Can I read MUADDIB: A distributed recommender system supporting device adaptivity on EtoBox?

MUADDIB: A distributed recommender system supporting device adaptivity by Domenico Rosaci; Giuseppe M. L. Sarné; Salvatore Garruzzo is a Computer Science article available to read on EtoBox.

What is MUADDIB: A distributed recommender system supporting device adaptivity about?

Web recommender systems are Web applications capable of generating useful suggestions for visitors of Internet sites. However, in the case of large user communities and in presence of a high number of Web sites, these tasks are computationally onerous, even more if the client software runs on devices with limited resources. Moreover, the quality of the recommendations strictly depends on how the recommendation algorithm takes into account the currently used device. Some approaches proposed in the literature provide multidimensional recommendations considering, besides items and users, also the exploited device. However, these systems do not efficiently perform, since they assign to either the client or the server the arduous cost of computing recommendations. In this article, we argue that a fully distributed organization is a suitable solution to improve the efficiency of multidimensional recommender systems. In order to address these issues, we propose a novel distributed architecture, called MUADDIB, where each user's device is provided with a __device assistant__ that autonomously retrieves information about the user's behavior. Moreover, a single __profiler__ , associated with

Who reads MUADDIB: A distributed recommender system supporting device adaptivity?

Author

Domenico Rosaci; Giuseppe M. L. Sarné; Salvatore Garruzzo

Publisher

ACM

Published

2009

Language

EN

Field

Computer Science (Physical Sciences)