Topic modeling is a statistical data mining method for organizing the documents with
variable contents under similar topics. It is utilized to reveal the concealed topics from an …

Text segmentation (TS) is the process of dividing multi-topic text collections into cohesive
segments using topic boundaries. Similarly, text clustering has been renowned as a major …

The main focus of this research is to find the reasons behind the fresh cases of COVID-19
from the public's perception for data specific to India. The analysis is done using machine …

The growth of e-news platforms, the most popular and accessible media for sharing
information, has resulted in the increase of digital news articles volume. Users' navigation …

A key step in publishing on Google Play Store (GPS) is the manual selection of the app
category. The category is highly relevant for users when searching for a suitable app. To …

Document clustering techniques often produce clusters that require human intervention to
interpret the meaning of such clusters. Automatic cluster labeling refers to the process of …

[Objective] This paper reviews methods of automatic topic labeling, aiming to promote the
development of topic modelling.[Coverage] We used “Topic Labeling OR Topic Labeling OR …

Text mining methods contribute significantly to the understanding and the management of
digital content, increasing the potential of entry links. This paper introduces a method for …

Different topic modeling techniques have been applied over the years to categorize and
make sense of large volumes of unstructured textual data. Our observation shows that there …

Text datasets in Indonesian are processed systematically. The process starts with loading a
text dataset, preprocessing the text, tokenizing it, removing stop words, and stemming it to …