Trajectory Metadata Filtering for Faster Multi-Type Query Retrieval
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Solution Overview
Problem
Existing trajectory query methods suffer from slow query speeds due to the need to sift through large volumes of candidate trajectories, limited by pre-established index depth, making it difficult to directly acquire target trajectories.
Innovation Solution
A method and apparatus that utilize metadata digests of trajectories to determine query ranges, identify candidate metadata within those ranges, and acquire target trajectories efficiently, reducing processing time by filtering through metadata rather than full trajectories.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If pre-established index depth is used for trajectory query, then the query system can be simplified, but the query speed deteriorates due to the need to sift through large volumes of candidate trajectories
Solution Approach 1:
The patent segments the trajectory data structure into two parts: metadata (compact representation) and full trajectory data. The metadata contains essential queryable attributes and is stored in an index, while the full trajectory data is stored separately. This segmentation allows the query system to work with compact metadata instead of full trajectories, improving query speed without requiring complex system changes.
Solution Approach 2:
The patent introduces metadata as an intermediary between the query system and full trajectory data. The metadata acts as a compact proxy that contains sufficient information for filtering and candidate selection, allowing the query system to efficiently narrow down search space before retrieving full trajectory data, thus resolving the speed-complexity contradiction.
2Loss of information
If full trajectories are processed during query, then complete trajectory information is available, but processing time increases due to large data volume
Solution Approach 1:
The patent extracts essential queryable attributes from full trajectories to create compact metadata. The metadata contains key attributes needed for filtering and candidate selection, allowing the system to process only this extracted information during the query phase. Full trajectory data is retrieved only for final candidate verification, minimizing processing time while preserving necessary information.
Solution Approach 2:
The patent performs preliminary processing to create metadata that summarizes essential trajectory characteristics before the query occurs. This pre-computed metadata enables efficient filtering and candidate selection during query execution, reducing the amount of full trajectory data that needs to be processed while maintaining information necessary for accurate query results.
Data Source
AI summary
Provided in the present application are a trajectory query method and apparatus. The trajectory query method comprises: acquiring a trajectory query request, which comprises query information of a plurality of types; according to query information of a service type in the query information of the plurality of types, determining a query range of metadata used as a digest of a trajectory, then determining a plurality of pieces of candidate metadata that are within the query range, and determining, from the plurality of pieces of candidate metadata, target metadata that matches the query information of the plurality of types; and acquiring a target trajectory according to the target metadata. By means of the present application, the trajectory query speed can be increased.