MASS-CSP: mining with answer set solving for contrast sequential pattern mining
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.
Authors
- Gioacchino Sterlicchio (ORCID: https://orcid.org/0000-0002-2936-0777)
- Francesca A. Lisi (ORCID: https://orcid.org/0000-0001-5414-5844)
Institutions
- University of Bari Aldo Moro (IT)
- Polytechnic University of Bari (IT)
Publication Details
- Journal
- Machine Learning
- Published
- 2025-09-28
- DOI
- https://doi.org/10.1007/s10994-025-06876-0
- Primary Topic
- Logic, Reasoning, and Knowledge
- Type
- article
- Field-Weighted Citation Impact
- 0.00