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MASS-CSP: mining with answer set solving for contrast sequential pattern mining
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DOI：10.1007/s10994-025-06876-0.png)
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Abstract
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In this paper, we present MASS-CSP (Mining with Answer Set Solving - Contrast Sequential Patterns), a declarative approach to the Contrast Sequential Pattern Mining (CSPM) task, which is based on the logic-based framework of Answer Set Programming (ASP). The CSPM task focuses on identifying significant differences in frequent sequences relative to specific classes, leading to the concept of a contrast sequential pattern. The article describes how MASS-CSP addresses the CSPM task and related extensions-mining closed, maximal and constrained patterns. Evaluation aims at comparing the basic version of MASS-CSP against the extended versions as regards the size of output and time-memory requirements.
Keywords:
Declarative pattern mining
Contrast sequential pattern mining
Answer set programming
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