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.
MASS-CSP: mining with answer set solving for contrast sequential pattern mining
Sterlicchio G.
Writing – Original Draft Preparation
;Lisi F. A.
Supervision
2025-01-01
Abstract
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


