Equitable Conceptual Clustering Using OWA Operator

Aribi, Noureddine; Ouali, Abdelkader; Lebbah, Yahia; Loudni, Samir

doi:10.1007/978-3-319-93040-4_37

Cited by 2 publications

(1 citation statement)

References 20 publications

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“…This aggregation function ensures a minimal quality over all clusters. Aribi, Ouali, Lebbah, and Loudni (2018) consider other aggregation functions for evaluating the quality of a clustering, and they show that the Ordered Weighted Average function (that returns a weighted sum of qualities) ensures equity by weighting quality measures according to their rank. This kind of aggregation function hardly scales with CP, and it would be interesting to design a specific propagator for it.…”

Section: Discussionmentioning

confidence: 99%

A Global Constraint for the Exact Cover Problem: Application to Conceptual Clustering

Chabert¹,

Solnon

2020

jair

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We introduce the exactCover global constraint dedicated to the exact cover problem, the goal of which is to select subsets such that each element of a given set belongs to exactly one selected subset. This NP-complete problem occurs in many applications, and we more particularly focus on a conceptual clustering application. We introduce three propagation algorithms for exactCover, called Basic, DL, and DL+: Basic ensures the same level of consistency as arc consistency on a classical decomposition of exactCover into binary constraints, without using any specific data structure; DL ensures the same level of consistency as Basic but uses Dancing Links to efficiently maintain the relation between elements and subsets; and DL+ is a stronger propagator which exploits an extra property to filter more values than DL. We also consider the case where the number of selected subsets is constrained to be equal to a given integer variable k, and we show that this may be achieved either by combining exactCover with existing constraints, or by designing a specific propagator that integrates algorithms designed for the NValues constraint. These different propagators are experimentally evaluated on conceptual clustering problems, and they are compared with state-of-the-art declarative approaches. In particular, we show that our global constraint is competitive with recent ILP and CP models for mono-criterion problems, and it has better scale-up properties for multi-criteria problems.

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Section: Discussionmentioning

confidence: 99%

A Global Constraint for the Exact Cover Problem: Application to Conceptual Clustering

Chabert¹,

Solnon

2020

jair

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Equitable Optimization for Multicast Communication

Fourour

Lebbah

2020

International Journal of Decision Support System Technology

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Multicast communication is characterized by the multiplicity of streams defining different groups, where each stream has multiple sources. A multicast communication tends to flood the network with a large number of flows that can overload some nodes and unload others. This imbalance in the load distribution weakens network performance and could produce bottlenecks around overloaded nodes. We propose in this article an approach based on a combination of a flow approach and a multi-agent optimization to resolve the load balancing issue of multicast communication. We use ordered weighted average (OWA), a multi-criteria optimization method, to balance the degree of the nodes, ensuring a balanced load distribution across the network. The experiments conducted on a series of networks show that our approach provides a better equitable load assignment.

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Equitable Conceptual Clustering Using OWA Operator

Cited by 2 publications

References 20 publications

A Global Constraint for the Exact Cover Problem: Application to Conceptual Clustering

A Global Constraint for the Exact Cover Problem: Application to Conceptual Clustering

Equitable Optimization for Multicast Communication

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