The application discloses a kind of multi-dimensional
time series data compression and fast retrieval method and
system, it is related to
big data compression retrieval technical field.The kind of multi-dimensional
time series data compression and fast retrieval method and
system, including S1, the multi-
source data in monitoring abstract video
stream is collected and preprocessed, constructs
standardization time series behavior dataset;S2, the behavior characteristics of frame section in sliding window are analyzed,
anchor point labeling and compression strategy are dynamically adjusted;S3, the coverage completeness of
anchor point information in compressed section is evaluated, and index
path generation is driven;S4, the behavior correlation strength of path is comprehensively evaluated and dynamically adjusted loading decision;S5, the matching integrity of behavior
anchor point field and jump pointer is verified, and the positionability and jump stability of event in compression structure are guaranteed.Solve the problem that video abstract compression is not bound with behavior
semantics in intelligent monitoring scheme, lacks fine-grained positioning
mechanism based on behavior
label, and user playback cannot directly locate key action section.