Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
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
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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
Mining for Strong Negative Associations in a Large Database of Customer Transactions
ICDE '98 Proceedings of the Fourteenth 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
Mining Negative Association Rules
ISCC '02 Proceedings of the Seventh International Symposium on Computers and Communications (ISCC'02)
Efficient mining of both positive and negative association rules
ACM Transactions on Information Systems (TOIS)
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
Mining negative sequential patterns
ACOS'07 Proceedings of the 6th Conference on WSEAS International Conference on Applied Computer Science - Volume 6
Mining Both Positive and Negative Impact-Oriented Sequential Rules from Transactional Data
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
An order-clique-based approach for mining maximal co-locations
Information Sciences: an International Journal
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part II
CMRules: Mining sequential rules common to several sequences
Knowledge-Based Systems
An efficient GA-Based algorithm for mining negative sequential patterns
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Negative-GSP: an efficient method for mining negative sequential patterns
AusDM '09 Proceedings of the Eighth Australasian Data Mining Conference - Volume 101
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Traditional sequential pattern mining deals with positive sequential patterns only, that is, only frequent sequential patterns with the appearance of items are discovered. However, it is often interesting in many applications to find frequent sequential patterns with the non-occurrence of some items, which are referred to as negative sequential patterns. This paper analyzes three types of negative sequential rules and presents a new technique to find event-oriented negative sequential rules. Its effectiveness and efficiency are shown in our experiments.