A Robust System Architecture for Mining Semi-Structured Data

The value of extracting knowledge from semi-structured data is readily apparent with the explosion of the WWW and the advent of digital libraries. This paper proposes a versatile system architecture for text mining that maintains structured data components in a relational database and unstructured concepts in a concept library. After a detailed explanation of our system architecture, we briefly describe IRIS, our prototype rule generation system

• Type: Conference
• Year: 1998
• Where: KDD
• Authors: Lisa Singh, Bin Chen, Rebecca Haight, Peter Scheuermann, Kiyoko Aoki
• Keywords: Data Mining, KDD 1998, Prototype Rule Generation, Semi-structured Data, Unstructured Concepts