Mining asynchronous periodic patterns in time series data
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Sequence mining in categorical domains: incorporating constraints
Proceedings of the ninth international conference on Information and knowledge management
Multi-dimensional sequential pattern mining
Proceedings of the tenth international conference on Information and knowledge management
Mining sequential patterns with constraints in large databases
Proceedings of the eleventh international conference on Information and knowledge management
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
Mining hybrid sequential patterns and sequential rules
Information Systems
SPADE: An Efficient Algorithm for Mining Frequent Sequences
Machine Learning
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Efficient Data Mining for Path Traversal Patterns
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
Analyzing the Interestingness of Association Rules from the Temporal Dimension
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Efficient Mining of Partial Periodic Patterns in Time Series Database
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Progressive Partition Miner: An Efficient Algorithm for Mining General Temporal Association Rules
IEEE Transactions on Knowledge and Data Engineering
Discovering Calendar-Based Temporal Association Rules
TIME '01 Proceedings of the Eighth International Symposium on Temporal Representation and Reasoning (TIME'01)
Efficient closed pattern mining in the presence of tough block constraints
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Sequential Patterns from Multidimensional Sequence Data
IEEE Transactions on Knowledge and Data Engineering
Efficient mining of sequential patterns with time constraints by delimited pattern growth
Knowledge and Information Systems
Efficient mining method for retrieving sequential patterns over online data streams
Journal of Information Science
Mining condensed frequent-pattern bases
Knowledge and Information Systems
Constraint-based sequential pattern mining: the consideration of recency and compactness
Decision Support Systems
Identifying synonymous concepts in preparation for technology mining
Journal of Information Science
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Sequential pattern mining is a powerful data mining technique for finding time-related behaviour in sequence databases. In this paper, we focus on mining sequential patterns in the business-to-business (B2B) environment. Because customers芒聙聶 sequences in the B2B environment are very long, and almost all items are frequently purchased by all customers, using traditional methods may result in a large number of uninteresting and meaningless patterns and a long computational time. To solve these problems, we introduce three conditions (constraints) 芒聙聰 compactness, repetition, and recency 芒聙聰 and consider them jointly with frequency in selecting sequential patterns. An efficient algorithm is developed to discover frequent sequential patterns which satisfy the conditions. Empirical results show that the proposed method is computationally efficient and effective in extracting useful sequential patterns in the B2B environment.