Recommendation systems are gaining increasing popularity in many application areas like
e-commerce, movie and music recommendations, tourism, news, advertisement, stock …

Recent advances in mobile devices and their sensing capabilities have enabled the
collection of rich contextual information and mobile device usage records through the device …

Geo-tagged photos of users on social media sites (eg, Flickr) provide plentiful location-
based data. This data provide a wealth of information about user behaviours and their …

In many applications, flexibility of recommendation, which is the capability of handling
multiple dimensions and various recommendation types, is very important. In this paper, we …

The study of the use of mobile Apps plays an important role in understanding the user
preferences, and thus provides the opportunities for intelligent personalized context-based …

The extensive usage of internet is fundamentally changing the way we live and
communicate. Consequently, the requirements of users while browsing internet are …

Web 2.0 platforms such as blogs, online news, social networks, and Internet forums allow
users to write comments to express their interests and opinions about the content of news …

A key step for the mobile app usage analysis is to classify apps into some predefined
categories. However, it is a nontrivial task to effectively classify mobile apps due to the …

In this paper, we illustrate how to extract personal context-aware preferences from the
context-rich device logs (ie, context logs) for building novel personalized context-aware …

Nowadays recommender systems are successfully used in various fields. One application is
the recommendation of restaurants, where even if the method of customer service is the …