Incremental and interactive sequence mining
Proceedings of the eighth international conference on Information and knowledge management
SPADE: an efficient algorithm for mining frequent sequences
Machine Learning
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
Sequential PAttern mining using a bitmap representation
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Incremental mining of sequential patterns in large databases
Data & Knowledge Engineering
Frequent-subsequence-based prediction of outer membrane proteins
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
BIDE: Efficient Mining of Frequent Closed Sequences
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Information Systems - Databases: Creation, management and utilization
IncSpan: incremental mining of sequential patterns in large database
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Web Log Sequential Patterns with Position Coded Pre-Order Linked WAP-Tree
Data Mining and Knowledge Discovery
Efficient Algorithms for Mining and Incremental Update of Maximal Frequent Sequences
Data Mining and Knowledge Discovery
Identifying comparative sentences in text documents
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Mining contiguous sequential patterns from web logs
Proceedings of the 16th international conference on World Wide Web
Efficient mining of frequent sequence generators
Proceedings of the 17th international conference on World Wide Web
Efficient algorithms for incremental maintenance of closed sequential patterns in large databases
Data & Knowledge Engineering
Incremental Discovery of Sequential Patterns Using a Backward Mining Approach
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 01
Improvements of incspan: incremental mining of sequential patterns in large database
PAKDD'05 Proceedings of the 9th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining
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Recently, mining sequential patterns, especially closed sequential patterns and generator patterns, has attracted much attention from both academic and industrial communities. In recent years, incremental mining of all sequential patterns (all closed sequential patterns) has been widely studied. However, to our best knowledge, there has not been any study for incremental mining of sequence generators. In this paper, by carefully examining the existing expansion strategies for mining sequential databases, we design a GenTree structure to keep track of the relevant mining information, and propose an efficient algorithm, IncGen, for incremental generator mining. We have conducted thorough experiment evaluation and the experimental results show that the IncGen algorithm outperforms state-of-the-art generator-mining method FEAT significantly.