Intelligent data handling techniques are beneficial for users; to store, process, analyze and
access the vast amount of information produced by electronic and automated devices. The …

Many predictive tasks of web applications need to model categorical variables, such as user
IDs and demographics like genders and occupations. To apply standard machine learning …

In recent years, deep neural networks have yielded immense success on speech
recognition, computer vision and natural language processing. However, the exploration of …

Factorization Machines (FMs) are a supervised learning approach that enhances the linear
regression model by incorporating the second-order feature interactions. Despite …

Multimedia content is dominating today's Web information. The nature of multimedia user-
item interactions is 1/0 binary implicit feedback (eg, photo likes, video views, song …

Agenda 2030 of Sustainable Development Goals (SDGs) 9 and 11 recognizes tourism as
one of the central industries to global development to tackle global challenges. With the …

Recently micro-videos have become more popular in social media platforms such as TikTok
and Instagram. Engagements in these platforms are facilitated by multi-modal …

Graph neural networks (GNNs) have shown great potential for personalized
recommendation. At the core is to reorganize interaction data as a user-item bipartite graph …

Embedding network data into a low-dimensional vector space has shown promising
performance for many real-world applications, such as node classification and entity …

Personalized rating prediction is an important research problem in recommender systems.
Although the latent factor model (eg, matrix factorization) achieves good accuracy in rating …