Results 1 - 10 of 1,380

Integrating classification and association rule mining

by Bing Liu, Wynne Hsu, Yiming Ma - In Proc of KDD , 1998
"... Classification rule mining aims to discover a small set of rules in the database that forms an accurate classifier. Association rule mining finds all the rules existing in the database that satisfy some minimum support and minimum confidence constraints. For association rule mining, the target of di ..."
Abstract - Cited by 578 (21 self) - Add to MetaCart
of discovery is not pre-determined, while for classification rule mining there is one and only one predetermined target. In this paper, we propose to integrate these two mining techniques. The integration is done by focusing on mining a special subset of association rules, called class association rules (CARs

Discovery of Multiple-Level Association Rules from Large Databases

by Jiawei Han, Yongjian Fu - In Proc. 1995 Int. Conf. Very Large Data Bases , 1995
"... 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 mu ..."
Abstract - Cited by 463 (34 self) - Add to MetaCart
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

Authoritative Sources in a Hyperlinked Environment

by Jon M. Kleinberg - JOURNAL OF THE ACM , 1999
"... The network structure of a hyperlinked environment can be a rich source of information about the content of the environment, provided we have effective means for understanding it. We develop a set of algorithmic tools for extracting information from the link structures of such environments, and repo ..."
Abstract - Cited by 3632 (12 self) - Add to MetaCart
an algorithmic formulation of the notion of authority, based on the relationship between a set of relevant authoritative pages and the set of “hub pages ” that join them together in the link structure. Our formulation has connections to the eigenvectors of certain matrices associated with the link graph

Sampling Large Databases for Association Rules

by Hannu Toivonen , 1996
"... Discovery of association rules is an important database mining problem. Current algorithms for nding association rules require several passes over the analyzed database, and obviously the role of I/O overhead is very signi cant for very large databases. We present new algorithms that reduce the data ..."
Abstract - Cited by 470 (3 self) - Add to MetaCart
Discovery of association rules is an important database mining problem. Current algorithms for nding association rules require several passes over the analyzed database, and obviously the role of I/O overhead is very signi cant for very large databases. We present new algorithms that reduce

New Algorithms for Fast Discovery of Association Rules

by Mohammed Javeed Zaki, Srinivasan Parthasarathy, Mitsunori Ogihara, Wei Li - In 3rd Intl. Conf. on Knowledge Discovery and Data Mining , 1997
"... Association rule discovery has emerged as an important problem in knowledge discovery and data mining. The association mining task consists of identifying the frequent itemsets, and then forming conditional implication rules among them. In this paper we present efficient algorithms for the discovery ..."
Abstract - Cited by 397 (26 self) - Add to MetaCart
Association rule discovery has emerged as an important problem in knowledge discovery and data mining. The association mining task consists of identifying the frequent itemsets, and then forming conditional implication rules among them. In this paper we present efficient algorithms

Mining Quantitative Association Rules in Large Relational Tables

by Ramakrishnan Srikant, Rakesh Agrawal , 1996
"... We introduce the problem of mining association rules in large relational tables containing both quantitative and categorical attributes. An example of such an association might be "10% of married people between age 50 and 60 have at least 2 cars". We deal with quantitative attributes by fi ..."
Abstract - Cited by 444 (3 self) - Add to MetaCart
"greater-than-expected-value" interest measure to identify the interesting rules in the output. We give an algorithm for mining such quantitative association rules. Finally, we describe the results of using this approach on a real-life dataset. 1 Introduction Data mining, also known

Database Mining: A Performance Perspective

by Rakesh Agrawal, Tomasz Imielinski, Arun Swami - IEEE Transactions on Knowledge and Data Engineering , 1993
"... We present our perspective of database mining as the confluence of machine learning techniques and the performance emphasis of database technology. We describe three classes of database mining problems involving classification, associations, and sequences, and argue that these problems can be unifor ..."
Abstract - Cited by 345 (13 self) - Add to MetaCart
an example of an algorithm for classification obtained by combining the basic rule discovery operations. This algorithm not only is efficient in discovering classification rules but also has accuracy comparable to ID3, one of the current best classifiers. Index Terms. database mining, knowledge discovery

Scalable Algorithms for Association Mining

by Mohammed J. Zaki - IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING , 2000
"... Association rule discovery has emerged as an important problem in knowledge discovery and data mining. The association mining task consists of identifying the frequent itemsets, and then forming conditional implication rules among them. In this paper we present efficient algorithms for the discovery ..."
Abstract - Cited by 259 (23 self) - Add to MetaCart
Association rule discovery has emerged as an important problem in knowledge discovery and data mining. The association mining task consists of identifying the frequent itemsets, and then forming conditional implication rules among them. In this paper we present efficient algorithms

Automatic Translation of FORTRAN Programs to Vector Form

by Randy Allen, Ken Kennedy - ACM Transactions on Programming Languages and Systems , 1987
"... This paper discusses the theoretical concepts underlying a project at Rice University to develop an automatic translator, called PFC (for Parallel FORTRAN Converter), from FORTRAN to FORTRAN 8x. The Rice project, based initially upon the research of Kuck and others at the University of Illinois [6, ..."
Abstract - Cited by 329 (34 self) - Add to MetaCart
as PARAFRASE). Other projects that have influenced our work are the Texas Instruments ASC compiler [9, 33], the Cray-1 FORTRAN compiler [15], and the Massachusetts Computer Associates Vectorizer [22, 25]. The paper is organized into seven sections. Section 2 introduces FORTRAN 8x and gives examples of its use

Mining Association Rules with Item Constraints

by Ramakrishnan Srikant, Quoc Vu, Rakesh Agrawal
"... The problem of discovering association rules has received considerable research attention and several fast algorithms for mining association rules have been developed. In practice, users are often interested in a subset of association rules. For example, they may only want rules that contain a speci ..."
Abstract - Cited by 289 (0 self) - Add to MetaCart
expressions over the presence or absence of items into the association discovery algorithm. We present three integrated algorithms for mining association rules with item constraints and discuss their tradeoffs. 1. Introduction The problem of discovering association rules was introduced in (Agrawal, Imielinski
Results 1 - 10 of 1,380