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A direction-sensing k-nearest neighbor inquiry method of the road network moving object

A moving object and direction-aware technology, applied in database indexing, geographic information database, structured data retrieval, etc., can solve the problem of not being able to judge whether a moving object is moving towards the query point, and achieve simple grid indexing of moving objects and fast update and query, the effect of efficient query

Active Publication Date: 2019-01-25
ZHEJIANG UNIV OF TECH
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AI Technical Summary

Problems solved by technology

Among the few query methods that consider the movement direction of moving objects, most of them are based on Euclidean distance query processing, which cannot judge whether the moving object is moving towards the query point on a large-scale and complex road.

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  • A direction-sensing k-nearest neighbor inquiry method of the road network moving object

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Embodiment Construction

[0032] The technical solution of the present invention will be further described below in conjunction with the accompanying drawings.

[0033] The direction-aware road network mobile object k-nearest neighbor query method of the present invention comprises the following steps:

[0034] 1 Evaluate the scope of the query;

[0035] Direction-aware road network mobile object k-nearest neighbor query first determines a suitable query range, which includes k-nearest neighbor candidates. The k-nearest neighbor query method of moving objects in the road network that performs direction awareness within the query range improves the query efficiency of the algorithm. The steps are as follows:

[0036] (11) Use the grid index to locate the grid where the query point is located, and then count the number num of moving objects in the grid. Set detection coefficient μ=2, if num is greater than or equal to μ*k, get the range covered by the grid.

[0037] (12) If num is less than μ*k, take ...

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Abstract

A direction-sensing k-nearest neighbor inquiry method of the road network moving object comprises the following steps: step 1, evaluating the inquiry range; 2, constructing a local road network; 3, expanding that direction perceived road network; 4, iteratively expanding the query range; The invention loads a local road network from the road network and predicts the road network distance from thelocal road network node to the inquiry point, thereby realizing the high efficiency of the algorithm. The invention considers the relatively stable 'static' characteristic of the road network and thefrequently updated 'dynamic' characteristic of the moving object, and combines R-Tree efficient and stable query performance and grid index update insensitive characteristics, reasonable use of R-Treeindex road network data, simple grid index moving object, dual index structure to achieve the purpose of rapid updating and efficient query.

Description

technical field [0001] The invention relates to a query method for k nearest neighbors of a mobile object in a road network. Background technique [0002] With the widespread popularity of smart mobile devices and the rapid development of location-based services (Location-based Services, LBS), more and more applications use spatial database technology to meet people's various needs. As one of the most basic query types in spatial databases, k-nearest neighbor query is widely used in real life. For example, the user searches for the nearest k cars to rent a car through taxi-hailing software, which is a typical application of k-nearest neighbor query technology. [0003] K-nearest neighbor query has experienced from simple static object query based on Euclidean distance to complex mobile object query based on road network distance. However, most of the existing k-nearest neighbor queries use distance as the only selection criterion for neighbor objects, without considering t...

Claims

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Application Information

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IPC IPC(8): G06F16/29G06F16/22
Inventor 董天阳苑露露程强
Owner ZHEJIANG UNIV OF TECH
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