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
Efficient mining of both positive and negative association rules
ACM Transactions on Information Systems (TOIS)
IncSpan: incremental mining of sequential patterns in large database
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining Sequential Patterns by Pattern-Growth: The PrefixSpan Approach
IEEE Transactions on Knowledge and Data Engineering
Mining positive and negative association rules: an approach for confined rules
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Parallel mining of closed sequential patterns
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
HYPE: mining hierarchical sequential patterns
DOLAP '06 Proceedings of the 9th ACM international workshop on Data warehousing and OLAP
A Parallel Mining Algorithm for Closed Sequential Patterns
AINAW '07 Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 01
Usage-Based Positive and Negative Verification of User Interface Structure
ICAS '08 Proceedings of the Fourth International Conference on Autonomic and Autonomous Systems
GraSeq: A Novel Approximate Mining Approach of Sequential Patterns over Data Stream
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
Incremental mining of sequential patterns using prefix tree
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Filtering of web recommendation lists using positive and negative usage patterns
KES'07/WIRN'07 Proceedings of the 11th international conference, KES 2007 and XVII Italian workshop on neural networks conference on Knowledge-based intelligent information and engineering systems: Part III
A new algorithm for fast discovery of maximal sequential patterns in a document collection
CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
An efficient algorithm for incremental mining of sequential patterns
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Mining compressed sequential patterns
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
Expert Systems with Applications: An International Journal
| Hi-index | 0.00 |
The new type of patterns: sequential patterns with the negative conclusions is proposed in the paper. They denote that a certain set of items does not occur after a regular frequent sequence. Some experimental results and the SPAWN algorithm for mining sequential patterns with the negative conclusions are also presented.