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 proceedingConference article published in proceeding or bookAcademic researchpeer-review

5 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 languageEnglish
Title of host publicationCIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management
Pages279-280
Number of pages2
Publication statusPublished - 1 Dec 2005
EventCIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management - Bremen, Germany
Duration: 31 Oct 20055 Nov 2005

Conference

ConferenceCIKM'05 - Proceedings of the 14th ACM International Conference on Information and Knowledge Management
CountryGermany
CityBremen
Period31/10/055/11/05

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)

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