An effective hash-based algorithm for mining association rules
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
FreeSpan: frequent pattern-projected sequential pattern mining
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining frequent patterns by pattern-growth: methodology and implications
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
An efficient approach to discovering knowledge from large databases
DIS '96 Proceedings of the fourth international conference on on Parallel and distributed information systems
Efficient Data Mining for Path Traversal Patterns
IEEE Transactions on Knowledge and Data Engineering
Scalable Algorithms for Association Mining
IEEE Transactions on Knowledge and Data Engineering
A Graph-Based Approach for Discovering Various Types of Association Rules
IEEE Transactions on Knowledge and Data Engineering
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
PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
COMPSAC '00 24th International Computer Software and Applications Conference
Mining Web Transaction Patterns in an Electronic Commerce Environment
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Mining Access Patterns Efficiently from Web Logs
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Capturing User Access Patterns in the Web for Data Mining
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Discovering forward sequences from temporal data
Knowledge-Based Systems
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Due to the rapid growth in the field of electronic commerce (EC), a huge amount of data has been gathered in many EC sites since their inception. Although many studies have focused on the mining of an EC site's frequent traversal paths and frequent purchase items, an efficient combination of the two types of mining, however, is still not available up to date. To resolve this problem, we first combine both types of data, i.e. the traversal paths and the purchase records, and then mine the combined data for the frequent purchase behavior pattern. In this study, we propose an effective algorithm named Mining Frequent Purchase Behavior (MFPB), which will dig for all frequent path patterns and all frequent purchase records, with a pattern growth concept for an efficient and complete pattern mining, within the projected transactions.