While generative models such as Latent Dirichlet Allocation (LDA) have proven fruitful in
topic modeling, they often require detailed assumptions and careful specification of …

We present a novel method for hierarchical topic detection where topics are obtained by
clustering documents in multiple ways. Specifically, we model document collections using a …

Objective: to analyse research articles on pain and nursing issues using bibliometric and
scientometric methodologies. Method: articles in the Web of Science database containing …

Background Several studies have investigated the social and technical dimensions of a
career in nursing. This paper reveals tendencies and patterns in relevant literature, through …

A comprehensive and comprehensible summary of existing deep neural networks (DNNs)
helps practitioners understand the behaviour and evolution of DNNs, offers insights for …

The rising demands of gauging training transfer and the abundant wastes of training
investment has become a severe concern among the organizations and have stimulated …

Scientometrics, bibliometrics, webometrics, and informetrics are specific research fields that
cover statistical analyses of a particular research field which summarize the information …

Learning by children and animals occurs effortlessly and largely without obvious
supervision. Successes in automating supervised learning have not translated to the more …

Latent tree analysis seeks to model the correlations amonga set of random variables using a
tree of latent variables. It was proposed as an improvement to latent class analysis—a …

In this paper, we propose TopicAE, a simple autoencoder designed to perform topic
modeling with input texts. Topic modeling has grown in popularity especially in recent years …