The paper presents the results of experiments of usage of LSA for analysis of textual data. The method is explained in brief and special attention is pointed on its potential for c...
—This study examines the ability of nonnegative matrix factorization (NMF) as a method for constructing semantic spaces, in which the meaning of each word is represented by a hig...
Probabilistic Latent Semantic Analysis (PLSA) models have been shown to provide a better model for capturing polysemy and synonymy than Latent Semantic Analysis (LSA). However, th...
Text summarization solves the problem of extracting important information from huge amount of text data. There are various methods in the literature that aim to find out well-form...
Given a set of images of scenes containing multiple object categories (e.g. grass, roads, buildings) our objective is to discover these objects in each image in an unsupervised man...