@inproceedings{3070a2c738464b65bf7f8f6659be1f45,
title = "Detecting implicit meta-patterns in relational databases",
abstract = "Association rule mining identifies patterns in transaction data that are not explicit. In the area of Knowledge Representation, cycle mining algorithms identify metapatterns of these associations depicting inferences forming feedback chains of positive and negative rule dependencies. This paper presents a new algorithm applying the traditional formalism of association rule mining to the new domain of cycle mining. We use this algorithm, along with causal graphs, to detect cycles.",
keywords = "Association rules, Casual graphs, Cycle mining, Data mining, Hypergraphs, Knowledge base",
author = "Buckley, {James P.} and Seitzer, {Jennifer M.}",
year = "2010",
language = "English",
series = "IMCIC 2010 - International Multi-Conference on Complexity, Informatics and Cybernetics, Proceedings",
publisher = "International Institute of Informatics and Systemics, IIIS",
pages = "162--164",
editor = "Jorge Baralt and Savoie, {Michael J.} and Hsing-Wei Chu and Zinn, {C. Dale} and Callaos, {Nagib C.}",
booktitle = "IMCIC 2010 - International Multi-Conference on Complexity, Informatics and Cybernetics, Proceedings",
note = "International Multi-Conference on Complexity, Informatics and Cybernetics, IMCIC 2010 ; Conference date: 06-04-2010 Through 09-04-2010",
}