Protein complexes play a crucial role in cellular biological processes. Identifying these complexes is essential for understanding cellular functions and biological mechanisms. Graph clustering ...

This repository contains the endterm project for the Mining Massive Data Sets course at Ton Duc Thang University. The project is organized into four main tasks: Hierarchical clustering in a ...

Abstract: Hierarchical clustering is a method in data mining and statistics used to build a hierarchy of clusters. Traditional hierarchical clustering relies on a measure of dissimilarity to combine ...

Many modern clustering methods scale well to a large number of data items, N, but not to a large number of clusters, K. This paper introduces PERCH, a new non-greedy algorithm for online hierarchical ...

ABSTRACT: This paper presents a new algorithm for solving unit commitment (UC) problems using a binary-real coded genetic algorithm based on k-means clustering technique. UC is a NP-hard nonlinear ...

About every 10 minutes, it seems, a new article about a "revolutionary breakthrough" in AI hits my screen. A new approach, a new feature, billions of dollars this, AI agents that. It has been non-stop ...

1 Facultad de Ingeniería, Universidad Andres Bello, Santiago, Chile. 2 Department of Mining Engineering, Universidad de Chile, Santiago, Chile. 3 Advanced Mining Technology Center, Universidad de ...

Abstract: Hierarchical clustering algorithm is a very important method in data mining. The disadvantage of hierarchical clustering lies in the time complexity of the algorithm and the one-way ...