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 |
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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 |
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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
- General Decision Sciences
- General Business,Management and Accounting