Sentence examples for topics are characterized from inspiring English sources

Examining word frequency and use can offer insights into speaking style, topics discussed, and how those topics are characterized.

The basic idea is that the visual and semantic modalities of images are represented as random mixtures over multiple latent topics, where each topic is characterized by a distribution over each modality.

However, topic modeling considers samples as a mixture of latent topics and each topic is characterized by the probabilistic distribution of genes.

The basic idea is that a document is represented as a mixture of several topics, where each topic is characterized by a word distribution.

LDA is a generative probabilistic model in which documents are represented as random mixtures over latent topics, and each topic is characterized by a distribution over words (22).

LDA is a probabilistic model that hypothesizes that each document (e.g., individual tweets) in a given corpus (e.g., all the tweets) has been generated as a mixture of unobserved, or latent, topics, where a topic is characterized by a categorical distribution over words.

Banded blurred Infrared image segmentation is a challenging topic since banded blurred infrared images are characterized by high noise, low contrast, and weak edges.

The text corpora collected from various resources such as web pages or electronic documents are characterized by many possible topics.

They state that research activities are characterized by a concentration on topics guided by special interests of stakeholders.

In this, university lectures are characterized by a multitude of diverse topics and a large amount of technical terms.

Narrative interviews are characterized by an initial phase of topic formulation carried out by the interviewer, followed by the main narrative phase.