Meetings are an important communication and coordination activity of teams where status is discussed, new decisions are made, alternatives are considered, details are explained, information is presented, and new ideas are generated. As such, meetings contain a large amount of rich information which is not often formally documented. Capturing all of this informal meeting information has been a topic of research in several communities over the past decade. In this paper, data mining techniques are used to detect and analyze the frequent interaction patterns to discover various types of knowledge on human interactions.