Algorithms on Trees and Graphs
Algorithms on Trees and Graphs
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
LOGML: Log Markup Language for Web Usage Mining
WEBKDD '01 Revised Papers from the Third International Workshop on Mining Web Log Data Across All Customers Touch Points
TreeFinder: a First Step towards XML Data Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
Constraint-Based Rule Mining in Large, Dense Databases
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Efficiently Mining Frequent Trees in a Forest: Algorithms and Applications
IEEE Transactions on Knowledge and Data Engineering
Canonical forms for labelled trees and their applications in frequent subtree mining
Knowledge and Information Systems
AMIOT: Induced Ordered Tree Mining in Tree-Structured Databases
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
TRIPS and TIDES: new algorithms for tree mining
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Mining Frequent Induced Subtrees by Prefix-Tree-Projected Pattern Growth
WAIMW '06 Proceedings of the Seventh International Conference on Web-Age Information Management Workshops
Efficiently Mining Frequent Embedded Unordered Trees
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Frequent Subtree Mining - An Overview
Fundamenta Informaticae - Advances in Mining Graphs, Trees and Sequences
Mining Substructures in Protein Data
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
Knowledge Analysis with Tree Patterns
HICSS '08 Proceedings of the Proceedings of the 41st Annual Hawaii International Conference on System Sciences
Tree model guided candidate generation for mining frequent subtrees from XML documents
ACM Transactions on Knowledge Discovery from Data (TKDD)
U3 - Mning Unordered Embedded Subtrees Using TMG Candidate Generation
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
IMB3-Miner: mining induced/embedded subtrees by constraining the level of embedding
PAKDD'06 Proceedings of the 10th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
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Large amount of online information is or can be represented using semi-structured documents, such as XML. The information contained in an XML document can be effectively represented using a rooted ordered labeled tree. This has made the frequent pattern mining problem recast as the frequent subtree mining problem, which is a pre-requisite for association rule mining form tree-structured documents. Driven by different application needs a number of algorithms have been developed for mining of different subtree types under different support definitions. In this paper we present an algorithm for mining unordered embedded subtrees. It is an extension of our general tree model guided (TMG) candidate generation framework and the proposed U3 algorithm considers all support definitions, namely, transaction-based, occurrence-match and hybrid support. A number of experiments are presented on synthetic and real world data sets. The results demonstrate the flexibility of our general TMG framework as well as its efficiency when compared to the existing state-of-the-art approach.