Thanks to the continuous growth of collaborative platforms like YouTube, Flickr and Delicious, we are recently witnessing to a rapid evolution of web dynamics towards a more `soci...
Cataldo Musto, Fedelucio Narducci, Marco de Gemmis...
Recommender systems are intelligent applications that help on-line users to tackle information overload by providing recommendations of relevant items. Collaborative Filtering (CF...
We study the evaluation of opinion retrieval systems. Opinion retrieval is a relatively new research area, nevertheless classical evaluation measures, those adopted for ad hoc ret...
Giambattista Amati, Giuseppe Amodeo, Valerio Capoz...
In this work, we summarise the development of a ranking principle based on quantum probability theory, called the Quantum Probability Ranking Principle (QPRP), and we also provide...
In this work we propose a comparative study of the effects of a continuous model update on the effectiveness of wellknown query recommendation algorithms. In their original formul...
Daniele Broccolo, Franco Maria Nardini, Raffaele P...
This paper presents a vector space model approach, for representing documents and queries, using concepts instead of terms and WordNet as a light ontology. This way, information o...
The goal of any clustering algorithm is to find the optimal clustering solution with the optimal number of clusters. In order to evaluate a clustering solution, a number of validit...
Recommender systems are widely used in E-Commerce for making automatic suggestions of new items that could meet the interest of a given user. Collaborative Filtering approaches co...
Increasing applications are demanding effective and efficient support to perform retrieval in large collections of digital images. The work presented here is an early stage resear...
Giovanna Castellano, Gianluca Sforza, Maria Alessa...
This paper presents a Web page indexation model. In this model, a Web page is not viewed as a whole, but as a combination of a set of blocks based on their visual rendering, where ...