M-tree as an index structure for time series data

Huynh Huu Viet; Duong Tuan Anh

doi:10.1109/ComManTel.2013.6482381

M-tree as an index structure for time series data

Huynh Huu Viet, Duong Tuan Anh

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

5 Citations (Scopus)

Abstract

A very effective method for fast retrieval in time series data is to map each data sequence into a small set of multidimensional rectangles in feature space, then these rectangles can be readily indexed using traditional multidimensional index trees, like R^*-tree. This paper describes the use of another multidimensional index tree, M-tree, for fast retrieval in wavelet transformed time series and compares its performance to that of R^*-tree as an index structure for this transformed time series representation.

Original language	English
Title of host publication	2013 International Conference on Computing, Management and Telecommunications, ComManTel 2013
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	146-151
Number of pages	6
ISBN (Print)	9781467320870
DOIs	https://doi.org/10.1109/ComManTel.2013.6482381
Publication status	Published - 12 Apr 2013
Externally published	Yes
Event	International Conference on IEEE Computing, Management and Telecommunications (IEEE ComManTel) 2013 - REX Hotel, Ho Chi Minh City, Vietnam Duration: 21 Jan 2013 → 24 Jan 2013

Conference

Conference	International Conference on IEEE Computing, Management and Telecommunications (IEEE ComManTel) 2013
Abbreviated title	ComManTel 2013
Country/Territory	Vietnam
City	Ho Chi Minh City
Period	21/01/13 → 24/01/13

Keywords

dimensionality reduction
M-tree
multidimensional index structure
R-tree
subsequence matching
time series

Access to Document

10.1109/ComManTel.2013.6482381

Cite this

@inproceedings{4c06ae930c47488e9bfef0466f43ec74,

title = "M-tree as an index structure for time series data",

abstract = "A very effective method for fast retrieval in time series data is to map each data sequence into a small set of multidimensional rectangles in feature space, then these rectangles can be readily indexed using traditional multidimensional index trees, like R*-tree. This paper describes the use of another multidimensional index tree, M-tree, for fast retrieval in wavelet transformed time series and compares its performance to that of R*-tree as an index structure for this transformed time series representation.",

keywords = "dimensionality reduction, M-tree, multidimensional index structure, R-tree, subsequence matching, time series",

author = "Viet, {Huynh Huu} and Anh, {Duong Tuan}",

year = "2013",

month = apr,

day = "12",

doi = "10.1109/ComManTel.2013.6482381",

language = "English",

isbn = "9781467320870",

pages = "146--151",

booktitle = "2013 International Conference on Computing, Management and Telecommunications, ComManTel 2013",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "International Conference on IEEE Computing, Management and Telecommunications (IEEE ComManTel) 2013, ComManTel 2013 ; Conference date: 21-01-2013 Through 24-01-2013",

}

Viet, HH & Anh, DT 2013, M-tree as an index structure for time series data. in 2013 International Conference on Computing, Management and Telecommunications, ComManTel 2013., 6482381, IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 146-151, International Conference on IEEE Computing, Management and Telecommunications (IEEE ComManTel) 2013, Ho Chi Minh City, Vietnam, 21/01/13. https://doi.org/10.1109/ComManTel.2013.6482381

M-tree as an index structure for time series data. / Viet, Huynh Huu; Anh, Duong Tuan.
2013 International Conference on Computing, Management and Telecommunications, ComManTel 2013. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2013. p. 146-151 6482381.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - M-tree as an index structure for time series data

AU - Viet, Huynh Huu

AU - Anh, Duong Tuan

PY - 2013/4/12

Y1 - 2013/4/12

N2 - A very effective method for fast retrieval in time series data is to map each data sequence into a small set of multidimensional rectangles in feature space, then these rectangles can be readily indexed using traditional multidimensional index trees, like R*-tree. This paper describes the use of another multidimensional index tree, M-tree, for fast retrieval in wavelet transformed time series and compares its performance to that of R*-tree as an index structure for this transformed time series representation.

AB - A very effective method for fast retrieval in time series data is to map each data sequence into a small set of multidimensional rectangles in feature space, then these rectangles can be readily indexed using traditional multidimensional index trees, like R*-tree. This paper describes the use of another multidimensional index tree, M-tree, for fast retrieval in wavelet transformed time series and compares its performance to that of R*-tree as an index structure for this transformed time series representation.

KW - dimensionality reduction

KW - M-tree

KW - multidimensional index structure

KW - R-tree

KW - subsequence matching

KW - time series

UR - http://www.scopus.com/inward/record.url?scp=84875943799&partnerID=8YFLogxK

U2 - 10.1109/ComManTel.2013.6482381

DO - 10.1109/ComManTel.2013.6482381

M3 - Conference Paper

AN - SCOPUS:84875943799

SN - 9781467320870

SP - 146

EP - 151

BT - 2013 International Conference on Computing, Management and Telecommunications, ComManTel 2013

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

T2 - International Conference on IEEE Computing, Management and Telecommunications (IEEE ComManTel) 2013

Y2 - 21 January 2013 through 24 January 2013

ER -

M-tree as an index structure for time series data

Abstract

Conference

Keywords

Access to Document

Other files and links

Cite this