A text segmentation approach for automated annotation of online customer reviews, based on topic modeling
Online customer review classification and analysis have been recognized as an important
problem in many domains, such as business intelligence, marketing, and e-governance. To …
problem in many domains, such as business intelligence, marketing, and e-governance. To …
Dependency-Aware Neural Topic Model
Existing topic models that aim to discover relationships between topics typically focus on two
types of relations: undirected correlation and hierarchy with a tree structure. However, these …
types of relations: undirected correlation and hierarchy with a tree structure. However, these …
Exploring consumer engagement and satisfaction in health and wellness tourism through text-mining
YS Balcioglu - Kybernetes, 2024 - emerald.com
Purpose This study aims to deepen the understanding of consumer engagement and
satisfaction within the health and wellness tourism sector, a rapidly growing niche in the …
satisfaction within the health and wellness tourism sector, a rapidly growing niche in the …
Bayesian estimation of inverted beta mixture models with extended stochastic variational inference for positive vector classification
Y Lai, W Guan, L Luo, Y Guo, H Song… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
The finite inverted beta mixture model (IBMM) has been proven to be efficient in modeling
positive vectors. Under the traditional variational inference framework, the critical challenge …
positive vectors. Under the traditional variational inference framework, the critical challenge …
Beyond Labels and Topics: Discovering Causal Relationships in Neural Topic Modeling
Topic models that can take advantage of labels are broadly used in identifying interpretable
topics from textual data. However, existing topic models tend to merely view labels as names …
topics from textual data. However, existing topic models tend to merely view labels as names …
Implementation of Dynamic Topic Modeling to Discover Topic Evolution on Customer Reviews
VR Hananto - Jurnal Online Informatika, 2023 - join.if.uinsgd.ac.id
Annotation and analysis of online customer reviews were identified as significant problems
in various domains, including business intelligence, marketing, and e-governance. In the …
in various domains, including business intelligence, marketing, and e-governance. In the …
Unsupervised attack pattern detection in honeypot data using Bayesian topic modelling
Cyber-systems are under near-constant threat from intrusion attempts. Attacks types vary,
but each attempt typically has a specific underlying intent, and the perpetrators are typically …
but each attempt typically has a specific underlying intent, and the perpetrators are typically …
Efficient inference for dynamic topic modeling with large vocabularies
Dynamic topic modeling is a well established tool for capturing the temporal dynamics of the
topics of a corpus. In this work, we develop a scalable dynamic topic model by utilizing the …
topics of a corpus. In this work, we develop a scalable dynamic topic model by utilizing the …
mixSTM: Adapting the Structural Topic Model for a quantitative analysis of focus group data
PA Nevins - 2024 - search.proquest.com
Abstract The Structural Topic Model (STM) incorporates external information about expected
document-topic proportions to enhance the model. Motivated by focus groups, whose …
document-topic proportions to enhance the model. Motivated by focus groups, whose …
Probabilistic models for opinion dynamics understanding
R Zhao - 2023 - wrap.warwick.ac.uk
Social media platforms produce an abundance of user-generated content, which are crucial
for the purpose of both private profits and public benefit. As manual summarization is …
for the purpose of both private profits and public benefit. As manual summarization is …