A Case-Based Reasoning Approach to Collaborative Filtering

Collaborative filtering systems make recommendations based on the accumulation of ratings by many users. The process has a case-based reasoning flavor: recommendations are generated by looking at the behavior of other users who are considered similar. However, the features associated with a user are semantically weak compared with those used by CBR systems. This research examines multi-dimensional or semantic ratings in which a system gets information about the reason behind a preference. Experiments show that metrics in which the semantic meaning of each rating is taken into account have markedly superior performance than simpler techniques.

• Type: Conference
• Year: 2000
• Where: EWCBR
• Authors: Robin D. Burke
• Keywords: Automated Reasoning, Case-based Reasoning Flavor, EWCBR 2000, Semantic Ratings, Systems Make Recommendations