Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
Effective personalization based on association rule discovery from web usage data
Proceedings of the 3rd international workshop on Web information and data management
Eigentaste: A Constant Time Collaborative Filtering Algorithm
Information Retrieval
Web usage mining based on probabilistic latent semantic analysis
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
An Online Recommender System for Large Web Sites
WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
Management and Controlling of Time-Sensitive Business Processes with Sense & Respond
CIMCA '05 Proceedings of the International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce Vol-1 (CIMCA-IAWTIC'06) - Volume 01
Concepts and models for typing events for event-based systems
Proceedings of the 2007 inaugural international conference on Distributed event-based systems
Event-driven rules for sensing and responding to business situations
Proceedings of the 2007 inaugural international conference on Distributed event-based systems
| Hi-index | 0.00 |
With increasing product portfolios of eCommerce companies it is getting harder for their customers to find the products they like best. A solution to this problem is to analyze the customer's behavior, and recommend products based on ratings. By considering click-stream data, the customer is unburdened with explicitly rating his favored. In this paper, we introduce a system for segmenting visitors and recommending adequate items in real time by using an event-based system called Sense and Respond Infrastructure (SARI) for processing click-stream data. We present the architecture and components for a real-time click-stream analysis which can be easily customized to business needs of domain experts and business users. SARI provides functionality to monitor visitor and customer behavior, respond accordingly and at the same time optimize and adapt customer processes in real time. To illustrate this approach, we introduce a reference implementation, its underlying infrastructure and business scenarios.