| Alternate document: Details Discovery of Spatial Association Rules in Geographic Information Databases (95) Krzysztof Koperski, Jiawei Hah |
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Abstract: Previous studies on mining association rules find rules at single concept level, however, mining association rules at multiple concept levels may lead to the discovery of more specific and concrete knowledge from data. In this study, a top-down progressive deepening method is developed for mining multiplelevel association rules from large transaction databases by extension of some existing association rule mining techniques. A group of variant algorithms are proposed based on the ways of... (Update)
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BibTeX entry: (Update)
J. Han and Y. Fu. Discovery of multiple-level association rules from large databases. In Proc. of the 21st Int'l Conference on Very Large Databases, Zurich, Switzerland, September 1995. http://citeseer.ist.psu.edu/han95discovery.html More
@inproceedings{ han95discovery,
author = "J. Han and Y. Fu",
title = "Discovery of Multiple-Level Association Rules from Large Databases",
booktitle = "Proc. of 1995 Int'l Conf. on Very Large Data Bases ({VLDB}'95), Z{\"u}rich, Switzerland, September 1995",
pages = "420--431",
year = "1995",
url = "citeseer.ist.psu.edu/han95discovery.html" }
Citations (may not include all citations):
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Fast algorithms for mining association rules
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Mining sequential pat- terns
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An effective hash- based algorithm for mining association ru..
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A Multistrategy Approach (context) - Michalski, Tecuci - 1994
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Dynamic generation and refine- ment of concept hierarchies f.. (context) - ttan, Fu - 1994
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The inter- estingness of deviations (context) - Piatesky-Shapiro, Matheus - 1994
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