Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments

Understand

Recommender systems leverage product and community information to target products to consumers.

• Researchers have developed collaborative recommenders, content-based recommenders, and (largely ad-hoc) hybrid systems.
• We propose a unified probabilistic framework for merging collaborative and content-based recommendations.
• We extend Hofmann's [1999] aspect model to incorporate three-way co-occurrence data among users, items, and item content.