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Publications

Publications by HumanISE

2024

Normalized strength-degree centrality: identifying influential spreaders for weighted network

Authors
Sadhu, S; Namtirtha, A; Malta, MC; Dutta, A;

Publication
SOCIAL NETWORK ANALYSIS AND MINING

Abstract
Influential spreaders are key nodes in networks that maximize or control the spreading processes. Many real-world systems are represented as weighted networks, and several indexing methods, such as weighted betweenness, closeness, k-shell decomposition, voterank, and mixed degree decomposition, among others, have been proposed to identify these influential nodes. However, these methods often face limitations such as high computational cost, non-monotonic rankings, and reliance on tunable parameters. To address these issues, this paper introduces a new tunable parameter-free method, Normalized Strength-Degree Centrality (nsd), which efficiently combines a node's normalized degree and strength to measure its influence across various network structures. Experimental results on eleven real and synthetic weighted networks show that nsd outperforms the existing methods in accurately identifying influential spreaders, strongly correlating to the Weighted Susceptible-Infected-Recovered (WSIR) model. Additionally, nsd is a parameter-free method that does not require time-consuming preprocessing to estimate rankings.

2024

Exploring multimodal learning applications in marketing: A critical perspective

Authors
César, I; Pereira, I; Rodrigues, F; Miguéis, V; Nicola, S; Madureira, A;

Publication
International Journal of Hybrid Intelligent Systems

Abstract
This review discusses the integration of intelligent technologies into customer interactions in organizations and highlights the benefits of using artificial intelligence systems based on a multimodal approach. Multimodal learning in marketing is explored, focusing on understanding trends and preferences by analyzing behavior patterns expressed in different modalities. The study suggests that research in multimodality is scarce but reveals that it is as a promising field for overcoming decision-making complexity and developing innovative marketing strategies. The article introduces a methodology for accurately representing multimodal elements and discusses the theoretical foundations and practical impact of multimodal learning. It also examines the use of embeddings, fusion techniques, and explores model performance evaluation. The review acknowledges the limitations of current multimodal approaches in marketing and encourages more guidelines for future research. Overall, this work emphasizes the importance of integrating intelligent technology in marketing to personalize customer experiences and improve decision-making processes.

2024

An automated approach for binary classification on imbalanced data

Authors
Vieira, PM; Rodrigues, F;

Publication
KNOWLEDGE AND INFORMATION SYSTEMS

Abstract
Imbalanced data are present in various business sectors and must be handled with the proper resampling methods and classification algorithms. To handle imbalanced data, there are numerous resampling and learning method combinations; nonetheless, their effective use necessitates specialised knowledge. In this paper, several approaches, ranging from more accessible to more advanced in the domain of data resampling techniques, will be considered to handle imbalanced data. The application developed delivers recommendations of the most suitable combinations of techniques for a specific dataset by extracting and comparing dataset meta-feature values recorded in a knowledge base. It facilitates effortless classification and automates part of the machine learning pipeline with comparable or better results than state-of-the-art solutions and with a much smaller execution time.

2023

Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2023, Volume 1: GRAPP, Lisbon, Portugal, February 19-21, 2023

Authors
de Sousa, AA; Rogers, TB; Bouatouch, K;

Publication
VISIGRAPP (1: GRAPP)

Abstract

2023

Computer Vision, Imaging and Computer Graphics Theory and Applications - 16th International Joint Conference, VISIGRAPP 2021, Virtual Event, February 8-10, 2021, Revised Selected Papers

Authors
de Sousa, AA; Havran, V; Paljic, A; Peck, TC; Hurter, C; Purchase, HC; Farinella, GM; Radeva, P; Bouatouch, K;

Publication
VISIGRAPP (Revised Selected Papers)

Abstract

2023

Computer Vision, Imaging and Computer Graphics Theory and Applications - 17th International Joint Conference, VISIGRAPP 2022, Virtual Event, February 6-8, 2022, Revised Selected Papers

Authors
de Sousa, AA; Debattista, K; Paljic, A; Ziat, M; Hurter, C; Purchase, HC; Farinella, GM; Radeva, P; Bouatouch, K;

Publication
VISIGRAPP (Revised Selected Papers)

Abstract

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