Logic-Based association rule mining in XML documents

Authors:
Hong-Cheu Liu;John Zeleznikow;Hasan M. Jamil
Affiliations:
School of Economics and Information Systems, University of Wollongong, Wollongong, NSW, Australia;School of Information Systems, Victoria University, Melbourne, Vic., Australia;Department of Computer Science, Wayne State University, Detroit, MI
Venue:
APWeb'06 Proceedings of the 2006 international conference on Advanced Web and Network Technologies, and Applications
Year:
2006

Citing 12
Cited 1

Mining association rules between sets of items in large databases

SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Query flocks: a generalization of association-rule mining

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SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Foundations of Databases: The Logical Level

Foundations of Databases: The Logical Level
Ad Hoc Association Rule Mining as SQL3 Queries

ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Mining First-order Knowledge Bases for Association Rules

ICTAI '01 Proceedings of the 13th IEEE International Conference on Tools with Artificial Intelligence
Processing frequent itemset discovery queries by division and set containment join operators

DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Discovering interesting information in XML data with association rules

Proceedings of the 2003 ACM symposium on Applied computing
Optimizing subset queries: a step towards SQL-based inductive databases for itemsets

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Mining association rules from XML data using XQuery

ACSW Frontiers '04 Proceedings of the second workshop on Australasian information security, Data Mining and Web Intelligence, and Software Internationalisation - Volume 32
XAR-miner: efficient association rules mining for XML data

WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Algebraic equivalences of nested relational operators

Information Systems

Optimizing queries for web generated sensor data

ADC '11 Proceedings of the Twenty-Second Australasian Database Conference - Volume 115

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Abstract

In this paper, we propose a new framework, called XLogic- Miner, to mine association rules from XML data. We consider the generate-and-test and the frequent-pattern growth approaches. In XLogic-Miner, we propose an novel method to represent a frequent-pattern tree in an object-relational table and exploit a new join operator developed in the paper. The principal focus of this research is to demonstrate that association rule mining can be expressed in an extended datalog program and be able to mine XML data in a declarative way. We also consider some optimization and performance issues.