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2013 IEEE 13th International Conference on Data Mining (2005)
Houston, Texas
Nov. 27, 2005 to Nov. 30, 2005
ISSN: 1550-4786
ISBN: 0-7695-2278-5
pp: 354-361
Stan Sclaroff , Boston University
George Kollios , Boston University
Panagiotis Papapetrou , Boston University
Dimitrios Gunopulos , University of California at Riverside
ABSTRACT
In this paper we study a new problem in temporal pattern mining: discovering frequent arrangements of temporal intervals. We assume that the database consists of sequences of events, where an event occurs during a time-interval. The goal is to mine arrangements of event intervals that appear frequently in the database. There are many applications where these type of patterns can be useful, including data network, scientific, and financial applications. Efficient methods to find frequent arrangements of temporal intervals using both breadth first and depth first search techniques are described. The performance of the proposed algorithms is evaluated and compared with other approaches on real datasets (American Sign Language streams and network data) and large synthetic datasets.
INDEX TERMS
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CITATION
Stan Sclaroff, George Kollios, Panagiotis Papapetrou, Dimitrios Gunopulos, "Discovering Frequent Arrangements of Temporal Intervals", 2013 IEEE 13th International Conference on Data Mining, vol. 00, no. , pp. 354-361, 2005, doi:10.1109/ICDM.2005.50
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