Rajeev Rastogi, Kyuseok Shim  Home/Search
Context Related
| belllabs.com/user/shim/icde98.ps.gz dblab.kaist.ac.kr/~shim/icde98.ps.gz cs.kaist.ac.kr/~shim/icde98.ps Cached: PS.gz PS PDF This document uses CoBlitz to cache paper downloads. If your firewall is blocking outgoing connections to port 3125, you can use these links to download local copies.
Image Update HelpPS.gz PS PDF From: belllabs.com/user/shim/ (more) From: dblab.kaist.ac.kr/~shim/ (Enter author homepages) |
Rate this article:      (best)Comment on this article |
Abstract: 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 determine instantiations such that either the support or confidence of the rule is maximized. In... (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...
Cited by: More
Exploiting A Support-based Upper Bound of Pearson's - Correlation Coefficient For (Correct)
TAPER: A Two-Step Approach for All-strong-pairs.. - Xiong, Shekhar, Tan.. (Correct)
Identifying Most Predictive Items - Keim, Wawryniuk (Correct)
Similar documents (at the sentence level):
15.5%: Mining Optimized Support Rules for Numeric Attributes - Rastogi, Shim (1999) (Correct)
12.3%: Mining Optimized Gain Rules for Numeric Attributes - Brin, Rastogi, Shim (1999) (Correct)
Active bibliography (related documents): More All
0.2: Mining Optimized Association Rules with Categorical and.. - Rastogi, Shim (1998) (Correct)
0.1: Depth First Generation of Long Patterns - Agarwal, Aggarwal (2000) (Correct)
0.1: Efficient Mining Of Interesting Association Rules From.. - Tatarinov (1999) (Correct)
Similar documents based on text: More All
0.6: A Compositional Framework for Mining Longest Ranges - Zhao, Hu, Takeichi (2002) (Correct)
0.4: Efficient Algorithms for Mining Outliers from Large Data Sets - Ramaswamy, Rastogi, Shim (Correct)
0.3: ROCK: A Robust Clustering Algorithm for Categorical Attributes - Guha, Rastogi, Shim (2000) (Correct)
Related documents from co-citation: More All
13: Mining association rules between sets of items in large databases - Agrawal, Imielinski et al. - 1993
8: Beyond market baskets: Generalizing association rules to correlations - Brin, Motwani et al. - 1997
8: Fast Algorithms for Mining Association Rules - Agrawal, Srikant - 1994
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/article/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/article/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
474 Advances in Knowledge Discovery and Data Mining (context) - Fayyad, Piatetsky-Shapiro et al. - 1996
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
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
41 Mining optimized association rules for numeric attributes (context) - Fukuda, Morimoto et al. - 1996
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.
Documents on the same site (http://www-db.research.bell-labs.com/user/shim/): More
Query Optimization in the Presence of Foreign Functions - Chaudhuri, Shim (1993) (Correct)
Fast Similarity Search in the Presence of Noise, Scaling, and .. - Rakesh Agrawal (1995) (Correct)
Optimizing Queries with Aggregate Views - Chaudhuri, Shim (1996) (Correct)
Online articles have much greater impact More about CiteSeer.IST Add search form to your site Submit documents Feedback
CiteSeer.IST - Copyright Penn State and NEC