This study selects the U.S. automotive industry as the research subject to explore the recent trends in automotive development. Since the analysis was based on the content of reviews, a topic model for textual analysis is chosen as the methodology,...

This study explores the integration and impact of the Internet of Things (IoT) and e commerce, revealing significant advancements and challenges. Through Latent Dirichlet Allocation (LDA) topic modeling, five core themes emerged, highlighting the pivotal ...

With the increasing popularity of e-commerce live streaming, comprehensive analysis of live barrage text has become increasingly crucial. This study presents a thematic analysis method for categorizing e-commerce live streaming barrage text using latent ...

ChatGPT has attracted much attention from industries, such as the medical industry, since its release in late 2022. Being an innovative artificial intelligence (AI) technology that has the potential to reshape the medical industry, ChatGPT has ...

In recent years, food consumption in Japan has changed significantly due to a variety of factors such as imports from over-seas, a declining and aging population, a rapid increase in dual-earner households, and diversification of lifestyles and so ...

Land transportation in Mexico plays a crucial role in ensuring connectivity and facilitating the mobility of both people and commodity. Nevertheless, this sector confronts substantial challenges, predominantly related with road accidents. ...

The classification of molecules is of particular importance to the drug discovery process and several other use cases. Data in this domain can be partitioned into structural and sequence/text data. Several techniques such as deep learning are ...

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• Simple embedding techniques for text data.
• Robust and simple technique for molecular classification.
• Simple embedding technique for SMILES and FASTA sequence data.
• Text embedding for SMILES stings.
• Molecular classification ...

This study undertakes a topic modelling-based approach to identify how businesses are transforming with digital platforms. The corpus for this study comprises of high-quality research contributions in digital business platforms (DBPs). The study ...

Human-in-the-loop topic modeling (HLTM) empowers users to modify topic models and enhance their quality, by enabling them to directly refine the model. Prior studies have made significant strides in this area, specifically keyphrase-based ...

• Ten potential scientific topics were revealed from the collected fuzzy research literature using LDA.
• The distribution characteristics and dynamic trends of the topics were identified at the journal and country/region level.
• The ...

Over the past few decades, the field of fuzzy research has experienced rapid growth. However, there remains a dearth of a comprehensive overview and summary of fuzzy research that provides a macro understanding of the field, particularly from the ...

The number of Android apps is constantly on the rise. Existing stores allow selecting apps from general named categories. To prevent miscategorization and facilitate user selection of the appropriate app, a closer examination of the categories’ ...

As live video streaming has become an everyday activity, influential users on video streaming platforms are taking on the role of billboards for product services. Predicting channel growth would be useful for advertising marketing. In this study, ...

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 prevent misclassification, existing work focused on automating the ...

Topic modeling is a popular method for discovering semantic information from textual data, with latent Dirichlet allocation (LDA) being a representative model. Recently, researchers have explored the use of variational autoencoders (VAE) to ...

• The research interest and research impact of supply chain has been rising.
• The ...

In recent years, supply chain research has grown at a tremendous pace. Many review papers use systematic literature reviews to describe longer-term trends and perspectives. However, many of these studies analyze a limited number of ...

In April 2022, Sina Weibo began to display users’ coarse location for the stated purpose of regulating their online community. However, this raised concerns about location privacy. Through sentiment analysis and Latent Dirichlet Allocation (LDA), ...

Questioning and answering (Q&A) communities have been widely used by user experience (UX) professionals to exchange knowledge online. As online content has been increasingly generated by professional users in the community, it becomes infeasible ...

Through an overview of the history of the disease, Narrative Medicine (NM) aims to define and implement an effective, appropriate and shared treatment path. In the context of COVID-19, several blogs were produced, among those the “Sindrome Post ...

The search for relevant scientific articles is a crucial step in any research project. However, the vast number of articles published and available online in digital databases (Google Scholar, Semantic Scholar, etc.) can make this task tedious and ...

The increasing reliance on mobile health for managing disease conditions has opened a new frontier in digital health, thus, the need for understanding what constitutes positive and negative sentiments of the various apps. This paper ...

• Developed Embedded-Deep Neural Networks (E-DNN) for user sentiments prediction
• ...