Abstract Recommender Systems (RSs) are software tools and techniques providing
suggestions for items to be of use to a user. In this introductory chapter we briefly discuss …

Collaborative filtering is one of the most successful and widely used methods of automated
product recommendation in online stores. The most critical component of the method is the …

A basic yet crucial question is: why should the firm engage in database marketing? We
discuss three fundamental motivations: enhancing marketing productivity, creating and …

Whether users are likely to accept the recommendations provided by a recommender
system is of utmost importance to system designers and the marketers who implement them …

Nowadays, many online shops try to improve their customer service by personalization.
Personal welcomings, individual assistance as well as recommendations to inform and buy …

Consumers engage in costly searches to evaluate the increasing number of product options
available from online retailers. Presenting the best alternatives at the beginning reduces …

Studies in human-computer interaction recommend creating fewer than ten personas, based
on stakeholders' limitations to cognitively process and use personas. However, no existing …

This paper presents a novel approach to automated product recommendation based on the
popularity characteristics of products. Popularity plays a significant role in the consumer …

The study explores the effects of artificial intelligence (AI) and predictive analytics on digital
marketing strategy and return on investment (ROI). It reviews relevant literature on the use of …

As electronic commerce has penetrated into the publication business, personalized content
recommendation has drawn much attention in recent years for automated informational …