Abstract Web Data Extraction is an important problem that has been studied by means of
different scientific tools and in a broad range of applications. Many approaches to extracting …

The proliferation of e-commerce sites and online social media has allowed users to provide
preference feedback and maintain profiles in multiple systems, reflecting a variety of their …

In order to adapt functionality to their individual users, systems need information about these
users. The Social Web provides opportunities to gather user data from outside the system …

Providing relevant personalized recommendations for new users is one of the major
challenges in recommender systems. This problem, known as the user cold start has 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 …

In this paper we propose an approach to recommend to a user similar users, resources and
social networks in a Social Internetworking Scenario. Our approach presents some …

In this work we present an in-depth analysis of the user behaviors on different Social
Sharing systems. We consider three popular platforms, Flickr, Delicious and StumbleUpon …

Online recommender systems generally suffer from severe data sparsity problems, and this
are particularly prevalent in newly launched systems that do not have sufficient amounts of …

While browsing the Web, providing profile information in social networking services, or
tagging pictures, users leave a plethora of traces. In this paper, we analyze the nature of …

The rapid development of the number and the size of Online Social Networks (OSNs) makes
the analysis of Social Internetworking Scenarios (SISs) extremely challenging. In a SIS, a …