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Continuous Query Processing Utilizing Follows Relationship between Queries in Stock Databases  

Ha, You-Min (연세대학교 컴퓨터과학과)
Kim, Sang-Wook (한양대학교 정보통신학부)
Park, Sang-Hyun (연세대학교 컴퓨터과학과)
Publication Information
Journal of KIISE:Databases / v.33, no.6, 2006 , pp. 644-653 More about this Journal
Abstract
This paper analyzes the properties of user query for stock investment recommendation, and defines the 'following relation', which is a new relation between two queries. A following relation between two queries $Q_1,\;Q_2$ and a recommendation value X means 'If the recommendation value of a preceding Query $Q_1$ is X, then a following query $Q_2$ always has X as its recommendation value'. If there exists a following relation between $Q_1\;and\;Q_2$, the recommendation value of $Q_2$ is decided immediately by that of $Q_1$, therefore we can eliminate the running process for $Q_2$. We suggest two methods in this paper. The former method analyzes all the following relations among user queries and represents them as a graph. The latter searches the graph and decides the order of queries to be processed, in order to make the number of eliminated query-running process maximized. When we apply the suggested procedures that use the following relation, most of user queries do not need to be processed directly, hence the performance of running overall queries is greatly improved. We examined the superiority of the suggested methods through experiments using real stock market data. According to the results of our experiments, overall query processing time has reduced less than 10% with our proposed methods, compared to the traditional procedure.
Keywords
Continuous Query Processing; Stock Database; Rule Discovery;
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