Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
The data webhouse toolkit: building the web-enabled data warehouse
The data webhouse toolkit: building the web-enabled data warehouse
Separating the swarm: categorization methods for user sessions on the web
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Meta-recommendation systems: user-controlled integration of diverse recommendations
Proceedings of the eleventh international conference on Information and knowledge management
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization
Data Mining and Knowledge Discovery
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Total
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
An Adaptive Recommendation System with a Coordinator Agent
WI '01 Proceedings of the First Asia-Pacific Conference on Web Intelligence: Research and Development
HCC '02 Proceedings of the IEEE 2002 Symposia on Human Centric Computing Languages and Environments (HCC'02)
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
An Adaptive Recommendation System without Explicit Acquisition of User Relevance Feedback
Distributed and Parallel Databases
A Framework for the Evaluation of Session Reconstruction Heuristics in Web-Usage Analysis
INFORMS Journal on Computing
Reinforcement Learning Architecture for Web Recommendations
ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2
REFEREE: an open framework for practical testing of recommender systems using ResearchIndex
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Adaptive Web SitesA Knowledge Extraction from Web Data Approach
Proceedings of the 2008 conference on Adaptive Web Sites: A Knowledge Extraction from Web Data Approach
Integrating OLAP and recommender systems: an evaluation perspective
DOLAP '10 Proceedings of the ACM 13th international workshop on Data warehousing and OLAP
Automatic optimization of web recommendations using feedback and ontology graphs
ICWE'05 Proceedings of the 5th international conference on Web Engineering
Proceedings of the 15th International Conference on Extending Database Technology
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Recommendations are crucial for the success of large websites. While there are many ways to determine recommendations, the relative quality of these recommenders depends on many factors and is largely unknown. We propose a new classification of recommenders and comparatively evaluate their relative quality for a sample web-site. The evaluation is performed with AWESOME (Adaptive website recommendations), a new data warehouse-based recommendation system capturing and evaluating user feedback on presented recommendations. Moreover, we show how AWESOME performs an automatic and adaptive closed-loop website optimization by dynamically selecting the most promising recommenders based on continuously measured recommendation feedback. We propose and evaluate several alternatives for dynamic recommender selection including a powerful machine learning approach.