Providing rich and accurate metadata for indexing media content is a crucial problem for all the companies offering streaming entertainment services. These metadata are commonly employed to enhance search engine results and feed recommendation …

Retail companies are greatly interested in performing continuous monitoring of purchase traces of customers, to identify weak customers and take the necessary actions to improve customer satisfaction and ensure their revenues remain unaffected. In …

In this paper, we propose and experimentally assess an innovative framework for scaling posterior distributions over different-curation datasets, based on Bayesian-Neural-Networks (BNN). Another innovation of our proposed study consists in …

Audio super-resolution refers to techniques that improve the audio signals quality, usually by exploiting bandwidth extension methods, whereby audio enhancement is obtained by expanding the phase and the spectrogram of the input audio traces.

Preference elicitation is a crucial step for every recommendation algorithm. In this paper, we present a strategy that allows users to express their preferences and needs through natural language statements. In particular, our natural language …

Food Security (FS) is a major concern in West Africa, particularly in Burkina Faso, which has been the epicenter of a humanitarian crisis since the beginning of this century. Early warning systems for FS and famines rely mainly on numerical data …

Argument pair extraction (APE) is a fine-grained task of argument mining which aims to identify arguments offered by different participants in some discourse and detect interaction relationships between arguments from different participants. In …

Hiring knowledgeable and cost-effective individuals, who use their knowledge and expertise to boost the organization, is extremely important for organizations as they are the most valuable assets. T-shaped experts are the best option based on …

$${{\textbf{Latent}}\varvec{Out}}$$ Latent Out is a recently introduced algorithm for unsupervised anomaly detection which enhances latent space-based neural methods, namely (Variational) Autoencoders, GANomaly and ANOGan architectures. The main …

Geomagnetic activities have a crucial impact on Earth, which can affect spacecraft and electrical power grids. Geospace scientists use a geomagnetic index, called the Kp index, to describe the overall level of geomagnetic activity. This index is …

Recommender systems are deployed heavily by many online platforms for better user engagement and providing recommendations. Despite being so popular, several works have shown the existence of popularity bias due to the non-random nature of missing …

In the domain of sequence recommendation, contextual information has been shown to effectively improve the accuracy of predicting the user’s next interaction. However, existing studies do not consider the dependencies between contextual …

The growth of Big Data has resulted in an overwhelming increase in the volume of data available, including the number of features. Feature selection, the process of selecting relevant features and discarding irrelevant ones, has been successfully …

Modern IoT ecosystems are the preferred target of threat actors wanting to incorporate resource-constrained devices within a botnet or leak sensitive information. A major research effort is then devoted to create countermeasures for mitigating …

Besides the need for more advanced predictive methods, there is increasing demand for easily interpretable results. Couples of enhanced association rules (a generalization of association rules/apriori/frequent itemsets) are excellent candidates …

The study of influential spreaders has become a growing area of interest within network sciences due to its critical implications in understanding the robustness and vulnerability of complex networks. There is a significant degree of focus on the …

Session-aware recommender systems capture user-specific preferences that emerge within multiple user sessions by leveraging the sequential nature of user interactions. Existing session-aware recommendation methods face challenges in finding the …

One of the serious consequences of social media usage is fake information dissemination that locomotes society towards negativity. Existing solutions focus on supervised fake news detection models, which requires extensive labelled data. In this …

Frailty is associated with poor post-operative outcomes. However, frailty assessments in clinical practice are challenging due to the need for more resources and pragmatic complexities. We aimed to create a pre-operative frailty ascertainment …

As a popular graph learning technique, graph neural networks (GNN) show great advantages in the field of personalized recommendation. Existing GNN-based recommendation methods organized user-item interactions (e.g., click, purchase, review, etc.) …