標題: A unified, adjustable, and extractable biological data mining-broker
作者: Ho, MH
Chang, YS
Cheng, MC
Li, KL
Yuan, SM
資訊工程學系
Department of Computer Science
公開日期: 2003
摘要: The document formats of biological data sources typically are more versatile and more complicated than the traditional data sources. It is hard to efficiently retrieve useful information from biological data sources by traditional information retrieval technologies. In this paper, we propose a unified, adjustable, and extractable Biological Data Mining-Broker mechanism. Based on XML methodology, the mechanism provides a federated forum model to overcome the heterogeneities of both form and meaning from those different diverse biological data sources. Furthermore, the mechanism also utilizes the feedback-based direct raw and meaningful extracted cache technique to improve the efficiency and accuracy of the system. The experimental results show that our proposed system has good performance, and it is a good choice for biological data mining process with multiple heterogeneous data sources, different mining applications, and knowledge analysts. It is highly useful for target discovery and bioinformatics research projects.
URI: http://hdl.handle.net/11536/28278
ISBN: 3-540-40550-X
ISSN: 0302-9743
期刊: INTELLIGENT DATA ENGINEERING AND AUTOMATED LEARNING
Volume: 2690
起始頁: 773
結束頁: 777
Appears in Collections:Conferences Paper