Related papers: pyBiblioNet: a Python library for a comprehensive …

Scholarly usage data provides unique opportunities to address the known shortcomings of citation analysis. However, the collection, processing and analysis of usage data remains an area of active research. This article provides a review of…

In recent years, there has been increasing interest in network diffusion models and related problems. The most popular of these are the independent cascade and linear threshold models. Much of the recent experimental work done on these…

In recent years, tree tensor network methods have proven capable of simulating quantum many-body and other high-dimensional systems. This work is a user guide to our Python library PyTreeNet. It includes code examples and exercises to…

The recomputability and reproducibility of results from scientific software requires access to both the source code and all associated input and output data. However, the full collection of these resources often does not accompany the key…

The rapid growth of publicly available textual resources, such as lexicons and domain-specific corpora, presents challenges in efficiently identifying relevant resources. While repositories are emerging, they often lack advanced search and…

Clustering methods are applied regularly in the bibliometric literature to identify research areas or scientific fields. These methods are for instance used to group publications into clusters based on their relations in a citation network.…

Bibliometric techniques are not yet widely used to enhance retrieval processes in digital libraries, although they offer value-added effects for users. In this paper we will explore how statistical modelling of scholarship, such as…

PyPOTS is an open-source Python library dedicated to data mining and analysis on multivariate partially-observed time series with missing values. Particularly, it provides easy access to diverse algorithms categorized into five tasks:…

Telegram is a popular platform for public communication, generating large amounts of messages through its channels. pytopicgram is a Python library that helps researchers collect, organize, and analyze these Telegram messages. The library…

The increase in the number of publications has made more difficult for authors to situate their work within previous literature, especially on subjects studied from different disciplinary viewpoints. Besides, new data analysis techniques…

Information exposing, in conjunction with technological innovations and the emergence of social media, altered the traditional roles of academic libraries and enabled librarians to become necessary partners in research. The role of academic…

Literature recommendation is essential for researchers to find relevant articles in an ever-growing academic field. However, traditional methods often struggle due to data limitations and methodological challenges. In this work, we…

Identifying technological convergence among emerging technologies in cybersecurity is crucial for advancing science and fostering innovation. Unlike previous studies focusing on the binary relationship between a paper and the concept it…

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…

Bibliometric techniques are not yet widely used to enhance retrieval processes in digital libraries, although they offer value-added effects for users. In this workshop we will explore how statistical modelling of scholarship, such as…

We present an open-source Python library for building and using datasets where inputs are clusters of textual data, and outputs are sequences of real values representing one or more time series signals. The news-signals library supports…

Identifying suitable datasets for a research question remains challenging because existing dataset search engines rely heavily on metadata quality and keyword overlap, which often fail to capture the semantic intent of scientific…

Biomedical research yields a wealth of information, much of which is only accessible through the literature. Consequently, literature search is an essential tool for building on prior knowledge in clinical and biomedical research. Although…

Exploratory visual data analysis tools empower data analysts to efficiently and intuitively explore data insights throughout the entire analysis cycle. However, the gap between common programmatic analysis (e.g., within computational…

Structured information extraction from scientific literature is crucial for capturing core concepts and emerging trends in specialized fields. While existing datasets aid model development, most focus on specific publication sections due to…