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We are interested in understanding the underlying generation process for longsequences of symbolic events. To do so, we propose COSSU, an algorithm to minesmall and meaningful sets of sequential rules. The rules are selected using anMDL-inspired criterion that favors compactness and relies on a novel rule-basedencoding scheme for sequences. Our evaluation shows that COSSU can successfullyretrieve relevant sets of closed sequential rules from a long sequence. Suchrules constitute an interpretable model that exhibits competitive accuracy forthe tasks of next-element prediction and classification.

Discovering Useful Compact Sets of Sequential Rules in a Long Sequence