In Latent Semantic Indexing (LSI), a collection of documents is often pre-processed to form a sparse term-document matrix, followed by a computation of a low-rank approximation to...
Semantic analysis of a document collection can be viewed as an unsupervised clustering of the constituent words and documents around hidden or latent concepts. This has shown to i...
Image categorization is undoubtedly one of the most challenging open problems faced in Computer Vision, far from being solved by employing pure visual cues. Recently, additional t...
Marco Cristani, Alessandro Perina, Umberto Castell...
Contextual text mining is concerned with extracting topical themes from a text collection with context information (e.g., time and location) and comparing/analyzing the variations...
We propose a novel unsupervised learning algorithm to extract the layout of an image by learning latent object-related aspects. Unlike traditional image segmentation algorithms th...