Mining high utility episodes in complex event sequences
Frequent episode mining (FEM) is an interesting research topic in data mining with wide
range of applications. However, the traditional framework of FEM treats all events as having …
range of applications. However, the traditional framework of FEM treats all events as having …
Efficient mining of frequent episodes from complex sequences
KY Huang, CH Chang - Information Systems, 2008 - Elsevier
Discovering patterns with great significance is an important problem in data mining
discipline. An episode is defined to be a partially ordered set of events for consecutive and …
discipline. An episode is defined to be a partially ordered set of events for consecutive and …
Constraint-based mining of episode rules and optimal window sizes
N Méger, C Rigotti - European Conference on Principles of Data Mining …, 2004 - Springer
Episode rules are patterns that can be extracted from a large event sequence, to suggest to
experts possible dependencies among occurrences of event types. The corresponding …
experts possible dependencies among occurrences of event types. The corresponding …
Mining precise-positioning episode rules from event sequences
Episode Rule Mining is a popular framework for discovering sequential rules from event
sequential data. However, traditional episode rule mining methods only tell that the …
sequential data. However, traditional episode rule mining methods only tell that the …
Online frequent episode mining
Frequent episode mining is a popular framework for discovering sequential patterns from
sequence data. Previous studies on this topic usually process data offline in a batch mode …
sequence data. Previous studies on this topic usually process data offline in a batch mode …
Sequential data mining: A comparative case study in development of atherosclerosis risk factors
J Klema, L Nováková, F Karel… - … on Systems, Man …, 2007 - ieeexplore.ieee.org
Sequential data represent an important source of potentially new medical knowledge.
However, this type of data is rarely provided in a format suitable for immediate application of …
However, this type of data is rarely provided in a format suitable for immediate application of …
Extracting trees of quantitative serial episodes
Among the family of the local patterns, episodes are commonly used when mining a single
or multiple sequences of discrete events. An episode reflects a qualitative relation is …
or multiple sequences of discrete events. An episode reflects a qualitative relation is …
Data mining of temporal sequences for the prediction of infrequent failure events: application on floating train data for predictive maintenance
W Sammouri - 2014 - theses.hal.science
In order to meet the mounting social and economic demands, railway operators and
manufacturers are striving for a longer availability and a better reliability of railway …
manufacturers are striving for a longer availability and a better reliability of railway …
Discovering and learning sensational episodes of news events
In this paper, we study the problem of discovering and learning sensational episodes of
news events. A sensational episode of news events is in the form of lhs→ rhs, where lhs is …
news events. A sensational episode of news events is in the form of lhs→ rhs, where lhs is …
Mining weighted frequent closed episodes over multiple sequences
Sažetak Frequent episode discovery is introduced to mine useful and interesting temporal
patterns from sequential data. The existing episode mining methods mainly focused on …
patterns from sequential data. The existing episode mining methods mainly focused on …