Sequential pattern mining first proposed by Agrawal and Srikant has received intensive research due to its wide range applicability in many real-life domains. Various improvements...
Finding sequential patterns is one of important issues in data mining. This paper deals with linguistic (fuzzy) sequential patterns. The existing algorithms for discovering such p...
— Since sequential patterns may exist in multiple sequence databases, we propose algorithm PropagatedMine+ to efficiently discover multi-domain sequential patterns. Prior works ...
Abstract. 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 regul...
Sequential pattern mining aims to find frequent patterns (guarded by a minimum support) in a database of sequences. As the support decreases the number of sequential patterns will...
This paper explores the use of alternating sequential patterns of local features and saccading actions to learn robust and compact object representations. The temporal encoding rep...
Discovering sequential patterns is an important problem in data mining with a host of application domains including medicine, telecommunications, and the World Wide Web. Conventio...
Minos N. Garofalakis, Rajeev Rastogi, Kyuseok Shim
A sequential pattern in data mining is a finite series of elements such as A → B → C → D where A, B, C, and D are elements of the same domain. The mining of sequential patte...
Pak Chung Wong, Wendy Cowley, Harlan Foote, Elizab...
Discovery of sequential patterns is becoming increasingly useful and essential in many scienti c and commercial domains. Enormous sizes of available datasets and possibly large nu...
We describe an efficient framework for Web personalization based on sequential and non-sequential pattern discovery from usage data. Our experimental results performed on real us...
Bamshad Mobasher, Honghua Dai, Tao Luo, Miki Nakag...