Communications of the ACM
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
A Movie Recommendation System—An Application of Voting Theory in User Modeling
User Modeling and User-Adapted Interaction
Incorporating contextual information in recommender systems using a multidimensional approach
ACM Transactions on Information Systems (TOIS)
IEEE Transactions on Knowledge and Data Engineering
A Generic Multipurpose recommender System for Contextual Recommendations
ISADS '07 Proceedings of the Eighth International Symposium on Autonomous Decentralized Systems
Introduction to recommender systems
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
From Web to Social Web: Discovering and Deploying User and Content Profiles
Exploiting contextual information in recommender systems
Proceedings of the 2008 ACM conference on Recommender systems
Design of Multi-mode E-commerce Recommendation System
IITSI '10 Proceedings of the 2010 Third International Symposium on Intelligent Information Technology and Security Informatics
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Recommender Systems have emerged to help support, augment and systematize the everyday natural social process of creating and sharing recommendations by developing tools that can be used to quickly identify interesting products, and therefore, reduce a search space of alternatives. This paper aims to present a framework, constructed under a generic approach, which provides services to Information Retrieval applications so these may offer product recommendations that consider several Adaptation/Personalization dimensions (e.g., user dimension, context, among others). With this purpose, the Multi-Agent Vizier Recommendation Framework (Vizier) is proposed; on the one hand, to assist those entities that currently develop Information Retrieval applications and wish to add recommendations to their services (e.g., E-Commerce applications); on the other hand, in order to offer a solution that hopefully provides better adapted/personalized results than current solutions by considering the multidimensionality of users, items and context. In order to validate Vizier, ZoundBeat was implemented. ZoundBeat is a functional application of a music player that is capable of invoking the proposed framework to offer its users song recommendations.