaded to server 12.

Terminal device 11 can be the mobile terminals such as smart phone, PAD, laptop.It can be right in terminal device 11 Position where user positions, to obtain position data, and is uploaded in server 12.

Server 12 can analyze multiple position datas of each user, obtain the trip track of each user；Preferably, The trip place preference of the user can also be obtained according to the trip track of each user, and/or, the traffic that each user uses Tool, and/or, the distance in place and destination, the city class of destination, the vehicles are originated according to each user trip The consuming capacity etc. of the excavation such as class user.

Server 12 it is (such as May Day, ten first-class can also to analyze great festivals or holidays according to the trip track of multiple users Deng) each province city tour's situation, it might even be possible to predict possible tourism situation of coming great festivals or holidays.It can be with According to trip track of multiple users during the Spring Festival, analyzing the Spring Festival returns to one's native place the mobility status of personnel, or even the prediction Spring Festival in future Return to one's native place the mobility status of personnel, can also be according to prediction as a result, the traffic programme and management of Optimizing City.

Server can also excavate specific crowd according to the trip track of multiple users, such as weekend goes to Hong Kong from Shenzhen The same day round-trip crowd etc..

Server can be collected into the position data of the user of terminal device acquisition, but the geography of terminal device positioning at present The accuracy of position is not high, for example, by using IP (Internet Protocol Address, internet protocol address) address location side The accuracy in the geographical location that method, WiFi localization method are oriented is not high, using GPS (Global Positioning System, global positioning system) localization method obtain geographical location accuracy it is higher, it is also possible to there is mistake.And During the position data of user is uploaded to server by terminal device, the convenient limitation of privacy of user protection also will receive, Such as some positioning softwares are provided with access authority, then server cannot obtain the user location number of these positioning softwares acquisition According to.

The server location data not high based on these accuracy, the user of acquisition go on a journey the accuracy also phase of track Answer lower, so that server is based on the lower user of accuracy and goes on a journey track, the accuracy of the information of excavation is relatively low.To understand The certainly above problem, the embodiment of the invention provides a kind of trip track acquisition methods, can effectively remove interference position data, Server can obtain accuracy higher user's trip track according to accurate position data.

The trip track approach that server obtains a user below is illustrated, and specific steps are as shown in Fig. 2, trip track Acquisition methods include：

Step S201：Multiple position datas of user are obtained, each position data include that the user is corresponding in the time Geographical location and the accuracy for characterizing geographical location confidence level.

Multiple position datas of user can be at least one terminal device 11 and acquire and be uploaded to server 12.Due to Server 12 may receive the position data of multiple users, and therefore, each position data also need to include user identifier ID, User identifier ID can be IMEI (International Mobile Equipment Identity, the world shifting of terminal device Dynamic device identity) or user cell-phone number or the login name of user etc..

In an application scenarios, user always carries mobile phone trip, and therefore, multiple position datas of user can benefit It is obtained with its portable mobile phone, user identifier ID can be the IMEI of terminal device or the cell-phone number of user at this time；Another In one application scenarios, user may not only one terminal device, but user is positioned using a positioning software, using fixed User is needed to input login name and password during the software of position, user identifier ID can also be the login name of user at this time.? Middle user identifier ID may be identical possible different in different application scenarios, and the present invention is not especially limit this.

Each position data may include at least four element, i.e. user identifier ID, geographical location, time, confidence level grade Not, it is preferred that the format of each position data can be：(user identifier ID, geographical location, time, confidence level), it is each The sequence for 4 elements for including in position data can be any, and the embodiment of the present invention is not specifically limited this.It geographical location can To include：National title, province claim, one or more fields in city name, street name etc., and geographical location can also wrap Include the cell name where user.

In the embodiment of the present invention by terminal device during positioning to user, the data of acquisition are known as original number According to；Terminal device can handle each initial data, and obtain corresponding with each initial data has above-mentioned format respectively Position data.Alternatively, multiple initial data are sent to server by terminal device, server handles each initial data, The position data with above-mentioned format corresponding with each initial data is obtained respectively.

Step S202：According to the corresponding geographical location of each time that the multiple position data indicates, geographical location is obtained Variation tendency according to the time.

Geographical location includes according to the variation tendency of time：User goes out line direction trend, and/or, the purpose of user's trip Ground trend.It is illustrated below with the destination trend that a specific example goes out line direction trend and user's trip to user.Assuming that Geographical location include national title, province claim, city name, and multiple position datas that a user identifier ID is 10001 are such as Under：

(10001, China, Guangdong Province, Shenzhen, September 12 days 9:48, confidence level)；

(10001, China, Guangdong Province, Shenzhen, September 12 days 13:48, confidence level)；

(10001, China, Henan Province, Zhengzhou City, September 12 days 21:48, confidence level)；

(10001, the U.S., California, San Francisco, September 12 days 23:48, confidence level)

(10001, China, Shaanxi Province, Xi'an, September 13 days 06:48, confidence level)；

(10001, China, Shaanxi Province, Xi'an, September 13 days 10:48, confidence level)；

(10001, China, Shaanxi Province, Xi'an, September 14 days 15:48, confidence level).

In above-mentioned multiple position datas, the geographical location process of changing with time is：China, Guangdong Province, Shenzhen's (September 12 days 9:48) → China, Guangdong Province, Shenzhen (September 12 days 13:47) → China, Henan Province, Zhengzhou City (September 12 days 21:22) → the U.S., California, (September 12 days 21, San Francisco:22) → China, Shaanxi Province, Xi'an (September 13 days 06:2) → in State, Shaanxi Province, Xi'an (September 13 days 10:22) → China, Shaanxi Province, Xi'an (September 14 days 15:22).

User goes out line direction trend：8 hours are from Chinese Shenzhen City, Guangdong Province to Henan, China Zhengzhou City；2 Hour is from Chinese Zhengzhou City Henan Province to San Francisco, State of California, US；7 hours are from the old gold of California, USA Mountain to Shaanxi Province, China Xi'an.

User trip destination trend include：4 hours are stopped in Shenzhen of Guangdong province, China；In Henan, China Zheng State city does not stop；It is not stayed in San Francisco, State of California, US；33 hours are stopped in Shaanxi Province, China Xi'an.

Step S203：The confidence level of accuracy according to the variation tendency and for characterizing geographical location, from Interference position data are determined in the multiple position data.

Interference position data may include the position data of geographical location exception, the production of the position data of geographical location exception Reason there are many raw, the embodiment of the present invention are provided but are not limited to following several：

The first, terminal device is to user position position inaccurate.

The position data that terminal device is obtained according to IP address localization method, may lead to geographical location due to following problems Position mistake：One, operator IP assignment error, so that the corresponding geographical location of IP address true geographical position corresponding with IP address It sets and is not inconsistent；Two, carry out IP address positioning using proxy server, then what is obtained is the geographical location where proxy server, and The geographical location where geographical location and user where proxy server is not inconsistent.

The position data that terminal device is obtained according to WiFi localization method may cause geographical location fixed due to following problems Bit-errors：One, the position coordinates mistake of the Wi-Fi hotspot of fixed position；Two, the WiFi heat of the fixation position near terminal device The negligible amounts of point.

Second, multiple users positioned at diverse geographic location log in positioning software using same account.

Assuming that user identifier is that the login name of user just may be used after user needs to log in a positioning software using the login name To obtain the geographical location where oneself by the positioning software, if at a time (being assumed to be for the first moment), user (assuming that Location is Beijing) account has been lent into other users (assuming that location is the U.S.), it will obtain in the first moment user Position data in the U.S., although the positioning of this position data is correct, for the user, this position data is dry Disturb position data.

The position data of geographical location exception, may result in user to go out in line direction trend includes that abnormal line direction out becomes Gesture, for example, 2 hours add from Chinese Zhengzhou City Henan Province to San Francisco, State of California, US and 7 hours from the U.S. The state Li Funiya San Francisco to Shaanxi Province, China Xi'an.

In a preferred embodiment, interference position data can also include：The corresponding position in user's short stay geographical location Set data.

It is only the place passed by because the geographical location of user's short stay is not that user needs destination to be achieved, this A little position datas can interfere the destination in the trip track for obtaining user, it is preferred, therefore, that interference position data Including the corresponding position data in user's short stay geographical location.

For example, in above-mentioned specific example, interference position data include：(10001, the U.S., California, San Francisco, September 12 days 23:48) and (10001, China, Henan Province, Zhengzhou City, September 12 days 21:48).

Step S204：The interference position data are removed from the multiple position data, obtain target position data.

Step S205：According to the target position data, the trip track of the user is obtained.

A kind of trip track acquisition methods provided in an embodiment of the present invention obtain multiple position datas of user, according to institute The corresponding geographical location of each time that multiple position datas indicate is stated, variation tendency of the geographical location according to the time is obtained；According to The confidence level in the corresponding geographical location of each time that the variation tendency and the multiple position data indicate, from described Interference position data are determined in multiple position datas；Interference position data are excluded, according to the target in addition to interference position data Position data, can obtain the trip track of accurate user, to improve the accuracy for obtaining trip track.

It is provided in an embodiment of the present invention " according to the corresponding geographical location of each time that the multiple position data indicates, to obtain Obtain variation tendency of the geographical location according to the time " there are many ways to, the embodiment of the present invention is provided but is not limited to following several：

The first, user goes out line direction trend.

Due to the limitation of running speed of transportation means, each geographical location jumps speed also and has certain rate limitation, And do not had to using different vehicles users by the travel speed in each geographical location, that is, the different vehicles are used, respectively Geographical location jumps speed difference.

For example, if the vehicles be aircraft, and the travel speed of aircraft be likely larger than or be equal to First Speed, and be less than or In second speed, then the speed that jumps in geographical location can be more than or equal to First Speed, and is less than or equal to second speed；If The vehicles are high-speed rail, and the travel speed of high-speed rail is likely larger than or is equal to third speed, and is less than or equal to fourth speed, then The speed that jumps in geographical location can be more than or equal to third speed and less than or equal to fourth speed；If the vehicles are Vehicle, and the travel speed of motor-car is greater than or equal to the 5th speed and is less than or equal to the 6th speed, then geographical location jumps speed Degree can be greater than or equal to the 5th speed and be less than or equal to the 6th speed.

To sum up, each vehicles have the travel speed range of oneself, use the different vehicles, the jump in geographical location The affiliated velocity interval of rotary speed is different.

Specifically, " according to the multiple position data indicate corresponding geographical location of each time, obtain geographical location according to According to the variation tendency of time " include：

The multiple position data is divided at least one set of trip data set, a trip data set includes at least two Temporally adjacent position data.According to the corresponding geographical location of each group trip data set, each group trip data collection is determined respectively It closes corresponding geographical location and jumps speed.

Still it is illustrated with the example above to temporally adjacent, with (10001, China, Shaanxi Province, Xi'an, September 13 days 06: 48, confidence level) the temporally adjacent position data of this position data includes：(10001, the U.S., California is old Kingsoft, September 12 days 23:48, confidence level) and (10001, China, Shaanxi Province, Xi'an, September 13 days 10:48, confidence Spend rank).

Shaanxi Province, China Xi'an, the time of cost are still jumped to from San Francisco, State of California, US with geographical location For 7 hours, then the speed that jumps in the two geographical locations is：San Francisco, State of California, US and Shaanxi Province, China Distance/7 hour of Xi'an.

Correspondingly, each time indicated according to the variation tendency and the multiple position data is geographical accordingly The confidence level of position determines that interference position data include from the multiple position data：According to each group trip data collection Close the confidence that corresponding geographical location jumps the corresponding geographical location of each time that speed and the multiple position data indicate Rank is spent, determines the interference position data.

" jump what speed and the multiple position data indicated according to the corresponding geographical location of each group trip data set The confidence level in each time corresponding geographical location, determines the interference position data " implementation there are many, the present invention Embodiment is provided but is not limited to following several.

If one, server only needs to obtain using the position data under a certain vehicles, can be handed over according to this kind The logical corresponding velocity interval of tool, is obtained the position data during being gone on a journey using the vehicles, will use other The vehicles gone on a journey during position data, be determined as interference position data.

Specifically, by use other vehicles gone on a journey during position data in confidence level be set as Pre-set level, pre-set level can be less than any confidence in the corresponding geographical location of each time that the multiple position data indicates Spend rank.

Confidence level is less than or equal to the position data of pre-set level, is determined as interference position data, wherein confidence Degree rank is less than or equal to the position that the position data of pre-set level includes during being gone on a journey using other vehicles Data.

Two, speed can also be jumped by geographical location, determines erroneous position data, it is assumed that present speed is most fast The travel speed of the vehicles is speed A, if geographical location jumps speed greater than speed A, due in actual life, user's Travel speed can not be more than speed A, it is clear that have the position data of geographical location mistake.

Specifically, " jumping speed and the multiple positional number according to the corresponding geographical location of each group trip data set According to the confidence level in the corresponding geographical location of each time of expression, the interference position data are determined " include：

From each group trip data set, determine that geographical location jumps speed and goes out line number more than or equal to the target of threshold speed According to set；

By the smallest position data of confidence level in the target trip data set, it is determined as the interference position number According to or, the target is gone out line number when the confidence level of all position datas in the target trip data set is identical According to position datas all in set, it is determined as the interference position data.

Since the localization method of each position data may be different, the geographical location that different localization methods is oriented it is accurate Degree is different, and in a preferred embodiment, server or mobile terminal can determine respectively according to the data source of each position data The corresponding confidence level of each position data.Data source refers to the localization method for obtaining corresponding position data；Confidence level The higher accuracy for illustrating the Geographic mapping in position data is higher.Preferably, the accuracy in the geographical location of GPS positioning Higher than the accuracy in the geographical location in the geographical location and IP address positioning of WiFi positioning；The geographical location of WiFi positioning and IP Depending on the height of the accuracy in the geographical location of location positioning can be according to actual conditions.For example, the Wi-Fi hotspot in fixed position In more application scenarios, the accuracy in the geographical location of WiFi positioning is higher than the accuracy in the geographical location of IP address positioning, That is the confidence level in the geographical location of WiFi positioning is higher than several times of confidence level of the geographical location of IP address positioning.

Confidence level can be indicated with number and/or letter, and the present invention is not especially limit this.Example Such as, it is 0.5, IP that the confidence level of the position data of GPS positioning, which is the confidence level of the position data of 1, WiFi positioning, The confidence level of the position data of location positioning is 0.3.If the data source of position data only one, may not need setting at this time and set Confidence level, if there are two the data sources of position data, confidence level can be simply provided, for example, confidence level Including accurate rank and fuzzy rank, wherein the other value of class of accuracy is greater than the other value of blur level, such as the other value of class of accuracy is 1, The other value of blur level is 0.

The confidence level in each geographical location can be by mobile terminal acquisition, be then forwarded to server；It can be with It is the data source that mobile terminal identifies each geographical location, and each geographical location is marked, different data sources pair The mark in the geographical location answered is different, and server can identify accordingly according to each geographical location, determines each geographical location respectively Confidence level.

Second, the destination trend of user's trip.

If geographical location is the destination of user's trip, user is greater than or equal to pre- in the geographical location residence time If the time, if being less than preset time in a geographical location residence time, which should be the place that user passes by, It is not that user wants the destination reached.

" according to the corresponding geographical location of each time that the multiple position data indicates, geographical location is obtained according to the time Variation tendency " include：

The multiple position data is divided at least one set of trip data set, a trip data set includes at least two Temporally adjacent position data；According to the corresponding geographical location of each group trip data set, each group trip data collection is determined respectively Close the corresponding geographical location residence time.

Correspondingly, each time indicated according to the variation tendency and the multiple position data is geographical accordingly The confidence level of position determines that interference position data include from the multiple position data：According to each group trip data collection Close the confidence in the corresponding geographical location of each time of corresponding geographical location residence time and the expression of the multiple position data Rank is spent, determines the interference position data.

Specifically, described according to each group trip data set corresponding geographical location residence time and the multiple position The confidence level in the corresponding geographical location of each time that data indicate, determines that the interference position data include：

From each group trip data set, determine that the residence time is less than or equal to the target trip data collection of preset time It closes；

The confidence level in the corresponding geographical location of each time that each position data in the target trip data set are indicated Rank is set as pre-set level；

Confidence level in the multiple position data is less than or equal to the position data of the pre-set level, is determined as The interference position data.

Alternatively, the direct basis each group trip data set corresponding geographical location residence time, determines the interference position Data, specifically：

From each group trip data set, determine that the residence time is less than or equal to the target trip data collection of preset time It closes；By all position datas in the target data set, it is determined as the interference position data.

The third is jumped in conjunction with the first and the second way according to the corresponding geographical location of each group trip data set The confidence level in the corresponding geographical location of each time that rotary speed and the multiple position data indicate, determines the interference Position data；And according to each group trip data set corresponding geographical location residence time and the multiple position data table The confidence level in the corresponding geographical location of each time shown determines the interference position data.

To sum up, three kinds of methods provided in an embodiment of the present invention mainly using geographical location jump the normal principle of speed and The principle of valuable stop has carried out the filtering of interference position data.And it is preferred, during filtering interference position data The higher position data of confidence level can be retained.

It is understood that there are temporally adjacent and have in the multiple position datas being related in above-mentioned three kinds of modes Multiple position datas of same geographic location, in the mistake of " the multiple position data is divided at least one set of trip data set " Identical two position datas in temporally adjacent and geographical location may be divided into one group of trip data set, it is clear that this group by Cheng Zhong The speed that jumps in the corresponding geographical location of trip data set is zero, and this calculating is nonsensical；Although this group of trip data Gather the corresponding residence time less than or equal to preset time, cannot guarantee that the geographical location is not destination, because may There are also temporally adjacent with the two position datas and with same geographic location position datas to be not contained in the trip of this group In data acquisition system.

So in order to reduce calculating similar this meaningless and that error may be brought, it is preferred that by temporally adjacent and tool There are multiple position datas of same geographic location to merge.Then again by by after merging position data and do not need to close And position data gathered, the position data after set is divided at least one set of trip data set, then determine to interfere After position data, interference position data are removed.

It is understood that the time non-conterminous position data before removing interference position data, interferes position in removal After setting data, be likely to become temporally adjacent position data because by interference position data removal after, before with interference position number Become position data temporally adjacent each other according to two temporally adjacent position datas, if the geographical location phase of the two data Together, then it also needs to merge again, then removes interference position data again, therefore, the process for obtaining target position data includes： Merge → going interference position data → and merges → go the cyclic process of interference position data.

As shown in figure 3, for the flow chart of another trip track acquisition methods provided in an embodiment of the present invention, this method packet It includes：

Step S301：Multiple position datas of user are obtained, each position data include that the user is corresponding in the time Geographical location and the accuracy for characterizing geographical location confidence level.

Assuming that geographical location includes country, province, city, it is assumed that the data source of multiple position datas in step S301 There are two types of, for the position data that is positioned using IP address and using the position data of GPS positioning, and using IP address into The confidence level of the position data of row status is 0, and the confidence level using the position data of GPS positioning is 1, it is assumed that each The format of position data can be：(user identifier ID, country, province, city, time, confidence level), it is assumed that user identifier ID is 10001, and multiple position datas of user are as follows：

(10001, China, Guangdong Province, Shenzhen, September 12 days 9:48,1)；

(10001, China, Guangdong Province, Shenzhen, September 12 days 13:47,0)；

(10001, China, Guangdong Province, unknown city, September 12 days 14:32,0)；

(10001, China, Henan Province, unknown city, September 12 days 20:45,0)；

(10001, China, Henan Province, Zhengzhou City, September 12 days 21:22,1)；

(10001, China, Shaanxi Province, Xi'an, September 13 days 06:22,1)；

(10001, China, Shaanxi Province, Xi'an, September 13 days 10:22,0)；

(10001, China, Shaanxi Province, Xi'an, September 13 days 15:22,1)；

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

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

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

Step S302：At least one set of position data to be combined is determined from the multiple position data, wherein one group is waited closing And position data includes multiple position datas temporally adjacent and with same geographic location.

It is understood that the data source due to geographical location is different, the precision of some Geographic mappings is higher, example City can be such as navigated to, or even navigates to street or cell；Some positioning accuracy is lower, such as navigates to province, or even only Country can be navigated to, since the position data lacked to geographic location field can not judge the position data temporally adjacent with it Whether geographical location is identical, it is preferred that executes in step S302 and " determines at least one set of position to be combined in the multiple position data Set data " during to geographic location field missing position data carry out completion.

If not carrying out completion in step s 302, position data that step S302 can only be complete to geographic location field into Row data merge, such as in the above example, including 3 groups of position datas to be combined, wherein one group of position data packet to be combined It includes：(10001, China, Guangdong Province, Shenzhen, September 12 days 9:48,1) and (10001, China, Guangdong Province, Shenzhen, September 12 days 13:47), 0；One group of position data to be combined includes：(10001, China, Shaanxi Province, Xi'an, September 13 days 06:22, 1), (10001, China, Shaanxi Province, Xi'an, September 13 days 10:22,0), (10001, China, Shaanxi Province, Xi'an, September 13 Day 15:22,1)；One group of position data to be combined includes：(10001, China, Beijing, Beijing, September 13 days 20:22,0), (10001, China, Beijing, Beijing, September 14 days 09:45,1).

Step S303：Data merging is carried out to each group position data to be combined respectively, obtains each group position data to be combined It is corresponding to merge position data, wherein to merge the initial time of position data for the position in corresponding position data group to be combined The minimum time of data is set, the maximum time that the time is the position data in corresponding position data group to be combined is terminated.

Due to merge position data include initial time and terminate the time, it is preferred that can by each position data conversion at The position data (user identifier ID, country, province, city, initial time terminate time, confidence level) of following format, by It is not merged in each position data, so the initial time of each position data is identical as the time is terminated.To each position data Result after being changed is as follows：

(10001, China, Guangdong Province, Shenzhen, September 12 days 9:48, September 12 days 9:48,1)；

(10001, China, Guangdong Province, Shenzhen, September 12 days 13:47, September 12 days 13:47,0)；

(10001, China, Guangdong Province, unknown city, September 12 days 14:32, September 12 days 14:32,0)；

(10001, China, Henan Province, unknown city, September 12 days 20:45, September 12 days 20:45,0)；

(10001, China, Henan Province, Zhengzhou City, September 12 days 21:22, September 12 days 21:22,1)；

(10001, China, Shaanxi Province, Xi'an, September 13 days 06:22, September 13 days 06:22,1)；

(10001, China, Shaanxi Province, Xi'an, September 13 days 10:22, September 13 days 10:22,0)；

(10001, China, Shaanxi Province, Xi'an, September 13 days 15:22, September 13 days 15:22,1)；

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

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

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

Data merging is carried out to each group position data to be combined, obtaining merging position data can be as follows：

(10001, China, Guangdong Province, Shenzhen, September 12 days 9:12 days 48,09 months 13:47,1)；

(10001, China, Shaanxi Province, Xi'an, September 13 days 06:22, September 13 days 15:22,1)；

(10001, China, Beijing, Beijing, September 13 days 20:22, September 14 days 09:45,1).

Preferably, each confidence level for merging position data is corresponding positional number to be combined in the embodiment of the present invention According to the maximum confidence rank of the position data in group.

By the confidence level of position data after merging：The higher position data of confidence level can be to confidence Spend the support that the lower position data of rank carries out a confidence level.I.e. near the lower position data of confidence level if There is the higher position data of confidence level, then will to be authenticated to be confidence level higher for the lower position data of confidence level Position data.So inventive point herein is that precise information (i.e. the higher position data of confidence level) can be to fuzzy number It is promoted according to the confidence level of (i.e. the lower position data of confidence level), and fuzzy data is identified as being perfect number According to overall data being made more comprehensive later.

Step S304：Each merging position data is mutually collected with the position data not merged in the multiple position data It closes, the position data after being gathered；Position data temporally adjacent in position data after set is determined as one group of trip Data acquisition system.

Still for above-mentioned, then the position data after gathering includes：

(10001, China, Guangdong Province, Shenzhen, September 12 days 9:12 days 48,09 months 13:47,1)；

(10001, China, Guangdong Province, unknown city, September 12 days 14:32, September 12 days 14:32,0)；

(10001, China, Henan Province, unknown city, September 12 days 20:45, September 12 days 20:45,0)；

(10001, China, Henan Province, Zhengzhou City, September 12 days 21:22, September 12 days 21:22,1)；

(10001, China, Shaanxi Province, Xi'an, September 13 days 06:22, September 13 days 15:22,1)；

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

(10001, China, Beijing, Beijing, September 13 days 20:22, September 14 days 09:45,1).

For set after position data in, if each position data are sorted from small to large according to initial time, one The termination time of data is set, is the initial time of its next position data, the initial time of a position data is that its is previous The termination time of position data.

If having carried out completion to the position data of geographic location field missing in step S302, walked herein without this completion Suddenly；If step S302 does not carry out completion to the position data of geographic location field missing, step S304 is also needed to geographical position The position data for setting field missing carries out completion.

Either in step s 302, still the position data of geographic location field missing is mended in step s 304 Full method, including：

From position data to be processed, the position data of geographic location field missing is determined；

The position data complete according to the geographical location temporally adjacent with the position data of geographic location field missing, over the ground The position data for managing location field missing carries out completion；

At least one set of position data to be combined is determined in the position data complete from geographic location field.

For step S302, position data to be processed is the multiple position data；For step S304, wait locate Reason position data is the position data after set.

It is exemplified below " complete according to the geographical location temporally adjacent with the position data of geographic location field missing The method of position data, the position data progress completion to geographic location field missing ".

Specifically, can sort from small to large to all position datas of user according to initial time, it is temporally adjacent in this way Position data, it is also adjacent in position.It is assumed that if discovery geographical location lacks this field of city after sequence, according to such as Under type carries out completion.

When two temporally adjacent position data (i.e. former and later two positional numbers of the position data lacked with geographic location field According to) province it is identical, when the difference of city, completion is not carried out to the position data of geographical topagnosis.When with geographic location field The position data of missing temporally adjacent two are lacked according to geographic location field when position data province is identical and city is identical The temporally adjacent any position data of the position data of mistake carry out completion to the position data of geographic location field missing；When with Two position data provinces that the position data of geographic location field missing is temporally adjacent are different, then foundation and geographic location field The identical and temporally adjacent position data in province in the position data of missing carries out the position data of geographic location field missing Completion.

The logic in completion province, city, street, cell etc. is similar, and which is not described herein again.

For example, it is as follows to carry out the position data after completion to the position data after above-mentioned set：

(10001, China, Guangdong Province, Shenzhen, September 12 days 9:12 days 48,09 months 13:47,1)；

(10001, China, Guangdong Province, Shenzhen, September 12 days 14:32, September 12 days 14:32,1)；

(10001, China, Henan Province, Zhengzhou City, September 12 days 20:45, September 12 days 20:45,1)；

(10001, China, Henan Province, Zhengzhou City, September 12 days 21:22, September 12 days 21:22,1)；

(10001, China, Shaanxi Province, Xi'an, September 13 days 06:22, September 13 days 15:22,1)；

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

(10001, China, Beijing, Beijing, September 13 days 20:22, September 14 days 09:45,1).

Preferably, can be temporally adjacent according to the position data lacked with geographic location field in the embodiment of the present invention, and The confidence level of the complete position data in geographical location determines the confidence level grade of the position data of geographic location field missing Not.

Specifically, when the geographical location phase of the temporally adjacent each position data of the position data lacked with geographic location field Meanwhile by the temporally adjacent each position data of the position data lacked with geographic location field, maximum confidence rank is determined For the confidence level of the position data of geographic location field missing；

When second word in the geographical location of the temporally adjacent each position data of the position data lacked with geographic location field When section is not identical, the position data lacked with geographic location field had into identical second field and temporally adjacent position data Confidence level, be determined as geographical location missing position data confidence level.

To sum up, the higher position data of confidence level can carry out a confidence to the lower position data of confidence level The support of degree.I.e. if there is the higher position data of confidence level near the lower position data of confidence level, then The lower position data of confidence level will be authenticated to be the higher position data of confidence level.So inventive point herein is Precise information (i.e. the higher position data of confidence level) can be to fuzzy data (i.e. the lower position data of confidence level) Confidence level promoted, and fuzzy data is identified as being that overall data can be made more comprehensive after precise information.

It is found by the example above, the position data after completion may can also carry out data merging, carry out data again Position data after merging is as follows：

(10001, China, Guangdong Province, Shenzhen, September 12 days 09:48, September 12 days 14:32,1)；

(10001, China, Henan Province, Zhengzhou City, September 12 days 20:45, September 12 days 21:22,1)；

(10001, China, Shaanxi Province, Xi'an, September 13 days 06:22, September 13 days 15:22,1)；

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

(10001, China, Beijing, Beijing, September 13 days 20:22, September 14 days 09:45,1).

To sum up, for ease of description the embodiment of the present invention by position data geographical location lack field be known as the first word Section, is known as the second field for the field not lacked in geographical location.

Wherein, " the positional number complete according to the geographical location temporally adjacent with the position data of geographic location field missing According to the position data progress completion lacked to geographic location field " may include：

When identical as the geographical location of each position data that the position data that geographic location field lacks is temporally adjacent, according to According to the geographical location of the temporally adjacent any position data of the position data lacked with geographic location field, to geographic location field The position data of missing carries out completion；

When second word in the geographical location of the temporally adjacent each position data of the position data lacked with geographic location field Duan Xiangtong, and when the first field difference, completion is not carried out to the position data of geographic location field missing；

When second word in the geographical location of the temporally adjacent each position data of the position data lacked with geographic location field When section is not identical, there is identical second field and temporally adjacent positional number according to the position data of geographic location field missing According to the position data progress completion lacked to geographic location field.

Step S305：According to the corresponding geographical location of each group trip data set, each group trip data set is determined respectively Corresponding geographical location jumps speed；And/or according to the corresponding geographical location of each group trip data set, each group is determined respectively The trip data set corresponding geographical location residence time.

Step S306：Speed and the multiple positional number are jumped according to the corresponding geographical location of each group trip data set According to the confidence level in the corresponding geographical location of each time of expression, the interference position data are determined；And/or according to each group Each time that trip data set corresponding geographical location residence time and the multiple position data indicate is geographical accordingly The confidence level of position determines the interference position data.

Step S307：The interference position data in position data after the set that removal step S304 is determined；Judgement is gone Except whether the position data after the set of interference position data has temporally adjacent and same geographic location multiple position datas, If so, thening follow the steps S308；If it is not, thening follow the steps S309.

Still for above-mentioned, then the position data after removing interference position data includes：

(10001, China, Guangdong Province, Shenzhen, September 12 days 09:48, September 12 days 14:32,1)；

(10001, China, Shaanxi Province, Xi'an, September 13 days 06:22, September 13 days 15:22,1)；

(10001, China, Beijing, Beijing, September 13 days 20:22, September 14 days 09:45,1).

Step S308：From the position data after the set of the removal interference position data determined in step S307, determine At least one set of position data to be combined, wherein one group of position data to be combined includes temporally adjacent and has same geographic location Multiple position datas, return step S303.

Step S309：Position data after the set for removing interference position data is determined as the target position data.

It is understood that still being remained by constantly merging into data, removing interference position data, completion Position data be only user whithin a period of time in some city or street or the correct location information of cell, then the time Adjacent position data is indicated as the primary trip of user.

To sum up, it obtains target position data process and is denoted as merging → completion → merging → removal interference position data circulation Process, or, the cyclic process of completion → merging → removal interference position data.

Still for above-mentioned, then target position data includes：

(10001, China, Guangdong Province, Shenzhen, September 12 days 09:48, September 12 days 14:32,1)；

(10001, China, Shaanxi Province, Xi'an, September 13 days 06:22, September 13 days 15:22,1)；

(10001, China, Beijing, Beijing, September 13 days 20:22, September 14 days 09:45,1).

According to target position data, the trip track of the user of acquisition includes：

Shenzhen to Xi'an, September 12 days 14:32 set out, and September 13 days 06:22 reach, and are determined as train or vapour according to speed per hour Vehicle is docked to September 13 days 15 in Xi'an:22；

Xi'an to Beijing, September 13 days 15:22 set out, September 13 days 20:22 reach, and are determined as high-speed rail according to speed per hour or move Vehicle is also not finished in Beijing residence time (since subsequent data have not yet been viewed).

Present example additionally provides trip track acquisition device corresponding with trip track acquisition methods, the two embodiment It can refer to each other, no longer be repeated herein.

As shown in figure 4, for a kind of structure chart for track acquisition device of going on a journey provided in an embodiment of the present invention, the device packet It includes：

First obtains module 41, and for obtaining multiple position datas of user, each position data include that the user exists One time corresponding geographical location and the accuracy for characterizing geographical location confidence level；

Second obtains module 42, and the corresponding geographical location of each time for indicating according to the multiple position data is obtained Obtain variation tendency of the geographical location according to the time；

First determining module 43, for each time phase according to the variation tendency and the expression of the multiple position data The confidence level in the geographical location answered determines interference position data from the multiple position data；

Third obtains module 44 and obtains target for removing the interference position data from the multiple position data Position data；

4th obtains module 45, for obtaining the trip track of the user according to the target position data.

Optionally, the second acquisition module 42 includes：

Division unit, for the multiple position data to be divided at least one set of trip data set, a trip data collection Closing includes at least two temporally adjacent position datas；

First determination unit, for determining each group trip respectively according to the corresponding geographical location of each group trip data set The corresponding geographical location of data acquisition system jumps speed.

Optionally, first determining module includes：

Third determination unit, for jumping speed and described more according to the corresponding geographical location of each group trip data set The confidence level in the corresponding geographical location of each time that a position data indicates, determines the interference position data.

Optionally, the third determination unit includes：

Second determines subelement, for determining that geographical location jumps speed and is greater than or waits from each group trip data set In the target trip data set of threshold speed；

Third determines subelement, is used for the smallest position data of confidence level in the target trip data set, It is determined as the interference position data, or, when the confidence level phase of all position datas in the target trip data set Meanwhile by all position datas in the target trip data set, it is determined as the interference position data.

Optionally, the second acquisition module 42 further includes：

Second determination unit, for determining each group trip respectively according to the corresponding geographical location of each group trip data set The data acquisition system corresponding geographical location residence time.

Optionally, the second acquisition module 42 includes：

Division unit, for the multiple position data to be divided at least one set of trip data set, a trip data collection Closing includes at least two temporally adjacent position datas；

4th determination unit, for determining each group trip respectively according to the corresponding geographical location of each group trip data set The data acquisition system corresponding geographical location residence time.

Optionally, first determining module 43 includes：

5th determination unit, for according to each group trip data set corresponding geographical location residence time and described more The confidence level in the corresponding geographical location of each time that a position data indicates, determines the interference position data.

Optionally, the 5th determination unit includes：

4th determines subelement, when for from each group trip data set, determining that the residence time is less than or equal to default Between target trip data set；

Subelement is set, and each time for indicating each position data in the target trip data set is accordingly The confidence level of reason position is set as pre-set level；

5th determines subelement, for confidence level in the multiple position data to be less than or equal to the default grade Other position data is determined as the interference position data.

Optionally, the division unit includes：

6th determines subelement, for determining at least one set of position data to be combined from position data to be processed, wherein One group of position data to be combined includes multiple position datas temporally adjacent and with same geographic location；

First obtains subelement, for carrying out data merging to each group position data to be combined respectively, obtains each group and waits closing And position data merges position data accordingly, wherein the initial time for merging position data is corresponding positional number to be combined According to the minimum time of the position data in group, the maximum that the time is the position data in corresponding position data group to be combined is terminated Time；

Second obtains subelement, for by each merging position data and the position not merged in the multiple position data Data are mutually gathered, the position data after being gathered；Position data temporally adjacent in position data after set is determined as One group of trip data set.

Optionally, the position data to be processed includes the multiple position data, or, having temporally adjacent and in the same manner Position data after managing multiple position data set of position, the third obtain module 44 and include：

Unit is deleted, for removing the interference position data in the position data after gathering；

6th determination unit, if for not having temporally adjacent and same geographic location position in the position data after gathering When setting data, the position data after the set is determined as the target position data.

Optionally, each geographical location includes multiple fields, and the described 6th determines that subelement includes：

First determines submodule, for from position data to be processed, determining the position data of geographic location field missing；

Completion submodule, for complete according to the geographical location temporally adjacent with the position data of geographic location field missing Position data, to geographic location field missing position data carry out completion；

Second determines submodule, for determining at least one set of position to be combined from the complete position data of geographic location field Set data.

Optionally, one merges the confidence level of position data for the position data in corresponding position data group to be combined Maximum confidence rank；

And/or further include：Second determining module, is used for：

The position data complete according to the geographical location temporally adjacent with the position data of geographic location field missing is set Confidence level determines the confidence level of the position data of geographic location field missing.

The embodiment of the invention also provides a kind of servers, as shown in figure 5, being a kind of service provided in an embodiment of the present invention The structure chart of device, the server include：

Memory 51, for storing program；

Program may include program code, and said program code includes computer operation instruction.

Processor 52, for executing described program.

Memory 51 may include high speed RAM memory, it is also possible to further include nonvolatile memory (non-volatile Memory), a for example, at least magnetic disk storage.

Processor 52 may be a central processor CPU or specific integrated circuit ASIC (Application Specific Integrated Circuit), or be arranged to implement the integrated electricity of one or more of the embodiment of the present invention Road.

Wherein, described program is specifically used for：

Multiple position datas of user are obtained, each position data include the user in a time corresponding geographical location And the confidence level of the accuracy for characterizing geographical location；

According to the corresponding geographical location of each time that the multiple position data indicates, geographical location is obtained according to the time Variation tendency；

According to the confidence in the corresponding geographical location of each time that the variation tendency and the multiple position data indicate Rank is spent, interference position data are determined from the multiple position data；

The interference position data are removed from the multiple position data, obtain target position data；

According to the target position data, the trip track of the user is obtained.

Optionally, electronic equipment can also include communication bus 53 and communication interface 54, wherein memory 51, processing Device 52, completes mutual communication by communication bus 53 at communication interface 54；

Optionally, communication interface 54 can be the interface of communication module, such as the interface of gsm module.

Finally, it is to be noted that, herein, relational terms such as first and second and the like be used merely to by One entity or operation are distinguished with another entity or operation, without necessarily requiring or implying these entities or operation Between there are any actual relationship or orders.Moreover, the terms "include", "comprise" or its any other variant meaning Covering non-exclusive inclusion, so that the process, method, article or equipment for including a series of elements not only includes that A little elements, but also including other elements that are not explicitly listed, or further include for this process, method, article or The intrinsic element of equipment.In the absence of more restrictions, the element limited by sentence "including a ...", is not arranged Except there is also other identical elements in the process, method, article or apparatus that includes the element.

Each embodiment in this specification is described in a progressive manner, the highlights of each of the examples are with other The difference of embodiment, the same or similar parts in each embodiment may refer to each other.

The foregoing description of the disclosed embodiments makes professional and technical personnel in the field can be realized or use the application. Various modifications to these embodiments will be readily apparent to those skilled in the art, as defined herein General Principle can be realized in other embodiments without departing from the spirit or scope of the application.Therefore, the application It is not intended to be limited to the embodiments shown herein, and is to fit to and the principles and novel features disclosed herein phase one The widest scope of cause.

Claims (15)

1. a kind of trip track acquisition methods, which is characterized in that including：

Obtain multiple position datas of user, each position data include the user the time corresponding geographical location and For characterizing the confidence level of the accuracy in geographical location；

According to the corresponding geographical location of each time that the multiple position data indicates, variation of the geographical location according to the time is obtained Trend；

According to the confidence level grade in the corresponding geographical location of each time that the variation tendency and the multiple position data indicate Not, interference position data are determined from the multiple position data；

The interference position data are removed from the multiple position data, obtain target position data；

According to the target position data, the trip track of the user is obtained.

2. track acquisition methods of going on a journey according to claim 1, which is characterized in that described according to the multiple position data table The corresponding geographical location of each time shown, the variation tendency for obtaining geographical location according to the time include：

The multiple position data is divided at least one set of trip data set, a trip data set included at least two times Adjacent position data；

According to the corresponding geographical location of each group trip data set, the corresponding geographical location of each group trip data set is determined respectively Jump speed.

3. track acquisition methods of going on a journey according to claim 2, which is characterized in that described according to the variation tendency and institute The confidence level for stating the corresponding geographical location of each time that multiple position datas indicate is determined from the multiple position data Interference position data include：

According to the corresponding geographical location of each group trip data set jump that speed and the multiple position data indicate it is each when Between corresponding geographical location confidence level, determine the interference position data.

4. track acquisition methods of going on a journey according to claim 3, which is characterized in that described according to each group trip data set phase The geographical location answered jumps the confidence level grade in the corresponding geographical location of each time that speed and the multiple position data indicate Not, determine that the interference position data include：

From each group trip data set, determine that geographical location jumps the target trip data that speed is greater than or equal to threshold speed Set；

By the smallest position data of confidence level in the target trip data set, it is determined as the interference position data, Or, when the confidence level of all position datas in the target trip data set is identical, by the target trip data All position datas in set are determined as the interference position data.

5. track acquisition methods of going on a journey according to claim 2, which is characterized in that indicated according to the multiple position data Each time corresponding geographical location, the variation tendency for obtaining geographical location according to the time further include：

According to the corresponding geographical location of each group trip data set, the corresponding geographical location of each group trip data set is determined respectively Residence time.

6. track acquisition methods of going on a journey according to claim 1, which is characterized in that described according to the multiple position data table The corresponding geographical location of each time shown, the variation tendency for obtaining geographical location according to the time include：

The multiple position data is divided at least one set of trip data set, a trip data set included at least two times Adjacent position data；

According to the corresponding geographical location of each group trip data set, the corresponding geographical location of each group trip data set is determined respectively Residence time.

7. track acquisition methods of going on a journey according to claim 6, which is characterized in that described according to the variation tendency and institute The confidence level for stating the corresponding geographical location of each time that multiple position datas indicate is determined from the multiple position data Interference position data include：

According to each group trip data set corresponding geographical location residence time and the multiple position data indicate it is each when Between corresponding geographical location confidence level, determine the interference position data.

8. track acquisition methods of going on a journey according to claim 7, which is characterized in that described according to each group trip data set phase The confidence level grade in the corresponding geographical location of each time that the geographical location residence time answered and the multiple position data indicate Not, determine that the interference position data include：

From each group trip data set, determine that the residence time is less than or equal to the target trip data set of preset time；

The confidence level in the corresponding geographical location of each time that each position data in the target trip data set are indicated It is set as pre-set level；

Confidence level in the multiple position data is less than or equal to the position data of the pre-set level, is determined as described Interference position data.

9. according to any trip track acquisition methods of claim 2 to 8, which is characterized in that described by the multiple position Data are divided at least one set of trip data set：

At least one set of position data to be combined is determined from position data to be processed, wherein one group of position data to be combined includes Multiple position datas temporally adjacent and with same geographic location；

Data merging is carried out to each group position data to be combined respectively, each group position data to be combined is obtained and merges position accordingly Data, wherein when merging minimum of the initial time of position data for the position data in corresponding position data group to be combined Between, terminate the maximum time that the time is the position data in corresponding position data group to be combined；

Each merging position data is mutually gathered with the position data not merged in the multiple position data, after being gathered Position data；Position data temporally adjacent in position data after set is determined as one group of trip data set.

10. track acquisition methods of going on a journey according to claim 9, which is characterized in that the position data to be processed includes institute Multiple position datas are stated, or, with the position data after temporally adjacent and same geographic location multiple position data set, institute It states and removes the interference position data from the multiple position data, obtaining target position data includes：

The interference position data in position data after removal set；

If do not have temporally adjacent and same geographic location position data in the position data after set, after the set Position data be determined as the target position data.

11. track acquisition methods of going on a journey according to claim 10, which is characterized in that each geographical location includes multiple words Section, it is described to determine that at least one set of position data to be combined includes from position data to be processed：

From position data to be processed, the position data of geographic location field missing is determined；

It is temporally adjacent according to the position data lacked with geographic location field, and the position data that geographical location is complete, to geography The position data of location field missing carries out completion；

At least one set of position data to be combined is determined in the position data complete from geographic location field.

12. track acquisition methods of going on a journey according to claim 11, which is characterized in that one merges the confidence level grade of position data Not Wei position data in corresponding position data group to be combined maximum confidence rank；

And/or

According to and geographic location field missing position data it is temporally adjacent, and the confidence level of the complete position data in geographical location Rank determines the confidence level of the position data of geographic location field missing.

13. a kind of trip track acquisition device, which is characterized in that including：

First obtains module, and for obtaining multiple position datas of user, each position data include the user in the time The confidence level of corresponding geographical location and the accuracy for characterizing geographical location；

Second obtains module, and the corresponding geographical location of each time for indicating according to the multiple position data obtains geographical Variation tendency of the position according to the time；

First determining module, each time for being indicated according to the variation tendency and the multiple position data is accordingly The confidence level for managing position determines interference position data from the multiple position data；

Third obtains module and obtains target position number for removing the interference position data from the multiple position data According to；

4th obtains module, for obtaining the trip track of the user according to the target position data.

14. 3 trip track acquisition device according to claim 1, which is characterized in that described second, which obtains module, includes：

Division unit, for the multiple position data to be divided at least one set of trip data set, a trip data set packet Include at least two temporally adjacent position datas；

First determination unit, for determining each group trip data respectively according to the corresponding geographical location of each group trip data set Gather corresponding geographical location and jumps speed；And/or second determination unit, for corresponding according to each group trip data set Geographical location determines each group trip data set corresponding geographical location residence time respectively.

15. a kind of server, which is characterized in that including：

Memory, for storing program；

Processor, for executing described program, described program is specifically used for：

Obtain multiple position datas of user, each position data include the user the time corresponding geographical location and For characterizing the confidence level of the accuracy in geographical location；

According to the corresponding geographical location of each time that the multiple position data indicates, variation of the geographical location according to the time is obtained Trend；

According to the confidence level grade in the corresponding geographical location of each time that the variation tendency and the multiple position data indicate Not, interference position data are determined from the multiple position data；

The interference position data are removed from the multiple position data, obtain target position data；

According to the target position data, the trip track of the user is obtained.