Recommender systems have become an important research field since the emergence of
the first paper on collaborative filtering in the mid-1990s. Although academic research on …

The purpose of this study is to analyze how channel characteristics influence the channel
attitudes of multi-channel research shoppers. In addition, the study also considers …

Recommender systems (RSs) are fundamental tools that address data redundancy and
serve as intelligent supplements for tasks such as data retrieval and refinement by analyzing …

In recent years, recommender systems (RS) provide a considerable progress to users. RSs
reduce the cost of a user's time in order to reach to desired results faster. The main issue of …

A novel model of distributed knowledge recommender system is proposed to facilitate
knowledge sharing among collaborative team members. Different from traditional …

The ever-growing amount of data available on the Internet calls for personalization. Yet, the
most effective personalization schemes, such as those based on collaborative filtering (CF) …

Recently, the extraction of valid information from big data has witnessed a growing interest.
Nowadays, in social networks, large parts of websites collect user profiles to provide some …

In the last years, the Web community has shown a broad interest in Web services that
handle multimedia contents. To improve the usability of these services different tools have …

Traditional recommender systems for e-Commerce support the customers' activities
providing them with useful suggestions about available products in Web stores. To this …

Most of the activities usually performed by Web users are today effectively supported by
using appropriate metadata that make the Web practically readable by software agents …