Towards a text mining methodology using association rule extraction

doi:10.1007/s00500-005-0504-x

2005-05-31

PRE

Hacène Cherfi

Amedeo Napoli

DOI：10.1007/s00500-005-0504-x

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摘要

En 中文

This paper proposes a methodology for text mining relying on the classical knowledge discovery loop, with a number of adaptations. First, texts are indexed and prepared to be processed by frequent itemset levelwise search. Association rules are then extracted and interpreted, with respect to a set of quality measures and domain knowledge, under the control of an analyst. The article includes an experimentation on a real-world text corpus holding on molecular biology.

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期刊

Soft Computing

IF:

2.5

论文数:

1.0W

被引数:

2.1W

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