Network clustering (or graph partitioning) is an important task for the discovery of underlying structures in networks. Many algorithms find clusters by maximizing the number of i...
Xiaowei Xu, Nurcan Yuruk, Zhidan Feng, Thomas A. J...
Instance selection and feature selection are two orthogonal methods for reducing the amount and complexity of data. Feature selection aims at the reduction of redundant features i...
Abstract. In this paper we describe a virtual laboratory that is designed to accelerate scientific exploration and discovery by minimizing the time between the generation of a scie...
Judith Ellen Devaney, Steven G. Satterfield, John ...
In the demonstration, we will present the concepts and an implementation of an inductive database ? as proposed by Imielinski and Mannila ? in the relational model. The goal is to...
—In graph-based learning models, entities are often represented as vertices in an undirected graph with weighted edges describing the relationships between entities. In many real...