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Abstract: Mining association rules on large data sets has received considerable attention in recent years. Association rules are useful for determining correlations between attributes of a relation and have applications in marketing, financial and retail sectors. Furthermore, optimized association rules are an effective way to focus on the most interesting characteristics involving certain attributes. Optimized association rules are permitted to contain uninstantiated attributes and the problem is to... (Update)
Context of citations to this paper: More
.... in supermarket data, the technique has been extended to work on numerical data and categorical data in more conventional databases [SA96, RS98], some researchers have noted the importance of association rule mining in relation to relational databases [STA00] Tools for...
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13: Mining association rules between sets of items in large databases - Agrawal, Imielinski et al. - 1993
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BibTeX entry: (Update)
Rastogi R., and Shim K. "Mining Optimized Association Rules with Categorical and Numeric Attributes." Proceedings of the International Conference on Data Engineering, Orlando, Florida, February 1998. http://citeseer.ist.psu.edu/rastogi98mining.html More
@article{ rastogi02mining,
author = "Rajeev Rastogi and Kyuseok Shim",
title = "Mining Optimized Association Rules with Categorical and Numeric Attributes",
journal = "Knowledge and Data Engineering",
volume = "14",
number = "1",
pages = "29-50",
year = "2002",
url = "citeseer.ist.psu.edu/rastogi98mining.html" }
Citations (may not include all citations):921 Mining association rules between sets of items in large data.. - Agrawal, Imielinski et al. - 1993
910 Fast algorithms for mining association rules - Agrawal, Srikant - 1994
268 Mining generalized association rules - Srikant, Agrawal - 1995
213 Discovery of multiple-level association rules from large dat.. - Han, Fu - 1995
209 Mining quantitative association rules in large relational ta.. - Srikant, Agrawal - 1996
164 An efficient algorithm for mining association rules in large.. (context) - Savasere, Omiecinski et al. - 1995
121 Efficient algorithms for discovering association rules - Mannila, Toivonen et al. - 1994
74 Data mining using two-dimensional optimized association rule.. (context) - Fukuda, Morimoto et al. - 1996
56 Clustering association rules - Lent, Swami et al. - 1997
41 Mining optimized association rules for numeric attributes (context) - Fukuda, Morimoto et al. - 1996
35 An effective hash based algorithm for mining association rul.. (context) - Park, Chen et al. - 1995
13 and presentation of strong rules (context) - Piatetsky-Shapiro, analysis - 1991
7 Mining optimized association rule for categorical and numeri.. (context) - Rastogi, Shim - 1997
The graph only includes citing articles where the year of publication is known.
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PUBLIC: A Decision Tree Classifier that Integrates Building and.. - Rastogi (1998) (Correct)
Mining Optimized Support Rules for Numeric Attributes - Rastogi, Shim (1999) (Correct)
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