This paper is a comparative study of feature selection methods in statistical learning of text
categorization. The focus is on aggressive dimensionality reduction. Five methods were …

The extraction of useful insights from text with various types of statistical algorithms is
referred to as text mining, text analytics, or machine learning from text. The choice of …

Clustering is a widely studied data mining problem in the text domains. The problem finds
numerous applications in customer segmentation, classification, collaborative filtering …

Abstract Multi-class Sentiment Analysis (SA) is an important field of computational linguistics
that extracts multiple opinions expressed in a text using NLP and text-mining techniques …

Individual happiness is a fundamental societal metric. Normally measured through self-
report, happiness has often been indirectly characterized and overshadowed by more …

Natural language is ubiquitous in the workflow of medical imaging. Radiologists create and
consume free text in their daily work, some of which can be amenable to enhancements …

Background Unstructured text, including medical records, patient feedback, and social
media comments, can be a rich source of data for clinical research. Natural language …

There are increasing applications of natural language processing techniques for information
retrieval, indexing, topic modelling and text classification in engineering contexts. A standard …

The aviation safety reporting system database has seen many applications of topic modeling
and natural language processing. Its size, metadata, and narratives have made it ideal for …

Researchers in information science and related areas have developed various methods for
analyzing textual data, such as survey responses. This article describes the application of …