This paper reviews the research trends that link the advanced technical aspects of
recommendation systems that are used in various service areas and the business aspects of …

This paper synthesises research on artificial intelligence (AI) in e-commerce and proposes
guidelines on how information systems (IS) research could contribute to this research …

The integration of deep learning (DL) and fuzzy learning (FL) is considered a recently
emerging and promising research direction in data embedding. The integrated fuzzy neural …

The completeness of features provided by each E-Commerce is one of the criteria for buyers
in determining where to make transactions. One of the features that attract the attention of …

Interactive calligraphy experience equipment has the characteristics of a large amount of
data, various types, and strong homogeneity, which makes it difficult for users to find …

With the unprecedented development in the internet technology, the information overload
issues have become more and more complex, resulting in users being unable to obtain the …

Deep learning models have been successfully applied in sequential recommendations.
However, previous studies ignored the interaction between static and dynamic features of …

Currently, the Internet is widely used for shopping. Online reviews have become a crucial
factor in helping people to make purchasing decisions. However, the large amount of data …

Most previous studies on matrix factorization (MF)-based collaborative filtering (CF) have
focused solely on user rating information for predicting recommendations. However, to …

With the recent growth in food-delivery applications, creating new recommendation systems
tailored to this platform is essential. State-of-the-art restaurant recommendation systems are …