Discovering metric temporal constraint networks on temporal databases

TítuloDiscovering metric temporal constraint networks on temporal databases
AutoresÁlvarez MR, Félix P, Cariñena P
TipoArtículo de revista
Fonte Artificial Intelligence in Medicine, ELSEVIER SCIENCE BV, Vol. 58, No. 3, pp. 139-154 , 2013.
AbstractIn this paper, we propose the ASTPminer algorithm for mining collections of time-stamped sequences to discover frequent temporal patterns, as represented in the simple temporal problem (STP) formalism: a representation of temporal knowledge as a set of event types and a set of metric temporal constraints among them. To focus the mining process, some initial knowledge can be provided by the user, also expressed as an STP, that acts as a seed pattern for the searching procedure. In this manner, the mining algorithm will search for those frequent temporal patterns consistent with the initial knowledge.
Palabras chaveConstraint satisfaction problems, Sleep apnea–hypopnea syndrome, Temporal data mining, Temporal knowledge representation