Topic modeling is a Natural Language Processing technique that has gained popularity over the last ten years, with applications in multiple fields of knowledge. However, there insufficient empirical evidence to show how this field study developed as well main models have been applied different contexts. The objective paper analyze evolution topic technique, areas which it applied, and are recom...

As one of the simplest probabilistic topic modeling techniques, latent Dirichlet allocation (LDA) has found many important applications in text mining, computer vision and computational biology. Recent training algorithms for LDA can be interpreted within a unified message passing framework. However, message passing requires storing previous messages with a large amount of memory space, increas...

Objectives The classification of crime into discrete categories entails a massive loss of information. Crimes emerge out of a complex mix of behaviors and situations, yet most of these details cannot be captured by singular crime type labels. This information loss impacts our ability to not only understand the causes of crime, but also how to develop optimal crime prevention strategies. Methods...

Podcasts have emerged as a massively consumed online content, notably due to wider accessibility of production means and scaled distribution through large streaming platforms. Categorization systems information access technologies typically use topics the primary way organize or navigate podcast collections. However, annotating podcasts with is still quite problematic because assigned editorial...