Temporal databases provide built-in supports for efficient recording and querying of time-evolving data. In this paper, data clustering issues in temporal database environment are...
Abstract—In this work, we investigate the relative hardness of shorttext corpora in clustering problems and how this hardness relates to traditional similarity measures. Our appr...
Marcelo Luis Errecalde, Diego Ingaramo, Paolo Ross...
In this paper, an HMM-embedded unsupervised learning approach is proposed to detect the music events by grouping the similar segments of the music signal. This approach can cluste...
Recent works in object recognition often use visual words, i.e. vector quantized local descriptors extracted from the images. In this paper we present a novel method to build such ...
We propose an approach for learning visual models of object categories in an unsupervised manner in which we first build a large-scale complex network which captures the interacti...