Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Efficient mining of emerging patterns: discovering trends and differences
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
FreeSpan: frequent pattern-projected sequential pattern mining
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
SPADE: an efficient algorithm for mining frequent sequences
Machine Learning
Discovering Frequent Event Patterns with Multiple Granularities in Time Sequences
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
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
Mining Partially Periodic Event Patterns with Unknown Periods
Proceedings of the 17th International Conference on Data Engineering
PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
FlExPat: Flexible Extraction of Sequential Patterns
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
The PSP Approach for Mining Sequential Patterns
PKDD '98 Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery
SPIRIT: Sequential Pattern Mining with Regular Expression Constraints
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Fast Discovery of Sequential Patterns by Memory Indexing
DaWaK 2000 Proceedings of the 4th International Conference on Data Warehousing and Knowledge Discovery
Finding surprising patterns in a time series database in linear time and space
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Asynchronous Periodic Patterns in Time Series Data
IEEE Transactions on Knowledge and Data Engineering
A novel method for discovering fuzzy sequential patterns using the simple fuzzy partition method
Journal of the American Society for Information Science and Technology
Efficient Mining of Partial Periodic Patterns in Time Series Database
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Incremental mining of sequential patterns in large databases
Data & Knowledge Engineering
Information Systems - Databases: Creation, management and utilization
FS-Miner: efficient and incremental mining of frequent sequence patterns in web logs
Proceedings of the 6th annual ACM international workshop on Web information and data management
Mining interval sequential patterns
International Journal of Intelligent Systems
Periodicity Detection in Time Series Databases
IEEE Transactions on Knowledge and Data Engineering
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Recency-based collaborative filtering
ADC '06 Proceedings of the 17th Australasian Database Conference - Volume 49
Constraint-based sequential pattern mining: the consideration of recency and compactness
Decision Support Systems
Data Mining and Knowledge Discovery
Competition policy for technological innovation in an era of knowledge-based economy
Knowledge-Based Systems
A change detection method for sequential patterns
Decision Support Systems
Handling sequential pattern decay: Developing a two-stage collaborative recommender system
Electronic Commerce Research and Applications
On mining multi-time-interval sequential patterns
Data & Knowledge Engineering
The Cyclic Model Analysis on Sequential Patterns
IEEE Transactions on Knowledge and Data Engineering
Discovering fuzzy time-interval sequential patterns in sequence databases
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Mining interestingness measures for string pattern mining
Knowledge-Based Systems
Improving the speed and stability of the k-nearest neighbors method
Pattern Recognition Letters
Towards group behavioral reason mining
Expert Systems with Applications: An International Journal
Discovering forward sequences from temporal data
Knowledge-Based Systems
An efficient tree-based algorithm for mining sequential patterns with multiple minimum supports
Journal of Systems and Software
On mining mobile apps usage behavior for predicting apps usage in smartphones
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Consumer market has several characteristics in common such as repeat-buying over the relevant time frame, a large number of customers, and a wealth of information detailing past customer purchases. Analyzing the characterizations of repeat-buying is necessary to understand and adapt to dynamics of customer behaviors for company to survive in a continuously changing environment. The aim of this paper is to develop a methodology to detect the existence of repeat-buying behavior and discover the potential period of the repeat-buying behavior. We propose a new mathematical model to capture the characteristics of repeat-buying behavior. The algorithms based on our previous works then proposed to provide a scheme to discover periodicity and trends of the purchase. Two fundamental repeat-buying types have been identified and analyzed. Any repeat-buying scenarios can be expressed as the combination of the two fundamental types. The proposed mathematical model coupled with our prior works on cyclic modeling form a systematic process to uncover the characteristics of repeat-buying phenomenon. The experiments against a domestic consumer goods company are provided. The experimental results show that the proposed model can predict likely periodic purchase more precisely than previous studies.