BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
Fab: content-based, collaborative recommendation
Communications of the ACM
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Query refinement for multimedia similarity retrieval in MARS
MULTIMEDIA '99 Proceedings of the seventh ACM international conference on Multimedia (Part 1)
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Peer-to-peer based recommendations for mobile commerce
WMC '01 Proceedings of the 1st international workshop on Mobile commerce
A reputation-based approach for choosing reliable resources in peer-to-peer networks
Proceedings of the 9th ACM conference on Computer and communications security
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
FALCON: Feedback Adaptive Loop for Content-Based Retrieval
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Opinion-Based Filtering through Trust
CIA '02 Proceedings of the 6th International Workshop on Cooperative Information Agents VI
Collaborative Filtering with Privacy
SP '02 Proceedings of the 2002 IEEE Symposium on Security and Privacy
QCluster: relevance feedback using adaptive clustering for content-based image retrieval
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Political artifacts and personal privacy: the yenta multiagent distributed matchmaking system
Political artifacts and personal privacy: the yenta multiagent distributed matchmaking system
PocketLens: Toward a personal recommender system
ACM Transactions on Information Systems (TOIS)
VISCORS: A Visual-Content Recommender for the Mobile Web
IEEE Intelligent Systems
A multi-swarm approach for neighbor selection in peer-to-peer networks
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Expert Systems with Applications: An International Journal
Retrieving video features for language acquisition
Expert Systems with Applications: An International Journal
Collaborative filtering based on workflow space
Expert Systems with Applications: An International Journal
Improving peer-to-peer search performance through intelligent social search
Expert Systems with Applications: An International Journal
Recommender system based on workflow
Decision Support Systems
A ranking method for multimedia recommenders
Proceedings of the ACM International Conference on Image and Video Retrieval
Distributed recommender for peer-to-peer knowledge sharing
Information Sciences: an International Journal
Expert Systems with Applications: An International Journal
A recommendation strategy based on user behavior in digital ecosystems
Proceedings of the International Conference on Management of Emergent Digital EcoSystems
Intelligent product search with soft-boundary preference relaxation
Expert Systems with Applications: An International Journal
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
Electronic Commerce Research and Applications
Towards a user based recommendation strategy for digital ecosystems
Knowledge-Based Systems
International Journal of Multimedia Data Engineering & Management
Exploiting two-faceted web of trust for enhanced-quality recommendations
Expert Systems with Applications: An International Journal
A Multimedia Recommender System
ACM Transactions on Internet Technology (TOIT)
| Hi-index | 12.06 |
The pervasive deployment of P2P (peer-to-peer) systems and the multimedia contents overload in web environment raise a serious complexity for the peers where peers that participate in a P2P network are no longer able to effectively choose the contents they want. Recommender systems have been popularly used for reducing information overload of internet surfers by suggesting products or digital contents that are most valuable for them. But most existing recommender systems have been worked in client-server architecture. This paper proposes a PEOR (PEer-ORiented Recommender system), a collaborative filtering-based multimedia contents recommender system in P2P architecture, to obtain the peers' search efficiency. To adopt a change in peer preferences PEOR uses recent ratings of peers for recommendations, thereby leading to better quality recommendations. And to enhance the system performance, PEOR searches for nearest peers with similar preference through peer-based local information only. We implemented the system and evaluated its performance with real transaction data in S content provider offering character images. Our experimental data shows that PEOR offers not only remarkably higher quality of recommendations but also the dramatically faster performance than the centralized benchmark system.