Incremental stock time series data delivery and visualization

Authors:
Tak-chung Fu;Fu-lai Chung;Pui-ying Tang;Robert Luk;Chak-man Ng
Affiliations:
The Hong Kong Polytechnic University, Hunghom, Hong Kong & HKIVE (Chai Wan), Hong Kong;The Hong Kong Polytechnic University, Hunghom, Hong Kong;The Hong Kong Polytechnic University, Hunghom, Hong Kong;The Hong Kong Polytechnic University, Hunghom, Hong Kong;HKIVE (Chai Wan), Hong Kong
Venue:
Proceedings of the 14th ACM international conference on Information and knowledge management
Year:
2005

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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.