Incremental stock time series data delivery and visualization

Tak Chung Fu; Fu Lai Korris Chung; Pui Ying Tang; Wing Pong Robert Luk; Chak Man Ng

Incremental stock time series data delivery and visualization

Tak Chung Fu, Fu Lai Korris Chung, Pui Ying Tang, Wing Pong Robert Luk, Chak Man Ng

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

7 Citations (Scopus)

Abstract

SB-Tree is a binary tree data structure proposed to represent time series according to the importance of data points. Its use in stock data management is distinguished by preserving the critical data points' attribute values, retrieving time series data according to the importance of data points and facilitating multi-resolution time series retrieval. As new stock data are available continuously, an effective updating mechanism for SB-Tree is needed. In this paper, a study of different updating approaches is reported. Three families of updating methods are proposed. They are periodic rebuild, batch update and point-by-point update. Their efficiency, effectiveness and characteristics are compared and reported.

Original language	English
Title of host publication	CIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management
Pages	279-280
Number of pages	2
Publication status	Published - 1 Dec 2005
Event	CIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management - Bremen, Germany Duration: 31 Oct 2005 → 5 Nov 2005

Conference

Conference	CIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management
Country/Territory	Germany
City	Bremen
Period	31/10/05 → 5/11/05

Keywords

Binary tree
Incremental data delivery
Multi-resolution visualization
Time series data management
Time series representation

ASJC Scopus subject areas

Decision Sciences(all)
Business, Management and Accounting(all)

Cite this

@inproceedings{1ec8cd23a5bc4cce8f33462ae88a2881,

title = "Incremental stock time series data delivery and visualization",

abstract = "SB-Tree is a binary tree data structure proposed to represent time series according to the importance of data points. Its use in stock data management is distinguished by preserving the critical data points' attribute values, retrieving time series data according to the importance of data points and facilitating multi-resolution time series retrieval. As new stock data are available continuously, an effective updating mechanism for SB-Tree is needed. In this paper, a study of different updating approaches is reported. Three families of updating methods are proposed. They are periodic rebuild, batch update and point-by-point update. Their efficiency, effectiveness and characteristics are compared and reported.",

keywords = "Binary tree, Incremental data delivery, Multi-resolution visualization, Time series data management, Time series representation",

author = "Fu, {Tak Chung} and Chung, {Fu Lai Korris} and Tang, {Pui Ying} and Luk, {Wing Pong Robert} and Ng, {Chak Man}",

year = "2005",

month = dec,

day = "1",

language = "English",

isbn = "1595931406",

pages = "279--280",

booktitle = "CIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management",

note = "CIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management ; Conference date: 31-10-2005 Through 05-11-2005",

}

Incremental stock time series data delivery and visualization. / Fu, Tak Chung; Chung, Fu Lai Korris; Tang, Pui Ying et al.

CIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management. 2005. p. 279-280.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - Incremental stock time series data delivery and visualization

AU - Fu, Tak Chung

AU - Chung, Fu Lai Korris

AU - Tang, Pui Ying

AU - Luk, Wing Pong Robert

AU - Ng, Chak Man

PY - 2005/12/1

Y1 - 2005/12/1

N2 - SB-Tree is a binary tree data structure proposed to represent time series according to the importance of data points. Its use in stock data management is distinguished by preserving the critical data points' attribute values, retrieving time series data according to the importance of data points and facilitating multi-resolution time series retrieval. As new stock data are available continuously, an effective updating mechanism for SB-Tree is needed. In this paper, a study of different updating approaches is reported. Three families of updating methods are proposed. They are periodic rebuild, batch update and point-by-point update. Their efficiency, effectiveness and characteristics are compared and reported.

AB - SB-Tree is a binary tree data structure proposed to represent time series according to the importance of data points. Its use in stock data management is distinguished by preserving the critical data points' attribute values, retrieving time series data according to the importance of data points and facilitating multi-resolution time series retrieval. As new stock data are available continuously, an effective updating mechanism for SB-Tree is needed. In this paper, a study of different updating approaches is reported. Three families of updating methods are proposed. They are periodic rebuild, batch update and point-by-point update. Their efficiency, effectiveness and characteristics are compared and reported.

KW - Binary tree

KW - Incremental data delivery

KW - Multi-resolution visualization

KW - Time series data management

KW - Time series representation

UR - http://www.scopus.com/inward/record.url?scp=33745771983&partnerID=8YFLogxK

M3 - Conference article published in proceeding or book

SN - 1595931406

SN - 9781595931405

SP - 279

EP - 280

BT - CIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management

T2 - CIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management

Y2 - 31 October 2005 through 5 November 2005

ER -

Incremental stock time series data delivery and visualization

Abstract

Conference

Keywords

ASJC Scopus subject areas

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