An important issue in text mining is how to make use of multiple pieces knowledge discovered to improve future decisions. In this paper, we propose a new approach to combining mult...
We have a large database consisting of sales transactions. We investigate the problem of online mining of association rules in this large database. We show how to preprocess the d...
Most commonly used inductive rule learning algorithms employ a hill-climbing search, whereas local pattern discovery algorithms employ exhaustive search. In this paper, we evaluat...
We present a browser-extending Semantic Web extraction system that maps HTML documents to tables and, where possible, to rules. First, the basic data extractor ViPER distills and ...
Abstract-- Data uncertainty is common in real-world applications due to various causes, including imprecise measurement, network latency, outdated sources and sampling errors. Thes...