ACS/IEEE International Conference on Computer Systems and Applications (AICCSA'01) Data Mining Using Classification Techniques in Query Processing Strategies Beirut, Lebanon June 25-June 29 ISBN: 0-7695-1165-1
Abstract: Given a query, there are many different query-processing strategies to fulfill user requirement. The selective of tuples are from 0% t o 100%. The found set of relation will determine the different of query processing strategies being implement. To implement the effective query processing strategies relies on the cost model of query processing strategies. Traditionally, the query-processing doesn't handle personalization user requirement. In the E-Commerce environment, in order to achieve the fast response time of a query which requires personalization in the relation. In this paper, we introduce the concept of personalization in the query processing level. We discuss cost model for each of the query processing strategies and use one of data mining techniques such as classification in selecting the most effective query processing strategy for personalization. We introduce the reader pertaining to the current query processing strategies. Next, we introduce the reader pertaining to the current query processing strategies. Finally, we conclude with data mining technique is an alternative in selecting query-processing strategy.
Index Terms:
Query Processing, E-Commerce, Personalization and Cost Model.
Citation:
Ying Wah Teh, Abu Bakar Zaitun, Sai Peck Lee, "Data Mining Using Classification Techniques in Query Processing Strategies," aiccsa, pp.0200, ACS/IEEE International Conference on Computer Systems and Applications (AICCSA'01), 2001 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||