Assessment on collaborative student behavior is a longstanding issue in user modeling. Nowadays thanks to the proliferation of online learning and the vast amount of data on studen...
In this paper we present a novel technique for nearest neighbor searching dubbed neighborhood approximation. The central idea is to divide the database into compact regions repres...
While the social and information networks have become ubiquitous, the challenge of collecting complete network data still persists. Many times the collected network data is incomp...
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
When multiple data sources are available for clustering, an a priori data integration process is usually required. This process may be costly and may not lead to good clusterings,...
Elisa Boari de Lima, Raquel Cardoso de Melo Minard...
This paper describes one of the first attempts to model the temporal structure of massive data streams in real-time using data stream clustering. Recently, many data stream clust...
The problem of monitoring a multivariate linear regression model is relevant in studying the evolving relationship between a set of input variables (features) and one or more depe...