The anatomy of a large-scale hypertextual Web search engine
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Temporary user modeling for adaptive product presentations in the Web
UM '99 Proceedings of the seventh international conference on User modeling
Learning users' interests by unobtrusively observing their normal behavior
Proceedings of the 5th international conference on Intelligent user interfaces
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Proceedings of the 6th international conference on Intelligent user interfaces
A resource-adaptive mobile navigation system
Proceedings of the 7th international conference on Intelligent user interfaces
Explorations in Automatic Thesaurus Discovery
Explorations in Automatic Thesaurus Discovery
Distributed Systems: Principles and Paradigms
Distributed Systems: Principles and Paradigms
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Eigentaste: A Constant Time Collaborative Filtering Algorithm
Information Retrieval
User Modeling for Adaptive News Access
User Modeling and User-Adapted Interaction
CLARANS: A Method for Clustering Objects for Spatial Data Mining
IEEE Transactions on Knowledge and Data Engineering
Amazon.com Recommendations: Item-to-Item Collaborative Filtering
IEEE Internet Computing
X-Compass: An XML Agent for Supporting User Navigation on the Web
FQAS '02 Proceedings of the 5th International Conference on Flexible Query Answering Systems
Multidimensional Recommender Systems: A Data Warehousing Approach
WELCOM '01 Proceedings of the Second International Workshop on Electronic Commerce
Content-boosted collaborative filtering for improved recommendations
Eighteenth national conference on Artificial intelligence
Proceedings of the 2nd international conference on Knowledge capture
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Display time as implicit feedback: understanding task effects
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
PocketLens: Toward a personal recommender system
ACM Transactions on Information Systems (TOIS)
CROC: A New Evaluation Criterion for Recommender Systems
Electronic Commerce Research
Incorporating contextual information in recommender systems using a multidimensional approach
ACM Transactions on Information Systems (TOIS)
Clustering for probabilistic model estimation for CF
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
The Essence of P2P: A Reference Architecture for Overlay Networks
P2P '05 Proceedings of the Fifth IEEE International Conference on Peer-to-Peer Computing
Usage-Based PageRank for Web Personalization
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Proceedings of the 11th international conference on Intelligent user interfaces
When Media Gets Wise: collaborative filtering with mobile media agents
Proceedings of the 11th international conference on Intelligent user interfaces
MASHA: A multi-agent system handling user and device adaptivity of Web sites
User Modeling and User-Adapted Interaction
Dynamic personalization of web sites without user intervention
Communications of the ACM - Spam and the ongoing battle for the inbox
Deploying personalized mobile services in an agent-based environment
Expert Systems with Applications: An International Journal
Web site personalization based on link analysis and navigational patterns
ACM Transactions on Internet Technology (TOIT)
Time spent on a web page is sufficient to infer a user's interest
IMSA'07 IASTED European Conference on Proceedings of the IASTED European Conference: internet and multimedia systems and applications
Usage-based web recommendations: a reinforcement learning approach
Proceedings of the 2007 ACM conference on Recommender systems
Clustering people according to their preference criteria
Expert Systems with Applications: An International Journal
A recommender system using GA K-means clustering in an online shopping market
Expert Systems with Applications: An International Journal
Learning implicit user interest hierarchy for context in personalization
Applied Intelligence
Nearest-biclusters collaborative filtering based on constant and coherent values
Information Retrieval
EC-XAMAS: SUPPORTING E-COMMERCE ACTIVITIES BY AN XML-BASED ADAPTIVE MULTI-AGENT SYSTEM
Applied Artificial Intelligence
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Distributed recommender for peer-to-peer knowledge sharing
Information Sciences: an International Journal
A framework for dynamic data source identification and orchestration on the web
Proceedings of the 3rd and 4th International Workshop on Web APIs and Services Mashups
A literature review and classification of recommender systems research
Expert Systems with Applications: An International Journal
A multi-agent recommender system for supporting device adaptivity in e-Commerce
Journal of Intelligent Information Systems
Recommending multimedia web services in a multi-device environment
Information Systems
Cloning mechanisms to improve agent performances
Journal of Network and Computer Applications
Statistical user model supported by R-Tree structure
Applied Intelligence
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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 the user, periodically collects information coming from the different user's device assistants to construct a global user's profile. In order to generate recommendations, a recommender precomputes data provided by the profilers. This way, the site manager has only the task of suitably presenting the content of the site, while the computation of the recommendations is assigned to the other distributed components. Some experiments conducted on real data and using some well-known metrics show that the system works more effectively and efficiently than other device-based distributed recommenders.