Sequence mining in categorical domains: incorporating constraints
Proceedings of the ninth international conference on Information and knowledge management
SPADE: an efficient algorithm for mining frequent sequences
Machine Learning
KDD-Cup 2000 organizers' report: peeling the onion
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Mining Sequential Patterns with Regular Expression Constraints
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
The PSP Approach for Mining Sequential Patterns
PKDD '98 Proceedings of the Second European Symposium on Principles of Data Mining and Knowledge Discovery
Sequential PAttern mining using a bitmap representation
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
A new algorithm for gap constrained sequence mining
Proceedings of the 2004 ACM symposium on Applied computing
An Efficient Algorithm for Mining Frequent Sequences by a New Strategy without Support Counting
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
BIDE: Efficient Mining of Frequent Closed Sequences
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Pre-Processing Time Constraints for Efficiently Mining Generalized Sequential Patterns
TIME '04 Proceedings of the 11th International Symposium on Temporal Representation and Reasoning
Interactive sequence discovery by incremental mining
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Informatics and computer science intelligent systems applications
Efficient mining of sequential patterns with time constraints by delimited pattern growth
Knowledge and Information Systems
Efficient Algorithms for Mining and Incremental Update of Maximal Frequent Sequences
Data Mining and Knowledge Discovery
Parallel mining of closed sequential patterns
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Benchmarking the effectiveness of sequential pattern mining methods
Data & Knowledge Engineering
Constraint-based sequential pattern mining: the pattern-growth methods
Journal of Intelligent Information Systems
Extended Time Constraints for Sequence Mining
TIME '07 Proceedings of the 14th International Symposium on Temporal Representation and Reasoning
Privacy preserving data mining of sequential patterns for network traffic data
Information Sciences: an International Journal
Efficient strategies for tough aggregate constraint-based sequential pattern mining
Information Sciences: an International Journal
A general effective framework for monotony and tough constraint based sequential pattern mining
DaWaK'05 Proceedings of the 7th international conference on Data Warehousing and Knowledge Discovery
Mining Mobile Sequential Patterns in a Mobile Commerce Environment
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Discovering fuzzy time-interval sequential patterns in sequence databases
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Information Sciences: an International Journal
An approach to discovering multi-temporal patterns and its application to financial databases
Information Sciences: an International Journal
Integrating induction and deduction for noisy data mining
Information Sciences: an International Journal
Knowledge gathering of fuzzy multi-time-interval sequential patterns
Information Sciences: an International Journal
Mining weighted sequential patterns in a sequence database with a time-interval weight
Knowledge-Based Systems
Discovering multi-label temporal patterns in sequence databases
Information Sciences: an International Journal
The MineSP operator for mining sequential patterns in inductive databases
MICAI'06 Proceedings of the 5th Mexican international conference on Artificial Intelligence
Effective next-items recommendation via personalized sequential pattern mining
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part II
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Sequential pattern mining algorithms can often produce more accurate results if they work with specific constraints in addition to the support threshold. Many systems implement time-independent constraints by selecting qualified patterns. This selection cannot implement time-dependent constraints, because the support computation process must validate the time attributes of every data sequence during mining. Therefore, we propose a memory time-indexing approach, called METISP, to discover sequential patterns with time constraints including minimum-gap, maximum-gap, exact-gap, sliding window, and duration constraints. METISP scans the database into memory and constructs time-index sets for effective processing. METISP uses index sets and a pattern-growth strategy to mine patterns without generating any candidates or sub-databases. The index sets narrow down the search space to the sets of designated in-memory data sequences, and speed up the counting of potential items within the indicated ranges. Our comprehensive experiments show that METISP has better efficiency, even with low support and large databases, than the well-known GSP and DELISP algorithms. METISP scales up linearly with respect to database size.