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http://dx.doi.org/10.3745/KIPSTD.2009.16-D.2.169

Efficient Storage Structures for a Stock Investment Recommendation System  

Ha, You-Min (연세대학교 컴퓨터과학)
Kim, Sang-Wook (한양대학교 정보통신학부)
Park, Sang-Hyun (연세대학교 컴퓨터과학과)
Lim, Seung-Hwan (한양대학교 전자통신컴퓨터공학과)
Publication Information
The KIPS Transactions:PartD / v.16D, no.2, 2009 , pp. 169-176 More about this Journal
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.
Keywords
Time-Series Data; Rule Discovery; Recommending Stock Investments;
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