Contact Recommendations from Aggegrated On-Line Activity

We describe a system for recommending people based on similar interests and activities as part of a company-wide social networking site. Our contact recommendation service aggregates input from multiple on-line data sources and combines them using a Bayesian network to generate a rating of the overall match between two users. The system is running as part of an experimental social networking site at MITRE. We present the results of two experiments in which we evaluated the performance of the recommender algorithm and user interface.