Recommendation systems have drawn an increasingly broad range of interest since early
1990s. Recently, a search with the query of “recommendation systems” on Google Scholar …

A recommender system aims to provide users with personalized online product or service
recommendations to handle the increasing online information overload problem and …

Recommender systems have developed in parallel with the web. They were initially based
on demographic, content-based and collaborative filtering. Currently, these systems are …

E-business leverages digital channels to scale its functions and services and operates by
connecting and retaining customers using marketing initiatives. To increase the likelihood of …

This report identifies two main bodies of academic research that pay sustained attention to
algorithmic recommendation in the realm of culture: a) academic computer science and b) …

Graphs are the most ubiquitous form of structured data representation used in machine
learning. They model, however, only pairwise relations between nodes and are not …

Nowadays many people are members of multiple online social networks simultaneously,
such as Facebook, Twitter and some other instant messaging circles. But these networks are …

Originating from Facebook, LinkedIn, Twitter, Instagram, YouTube, and many other
networking sites, the social media shared by users and the associated metadata are …

Recommender systems are software tools and techniques for suggesting items in an
automated fashion to users tailored their preferences. Collaborative Filtering (CF) …

Smart product-service system (Smart PSS) is a heterogeneous and integrated system in
which manufacturers/service providers deliver integrated and customized product-service …