Shoechicken: An Intelligent System for Recommending RSS/Atom Content

We present Shoechicken, an intelligent agentbased system for rating RSS and Atom news content based on user preferences. The system builds a user profile implicitly by observing a user;s interactions with news content. Shoechicken rates incoming content based on the user's preferences, and adapts to both long term and short term changes in these preferences. The system is interoperable such that it can supply rated content for use by any news aggregator. This paper describes the Shoechicken system, its architecture, and its implementation.

• Type: Conference
• Year: 2006
• Where: CATA
• Authors: James Horsley, Michael Wooten, Eman El-Sheikh
• Keywords: CATA 2006, CATA 2007, Short Term Changes, User Preferences, User's Preferences