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License: CC BY
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ABBAj.jl: v0.1.1

integration_instructionsResearch softwarekeyboard_double_arrow_right Software 25 Feb 2022Publisher:Zenodo
Authors: Chen, Xinye;

doi: 10.5281/zenodo.6286546 , 10.5281/zenodo.6286545

ABBAj.jl: v0.1.1

Abstract

ABBA (Adaptive Brownian bridge-based aggregation) is a symbolic time series representation method introduced by Elsworth Steven and Stefan Güttel, which archives time-series compression and discretization by transforming time series into a symbolic representation. The software fABBA (https://github.com/nla-group/fABBA) already provides ABBA transformation with appealing speed and tolerance-oriented digitization. The package provides lightweight Julia implementation of the ABBA method, also use ParallelKMeans.jl to achieve speedup in the digitization.

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Keywords

machine learning, knowledge representation, time series compression

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
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