A Robust System Architecture for Mining Semi-Structured Data

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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

Lisa Singh, Bin Chen, Rebecca Haight, Peter Scheue

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Data Mining | KDD 1998 | Prototype Rule Generation | Semi-structured Data | Unstructured Concepts |

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Added	06 Aug 2010
Updated	06 Aug 2010
Type	Conference
Year	1998
Where	KDD
Authors	Lisa Singh, Bin Chen, Rebecca Haight, Peter Scheuermann, Kiyoko Aoki

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A Robust System Architecture for Mining Semi-Structured Data

Data Mining | KDD 1998 | Prototype Rule Generation | Semi-structured Data | Unstructured Concepts |

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