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Big Data and Cognitive Computing, Volume 9, Issue 3

2025 March - 24 articles

Cover Story: Generative AI (GenAI) is transforming digital ecosystems, but concerns have been raised regarding trust and misinformation. This article explores decentralized Web3 mechanisms—blockchain, DAOs, and data cooperatives—to enhance trust in GenAI within democratic frameworks. In line with the EU’s AI Act and the Draghi Report, it evaluates seven detection techniques including (i) Federated Learning, (ii) Blockchain-Based Provenance Tracking, (iii) ZKPs, (iv) DAOs for Crowdsourced Verification, (v) AI-Powered Digital Watermarking, (vi) XAI, and (vii) PPML to counter AI-driven misinformation. By integrating decentralized verification and data sovereignty, this article—stemming from the EU-funded Enfield lighthouse project—advances AI governance, ensuring transparency, accountability, and resilience despite increasing technopolitical polarization. View this paper
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Articles (24)

  • Article
  • Open Access
2 Citations
3,592 Views
22 Pages

TACO: Adversarial Camouflage Optimization on Trucks to Fool Object Detectors

  • Adonisz Dimitriu,
  • Tamás Vilmos Michaletzky and
  • Viktor Remeli

Adversarial attacks threaten the reliability of machine learning models in critical applications like autonomous vehicles and defense systems. As object detectors become more robust with models like YOLOv8, developing effective adversarial methodolog...

  • Article
  • Open Access
3 Citations
2,815 Views
19 Pages

Data-Driven Forecasting of CO2 Emissions in Thailand’s Transportation Sector Using Nonlinear Autoregressive Neural Networks

  • Thananya Janhuaton,
  • Supanida Nanthawong,
  • Panuwat Wisutwattanasak,
  • Chinnakrit Banyong and ,
  • Chamroeun Se,
  • Thanapong Champahom,
  • Vatanavongs Ratanavaraha and
  • Sajjakaj Jomnonkwao
  • + 3 authors+ 0 author

Accurately forecasting CO2 emissions in the transportation sector is essential for developing effective mitigation strategies. This study uses an annually spanning dataset from 1993 to 2022 to evaluate the predictive performance of three methods: NAR...

  • Article
  • Open Access
15 Citations
7,123 Views
30 Pages

Generation Z’s Travel Behavior and Climate Change: A Comparative Study for Greece and the UK

  • Athanasios Demiris,
  • Grigorios Fountas,
  • Achille Fonzone and
  • Socrates Basbas

Climate change is one of the most pressing global threats, endangering the sustainability of the planet and quality of life, whilst urban mobility significantly contributes to exacerbating its effects. Recently, policies aimed at mitigating these eff...

  • Article
  • Open Access
4 Citations
3,984 Views
23 Pages

Defining, Detecting, and Characterizing Power Users in Threads

  • Gianluca Bonifazi,
  • Christopher Buratti,
  • Enrico Corradini,
  • Michele Marchetti and ,
  • Federica Parlapiano,
  • Domenico Ursino and
  • Luca Virgili
  • + 2 authors+ 0 author

Threads is a new social network that was launched by Meta in July 2023 and conceived as a direct alternative to X. It is a unique case study in the social network landscape, as it is content-based like X, but has an Instagram-based growth model, whic...

(This article belongs to the Special Issue Research Progress in Artificial Intelligence and Social Network Analysis)
  • Article
  • Open Access
1 Citations
2,767 Views
22 Pages

Margin-Based Training of HDC Classifiers

  • Laura Smets,
  • Dmitri Rachkovskij,
  • Evgeny Osipov,
  • Werner Van Leekwijck and ,
  • Olexander Volkov and
  • Steven Latré
  • + 1 author+ 0 author

The explicit kernel transformation of input data vectors to their distributed high-dimensional representations has recently been receiving increasing attention in the field of hyperdimensional computing (HDC). The main argument is that such represent...

  • Feature Paper
  • Article
  • Open Access
36 Citations
12,679 Views
18 Pages

A Comparative Analysis of Sentence Transformer Models for Automated Journal Recommendation Using PubMed Metadata

  • Maria Teresa Colangelo,
  • Marco Meleti,
  • Stefano Guizzardi,
  • Elena Calciolari and
  • Carlo Galli

We present an automated journal recommendation pipeline designed to evaluate the performance of five Sentence Transformer models—all-mpnet-base-v2 (Mpnet), all-MiniLM-L6-v2 (Minilm-l6), all-MiniLM-L12-v2 (Minilm-l12), multi-qa-distilbert-cos-v1...

(This article belongs to the Special Issue Knowledge Graphs in the Big Data Era: Navigating the Confluence of Distribution, Visualization, and Advanced Computational Models)
  • Article
  • Open Access
4 Citations
3,817 Views
26 Pages

This paper introduces PK-Judge, a novel neural network watermarking framework designed to enhance the intellectual property (IP) protection by incorporating an asymmetric cryptograp hic approach in the verification process. Inspired by the paradigm s...

  • Article
  • Open Access
11 Citations
7,097 Views
21 Pages

Enhancing Hierarchical Classification in Tree-Based Models Using Level-Wise Entropy Adjustment

  • Olga Narushynska,
  • Anastasiya Doroshenko,
  • Vasyl Teslyuk,
  • Volodymyr Antoniv and
  • Maksym Arzubov

Hierarchical classification, which organizes items into structured categories and subcategories, has emerged as a powerful solution for handling large and complex datasets. However, traditional flat classification approaches often overlook the hierar...

(This article belongs to the Special Issue Natural Language Processing Applications in Big Data)
  • Article
  • Open Access
9 Citations
12,400 Views
13 Pages

An Expected Goals On Target (xGOT) Model: Accounting for Goalkeeper Performance in Football

  • Blanca De-la-Cruz-Torres,
  • Miguel Navarro-Castro and
  • Anselmo Ruiz-de-Alarcón-Quintero

A key challenge in utilizing the expected goals on target (xGOT) metric is the limited public access to detailed football event and positional data, alongside other advanced metrics. This study aims to develop an xGOT model to evaluate goalkeeper (GK...

  • Article
  • Open Access
8 Citations
6,302 Views
26 Pages

A Novel Multimodal Data Fusion Framework: Enhancing Prediction and Understanding of Inter-State Cyberattacks

  • Jiping Dong,
  • Mengmeng Hao,
  • Fangyu Ding,
  • Shuai Chen and ,
  • Jiajie Wu,
  • Jun Zhuo and
  • Dong Jiang
  • + 2 authors+ 0 author

Inter-state cyberattacks are increasingly becoming a major hidden threat to national security and global order. However, current prediction models are often constrained by single-source data due to insufficient consideration of complex influencing fa...

  • Article
  • Open Access
16 Citations
7,828 Views
48 Pages

As generative AI (GenAI) technologies proliferate, ensuring trust and transparency in digital ecosystems becomes increasingly critical, particularly within democratic frameworks. This article examines decentralized Web3 mechanisms—blockchain, d...

  • Article
  • Open Access
15 Citations
10,680 Views
28 Pages

Transitioning from TinyML to Edge GenAI: A Review

  • Gloria Giorgetti and
  • Danilo Pietro Pau

Generative AI (GenAI) models are designed to produce realistic and natural data, such as images, audio, or written text. Due to their high computational and memory demands, these models traditionally run on powerful remote compute servers. However, t...

  • Article
  • Open Access
5,362 Views
21 Pages

Comparative Analysis of Audio Feature Extraction for Real-Time Talking Portrait Synthesis

  • Pegah Salehi,
  • Sajad Amouei Sheshkal,
  • Vajira Thambawita,
  • Sushant Gautam and ,
  • Saeed S. Sabet,
  • Dag Johansen,
  • Michael A. Riegler and
  • Pål Halvorsen
  • + 3 authors+ 0 author

This paper explores advancements in real-time talking-head generation, focusing on overcoming challenges in Audio Feature Extraction (AFE), which often introduces latency and limits responsiveness in real-time applications. To address these issues, w...

  • Article
  • Open Access
1 Citations
2,725 Views
16 Pages

The detection of synthetic speech has become a pressing challenge due to the potential societal risks posed by synthetic speech technologies. Existing methods primarily focus on either the time or frequency domain of speech, limiting their ability to...

  • Article
  • Open Access
4 Citations
3,564 Views
28 Pages

We present an automatic approach for generating learning problems for teaching introductory programming in different programming languages. The current implementation allows input and output in the three most popular programming languages for teachin...

(This article belongs to the Special Issue Application of Semantic Technologies in Intelligent Environment)
  • Review
  • Open Access
12 Citations
12,880 Views
16 Pages

ChatGPT’s Impact Across Sectors: A Systematic Review of Key Themes and Challenges

  • Hussam Hussein,
  • Madelina Gordon,
  • Cameron Hodgkinson,
  • Robert Foreman and
  • Sumaya Wagad

This paper critically examines the expanding body of literature on ChatGPT, a transformative AI tool with widespread global adoption. By categorising research into six key themes—sustainability, health, education, work, social media, and energy...

  • Article
  • Open Access
11 Citations
5,477 Views
58 Pages

Exploring Predictive Modeling for Food Quality Enhancement: A Case Study on Wine

  • Cemil Emre Yavas,
  • Jongyeop Kim,
  • Lei Chen,
  • Christopher Kadlec and
  • Yiming Ji

What makes a wine exceptional enough to score a perfect 10 from experts? This study explores a data-driven approach to identify the ideal physicochemical composition for wines that could achieve this highest possible rating. Using a dataset of 11 mea...

  • Review
  • Open Access
21 Citations
10,318 Views
27 Pages

Cognitive computing encompasses computing tools and methods that simulate and mimic the process of human thinking, without human supervision. Deep neural network architectures, natural language processing, big data tools, and self-learning tools base...

  • Article
  • Open Access
3 Citations
3,242 Views
14 Pages

Fine-Grained Local and Global Semantic Fusion for Multimodal Image–Text Retrieval

  • Shenao Peng,
  • Zhongmei Wang,
  • Jianhua Liu,
  • Changfan Zhang and
  • Lin Jia

An image–text retrieval method that integrates intramodal fine-grained local semantic information and intermodal global semantic information is proposed to address the weak fine-grained discrimination capabilities for the semantic features loca...

  • Article
  • Open Access
7 Citations
2,882 Views
16 Pages

A Web-Based Platform for Hand Rehabilitation Assessment

  • Dimitrios N. Soumis and
  • Nikolaos D. Tselikas

Hand impairment affects millions of people. There are multiple factors that cause deficits, varying from physical injuries to neurological disorders. Upper-limb patients face significant difficulties in daily life. Rehabilitation aims at supporting t...

  • Article
  • Open Access
11 Citations
3,788 Views
30 Pages

DeB3RTa: A Transformer-Based Model for the Portuguese Financial Domain

  • Higo Pires,
  • Leonardo Paucar and
  • Joao Paulo Carvalho

The complex and specialized terminology of financial language in Portuguese-speaking markets create significant challenges for natural language processing (NLP) applications, which must capture nuanced linguistic and contextual information to support...

  • Article
  • Open Access
12 Citations
5,208 Views
21 Pages

Large language models (LLMs) have demonstrated remarkable capabilities in text generation, which also raise numerous concerns about their potential misuse, especially in educational exercises and academic writing. Accurately identifying and tracing t...

  • Article
  • Open Access
7 Citations
3,270 Views
35 Pages

There is a rapid growth in mental disorders, thus leading to a pressing demand for more sophisticated diagnosis techniques. Clinical assessments and symptomatic analyses for traditional diagnostics suffer from subjectivity, delayed diagnosis, and spe...

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Big Data Cogn. Comput. - ISSN 2504-2289