PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Nanni M., Rigotti C. Extracting trees of quantitative serial episodes. Sašo Džeroski, Jan Struyf (eds.). (Lecture Notes in Computer Science, vol. 4747). Berlin / Heidelberg: Springer, 2007.
 
 
Abstract
(English)
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-followed-by over event types, and the refinement of episodes to incorporate quantitative temporal information is still an on going research, with many application opportunities. In this paper, focusing on serial episodes, we design such a refinement 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 behaviors 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.
URL: http://www.springerlink.com/content/e1q86609g43t05w0/?p=59efe84d1a67479d8e8c40b9b5818315&pi=10
DOI: 10.1007/978-3-540-75549-4_11
Subject Temporal sequences
Episode mining
Temporal data mining
H.2.8 Database Applications. Data Mining
62-07 Data analysis


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