Recommender systems have been proposed to exploit the potential of social network by filtering the information and offer recommendations to a user that he is predicted to like. Co...
: Recommender systems are widely used online to support users in finding relevant information. They can be based on different techniques such as content-based and collaborative ...
Katja Niemann, Maren Scheffel, Martin Friedrich, U...
Current recommender systems can support tourists in choosing travel products (accommodation, activities, means of transport, etc.), in planning long trips, and in profitably spendi...
Pierpaolo Di Bitonto, Francesco Di Tria, Maria Lat...
Peer-to-Peer (p2p) networks are used for sharing content by millions of users. Often, meta-data used for searching is missing or wrong, making it difficult for users to find cont...
Automated recommendation (e.g., personalized product recommendation on an ecommerce web site) is an increasingly valuable service associated with many databases--typically online ...
Recommender systems attempt to reduce information overload and retain customers by selecting a subset of items from a universal set based on user preferences. While research in rec...
Abstract. Provision of personalized recommendations to users requires accurate modeling of their interests and needs. This paper proposes a general framework and specific methodolo...
Abstract--Recommender systems are gaining widespread acceptance in e-commerce applications to confront the "information overload" problem. Providing justification to a re...
act 11 Recommender systems anticipate users’ needs by suggesting items that are likely to interest them. Most existing systems 12 employ collaborative filtering (CF) techniques,...
Chris Cornelis, Jie Lu, Xuetao Guo, Guanquang Zhan...
In this paper, we show how a user profile can be enhanced when a more detailed description of the products is included. Two main assumptions have been considered: the first implie...
Juan F. Huete, Luis M. de Campos, Juan M. Fern&aac...