Abstract
Data integration of geographically dispersed, heterogeneous, complex biological databases is a key research area. One of the key features of a successful data integration system is to have a simple self-describing data exchange format. However, many of the biological databases provide data in flat files which are poor data exchange formats. Fortunately, XML can be viewed as a powerful data model and better data exchange format. In this paper, we present the Bio2X system that transforms flat file data into highly hierarchical XML data using rule-based machine learning technique. Bio2X has been fully implemented using Java. Our experiments to transform real world biological data demonstrate the effectiveness of the Bio2X approach.
| Original language | American English |
|---|---|
| Pages (from-to) | 249-271 |
| Number of pages | 23 |
| Journal | Data and Knowledge Engineering |
| Volume | 52 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 1 2005 |
| Externally published | Yes |
ASJC Scopus Subject Areas
- Information Systems and Management
Keywords
- Flat Files
- Machine Learning
- Rule Base
- Transformer
- XML
Disciplines
- Computer Sciences
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