Related papers: pyBibX -- A Python Library for Bibliometric and Sc…
Computer simulation has become one of the most important tools in scientific research in many disciplines. Benefiting from the dynamical trajectories regulated by versatile interatomic interactions, various material properties can be…
Over the recent years, there has been a growing interest in developing new research evaluation methods that could go beyond the traditional citation-based metrics. This interest is motivated on one side by the wider availability or even…
Large language models are increasingly integrated into academic writing workflows; however, the most widely used \LaTeX\ editors remain AI-peripheral -- offering compilation and collaboration, but no native intelligence. This separation…
We show how faceted search using a combination of traditional classification systems and mixed-membership topic models can go beyond keyword search to inform resource discovery, hypothesis formulation, and argument extraction for…
EEG-based emotion recognition (EER) has gained significant attention due to its potential for understanding and analyzing human emotions. While recent advancements in deep learning techniques have substantially improved EER, the field lacks…
The information explosion in the form of ETDs poses the challenge of management and extraction of appropriate knowledge for decision-making. Thus, the present study forwards a solution to the above problem by applying topic mining and…
Context: The Debian system has historically participated in academic works and scientific projects, with well-known examples including NeuroDebian, Debian Med, Debsources, Debian Science, and Debian GIS, where the scientific relevance of…
By utilizing statistical methods to analyze bibliographic data, bibliometrics faces inherent limitations in identifying the most significant science and technology achievements and researchers. To overcome this challenge, we present an…
Bibliometric methods for the analysis of highly specialized subjects are increasingly investigated and debated. Information and assessments well-focused at the specialty level can help make important decisions in research and innovation…
As AI-driven document understanding and processing tools become increasingly prevalent in real-world applications, the need for rigorous evaluation standards has grown increasingly urgent. Existing benchmarks and evaluations often focus on…
Supply chain risk assessment (SCRA) is pivotal for ensuring resilience in increasingly complex global supply networks. While existing reviews have explored traditional methodologies, they often neglect emerging artificial intelligence (AI)…
This paper presents a bibliometric analysis of the scientific literature related to chatbots, focusing specifically on ChatGPT. Chatbots have gained increasing attention recently, with an annual growth rate of 19.16% and 27.19% on the Web…
Bibliometric analysis is essential for understanding research trends, scope, and impact in urban science, especially in high-impact journals, such Nature Portfolios. However, traditional methods, relying on keyword searches and basic NLP…
The BIR workshop brings together experts in Bibliometrics and Information Retrieval. While sometimes perceived as rather loosely related, these research areas share various interests and face similar challenges. Our motivation as organizers…
The large scale of scholarly publications poses a challenge for scholars in information seeking and sensemaking. Bibliometrics, information retrieval (IR), text mining and NLP techniques could help in these search and look-up activities,…
Despite the explosion of interest in healthcare AI research, the reproducibility and benchmarking of those research works are often limited due to the lack of standard benchmark datasets and diverse evaluation metrics. To address this…
The growth of large, programatically accessible bibliometrics databases presents new opportunities for complex analyses of publication metadata. In addition to providing a wealth of information about authors and institutions, databases such…
Understanding key insights from full-text scholarly articles is essential as it enables us to determine interesting trends, give insight into the research and development, and build knowledge graphs. However, some of the interesting key…
This study aims to conduct a bibliometric analysis of scientific publications discussing technology integration in the Project-Based Learning (PjBL) model during the 2015-2024 period. With the evolving 21st century educational paradigm,…
We introduce \texttt{pycobra}, a Python library devoted to ensemble learning (regression and classification) and visualisation. Its main assets are the implementation of several ensemble learning algorithms, a flexible and generic interface…