Using tags and other forms of textual information, online retailers can create their product
listings, descriptions, and categories. E-commerce information services, such as search and …

Combining recommendation systems and AI in e-commerce can improve the user
experience and decision-making. This study uses a method called bibliometrics to look at …

This work investigates the Supply chain evolution over diverse industries and forecasts a
telecom churn using a publicly available dataset, besides offering a thorough technique for …

Data output has increased dramatically in the twenty-first century. The speed at which data is
introduced into the stream has increased as a result of the digitization of practically all …

Embedding-based deep recommendation models (EDRMs), which contain small dense
models and large embedding tables, are widely used in industry. Embedding …

The rapid expansion of e-commerce resulted in the influx of data in the mainstream. The
data of customers can lead to better results and can help the stakeholders to take better …

The amelioration of information technology and the infiltration of it almost all the sectors of
world have resulted in massive efflux of data. The rampant increase in the generation of data …

A machine learning-based prediction model was developed to understand the repeated
purchase behavior of e-commerce customers. A data mining process and the logistic …

For physical offline stores as association analysis plays an important role in the
maximization of sales, similarly, for online E-Commerce stores recommendation systems …

In the internet world, data is generated quickly, every second, from different sources.
Therefore, various applications, including social networking sites, e-commerce websites …