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주식 투자 추천 시스템을 위한 효율적인 저장 구조
Efficient Storage Structures for a Stock Investment Recommendation System
- 하유민;
- 김상욱;
- 박상현;
- 임승환
초록
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.
키워드
Time-Series Data; Rule Discovery; Recommending Stock Investments; 시계열 데이터; 규칙 탐사; 주식 투자 추천; Time-Series Data; Rule Discovery; Recommending Stock Investments
- 제목
- 주식 투자 추천 시스템을 위한 효율적인 저장 구조
- 제목 (타언어)
- Efficient Storage Structures for a Stock Investment Recommendation System
- 저자
- 하유민; 김상욱; 박상현; 임승환
- 발행일
- 2009-04
- 저널명
- 정보처리학회논문지D
- 권
- 16
- 호
- 2
- 페이지
- 169 ~ 176