Data mining: concepts and techniques
Data mining: concepts and techniques
Mining patterns from graph traversals
Data & Knowledge Engineering
A Practical Introduction to Data Structures and Algorithm Analysis
A Practical Introduction to Data Structures and Algorithm Analysis
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Analysis of navigation behaviour in web sites integrating multiple information systems
The VLDB Journal — The International Journal on Very Large Data Bases
A framework for representing navigational patterns as full temporal objects
ACM SIGecom Exchanges
PLWAP sequential mining: open source code
Proceedings of the 1st international workshop on open source data mining: frequent pattern mining implementations
Enhancing Mobile Web Access Using Intelligent Recommendations
IEEE Intelligent Systems
Efficient sequential access pattern mining for web recommendations
International Journal of Knowledge-based and Intelligent Engineering Systems
Mining very long sequences in large databases with PLWAPLong
IDEAS '09 Proceedings of the 2009 International Database Engineering & Applications Symposium
A taxonomy of sequential pattern mining algorithms
ACM Computing Surveys (CSUR)
A top down algorithm for mining web access patterns from web logs
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
Web access pattern mining --- a survey
ICDEM'10 Proceedings of the Second international conference on Data Engineering and Management
User Behaviour Pattern Mining from Weblog
International Journal of Data Warehousing and Mining
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Web access pattern tree algorithm mines web log access sequences by first storing the original web access sequence database on a prefix tree (WAP-tree). WAP-tree algorithm then mines frequent sequences from the WAP-tree by recursively re-constructing intermediate WAP-trees, starting with their suffix subsequences. This paper proposes an efficient approach for using the preorder linked WAP-trees with binary position codes assigned to each node, to mine frequent sequences, which eliminates the need to engage in numerous re-construction of intermediate WAP-trees during mining. Experiments show huge performance advantages for sequential mining using prefix linked WAP-tree technique.