In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
The aim of data mining is to find novel and actionable insights in data. However, most algorithms typically just find a single (possibly non-novel/actionable) interpretation of th...
Given the pairwise affinity relations associated with a set of data items, the goal of a clustering algorithm is to automatically partition the data into a small number of homogen...
This paper presents a cluster-based text categorization system which uses class distributional clustering of words. We propose a new clustering model which considers the global in...
Dynamic configuration techniques such as DVFS (Dynamic Voltage and Frequency Scaling) and turning on/off computers are well known ways to promote energy consumption reduction in w...
Carlos Santana, Julius C. B. Leite, Daniel Moss&ea...