Rule Discovery in Stock Databases
We propose an approach for identifying potentially useful rules within stock data. Specifically, for a frequent pattern of stock prices, if its subsequent stock prices are matched a condition of an investor, the model recommends a corresponding investment type for this stock. The frequent pattern is regarded as a rule head, and the subsequent part a rule body. We observed that the conditions on rule bodies are quite different depending on dispositions of investors while rule heads are independent of characteristics of investors in most cases. With this observation, we propose a new method that discovers and stores only the rule heads rather than the whole rules in a rule discovery process. This allows investors to impose various conditions on rule bodies flexibly, and also improves the performance of a rule discovery process. For efficient discovery and matching of rules, we propose methods for discovering frequent patterns, constructing a frequent pattern base, and its indexing. We also suggest a method that finds the rules matched a query from a frequent pattern base, and a method that recommends an investment type by using the rules.
Yijuan Su
Department of Mathematics and Computer Science Guangxi Teachers Education University Nanning 530023, P.R.China
国际会议
南宁
英文
2007-07-20（万方平台首次上网日期，不代表论文的发表时间）