Discovering Useful Compact Sets of Sequential Rules in a Long Sequence

• URL: http://arxiv.org/abs/2109.07519v1
• Date: Wed, 15 Sep 2021 18:25:18 GMT
• Title: Discovering Useful Compact Sets of Sequential Rules in a Long Sequence
• Authors: Erwan Bourrand and Luis Gal\'arraga and Esther Galbrun and Elisa Fromont and Alexandre Termier
• Abstract summary: COSSU is an algorithm to mine small and meaningful sets of sequential rules. We show that COSSU can successfully retrieve relevant sets of closed sequential rules from a long sequence.
• Score: 57.684967309375274
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We are interested in understanding the underlying generation process for long sequences of symbolic events. To do so, we propose COSSU, an algorithm to mine small and meaningful sets of sequential rules. The rules are selected using an MDL-inspired criterion that favors compactness and relies on a novel rule-based encoding scheme for sequences. Our evaluation shows that COSSU can successfully retrieve relevant sets of closed sequential rules from a long sequence. Such rules constitute an interpretable model that exhibits competitive accuracy for the tasks of next-element prediction and classification.

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