CN107169260B - Heterogeneous multi-source data resonance system and method based on space-time trajectory - Google Patents
Heterogeneous multi-source data resonance system and method based on space-time trajectory Download PDFInfo
- Publication number
- CN107169260B CN107169260B CN201710179782.3A CN201710179782A CN107169260B CN 107169260 B CN107169260 B CN 107169260B CN 201710179782 A CN201710179782 A CN 201710179782A CN 107169260 B CN107169260 B CN 107169260B
- Authority
- CN
- China
- Prior art keywords
- time
- similarity
- track
- trajectory
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 238000000034 method Methods 0.000 title claims description 16
- 239000013598 vector Substances 0.000 claims abstract description 33
- 238000004364 calculation method Methods 0.000 claims abstract description 30
- 238000012216 screening Methods 0.000 claims abstract description 11
- 238000009774 resonance method Methods 0.000 claims abstract description 4
- 238000013507 mapping Methods 0.000 claims description 9
- 230000000007 visual effect Effects 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 abstract description 8
- 238000012800 visualization Methods 0.000 abstract description 8
- 238000004458 analytical method Methods 0.000 abstract description 3
- 238000005516 engineering process Methods 0.000 abstract description 3
- 230000003993 interaction Effects 0.000 abstract description 3
- 230000002123 temporal effect Effects 0.000 abstract description 2
- 230000008569 process Effects 0.000 description 4
- 238000006243 chemical reaction Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005065 mining Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 230000001360 synchronised effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
- G16Z99/00—Subject matter not provided for in other main groups of this subclass
Landscapes
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention discloses a spatial-temporal trajectory-based heterogeneous multi-source data resonance system and a spatial-temporal trajectory-based heterogeneous multi-source data resonance method, wherein the system comprises a real-time sequence flow receiving module, a trajectory similarity calculation module and a trajectory visualization module, wherein the real-time sequence flow receiving module is used for receiving a time sequence vector in real time and ensuring the integrity and consistency in the data transmission process; the track similarity calculation module is used for calculating track similarity and screening out tracks with the similarity larger than a certain threshold value as resonance tracks; the trajectory visualization module is used for visually displaying a target trajectory, the trajectory data contains spatial and temporal attributes at the same time, the data volume is large, the dimensionality is high, the difficulty in analysis is high, the visualization technology can visually present multi-dimensional space-time trajectory data and provide rich interaction so as to reveal the space-time law contained in the data. The invention can avoid the situation that the Euclidean distance is separated from the actual situation, ensure the integrity and consistency of data, improve the calculation efficiency and have wide application range.
Description
Technical Field
The invention relates to a data resonance system and a method, in particular to a heterogeneous multi-source data resonance system and a method based on space-time trajectories.
Background
In the traditional calculation process of the track similarity of the Euclidean distance function, the tracks are required to be equal in length and correspond to time points, and the track similarity with unequal length and local event offset cannot be measured. Therefore, the information loss generated in the process of discovering the heterogeneous synchronous track set is large, and the usability of the track data is affected.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a heterogeneous multi-source data resonance system and method based on space-time trajectory, so that the situation that Euclidean distance is separated from reality can be avoided, the integrity and consistency of data are ensured, the calculation efficiency is improved, and the application range is wide.
The invention solves the technical problems through the following technical scheme: a heterogeneous multi-source data resonance system based on spatio-temporal trajectories, comprising:
the real-time sequence flow receiving module is used for receiving the time sequence vector in real time and ensuring the integrity and consistency in the data transmission process;
the track similarity calculation module is used for calculating track similarity and screening out tracks with the similarity larger than a certain threshold value as resonance tracks;
the trajectory visualization module is used for visually displaying a target trajectory, the trajectory data contains space and time attributes at the same time, the data volume is large, the dimensionality is high, the difficulty in analysis is high, the multidimensional space-time trajectory data can be visually presented through a visualization technology, and rich interaction is provided so as to reveal the space-time law contained in the data.
Preferably, the real-time sequence stream receiving module includes:
the data conversion module is used for converting the original track data into a time sequence vector;
and the message transmission module is used for transmitting the time sequence vector to the similarity calculation module in a message mode in real time and ensuring the integrity and consistency in the data transmission process.
Preferably, the trajectory similarity calculation module includes:
the time sequence vector rule module is used for regularizing the received time sequence vector and ensuring the consistency of calculation;
the similarity screening module is used for screening out the track with the similarity larger than a certain threshold value as a resonance track, so that the calculation amount is greatly reduced, and the calculation efficiency is improved;
and the track missing value completion module is used for completing the original query track, the missing track is usually generated in the track data acquisition process, the missing track is completed, and the estimation area passing through the track point in the time range is reduced as much as possible, so that the track missing value completion module is very useful for actual service application.
The invention also provides a spatial-temporal trajectory based heterogeneous multi-source data resonance method, which comprises the following steps:
converting original track data into a time sequence vector;
step two, regularizing a time sequence vector;
step three, vector time slicing;
step four, calculating the similarity through a similarity calculation method to serve as the resonance rate;
screening tracks with the resonance rate larger than a certain numerical value as resonance tracks;
step six, complementing the original query track;
step seven, visualizing the track;
and step eight, finishing.
Preferably, the four steps calculate the distance between the points according to a space-time distance calculation method of hash region mapping, map the geodetic distance into the distance between the region points through a certain hash algorithm, find the corresponding geodetic distance as the similarity through the hash when actually calculating the similarity, and calculate the similarity as the resonance rate by using the hash distance through a similarity calculation method of a time-sequence offset space-time three-dimensional vector sequence; and for the calculation of the similarity of the sequence vectors with different lengths and the similarity of the sequence vectors with misaligned time points, the similarity is recalculated by considering the condition of possible deviation of a time axis through dynamic planning, so as to obtain the final similarity of the two space-time three-dimensional vector sequences.
Preferably, in the sixth step, a similar track is used for performing a track missing value completion method of hash mapping, and missing track points are completed as accurately as possible and the elapsed time range is estimated to be reduced.
Preferably, the seventh step completes the original query trajectory by using a trajectory missing value completion method of similar trajectory hash mapping, and performs visual display.
The positive progress effects of the invention are as follows: the method can effectively discriminate the data and correlate the real data through data resonance under the conditions that the accuracy of a large amount of acquired data is not high and the data is fragmented and the correlation cannot be carried out through a determining means; the data resonance is used for mining the internal relation which is not directly reflected on the data, so that the time-space correlation of different entities is deeply disclosed, and the mutual relation among different independent data is further discovered.
Drawings
FIG. 1 is a schematic structural diagram of the present invention.
FIG. 2 is a flow chart of the present invention.
Detailed Description
The following provides a detailed description of the preferred embodiments of the present invention with reference to the accompanying drawings.
As shown in fig. 1, the multi-source data resonance system based on spatial-temporal trajectory isomerism of the present invention includes a real-time sequence stream receiving module, a trajectory similarity calculation module, and a trajectory visualization module, wherein:
the real-time sequence flow receiving module is used for receiving the time sequence vector in real time and ensuring the integrity and consistency in the data transmission process;
the track similarity calculation module is used for calculating track similarity and screening out tracks with the similarity larger than a certain threshold value as resonance tracks;
the trajectory visualization module is used for visually displaying a target trajectory, the trajectory data contains spatial and temporal attributes at the same time, the data volume is large, the dimensionality is high, the difficulty in analysis is high, the visualization technology can visually present multi-dimensional space-time trajectory data and provide rich interaction so as to reveal the space-time law contained in the data.
The real-time sequence flow receiving module comprises a data conversion module and a message transmission module, wherein:
the data conversion module is used for converting the original track data into a time sequence vector;
the message transmission module is used for transmitting the time sequence vector to the similarity calculation module in a message mode in real time and ensuring the integrity and consistency in the data transmission process.
The track similarity calculation module comprises a time sequence vector rule module, a similarity screening module and a track missing value completion module, wherein:
the time sequence vector rule module is used for regularizing the received time sequence vector and ensuring the consistency of calculation;
the similarity screening module is used for screening out the track with the similarity larger than a certain threshold value as a resonance track, so that the calculation amount can be greatly reduced, and the calculation efficiency is improved;
the track missing value completion module is used for completing an original query track, the track data acquisition process is often missing, how to complete the missing track and how to reduce an estimated area passing through the time range of the track point as much as possible are achieved, and the track missing value completion module is very useful for actual business application.
As shown in FIG. 2, the heterogeneous multi-source data resonance method based on spatio-temporal trajectories of the invention comprises the following steps:
converting original track data into a time sequence vector;
step two, regularizing a time sequence vector;
step three, vector time slicing;
step four, calculating the similarity through a similarity calculation method to serve as the resonance rate;
screening tracks with the resonance rate larger than a certain numerical value as resonance tracks;
step six, complementing the original query track;
step seven, visualizing the track;
and step eight, finishing.
The distance between points is calculated according to a space-time distance calculation method of Hash region mapping, the geodesic distance is mapped into the distance between the region points through a certain Hash algorithm, when the similarity is actually calculated, the corresponding geodesic distance is searched through a Hash to serve as the similarity, and the similarity is calculated through a similarity calculation method of a time-sequence offset space-time three-dimensional vector sequence by using the Hash distance to serve as the resonance rate; for the calculation of the similarity of the sequence vectors with different lengths and the similarity of the sequence vectors with non-aligned time points (allowing the deviation of various time unequal pieces), the similarity is recalculated by considering the possible deviation of a time axis through dynamic planning, and the final similarity of two space-time three-dimensional vector sequences is obtained.
And sixthly, a track missing value completion method for Hash mapping by using similar tracks is used, and missing track points are completed as accurately as possible and the time range is estimated to be reduced.
And seventhly, complementing the original query track by using a track missing value complementing method of similar track Hash mapping, and performing visual display.
The above embodiments are described in further detail to solve the technical problems, technical solutions and advantages of the present invention, and it should be understood that the above embodiments are only examples of the present invention and are not intended to limit the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (1)
1. A heterogeneous multi-source data resonance method based on space-time trajectories is characterized by comprising the following steps:
converting original track data into a time sequence vector;
step two, regularizing a time sequence vector;
step three, vector time slicing;
step four, calculating the similarity through a similarity calculation method to serve as the resonance rate;
screening tracks with the resonance rate larger than a certain numerical value as resonance tracks;
step six, complementing the original query track;
step seven, visualizing the track;
step eight, finishing;
the distance between points is calculated according to a space-time distance calculation method of Hash region mapping, the geodesic distance is mapped into the distance between the region points through a certain Hash algorithm, when the similarity is actually calculated, the corresponding geodesic distance is searched through a Hash to serve as the similarity, and the similarity is calculated through a similarity calculation method of a time-sequence offset space-time three-dimensional vector sequence by using the Hash distance to serve as the resonance rate; for the calculation of the similarity of the sequence vectors with different lengths and the similarity of the sequence vectors with unaligned time points, the similarity is recalculated by considering the condition of time axis offset through dynamic programming to obtain the final similarity of two space-time three-dimensional vector sequences;
sixthly, a track missing value completion method for Hash mapping by using similar tracks is used for completing missing track points and reducing the estimation of the passing time range;
and seventhly, complementing the original query track by using a track missing value complementing method of similar track Hash mapping, and performing visual display.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710179782.3A CN107169260B (en) | 2017-03-23 | 2017-03-23 | Heterogeneous multi-source data resonance system and method based on space-time trajectory |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710179782.3A CN107169260B (en) | 2017-03-23 | 2017-03-23 | Heterogeneous multi-source data resonance system and method based on space-time trajectory |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN107169260A CN107169260A (en) | 2017-09-15 |
| CN107169260B true CN107169260B (en) | 2021-05-11 |
Family
ID=59848821
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710179782.3A Expired - Fee Related CN107169260B (en) | 2017-03-23 | 2017-03-23 | Heterogeneous multi-source data resonance system and method based on space-time trajectory |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN107169260B (en) |
Families Citing this family (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109558470B (en) * | 2017-09-27 | 2021-06-15 | 方正国际软件(北京)有限公司 | Trajectory data visualization method and device |
| CN109376178A (en) * | 2018-08-17 | 2019-02-22 | 中国电子科技集团公司电子科学研究院 | Space-time big data trajectory analysis platform, method, server and storage medium |
| CN111241217B (en) * | 2018-11-29 | 2023-05-30 | 阿里巴巴集团控股有限公司 | Data processing method, device and system |
| CN111666358A (en) * | 2019-03-05 | 2020-09-15 | 上海光启智城网络科技有限公司 | Track collision method and system |
| CN112309118B (en) * | 2020-11-03 | 2021-11-09 | 广州市交通规划研究院 | Vehicle trajectory calculation method based on space-time similarity |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102722541A (en) * | 2012-05-23 | 2012-10-10 | 中国科学院计算技术研究所 | Method and system for calculating space-time locus similarity |
| CN103092925A (en) * | 2012-12-30 | 2013-05-08 | 信帧电子技术（北京）有限公司 | Method and device of generation of video abstract |
| CN104036139A (en) * | 2014-06-12 | 2014-09-10 | 中国科学院软件研究所 | Moving object trajectory monitoring method |
| CN104657424A (en) * | 2015-01-21 | 2015-05-27 | 段炼 | Clustering method for interest point tracks under multiple temporal and spatial characteristic fusion |
| CN106211071A (en) * | 2016-07-04 | 2016-12-07 | 深圳大学 | Group activity method of data capture based on multi-source space-time trajectory data and system |
-
2017
- 2017-03-23 CN CN201710179782.3A patent/CN107169260B/en not_active Expired - Fee Related
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102722541A (en) * | 2012-05-23 | 2012-10-10 | 中国科学院计算技术研究所 | Method and system for calculating space-time locus similarity |
| CN103092925A (en) * | 2012-12-30 | 2013-05-08 | 信帧电子技术（北京）有限公司 | Method and device of generation of video abstract |
| CN104036139A (en) * | 2014-06-12 | 2014-09-10 | 中国科学院软件研究所 | Moving object trajectory monitoring method |
| CN104657424A (en) * | 2015-01-21 | 2015-05-27 | 段炼 | Clustering method for interest point tracks under multiple temporal and spatial characteristic fusion |
| CN106211071A (en) * | 2016-07-04 | 2016-12-07 | 深圳大学 | Group activity method of data capture based on multi-source space-time trajectory data and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN107169260A (en) | 2017-09-15 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN107169260B (en) | Heterogeneous multi-source data resonance system and method based on space-time trajectory | |
| KR102125959B1 (en) | Method and apparatus for determining a matching relationship between point cloud data | |
| CN105526934B (en) | Indoor and outdoor integrated high-precision positioning navigation system and positioning method thereof | |
| CN109100730B (en) | Multi-vehicle cooperative rapid map building method | |
| CN109916393B (en) | Multi-grid-value navigation method based on robot pose and application thereof | |
| US10648803B2 (en) | Movement line information generation system, movement line information generation method and movement line information generation program | |
| Philipp et al. | Mapgenie: Grammar-enhanced indoor map construction from crowd-sourced data | |
| CN110689622A (en) | Synchronous positioning and composition algorithm based on point cloud segmentation matching closed-loop correction | |
| CN102573052B (en) | A kind of target locating method and system based on wireless sensor network | |
| CN111540005B (en) | Loop detection method based on two-dimensional grid map | |
| Civera et al. | Structure from motion using the extended Kalman filter | |
| EP3623844A1 (en) | Obstacle detection method and device | |
| CN110532340B (en) | Spatial information space-time metadata construction method | |
| CN111781608A (en) | Moving target detection method and system based on FMCW laser radar | |
| CN112305559A (en) | Power transmission line distance measuring method, device and system based on ground fixed-point laser radar scanning and electronic equipment | |
| CN105101093A (en) | Network topology visualization method with respect to geographical location information | |
| CN103810751A (en) | Three-dimensional auricle point cloud shape feature matching method based on IsoRank algorithm | |
| Zhang et al. | Stereo plane slam based on intersecting lines | |
| CN110910389B (en) | Laser SLAM loop detection system and method based on graph descriptor | |
| KR20230059150A (en) | Construction method and device of three-dimensional map in high-precision map, equipment and storage medium | |
| CN116086484A (en) | Laser radar mileage calculation method based on ground plane constraint and loop detection | |
| Li et al. | Point-line feature fusion based field real-time RGB-D SLAM | |
| CN109726916A (en) | A method of suitable for highway life cycle management intelligent health monitoring | |
| CN112985410A (en) | Indoor robot self-map-building navigation system based on laser SLAM | |
| Mirdita et al. | Localization for intelligent systems using unsupervised learning and prediction approaches |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20210511 |
|
| CF01 | Termination of patent right due to non-payment of annual fee |