Tags (keywords freely assigned by users to describe web content) have become highly
popular on Web 2.0 applications, because of the strong stimuli and easiness for users to …

One of the main current applications of intelligent systems is recommender systems (RS).
RS can help users to find relevant items in huge information spaces in a personalized way …

Nowadays, the increasing demand for group recommendations can be observed. In this
paper we address the problem of recommendation performance for groups of users (group …

Researchers typically need to filter several academic papers to find those relevant to their
research. This filtering is cumbersome and time-consuming because the number of …

Event-based social networks (EBSNs) have experienced increased popularity and rapid
growth. Due to the huge volume of events available in EBSNs, event recommendation …

With the development of Web‐based social networks, many personalized tag
recommendation approaches based on multi‐information have been proposed. Due to the …

Recommendation models are vital to the success of recommender systems. The latent factor
model is one of the outstanding collaborative recommendation models. It faces many …

Various e-commerce platforms allow sellers to register, describe and organize their own
products, using tags and other textual metadata. The quality of these textual descriptors is …

Mashups are prevalent Service-Oriented Architecture (SOA) based applications consisting
of multiple Web Application Programming Interfaces (APIs) and content. Tags have been …

Collaborative tagging systems, also known as folksonomies, have grown in popularity over
the Web on account of their simplicity to organize several types of content (eg, Web pages …