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Information, Volume 13, Issue 1

January 2022 - 42 articles

Cover Story: Two-dimensional space embeddings are a popular means to gain insight into high-dimensional data. However, these embeddings suffer from distortions that occur both at the global inter-cluster and the local intra-cluster levels. The former leads to misinterpretation of the distances between the various N–D cluster populations, while the latter hampers the appreciation of their individual shapes and composition, which we call cluster appearance. In this paper, we propose techniques to overcome these limitations by conveying the N–D cluster appearance through N–D-based Scagnostics metrics and a framework inspired by illustrative design. We validated and refined our design choices via a series of user studies. View this paper
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Articles (42)

  • Article
  • Open Access
2 Citations
3,020 Views
13 Pages

12 January 2022

Edge detection is one of the fundamental computer vision tasks. Recent methods for edge detection based on a convolutional neural network (CNN) typically employ the weighted cross-entropy loss. Their predicted results being thick and needing post-pro...

  • Article
  • Open Access
6 Citations
7,644 Views
21 Pages

Exploring Business Strategy Modelling with ArchiMate: A Case Study Approach

  • Fotis Kitsios,
  • Maria Kyriakopoulou and
  • Maria Kamariotou

12 January 2022

Enterprise architecture (EA) is a high-level abstraction of a business’ levels that aids in organizing planning and making better decisions. Researchers have concluded that the scope of EA is not focused only on technology planning but that the...

  • Article
  • Open Access
54 Citations
10,313 Views
23 Pages

11 January 2022

The banking sector has been considered as one of the primary adopters of Information and Communications Technologies. Especially during the last years, they have invested a lot into the digital transformation of their business process. Concerning the...

  • Article
  • Open Access
26 Citations
9,960 Views
19 Pages

10 January 2022

This paper focuses on the study of automated process discovery using the Inductive visual Miner (IvM) and Directly Follows visual Miner (DFvM) algorithms to produce a valid process model for educational process mining in order to understand and predi...

  • Article
  • Open Access
16 Citations
4,030 Views
16 Pages

10 January 2022

In order to provide open access to data of public interest, it is often necessary to perform several data curation processes. In some cases, such as biological databases, curation involves quality control to ensure reliable experimental support for b...

  • Article
  • Open Access
33 Citations
5,977 Views
29 Pages

Extraction and Analysis of Social Networks Data to Detect Traffic Accidents

  • Nestor Suat-Rojas,
  • Camilo Gutierrez-Osorio and
  • Cesar Pedraza

10 January 2022

Traffic accident detection is an important strategy governments can use to implement policies intended to reduce accidents. They usually use techniques such as image processing, RFID devices, among others. Social network mining has emerged as a low-c...

  • Article
  • Open Access
17 Citations
4,378 Views
15 Pages

Dual Co-Attention-Based Multi-Feature Fusion Method for Rumor Detection

  • Changsong Bing,
  • Yirong Wu,
  • Fangmin Dong,
  • Shouzhi Xu,
  • Xiaodi Liu and
  • Shuifa Sun

9 January 2022

Social media has become more popular these days due to widely used instant messaging. Nevertheless, rumor propagation on social media has become an increasingly important issue. The purpose of this study is to investigate the impact of various featur...

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Information - ISSN 2078-2489