Efficient Storage Structures for a Stock Investment Recommendation System


The KIPS Transactions:PartD, Vol. 16, No. 2, pp. 169-176, Apr. 2009
10.3745/KIPSTD.2009.16.2.169,   PDF Download:

Abstract

Rule discovery is an operation that discovers patterns frequently occurring in a given database. Rule discovery makes it possible to find useful rules from a stock database, thereby recommending buying or selling times to stock investors. In this paper, we discuss storage structures for efficient processing of queries in a system that recommends stock investments. First, we propose five storage structures for efficient recommending of stock investments. Next, we discuss their characteristics, advantages, and disadvantages. Then, we verify their performances by extensive experiments with real-life stock data. The results show that the histogram-based structure improves the query performance of the previous one up to about 170 times.


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Cite this article
[IEEE Style]
Y. M. Ha, S. W. Kim, S. H. Park, S. H. Lim, "Efficient Storage Structures for a Stock Investment Recommendation System," The KIPS Transactions:PartD, vol. 16, no. 2, pp. 169-176, 2009. DOI: 10.3745/KIPSTD.2009.16.2.169.

[ACM Style]
You Min Ha, Sang Wook Kim, Sang Hyun Park, and Seung Hwan Lim. 2009. Efficient Storage Structures for a Stock Investment Recommendation System. The KIPS Transactions:PartD, 16, 2, (2009), 169-176. DOI: 10.3745/KIPSTD.2009.16.2.169.