Contact Recommendations from Aggegrated On-Line Activity

We describe a system for recommending people to contact 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 noisy-MAX function 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 a preliminary evaluation in which we compare the recommendations to existing friend rela-