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Information, Volume 15, Issue 6

June 2024 - 76 articles

Cover Story: Structured science summaries using properties beyond traditional keywords enhance science findability. Current methods, such as those used by the Open Research Knowledge Graph (ORKG), involve manual curation, which is labor-intensive and inconsistent. We propose using Large Language Models (LLMs) to automatically suggest these properties. Our study compares ORKG’s manually curated properties with those generated by LLMs, evaluating performance from the following four perspectives: semantic alignment, property mapping accuracy, cosine similarity, and expert surveys. LLMs show potential as recommendation systems for structuring science, but further fine-tuning is recommended to improve their alignment with scientific tasks and mimicry of human expertise. View this paper
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Articles (76)

  • Article
  • Open Access
1 Citations
1,800 Views
20 Pages

15 June 2024

Online conversation communities have become an influential source of consumer recommendations in recent years. We propose a set of meaningful user segments which emerge from user embedding representations, based exclusively on comments’ text in...

  • Article
  • Open Access
5 Citations
2,216 Views
22 Pages

14 June 2024

Diagnosing the financial health of companies and their performance is currently one of the basic questions that attracts the attention of researchers and experts in the field of finance and management. In this study, we focused on the proposal of mod...

  • Review
  • Open Access
12 Citations
14,854 Views
14 Pages

14 June 2024

Artificial intelligence (AI) has witnessed an exponential increase in use in various applications. Recently, the academic community started to research and inject new AI-based approaches to provide solutions to traditional software-engineering proble...

  • Review
  • Open Access
10 Citations
4,714 Views
16 Pages

14 June 2024

Risk assessment is a critical sub-process in information security risk management (ISRM) that is used to identify an organization’s vulnerabilities and threats as well as evaluate current and planned security controls. Therefore, adequate resou...

  • Article
  • Open Access
2,125 Views
24 Pages

A Novel Radio Network Information Service (RNIS) to MEC Framework in B5G Networks

  • Kaíque M. R. Cunha,
  • Sand Correa,
  • Fabrizzio Soares,
  • Maria Ribeiro,
  • Waldir Moreira,
  • Raphael Gomes,
  • Leandro A. Freitas and
  • Antonio Oliveira-Jr

13 June 2024

Multi-Access Edge Computing (MEC) reduces latency, provides high-bandwidth applications with real-time performance and reliability, supporting new applications and services for the present and future Beyond the Fifth Generation (B5G). Radio Network I...

  • Article
  • Open Access
2 Citations
2,087 Views
22 Pages

13 June 2024

In the field of visualization, understanding users’ analytical reasoning is important for evaluating the effectiveness of visualization applications. Several studies have been conducted to capture and analyze user interactions to comprehend thi...

  • Article
  • Open Access
6 Citations
2,213 Views
17 Pages

Machine Learning-Based Channel Estimation Techniques for ATSC 3.0

  • Yu-Sun Liu,
  • Shingchern D. You and
  • Yu-Chun Lai

13 June 2024

Channel estimation accuracy significantly affects the performance of orthogonal frequency-division multiplexing (OFDM) systems. In the literature, there are quite a few channel estimation methods. However, the performances of these methods deteriorat...

  • Article
  • Open Access
2 Citations
2,336 Views
25 Pages

Driving across Markets: An Analysis of a Human–Machine Interface in Different International Contexts

  • Denise Sogemeier,
  • Yannick Forster,
  • Frederik Naujoks,
  • Josef F. Krems and
  • Andreas Keinath

12 June 2024

The design of automotive human–machine interfaces (HMIs) for global consumers’ needs to cater to a broad spectrum of drivers. This paper comprises benchmark studies and explores how users from international markets—Germany, China, a...

  • Article
  • Open Access
1,551 Views
20 Pages

HitSim: An Efficient Algorithm for Single-Source and Top-k SimRank Computation

  • Jing Bai,
  • Junfeng Zhou,
  • Shuotong Chen,
  • Ming Du,
  • Ziyang Chen and
  • Mengtao Min

12 June 2024

SimRank is a widely used metric for evaluating vertex similarity based on graph topology, with diverse applications such as large-scale graph mining and natural language processing. The objective of the single-source and top-k SimRank query problem i...

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Information - ISSN 2078-2489