Nanni M., Rigotti C.
CNR-ISTI, Pisa, Italy; INSA-LIRIS UMR 5205 CNRS, Lyon, France
Among the family of the local patterns, episodes are com- monly used when mining a single or multiple sequences of discrete events. An episode re°ects a qualitative relation is-followed-by over event types, and the re¯nement of episodes to incorporate quantitative temporal in- formation is still an on going research, with many application opportu- nities. In this paper, focusing on serial episodes, we design such a re¯ne- ment called quantitative episodes and give a corresponding extraction algorithm. The three most salient features of these quantitative episodes are: (1) their ability to characterize main groups of homogeneous behav- iors among the occurrences, according to the duration of the is-followed- by steps, and providing quantitative bounds of these durations organized in a tree structure; (2) the possibility to extract them in a complete way; and (3) to perform such extractions at the cost of a limited overhead with respect to the extraction of standard episodes.
Workshop on Knowledge Discovery in Inductive Databases. KDID'06, Berlin, Germany, 18/09/2006
ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"
ID: 120338
Year: 2006
Type: Presentazione
Creation: 2009-06-16 00:00:00.000
Last update: 2018-01-24 11:38:03.000
CNR authors
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:120338