AMIC: An Adaptive Information Theoretic Method to Identify Multi-Scale Temporal Correlations in Big Time Series Data

Research output: Contribution to journalJournal articleResearchpeer-review

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Original languageEnglish
JournalIEEE Transactions on Big Data
ISSN2332-7790
Publication statusAccepted/In press - 19 Mar 2019

Cite this

@article{79a8a188239848f08d87650c77fa8884,
title = "AMIC: An Adaptive Information Theoretic Method to Identify Multi-Scale Temporal Correlations in Big Time Series Data",
author = "Ho, {Nguyen Thi Thao} and Huy Vo and Mai Vu and Pedersen, {Torben Bach}",
year = "2019",
month = "3",
day = "19",
language = "English",
journal = "IEEE Transactions on Big Data",
issn = "2332-7790",
publisher = "IEEE",

}

AMIC: An Adaptive Information Theoretic Method to Identify Multi-Scale Temporal Correlations in Big Time Series Data. / Ho, Nguyen Thi Thao; Vo, Huy ; Vu, Mai; Pedersen, Torben Bach.

In: IEEE Transactions on Big Data, 19.03.2019.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - AMIC: An Adaptive Information Theoretic Method to Identify Multi-Scale Temporal Correlations in Big Time Series Data

AU - Ho, Nguyen Thi Thao

AU - Vo, Huy

AU - Vu, Mai

AU - Pedersen, Torben Bach

PY - 2019/3/19

Y1 - 2019/3/19

M3 - Journal article

JO - IEEE Transactions on Big Data

JF - IEEE Transactions on Big Data

SN - 2332-7790

ER -