Skip to Main content Skip to Navigation

Constraint Programming for Multi-criteria Conceptual Clustering

Maxime Chabert 1 Christine Solnon 1
1 M2DisCo - Geometry Processing and Constrained Optimization
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : A conceptual clustering is a set of formal concepts (i.e., closed itemsets) that defines a partition of a set of transactions. Finding a conceptual clustering is an N P-complete problem for which Constraint Programming (CP) and Integer Linear Programming (ILP) approaches have been recently proposed. We introduce new CP models to solve this problem: a pure CP model that uses set constraints, and an hybrid model that uses a data mining tool to extract formal concepts in a preprocessing step and then uses CP to select a subset of formal concepts that defines a partition. We compare our new models with recent CP and ILP approaches on classical machine learning instances. We also introduce a new set of instances coming from a real application case, which aims at extracting setting concepts from an Enterprise Resource Planning (ERP) software. We consider two classic criteria to optimize, i.e., the frequency and the size. We show that these criteria lead to extreme solutions with either very few small formal concepts or many large formal concepts, and that compromise clusterings may be obtained by computing the Pareto front of non dominated clusterings.
Document type :
Conference papers
Complete list of metadatas

Cited literature [22 references]  Display  Hide  Download
Contributor : Christine Solnon <>
Submitted on : Wednesday, June 21, 2017 - 3:04:48 PM
Last modification on : Thursday, November 21, 2019 - 2:15:20 AM
Document(s) archivé(s) le : Saturday, December 16, 2017 - 1:15:41 AM


Files produced by the author(s)


  • HAL Id : hal-01544239, version 1


Maxime Chabert, Christine Solnon. Constraint Programming for Multi-criteria Conceptual Clustering. 23rd International Conference on Principles and Practice of Constraint Programming (CP), Aug 2017, Melbourne, Australia. pp.460-476. ⟨hal-01544239⟩



Record views


Files downloads